Add Fish Audio TTS service
This commit is contained in:
Mark Backman
99
examples/foundational/07t-interruptible-fish.py
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99
examples/foundational/07t-interruptible-fish.py
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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 LLMMessagesFrame
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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.services.fish import FishAudioTTSService
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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, token) = await configure(session)
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transport = DailyTransport(
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room_url,
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token,
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"Respond bot",
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DailyParams(
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audio_out_enabled=True,
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transcription_enabled=True,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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),
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)
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tts = FishAudioTTSService(
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api_key=os.getenv("FISH_API_KEY"),
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model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama
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)
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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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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(
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pipeline,
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PipelineParams(
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allow_interruptions=True,
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enable_metrics=True,
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enable_usage_metrics=True,
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report_only_initial_ttfb=True,
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),
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)
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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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await transport.capture_participant_transcription(participant["id"])
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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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@@ -50,6 +50,7 @@ daily = [ "daily-python~=0.14.0" ]
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deepgram = [ "deepgram-sdk~=3.7.7" ]
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elevenlabs = [ "websockets~=13.1" ]
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fal = [ "fal-client~=0.4.1" ]
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fish = [ "ormsgpack~=1.7.0", "websockets~=13.1" ]
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gladia = [ "websockets~=13.1" ]
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google = [ "google-generativeai~=0.8.3", "google-cloud-texttospeech~=2.21.1" ]
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grok = [ "openai~=1.57.2" ]
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234
src/pipecat/services/fish.py
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234
src/pipecat/services/fish.py
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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 uuid
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from typing import AsyncGenerator, Literal, Optional
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from loguru import logger
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from pydantic import BaseModel
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from tenacity import AsyncRetrying, RetryCallState, stop_after_attempt, wait_exponential
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from pipecat.frames.frames import (
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BotStoppedSpeakingFrame,
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CancelFrame,
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EndFrame,
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ErrorFrame,
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Frame,
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LLMFullResponseEndFrame,
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StartFrame,
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StartInterruptionFrame,
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TTSAudioRawFrame,
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TTSSpeakFrame,
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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.ai_services import TTSService
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from pipecat.transcriptions.language import Language
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try:
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import ormsgpack
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import websockets
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except ModuleNotFoundError as e:
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logger.error(f"Exception: {e}")
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logger.error(
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"In order to use Fish Audio, you need to `pip install pipecat-ai[fish]`. Also, set `FISH_API_KEY` environment variable."
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)
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raise Exception(f"Missing module: {e}")
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# FishAudio supports various output formats
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FishAudioOutputFormat = Literal["opus", "mp3", "pcm", "wav"]
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class FishAudioTTSService(TTSService):
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class InputParams(BaseModel):
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language: Optional[Language] = Language.EN
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latency: Optional[str] = "normal" # "normal" or "balanced"
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prosody_speed: Optional[float] = 1.0 # Speech speed (0.5-2.0)
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prosody_volume: Optional[int] = 0 # Volume adjustment in dB
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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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model: str, # This is the reference_id
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output_format: FishAudioOutputFormat = "pcm",
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sample_rate: int = 24000,
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params: InputParams = InputParams(),
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**kwargs,
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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._base_url = "wss://api.fish.audio/v1/tts/live"
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self._websocket = None
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self._receive_task = None
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self._request_id = None
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self._started = False
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self._settings = {
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"sample_rate": sample_rate,
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"latency": params.latency,
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"format": output_format,
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"prosody": {
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"speed": params.prosody_speed,
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"volume": params.prosody_volume,
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},
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"reference_id": model,
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}
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self.set_model_name(model)
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def can_generate_metrics(self) -> bool:
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return True
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async def set_model(self, model: str):
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self._settings["reference_id"] = model
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await super().set_model(model)
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logger.info(f"Switching TTS model to: [{model}]")
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async def start(self, frame: StartFrame):
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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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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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await super().cancel(frame)
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await self._disconnect()
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async def _connect(self):
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await self._connect_websocket()
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self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
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async def _disconnect(self):
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await self._disconnect_websocket()
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if self._receive_task:
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self._receive_task.cancel()
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await self._receive_task
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self._receive_task = None
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async def _connect_websocket(self):
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try:
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logger.debug("Connecting to Fish Audio")
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headers = {"Authorization": f"Bearer {self._api_key}"}
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self._websocket = await websockets.connect(self._base_url, extra_headers=headers)
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# Send initial start message with ormsgpack
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start_message = {"event": "start", "request": {"text": "", **self._settings}}
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await self._websocket.send(ormsgpack.packb(start_message))
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logger.debug("Sent start message to Fish Audio")
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except Exception as e:
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logger.error(f"Fish Audio initialization error: {e}")
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self._websocket = None
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async def _disconnect_websocket(self):
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try:
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await self.stop_all_metrics()
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if self._websocket:
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logger.debug("Disconnecting from Fish Audio")
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# Send stop event with ormsgpack
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stop_message = {"event": "stop"}
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await self._websocket.send(ormsgpack.packb(stop_message))
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await self._websocket.close()
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self._websocket = None
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self._request_id = None
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self._started = False
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except Exception as e:
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logger.error(f"Error closing websocket: {e}")
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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 _receive_messages(self):
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async for message in self._get_websocket():
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try:
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if isinstance(message, bytes):
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msg = ormsgpack.unpackb(message)
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if isinstance(msg, dict):
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event = msg.get("event")
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print(f"Received event: {event}")
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if event == "audio":
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await self.stop_ttfb_metrics()
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audio_data = msg.get("audio")
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# Only process larger chunks to remove msgpack overhead
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if audio_data and len(audio_data) > 1024:
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frame = TTSAudioRawFrame(
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audio_data, self._settings["sample_rate"], 1
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)
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await self.push_frame(frame)
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continue
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except Exception as e:
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logger.error(f"Error processing message: {e}")
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async def _reconnect_websocket(self, retry_state: RetryCallState):
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logger.warning(f"Fish Audio reconnecting (attempt: {retry_state.attempt_number})")
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await self._disconnect_websocket()
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await self._connect_websocket()
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async def _receive_task_handler(self):
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while True:
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try:
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async for attempt in AsyncRetrying(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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before_sleep=self._reconnect_websocket,
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reraise=True,
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):
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with attempt:
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await self._receive_messages()
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except asyncio.CancelledError:
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break
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except Exception as e:
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message = f"Fish Audio error receiving messages: {e}"
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logger.error(message)
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await self.push_error(ErrorFrame(message, fatal=True))
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break
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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await super().process_frame(frame, direction)
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if isinstance(frame, TTSSpeakFrame):
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await self.pause_processing_frames()
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elif isinstance(frame, LLMFullResponseEndFrame) and self._request_id:
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await self.pause_processing_frames()
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elif isinstance(frame, BotStoppedSpeakingFrame):
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await self.resume_processing_frames()
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async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
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await super()._handle_interruption(frame, direction)
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await self.stop_all_metrics()
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self._request_id = None
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async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
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logger.debug(f"Generating Fish TTS: [{text}]")
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try:
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if not self._websocket or self._websocket.closed:
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await self._connect()
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if not self._request_id:
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await self.start_ttfb_metrics()
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yield TTSStartedFrame()
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self._request_id = str(uuid.uuid4())
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text_message = {
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"event": "text",
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"text": text,
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}
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await self._get_websocket().send(ormsgpack.packb(text_message))
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await self.start_tts_usage_metrics(text)
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yield None
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except Exception as e:
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logger.error(f"Error generating TTS: {e}")
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yield ErrorFrame(f"Error: {str(e)}")
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