106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
#
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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 aiohttp
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import os
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import sys
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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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.frames.frames import LLMMessagesFrame
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from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.services.cartesia import CartesiaTTSService
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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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from runner import configure
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from loguru import logger
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from dotenv import load_dotenv
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from simli import SimliConfig
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from pipecat.services.simli import SimliVideoService
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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, token = await configure(session)
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transport = DailyTransport(
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room,
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token,
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"Simli",
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DailyParams(
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audio_out_enabled=True,
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camera_out_enabled=True,
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camera_out_width=512,
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camera_out_height=512,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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transcription_enabled=True,
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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"),
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voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab",
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)
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simli_ai = SimliVideoService(
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SimliConfig(os.getenv("SIMLI_API_KEY"), os.getenv("SIMLI_FACE_ID"))
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)
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-mini")
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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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simli_ai,
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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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PipelineParams(
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allow_interruptions=True,
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enable_metrics=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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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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