uv add "livekit-agents[silero,turn-detector]~=1.3" \
  "livekit-plugins-noise-cancellation~=0.2" \
  "python-dotenv"

lk app env -w

LIVEKIT_API_KEY=your_api_key
LIVEKIT_API_SECRET=your_api_secret
LIVEKIT_URL=wss://your-project.livekit.cloud

from dotenv import load_dotenv
from livekit import agents, rtc
from livekit.agents import AgentSession, Agent, AgentServer, room_io
from livekit.plugins import noise_cancellation, silero
from livekit.plugins.turn_detector.multilingual import MultilingualModel

load_dotenv(".env.local")

class Assistant(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="""You are a helpful voice AI assistant.
            Keep responses concise, 1-3 sentences. No markdown or emojis.""",
        )

server = AgentServer()

@server.rtc_session()
async def entrypoint(ctx: agents.JobContext):
    session = AgentSession(
        stt="assemblyai/universal-streaming:en",
        llm="openai/gpt-4.1-mini",
        tts="cartesia/sonic-3:9626c31c-bec5-4cca-baa8-f8ba9e84c8bc",
        vad=silero.VAD.load(),
        turn_detection=MultilingualModel(),
    )

    await session.start(
        room=ctx.room,
        agent=Assistant(),
        room_options=room_io.RoomOptions(
            audio_input=room_io.AudioInputOptions(
                noise_cancellation=lambda params: noise_cancellation.BVCTelephony()
                    if params.participant.kind == rtc.ParticipantKind.PARTICIPANT_KIND_SIP
                    else noise_cancellation.BVC(),
            ),
        ),
    )

    await session.generate_reply(
        instructions="Greet the user and offer your assistance."
    )

if __name__ == "__main__":
    agents.cli.run_app(server)

from dotenv import load_dotenv
from livekit import agents, rtc
from livekit.agents import AgentSession, Agent, AgentServer, room_io
from livekit.plugins import openai, noise_cancellation

load_dotenv(".env.local")

class Assistant(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="You are a helpful voice AI assistant."
        )

server = AgentServer()

@server.rtc_session()
async def entrypoint(ctx: agents.JobContext):
    session = AgentSession(
        llm=openai.realtime.RealtimeModel(voice="coral")
    )

    await session.start(
        room=ctx.room,
        agent=Assistant(),
        room_options=room_io.RoomOptions(
            audio_input=room_io.AudioInputOptions(
                noise_cancellation=lambda params: noise_cancellation.BVCTelephony()
                    if params.participant.kind == rtc.ParticipantKind.PARTICIPANT_KIND_SIP
                    else noise_cancellation.BVC(),
            ),
        ),
    )

    await session.generate_reply(
        instructions="Greet the user and offer your assistance."
    )

if __name__ == "__main__":
    agents.cli.run_app(server)

from livekit.agents import Agent, function_tool

class MyAgent(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="Your system prompt here",
        )

    async def on_enter(self) -> None:
        """Called when agent becomes active."""
        await self.session.generate_reply(
            instructions="Greet the user"
        )

    async def on_exit(self) -> None:
        """Called before agent hands off to another agent."""
        pass

    @function_tool()
    async def my_tool(self, param: str) -> str:
        """Tool description for the LLM."""
        return f"Result: {param}"

session = AgentSession(
    stt="assemblyai/universal-streaming:en",
    llm="openai/gpt-4.1-mini",
    tts="cartesia/sonic-3:voice_id",
    vad=silero.VAD.load(),
    turn_detection=MultilingualModel(),
)

from livekit.agents import function_tool, RunContext

@function_tool()
async def get_weather(self, context: RunContext, location: str) -> str:
    """Get the current weather for a location."""
    return f"Weather in {location}: Sunny, 72°F"

# Development mode with auto-reload
uv run agent.py dev

# Console mode (local testing)
uv run agent.py console

# Production mode
uv run agent.py start

# Download required model files
uv run agent.py download-files