Example with Gemini using google search to retrieve news.
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105
examples/foundational/26e-gemini-multimodal-google-search.py
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105
examples/foundational/26e-gemini-multimodal-google-search.py
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#
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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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from pathlib import Path
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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 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.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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sys.path.append(str(Path(__file__).parent.parent))
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from runner import configure
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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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# Function handlers for the LLM
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search_tool = {'google_search': {}}
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tools = [
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search_tool
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]
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system_instruction = """
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You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting.
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Always use the google search API to retrieve the latest news. You must also use it to check which day is today.
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You can:
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- Use the Google search API to check the current date.
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- Provide the most recent and relevant news from any place by using the google search API.
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- Answer any questions the user may have, ensuring your responses are accurate and concise.
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Start each interaction by asking the user about which place they would like to know the information.
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"""
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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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"Latest news!",
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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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# Initialize the Gemini Multimodal Live model
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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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transcribe_model_audio=True,
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system_instruction=system_instruction,
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tools=tools,
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)
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context = OpenAILLMContext(
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[{"role": "user", "content": "Start by greeting the user warmly, introducing yourself, and mentioning the current day. Be friendly and engaging to set a positive tone for the interaction."}],
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)
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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(), # Transport user input
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context_aggregator.user(), # User responses
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llm, # LLM
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transport.output(), # Transport bot output
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context_aggregator.assistant(), # Assistant spoken responses
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]
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)
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task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
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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([context_aggregator.user().get_context_frame()])
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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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