Merge pull request #716 from pipecat-ai/mb/mute-stt-service
Add STTMuteFilter to un/mute the STT
This commit is contained in:
@@ -11,6 +11,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- Added `RimeHttpTTSService` and the `07q-interruptible-rime.py` foundational
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- Added `RimeHttpTTSService` and the `07q-interruptible-rime.py` foundational
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example.
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example.
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- Added `STTMuteFilter`, a general-purpose processor that combines STT
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muting and interruption control. When active, it prevents both transcription
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and interruptions during bot speech. The processor supports multiple
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strategies: `FIRST_SPEECH` (mute only during bot's first
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speech), `ALWAYS` (mute during all bot speech), or `CUSTOM` (using provided
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callback).
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- Added `STTMuteFrame`, a control frame that enables/disables speech
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transcription in STT services.
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## [0.0.48] - 2024-11-10 "Antonio release"
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## [0.0.48] - 2024-11-10 "Antonio release"
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98
examples/foundational/24-stt-mute-filter.py
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98
examples/foundational/24-stt-mute-filter.py
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@@ -0,0 +1,98 @@
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#
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# Copyright (c) 2024, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import asyncio
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import os
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import sys
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import aiohttp
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from dotenv import load_dotenv
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from loguru import logger
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from runner import configure
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import (
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LLMMessagesFrame,
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)
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.processors.filters.stt_mute_filter import STTMuteConfig, STTMuteFilter, STTMuteStrategy
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from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
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from pipecat.services.openai import OpenAILLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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load_dotenv(override=True)
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logger.remove(0)
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logger.add(sys.stderr, level="DEBUG")
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async def main():
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async with aiohttp.ClientSession() as session:
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(room_url, _) = await configure(session)
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transport = DailyTransport(
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room_url,
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None,
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"Respond bot",
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DailyParams(
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audio_out_enabled=True,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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vad_audio_passthrough=True,
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),
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)
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stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
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# Configure the mute processor to mute only during first speech
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stt_mute_processor = STTMuteFilter(
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stt_service=stt, config=STTMuteConfig(strategy=STTMuteStrategy.FIRST_SPEECH)
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)
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tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
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messages = [
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{
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"role": "system",
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"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
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},
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]
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context = OpenAILLMContext(messages)
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context_aggregator = llm.create_context_aggregator(context)
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pipeline = Pipeline(
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[
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transport.input(), # Transport user input
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stt_mute_processor, # Add the mute processor before STT
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stt, # STT
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context_aggregator.user(), # User responses
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llm, # LLM
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tts, # TTS
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transport.output(), # Transport bot output
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context_aggregator.assistant(), # Assistant spoken responses
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]
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)
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task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
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@transport.event_handler("on_first_participant_joined")
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async def on_first_participant_joined(transport, participant):
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# Kick off the conversation.
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messages.append({"role": "system", "content": "Please introduce yourself to the user."})
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await task.queue_frames([LLMMessagesFrame(messages)])
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runner = PipelineRunner()
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await runner.run(task)
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -570,6 +570,13 @@ class TTSUpdateSettingsFrame(ServiceUpdateSettingsFrame):
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pass
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pass
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@dataclass
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class STTMuteFrame(ControlFrame):
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"""Control frame to mute/unmute the STT service."""
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mute: bool
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@dataclass
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@dataclass
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class STTUpdateSettingsFrame(ServiceUpdateSettingsFrame):
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class STTUpdateSettingsFrame(ServiceUpdateSettingsFrame):
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pass
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pass
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111
src/pipecat/processors/filters/stt_mute_filter.py
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111
src/pipecat/processors/filters/stt_mute_filter.py
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@@ -0,0 +1,111 @@
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#
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# Copyright (c) 2024, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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from dataclasses import dataclass
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from enum import Enum
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from typing import Awaitable, Callable, Optional
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from loguru import logger
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from pipecat.frames.frames import (
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BotStartedSpeakingFrame,
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BotStoppedSpeakingFrame,
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Frame,
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StartInterruptionFrame,
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StopInterruptionFrame,
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STTMuteFrame,
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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, FrameProcessor
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from pipecat.services.ai_services import STTService
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class STTMuteStrategy(Enum):
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FIRST_SPEECH = "first_speech" # Mute only during first bot speech
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ALWAYS = "always" # Mute during all bot speech
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CUSTOM = "custom" # Allow custom logic via callback
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@dataclass
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class STTMuteConfig:
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"""Configuration for STTMuteFilter"""
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strategy: STTMuteStrategy
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# Optional callback for custom muting logic
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should_mute_callback: Optional[Callable[["STTMuteFilter"], Awaitable[bool]]] = None
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class STTMuteFilter(FrameProcessor):
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"""A general-purpose processor that handles STT muting and interruption control.
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This processor combines the concepts of STT muting and interruption control,
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treating them as a single coordinated feature. When STT is muted, interruptions
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are automatically disabled.
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"""
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def __init__(self, stt_service: STTService, config: STTMuteConfig, **kwargs):
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super().__init__(**kwargs)
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self._stt_service = stt_service
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self._config = config
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self._first_speech_handled = False
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self._bot_is_speaking = False
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@property
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def is_muted(self) -> bool:
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"""Returns whether STT is currently muted."""
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return self._stt_service.is_muted
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async def _handle_mute_state(self, should_mute: bool):
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"""Handles both STT muting and interruption control."""
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if should_mute != self.is_muted:
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logger.debug(f"STT {'muting' if should_mute else 'unmuting'}")
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await self.push_frame(STTMuteFrame(mute=should_mute))
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async def _should_mute(self) -> bool:
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"""Determines if STT should be muted based on current state and strategy."""
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if not self._bot_is_speaking:
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return False
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if self._config.strategy == STTMuteStrategy.ALWAYS:
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return True
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elif (
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self._config.strategy == STTMuteStrategy.FIRST_SPEECH and not self._first_speech_handled
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):
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self._first_speech_handled = True
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return True
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elif self._config.strategy == STTMuteStrategy.CUSTOM and self._config.should_mute_callback:
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return await self._config.should_mute_callback(self)
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return False
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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# Handle bot speaking state changes
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if isinstance(frame, BotStartedSpeakingFrame):
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self._bot_is_speaking = True
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await self._handle_mute_state(await self._should_mute())
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elif isinstance(frame, BotStoppedSpeakingFrame):
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self._bot_is_speaking = False
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await self._handle_mute_state(await self._should_mute())
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# Handle frame propagation
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if isinstance(
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frame,
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(
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StartInterruptionFrame,
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StopInterruptionFrame,
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UserStartedSpeakingFrame,
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UserStoppedSpeakingFrame,
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),
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):
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# Only pass VAD-related frames when not muted
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if not self.is_muted:
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await self.push_frame(frame, direction)
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else:
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logger.debug(f"{frame.__class__.__name__} suppressed - STT currently muted")
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else:
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# Pass all other frames through
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await self.push_frame(frame, direction)
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@@ -22,6 +22,7 @@ from pipecat.frames.frames import (
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LLMFullResponseEndFrame,
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LLMFullResponseEndFrame,
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StartFrame,
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StartFrame,
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StartInterruptionFrame,
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StartInterruptionFrame,
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STTMuteFrame,
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STTUpdateSettingsFrame,
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STTUpdateSettingsFrame,
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TextFrame,
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TextFrame,
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TTSAudioRawFrame,
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TTSAudioRawFrame,
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@@ -454,6 +455,12 @@ class STTService(AIService):
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super().__init__(**kwargs)
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super().__init__(**kwargs)
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self._audio_passthrough = audio_passthrough
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self._audio_passthrough = audio_passthrough
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self._settings: Dict[str, Any] = {}
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self._settings: Dict[str, Any] = {}
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self._muted: bool = False
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@property
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def is_muted(self) -> bool:
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"""Returns whether the STT service is currently muted."""
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return self._muted
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@abstractmethod
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@abstractmethod
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async def set_model(self, model: str):
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async def set_model(self, model: str):
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@@ -482,7 +489,8 @@ class STTService(AIService):
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logger.warning(f"Unknown setting for STT service: {key}")
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logger.warning(f"Unknown setting for STT service: {key}")
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async def process_audio_frame(self, frame: AudioRawFrame):
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async def process_audio_frame(self, frame: AudioRawFrame):
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await self.process_generator(self.run_stt(frame.audio))
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if not self._muted:
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await self.process_generator(self.run_stt(frame.audio))
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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"""Processes a frame of audio data, either buffering or transcribing it."""
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"""Processes a frame of audio data, either buffering or transcribing it."""
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@@ -497,6 +505,9 @@ class STTService(AIService):
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await self.push_frame(frame, direction)
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await self.push_frame(frame, direction)
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elif isinstance(frame, STTUpdateSettingsFrame):
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elif isinstance(frame, STTUpdateSettingsFrame):
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await self._update_settings(frame.settings)
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await self._update_settings(frame.settings)
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elif isinstance(frame, STTMuteFrame):
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self._muted = frame.mute
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logger.debug(f"STT service {'muted' if frame.mute else 'unmuted'}")
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else:
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else:
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await self.push_frame(frame, direction)
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await self.push_frame(frame, direction)
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