162 lines
4.9 KiB
Python
162 lines
4.9 KiB
Python
#
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# Copyright (c) 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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import os
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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 pipecatcloud.agent import DailySessionArguments
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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.cartesia.tts import CartesiaTTSService
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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# Check if we're in local development mode
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LOCAL_RUN = os.getenv("LOCAL_RUN")
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if LOCAL_RUN:
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import asyncio
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import webbrowser
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try:
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from local_runner import configure
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except ImportError:
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logger.error("Could not import local_runner module. Local development mode may not work.")
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# Load environment variables
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load_dotenv(override=True)
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async def main(room_url: str, token: str):
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"""Main pipeline setup and execution function.
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Args:
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room_url: The Daily room URL
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token: The Daily room token
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"""
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logger.debug("Starting bot in room: {}", room_url)
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transport = DailyTransport(
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room_url,
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token,
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"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 = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY"), voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22"
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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(),
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context_aggregator.user(),
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llm,
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tts,
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transport.output(),
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context_aggregator.assistant(),
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]
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)
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task = PipelineTask(
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pipeline,
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params=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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logger.info("First participant joined: {}", participant["id"])
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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(
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{
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"role": "system",
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"content": "Please start with 'Hello World' and introduce yourself to the user.",
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}
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)
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await task.queue_frames([LLMMessagesFrame(messages)])
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@transport.event_handler("on_participant_left")
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async def on_participant_left(transport, participant, reason):
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logger.info("Participant left: {}", participant)
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await task.cancel()
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runner = PipelineRunner()
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await runner.run(task)
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async def bot(args: DailySessionArguments):
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"""Main bot entry point compatible with the FastAPI route handler.
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Args:
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room_url: The Daily room URL
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token: The Daily room token
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body: The configuration object from the request body
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session_id: The session ID for logging
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"""
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logger.info(f"Bot process initialized {args.room_url} {args.token}")
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try:
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await main(args.room_url, args.token)
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logger.info("Bot process completed")
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except Exception as e:
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logger.exception(f"Error in bot process: {str(e)}")
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raise
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# Local development functions
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async def local_main():
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"""Function for local development testing."""
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try:
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async with aiohttp.ClientSession() as session:
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(room_url, token) = await configure(session)
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logger.warning("_")
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logger.warning("_")
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logger.warning(f"Talk to your voice agent here: {room_url}")
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logger.warning("_")
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logger.warning("_")
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webbrowser.open(room_url)
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await main(room_url, token)
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except Exception as e:
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logger.exception(f"Error in local development mode: {e}")
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# Local development entry point
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if LOCAL_RUN and __name__ == "__main__":
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try:
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asyncio.run(local_main())
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except Exception as e:
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logger.exception(f"Failed to run in local mode: {e}")
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