6664c492ac
Add options to transcribe both user and model audio during the GeminiMultimodalLiveLLMService setup in the 26d-gemini-multimodal-live-text.py example.
93 lines
2.6 KiB
Python
93 lines
2.6 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.audio.vad.silero import SileroVADAnalyzer
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from pipecat.audio.vad.vad_analyzer import VADParams
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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.services.cartesia import CartesiaTTSService
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from pipecat.services.gemini_multimodal_live.gemini import (
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GeminiMultimodalLiveLLMService,
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GeminiMultimodalModalities,
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)
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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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_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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"Respond bot",
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DailyParams(
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audio_in_sample_rate=16000,
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audio_out_sample_rate=24000,
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audio_out_enabled=True,
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vad_enabled=True,
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vad_audio_passthrough=True,
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# set stop_secs to something roughly similar to the internal setting
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# of the Multimodal Live api, just to align events. This doesn't really
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# matter because we can only use the Multimodal Live API's phrase
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# endpointing, for now.
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vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
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),
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)
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llm = GeminiMultimodalLiveLLMService(
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api_key=os.getenv("GOOGLE_API_KEY"),
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# system_instruction="Talk like a pirate."
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transcribe_user_audio=True,
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transcribe_model_audio=True,
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)
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llm.set_model_modalities(
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GeminiMultimodalModalities.TEXT
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) # This forces model to produce text only responses
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tts = CartesiaTTSService(api_key=os.getenv("CARTESIA_API_KEY"))
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pipeline = Pipeline(
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[
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transport.input(),
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llm,
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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(
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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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enable_usage_metrics=True,
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),
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)
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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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