Gradium integration.
This commit is contained in:
laurent
@@ -63,6 +63,7 @@ fireworks = []
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fish = [ "ormsgpack~=1.7.0", "pipecat-ai[websockets-base]" ]
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gladia = [ "pipecat-ai[websockets-base]" ]
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google = [ "google-cloud-speech>=2.33.0,<3", "google-cloud-texttospeech>=2.31.0,<3", "google-genai>=1.41.0,<2", "pipecat-ai[websockets-base]" ]
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gradium = [ "pipecat-ai[websockets-base]" ]
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grok = []
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groq = [ "groq~=0.23.0" ]
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gstreamer = [ "pygobject~=3.50.0" ]
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5
src/pipecat/services/gradium/__init__.py
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5
src/pipecat/services/gradium/__init__.py
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@@ -0,0 +1,5 @@
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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256
src/pipecat/services/gradium/stt.py
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256
src/pipecat/services/gradium/stt.py
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@@ -0,0 +1,256 @@
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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"""Gradium's speech-to-text service implementation.
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This module provides integration with Gradium's real-time speech-to-text
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WebSocket API for streaming audio transcription.
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"""
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import asyncio
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import base64
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import json
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from typing import AsyncGenerator
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from loguru import logger
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from pipecat.frames.frames import (
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CancelFrame,
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EndFrame,
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Frame,
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StartFrame,
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TranscriptionFrame,
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UserStartedSpeakingFrame,
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UserStoppedSpeakingFrame,
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)
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.services.stt_service import WebsocketSTTService
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from pipecat.transcriptions.language import Language
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from pipecat.utils.time import time_now_iso8601
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from pipecat.utils.tracing.service_decorators import traced_stt
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try:
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from websockets.asyncio.client import connect as websocket_connect
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from websockets.protocol import State
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except ModuleNotFoundError as e:
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logger.error(f"Exception: {e}")
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logger.error('In order to use Gradium, you need to `pip install "pipecat-ai[gradium]"`.')
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raise Exception(f"Missing module: {e}")
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SAMPLE_RATE = 24000
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class GradiumSTTService(WebsocketSTTService):
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"""Gradium real-time speech-to-text service.
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Provides real-time speech transcription using Gradium's WebSocket API.
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Supports both interim and final transcriptions with configurable parameters
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for audio processing and connection management.
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"""
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def __init__(
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self,
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*,
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api_key: str,
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api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr",
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json_config: str | None = None,
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**kwargs,
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):
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"""Initialize the Gradium STT service.
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Args:
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api_key: Gradium API key for authentication.
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language: Language code for transcription. Defaults to English (Language.EN).
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api_endpoint_base_url: WebSocket endpoint URL. Defaults to Gradium's streaming endpoint.
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json_config: Optional JSON configuration string for additional model settings.
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**kwargs: Additional arguments passed to parent STTService class.
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"""
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super().__init__(sample_rate=SAMPLE_RATE, **kwargs)
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self._api_key = api_key
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self._api_endpoint_base_url = api_endpoint_base_url
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self._websocket = None
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self._json_config = json_config
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self._receive_task = None
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self._audio_buffer = bytearray()
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self._chunk_size_ms = 80
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self._chunk_size_bytes = 0
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def can_generate_metrics(self) -> bool:
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"""Check if the service can generate metrics.
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Returns:
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True if metrics generation is supported.
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"""
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return True
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async def start(self, frame: StartFrame):
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"""Start the speech-to-text service.
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Args:
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frame: Start frame to begin processing.
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"""
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await super().start(frame)
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self._chunk_size_bytes = int(self._chunk_size_ms * self._sample_rate * 2 / 1000)
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await self._connect()
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async def stop(self, frame: EndFrame):
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"""Stop the speech-to-text service.
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Args:
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frame: End frame to stop processing.
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"""
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await super().stop(frame)
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await self._disconnect()
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async def cancel(self, frame: CancelFrame):
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"""Cancel the speech-to-text service.
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Args:
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frame: Cancel frame to abort processing.
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"""
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await super().cancel(frame)
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await self._disconnect()
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async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
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"""Process audio data for speech-to-text conversion.
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Args:
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audio: Raw audio bytes to process.
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Yields:
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None (processing handled via WebSocket messages).
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"""
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self._audio_buffer.extend(audio)
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while len(self._audio_buffer) >= self._chunk_size_bytes:
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chunk = bytes(self._audio_buffer[: self._chunk_size_bytes])
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self._audio_buffer = self._audio_buffer[self._chunk_size_bytes :]
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chunk = base64.b64encode(chunk).decode("utf-8")
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msg = {"type": "audio", "audio": chunk}
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if self._websocket and self._websocket.state is State.OPEN:
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await self._websocket.send(json.dumps(msg))
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yield None
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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"""Process frames for VAD and metrics handling.
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Args:
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frame: Frame to process.
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direction: Direction of frame processing.
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"""
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await super().process_frame(frame, direction)
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if isinstance(frame, UserStartedSpeakingFrame):
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await self.start_ttfb_metrics()
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elif isinstance(frame, UserStoppedSpeakingFrame):
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await self.start_processing_metrics()
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@traced_stt
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async def _trace_transcription(self, transcript: str, is_final: bool, language: Language):
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"""Record transcription event for tracing."""
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pass
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async def _connect(self):
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await self._connect_websocket()
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if self._websocket and not self._receive_task:
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self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
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async def _connect_websocket(self):
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try:
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if self._websocket and self._websocket.state is State.OPEN:
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return
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ws_url = self._api_endpoint_base_url
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headers = {
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"x-api-key": self._api_key,
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"x-api-source": "pipecat",
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}
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self._websocket = await websocket_connect(
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ws_url,
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additional_headers=headers,
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)
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await self._call_event_handler("on_connected")
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setup_msg = {
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"type": "setup",
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"input_format": "pcm",
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}
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if self._json_config is not None:
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setup_msg["json_config"] = self._json_config
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await self._websocket.send(json.dumps(setup_msg))
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ready_msg = await self._websocket.recv()
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ready_msg = json.loads(ready_msg)
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if ready_msg["type"] == "error":
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raise Exception(f"received error {ready_msg['message']}")
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if ready_msg["type"] != "ready":
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raise Exception(f"unexpected first message type {ready_msg['type']}")
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except Exception as e:
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logger.error(f"{self}: unable to connect to Gradium: {e}")
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raise
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async def _disconnect(self):
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if self._receive_task:
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await self.cancel_task(self._receive_task)
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self._receive_task = None
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await self._disconnect_websocket()
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async def _disconnect_websocket(self):
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try:
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if self._websocket and self._websocket.state is State.OPEN:
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logger.debug("Disconnecting from Gradium STT")
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await self._websocket.close()
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except Exception as e:
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logger.error(f"{self} error closing websocket: {e}")
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finally:
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self._websocket = None
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await self._call_event_handler("on_disconnected")
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def _get_websocket(self):
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if self._websocket:
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return self._websocket
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raise Exception("Websocket not connected")
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async def _process_messages(self):
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async for message in self._get_websocket():
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try:
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data = json.loads(message)
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await self._process_response(data)
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except json.JSONDecodeError:
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logger.warning(f"Received non-JSON message: {message}")
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async def _receive_messages(self):
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while True:
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await self._process_messages()
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logger.debug(f"{self} Gradium connection was disconnected (timeout?), reconnecting")
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await self._connect_websocket()
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async def _process_response(self, msg):
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type_ = msg.get("type", "")
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if type_ == "text":
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await self._handle_text(msg["text"])
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elif type_ == "end_of_stream":
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await self._handle_end_of_stream()
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elif type_ == "error":
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logger.error(f"Gradium error: {msg.get('message', 'Unknown error')}")
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async def _handle_end_of_stream(self):
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"""Handle termination message."""
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logger.info("Received end_of_stream message from server")
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await self.push_frame(EndFrame())
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async def _handle_text(self, text: str):
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"""Handle transcription results."""
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await self.push_frame(
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TranscriptionFrame(
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text,
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self._user_id,
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time_now_iso8601(),
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)
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)
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338
src/pipecat/services/gradium/tts.py
Normal file
338
src/pipecat/services/gradium/tts.py
Normal file
@@ -0,0 +1,338 @@
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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"""Gradium Text-to-Speech service implementation."""
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import base64
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import json
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import uuid
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from typing import Any, AsyncGenerator, Mapping, Optional
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from loguru import logger
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from pydantic import BaseModel
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from pipecat.frames.frames import (
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CancelFrame,
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EndFrame,
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ErrorFrame,
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Frame,
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InterruptionFrame,
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StartFrame,
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TTSAudioRawFrame,
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TTSStartedFrame,
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TTSStoppedFrame,
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)
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.services.tts_service import InterruptibleWordTTSService
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from pipecat.utils.tracing.service_decorators import traced_tts
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try:
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from websockets import ConnectionClosedOK
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from websockets.asyncio.client import connect as websocket_connect
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from websockets.protocol import State
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except ModuleNotFoundError as e:
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logger.error(f"Exception: {e}")
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logger.error("In order to use Gradium, you need to `pip install pipecat-ai[gradium]`.")
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raise Exception(f"Missing module: {e}")
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SAMPLE_RATE = 48000
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class GradiumTTSService(InterruptibleWordTTSService):
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"""Text-to-Speech service using Gradium's websocket API."""
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class InputParams(BaseModel):
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"""Configuration parameters for Gradium TTS service.
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Parameters:
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temp: Temperature to be used for generation, defaults to 0.6.
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"""
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temp: Optional[float] = 0.6
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def __init__(
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self,
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*,
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api_key: str,
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voice: Optional[str] = None,
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voice_id: Optional[str] = None,
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url: str = "wss://eu.api.gradium.ai/api/speech/tts",
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model: str = "default",
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json_config: Optional[str] = None,
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params: Optional[InputParams] = None,
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**kwargs,
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):
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"""Initialize the Gradium TTS service.
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The voice used in the generation is specified by setting either the `voice` argument
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for catalog voices or the `voice_id` argument for custom voices.
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Args:
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api_key: Gradium API key for authentication.
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voice: name for a catalog voice.
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voice_id: identifier for a custom voice.
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url: Gradium websocket API endpoint.
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model: Model ID to use for synthesis.
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json_config: Optional JSON configuration string for additional model settings.
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params: Additional configuration parameters.
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**kwargs: Additional arguments passed to parent class.
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"""
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# Initialize with parent class settings for proper frame handling
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super().__init__(
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push_stop_frames=True,
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pause_frame_processing=True,
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sample_rate=SAMPLE_RATE,
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**kwargs,
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)
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if voice is None and voice_id is None:
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raise ValueError("one of voice and voice_id has to be set")
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if voice is not None and voice_id is not None:
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raise ValueError("voice and voice_id cannot be set at the same time")
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params = params or GradiumTTSService.InputParams()
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# Store service configuration
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self._api_key = api_key
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self._url = url
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self._voice = voice
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self._voice_id = voice_id
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self._json_config = json_config
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self._model = model
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self._settings = {
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"voice": voice,
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"voice_id": voice_id,
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"model_name": model,
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"output_format": "pcm",
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}
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# State tracking
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self._receive_task = None
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self._request_id = None
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def can_generate_metrics(self) -> bool:
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"""Check if this service can generate processing metrics.
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Returns:
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True, as Gradium service supports metrics generation.
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"""
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return True
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async def set_model(self, model: str):
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"""Update the TTS model.
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Args:
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model: The model name to use for synthesis.
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"""
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self._model = model
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await super().set_model(model)
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async def _update_settings(self, settings: Mapping[str, Any]):
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"""Update service settings and reconnect if voice changed."""
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prev_voice = self._voice_id
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await super()._update_settings(settings)
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if not prev_voice == self._voice_id:
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self._settings["voice_id"] = self._voice_id
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logger.info(f"Switching TTS voice to: [{self._voice_id}]")
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await self._disconnect()
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await self._connect()
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def _build_msg(self, text: str = "") -> dict:
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"""Build JSON message for Gradium API."""
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return {"text": text, "type": "text"}
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async def start(self, frame: StartFrame):
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"""Start the service and establish websocket connection.
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Args:
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frame: The start frame containing initialization parameters.
|
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"""
|
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await super().start(frame)
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await self._connect()
|
||||
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async def stop(self, frame: EndFrame):
|
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"""Stop the service and close connection.
|
||||
|
||||
Args:
|
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frame: The end frame.
|
||||
"""
|
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await super().stop(frame)
|
||||
await self._disconnect()
|
||||
|
||||
async def cancel(self, frame: CancelFrame):
|
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"""Cancel current operation and clean up.
|
||||
|
||||
Args:
|
||||
frame: The cancel frame.
|
||||
"""
|
||||
await super().cancel(frame)
|
||||
await self._disconnect()
|
||||
|
||||
async def _connect(self):
|
||||
"""Establish websocket connection and start receive task."""
|
||||
logger.debug(f"{self}: connecting")
|
||||
|
||||
# If the server disconnected, cancel the receive-task so that it can be reset below.
|
||||
if self._websocket is None or self._websocket.state is not State.OPEN:
|
||||
if self._receive_task:
|
||||
await self.cancel_task(self._receive_task)
|
||||
self._receive_task = None
|
||||
|
||||
await self._connect_websocket()
|
||||
|
||||
if self._websocket and not self._receive_task:
|
||||
logger.debug(f"{self}: setting receive task")
|
||||
self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
|
||||
|
||||
async def _disconnect(self):
|
||||
"""Close websocket connection and clean up tasks."""
|
||||
logger.debug(f"{self}: disconnecting")
|
||||
if self._receive_task:
|
||||
await self.cancel_task(self._receive_task)
|
||||
self._receive_task = None
|
||||
|
||||
await self._disconnect_websocket()
|
||||
|
||||
async def _connect_websocket(self):
|
||||
"""Connect to Gradium websocket API with configured settings."""
|
||||
try:
|
||||
if self._websocket and self._websocket.state is State.OPEN:
|
||||
return
|
||||
|
||||
headers = {"x-api-key": self._api_key, "x-api-source": "pipecat"}
|
||||
self._websocket = await websocket_connect(self._url, additional_headers=headers)
|
||||
|
||||
setup_msg = {
|
||||
"type": "setup",
|
||||
"output_format": "pcm",
|
||||
}
|
||||
if self._json_config is not None:
|
||||
setup_msg["json_config"] = self._json_config
|
||||
if self._voice is not None:
|
||||
setup_msg["voice"] = self._voice
|
||||
if self._voice_id is not None:
|
||||
setup_msg["voice_id"] = self._voice_id
|
||||
await self._websocket.send(json.dumps(setup_msg))
|
||||
ready_msg = await self._websocket.recv()
|
||||
ready_msg = json.loads(ready_msg)
|
||||
if ready_msg["type"] == "error":
|
||||
raise Exception(f"received error {ready_msg['message']}")
|
||||
if ready_msg["type"] != "ready":
|
||||
raise Exception(f"unexpected first message type {ready_msg['type']}")
|
||||
|
||||
await self._call_event_handler("on_connected")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} initialization error: {e}")
|
||||
self._websocket = None
|
||||
await self._call_event_handler("on_connection_error", f"{e}")
|
||||
|
||||
async def _disconnect_websocket(self):
|
||||
"""Close websocket connection and reset state."""
|
||||
try:
|
||||
await self.stop_all_metrics()
|
||||
if self._websocket:
|
||||
await self._websocket.close()
|
||||
except Exception as e:
|
||||
logger.error(f"{self} error closing websocket: {e}")
|
||||
finally:
|
||||
self._websocket = None
|
||||
self._request_id = None
|
||||
await self._call_event_handler("on_disconnected")
|
||||
|
||||
def _get_websocket(self):
|
||||
"""Get active websocket connection or raise exception."""
|
||||
if self._websocket:
|
||||
return self._websocket
|
||||
raise Exception("Websocket not connected")
|
||||
|
||||
async def flush_audio(self):
|
||||
"""Flush any pending audio synthesis."""
|
||||
if not self._websocket:
|
||||
return
|
||||
try:
|
||||
msg = {"type": "end_of_stream"}
|
||||
await self._websocket.send(json.dumps(msg))
|
||||
logger.trace(f"{self}: flushing audio")
|
||||
except ConnectionClosedOK:
|
||||
logger.debug(f"{self}: connection closed normally during flush")
|
||||
except Exception as e:
|
||||
logger.error(f"{self} exception: {e}")
|
||||
|
||||
async def _receive_messages(self):
|
||||
"""Process incoming websocket messages."""
|
||||
# TODO(laurent): This should not be necessary as it should happen when
|
||||
# receiving the messages but this does not seem to always be the case
|
||||
# and that may lead to a busy polling loop.
|
||||
if self._websocket and self._websocket.state is State.CLOSED:
|
||||
raise ConnectionClosedOK(None, None)
|
||||
async for message in self._get_websocket():
|
||||
msg = json.loads(message)
|
||||
|
||||
if msg["type"] == "audio":
|
||||
# Process audio chunk
|
||||
await self.stop_ttfb_metrics()
|
||||
self.start_word_timestamps()
|
||||
frame = TTSAudioRawFrame(
|
||||
audio=base64.b64decode(msg["audio"]),
|
||||
sample_rate=self.sample_rate,
|
||||
num_channels=1,
|
||||
)
|
||||
await self.push_frame(frame)
|
||||
|
||||
elif msg["type"] == "text":
|
||||
await self.add_word_timestamps([(msg["text"], msg["start_s"])])
|
||||
elif msg["type"] == "end_of_stream":
|
||||
await self.push_frame(TTSStoppedFrame())
|
||||
await self.stop_all_metrics()
|
||||
|
||||
elif msg["type"] == "error":
|
||||
logger.error(f"{self} error: {msg}")
|
||||
await self.push_frame(TTSStoppedFrame())
|
||||
await self.stop_all_metrics()
|
||||
await self.push_error(ErrorFrame(f"{self} error: {msg['message']}"))
|
||||
|
||||
async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
|
||||
"""Push frame and handle end-of-turn conditions.
|
||||
|
||||
Args:
|
||||
frame: The frame to push.
|
||||
direction: The direction to push the frame.
|
||||
"""
|
||||
await super().push_frame(frame, direction)
|
||||
|
||||
@traced_tts
|
||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||
"""Generate speech from text using Gradium's streaming API.
|
||||
|
||||
Args:
|
||||
text: The text to convert to speech.
|
||||
|
||||
Yields:
|
||||
Frame: Audio frames containing the synthesized speech.
|
||||
"""
|
||||
_state = self._websocket.state if self._websocket is not None else None
|
||||
logger.debug(f"{self}: Generating TTS [{text}] {_state}")
|
||||
try:
|
||||
if not self._websocket or self._websocket.state is State.CLOSED:
|
||||
self._websocket = None
|
||||
await self._connect()
|
||||
|
||||
try:
|
||||
if not self._request_id:
|
||||
await self.start_ttfb_metrics()
|
||||
yield TTSStartedFrame()
|
||||
self._request_id = str(uuid.uuid4())
|
||||
|
||||
msg = self._build_msg(text=text)
|
||||
await self._get_websocket().send(json.dumps(msg))
|
||||
await self.start_tts_usage_metrics(text)
|
||||
except Exception as e:
|
||||
logger.error(f"{self} error sending message: {e}")
|
||||
yield TTSStoppedFrame()
|
||||
await self._disconnect()
|
||||
await self._connect()
|
||||
return
|
||||
yield None
|
||||
except Exception as e:
|
||||
logger.error(f"{self} exception: {e}")
|
||||
Reference in New Issue
Block a user