112 lines
3.5 KiB
Python
112 lines
3.5 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 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.frames.frames import Frame, TextFrame, UserImageRequestFrame
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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 PipelineTask
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from pipecat.processors.aggregators.user_response import UserResponseAggregator
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from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
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from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
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from pipecat.services.cartesia import CartesiaTTSService
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from pipecat.services.google import GoogleLLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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from pipecat.vad.silero import SileroVADAnalyzer
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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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class UserImageRequester(FrameProcessor):
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def __init__(self, participant_id: str | None = None):
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super().__init__()
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self._participant_id = participant_id
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def set_participant_id(self, participant_id: str):
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self._participant_id = participant_id
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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 self._participant_id and isinstance(frame, TextFrame):
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await self.push_frame(
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UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
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)
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await self.push_frame(frame, direction)
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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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"Describe participant video",
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DailyParams(
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audio_in_enabled=True, # This is so Silero VAD can get audio data
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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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user_response = UserResponseAggregator()
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image_requester = UserImageRequester()
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vision_aggregator = VisionImageFrameAggregator()
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google = GoogleLLMService(
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model="gemini-1.5-flash-latest", api_key=os.getenv("GOOGLE_API_KEY")
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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="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
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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 tts.say("Hi there! Feel free to ask me what I see.")
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transport.capture_participant_video(participant["id"], framerate=0)
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transport.capture_participant_transcription(participant["id"])
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image_requester.set_participant_id(participant["id"])
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pipeline = Pipeline(
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[
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transport.input(),
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user_response,
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image_requester,
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vision_aggregator,
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google,
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tts,
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transport.output(),
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]
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)
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task = PipelineTask(pipeline)
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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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