29ca1b7855
* processors(rtvi): rtvi 0.1 message protocol * added a single function call handler * wip - function calling * fixup * fixup * fixup * processors(rtvi): no need for configure_on_start() * processors(rtvi): add new option values if they haven't been set yet * Add the model name to the LLM usage metrics * wip - anthropic tool calling * still wip - anthropic tool use and vision * anthropic tools and vision working * anthropic tool calling and vision * Cartesia error handling * Anthropic tool use core Pipecat pieces refactored as per plan * aleix has good ideas * Usage metrics for Anthropic LLMs * fix function call result state not getting cleared bug * Pass **kwargs through from AnthropicLLMService constructor * about to tinker with anthropic * added openai function calling * openai function calling * fixup --------- Co-authored-by: Aleix Conchillo Flaqué <aleix@daily.co> Co-authored-by: Chad Bailey <chadbailey@gmail.com> Co-authored-by: mattie ruth backman <mattieruth@gmail.com> Co-authored-by: chadbailey59 <chadbailey59@users.noreply.github.com>
109 lines
3.3 KiB
Python
109 lines
3.3 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.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.anthropic import AnthropicLLMService
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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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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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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(UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM)
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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_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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anthropic = AnthropicLLMService(
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api_key=os.getenv("ANTHROPIC_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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sample_rate=16000,
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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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transport.input(),
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user_response,
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image_requester,
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vision_aggregator,
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anthropic,
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tts,
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transport.output()
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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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