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src/agent.py

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@@ -64,14 +64,14 @@ async def entrypoint(ctx: JobContext):
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# Set up a voice AI pipeline using OpenAI, Cartesia, Deepgram, and the LiveKit turn detector
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session = AgentSession(
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# A Large Language Model (LLM) is your agent's brain, processing user input and generating a response
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# See all providers at https://docs.livekit.io/agents/integrations/llm/
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# See all available models at https://docs.livekit.io/agents/models/llm/
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llm="openai/gpt-4o-mini",
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# Speech-to-text (STT) is your agent's ears, turning the user's speech into text that the LLM can understand
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# See all providers at https://docs.livekit.io/agents/integrations/stt/
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# See all available models at https://docs.livekit.io/agents/models/stt/
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stt="deepgram/nova-3",
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# Text-to-speech (TTS) is your agent's voice, turning the LLM's text into speech that the user can hear
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# See all providers at https://docs.livekit.io/agents/integrations/tts/
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tts="cartesia:6f84f4b8-58a2-430c-8c79-688dad597532",
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# See all available models as well as voice selections at https://docs.livekit.io/agents/models/tts/
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tts="cartesia/sonic-2:6f84f4b8-58a2-430c-8c79-688dad597532",
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# VAD and turn detection are used to determine when the user is speaking and when the agent should respond
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# See more at https://docs.livekit.io/agents/build/turns
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# turn_detection=MultilingualModel(),
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)
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# To use a realtime model instead of a voice pipeline, use the following session setup instead.
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# This is for OpenAI Realtime API, for other providers, see https://docs.livekit.io/agents/integrations/realtime/
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# (Note: This is for the OpenAI Realtime API. For other providers, see https://docs.livekit.io/agents/models/realtime/))
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# 1. Install livekit-agents[openai]
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# 2. Set OPENAI_API_KEY in .env.local
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# 3. Add `from livekit.plugins import openai` to the top of this file

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