118 lines
3.5 KiB
Python
118 lines
3.5 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 argparse
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import asyncio
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import os
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import sys
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from dotenv import load_dotenv
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from loguru import logger
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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.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
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from pipecat.services.gemini_multimodal_live import GeminiMultimodalLiveLLMService
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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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SYSTEM_INSTRUCTION = f"""
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"You are Gemini Chatbot, a friendly, helpful robot.
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Your goal is to demonstrate your capabilities in a succinct way.
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Your output will be converted to audio so don't include special characters in your answers.
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Respond to what the user said in a creative and helpful way. Keep your responses brief. One or two sentences at most.
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"""
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def extract_arguments():
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parser = argparse.ArgumentParser(description="Instant Voice Example")
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parser.add_argument(
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"-u", "--url", type=str, required=True, help="URL of the Daily room to join"
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)
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parser.add_argument(
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"-t", "--token", type=str, required=False, help="Token of the Daily room to join"
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)
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args, unknown = parser.parse_known_args()
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url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
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token = args.token
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return url, token
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async def main():
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room_url, token = extract_arguments()
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print(f"room_url: {room_url}")
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daily_transport = DailyTransport(
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room_url,
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token,
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"Instant voice Chatbot",
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DailyParams(
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audio_out_enabled=True,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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vad_audio_passthrough=True,
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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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voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck
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transcribe_user_audio=True,
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system_instruction=SYSTEM_INSTRUCTION,
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)
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context = OpenAILLMContext()
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context_aggregator = llm.create_context_aggregator(context)
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# RTVI events for Pipecat client UI
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rtvi = RTVIProcessor(config=RTVIConfig(config=[]), transport=daily_transport)
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pipeline = Pipeline(
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[
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daily_transport.input(),
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context_aggregator.user(),
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rtvi,
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llm, # LLM
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daily_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(allow_interruptions=True),
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observers=[RTVIObserver(rtvi)],
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)
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@rtvi.event_handler("on_client_ready")
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async def on_client_ready(rtvi):
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await rtvi.set_bot_ready()
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@daily_transport.event_handler("on_first_participant_joined")
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async def on_first_participant_joined(transport, participant):
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await task.queue_frames([context_aggregator.user().get_context_frame()])
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@daily_transport.event_handler("on_participant_left")
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async def on_participant_left(transport, participant, reason):
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print(f"Participant left: {participant}")
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await task.cancel()
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runner = PipelineRunner(handle_sigint=False)
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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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