afa880f523
Register the worker with PipelineRunner.add_workers() before calling run() instead. The worker argument still works but now emits a DeprecationWarning and will be removed in a future release. Update the runner docstrings, the run_test() helper, and all examples (including the asyncio.gather() forms) to use the new pattern.
122 lines
4.0 KiB
Python
122 lines
4.0 KiB
Python
#
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# Copyright (c) 2024-2026, 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 pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import LLMRunFrame
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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.worker import PipelineParams, PipelineWorker
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from pipecat.processors.aggregators.llm_response_universal import (
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LLMContext,
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LLMContextAggregatorPair,
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LLMUserAggregatorParams,
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)
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from pipecat.services.cartesia.tts import CartesiaTTSService
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.google.llm import GoogleLLMService
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from pipecat.services.heygen.api_liveavatar import LiveAvatarNewSessionRequest
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from pipecat.transports.heygen.transport import HeyGenParams, HeyGenTransport, ServiceType
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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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transport = HeyGenTransport(
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api_key=os.environ["HEYGEN_LIVE_AVATAR_API_KEY"],
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service_type=ServiceType.LIVE_AVATAR,
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session=session,
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params=HeyGenParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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session_request=LiveAvatarNewSessionRequest(
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is_sandbox=True,
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# Sandbox mode only works with this specific avatar
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# https://docs.liveavatar.com/docs/developing-in-sandbox-mode#sandbox-mode-behaviors
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avatar_id="dd73ea75-1218-4ef3-92ce-606d5f7fbc0a",
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),
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)
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stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
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tts = CartesiaTTSService(
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api_key=os.environ["CARTESIA_API_KEY"],
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settings=CartesiaTTSService.Settings(
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voice="00967b2f-88a6-4a31-8153-110a92134b9f",
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),
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)
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llm = GoogleLLMService(
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api_key=os.environ["GOOGLE_API_KEY"],
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settings=GoogleLLMService.Settings(
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system_instruction="You are a helpful assistant. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Be succinct and 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 = LLMContext()
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user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
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)
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pipeline = Pipeline(
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[
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transport.input(), # Transport user input
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stt, # STT
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user_aggregator, # 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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assistant_aggregator, # Assistant spoken responses
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]
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)
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worker = PipelineWorker(
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pipeline,
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params=PipelineParams(
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enable_metrics=True,
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enable_usage_metrics=True,
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),
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)
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@transport.event_handler("on_client_connected")
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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# Kick off the conversation.
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context.add_message(
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{
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"role": "developer",
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"content": "Start by saying 'Hello' and then a short greeting.",
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}
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)
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await worker.queue_frames([LLMRunFrame()])
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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logger.info(f"Client disconnected")
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await worker.cancel()
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runner = PipelineRunner()
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await runner.add_workers(worker)
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await runner.run()
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if __name__ == "__main__":
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asyncio.run(main())
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