turn_detector.py

import logging

from dotenv import load_dotenv
from livekit.agents import (
    AutoSubscribe,
    JobContext,
    JobProcess,
    WorkerOptions,
    cli,
    llm,
    metrics,
)
from livekit.agents.pipeline import VoicePipelineAgent
from livekit.plugins import deepgram, openai, silero, turn_detector

load_dotenv()
logger = logging.getLogger("voice-assistant")


def prewarm(proc: JobProcess):
    proc.userdata["vad"] = silero.VAD.load()


# This example uses our open-weight turn detection model to detect when the user is
# done speaking. This approach is more accurate than the default VAD model, reducing
# false positive interruptions by the agent.
async def entrypoint(ctx: JobContext):
    initial_ctx = llm.ChatContext().append(
        role="system",
        text=(
            "You are a voice assistant created by LiveKit. Your interface with users will be voice. "
            "You should use short and concise responses, and avoiding usage of unpronouncable punctuation."
        ),
    )

    logger.info(f"connecting to room {ctx.room.name}")
    await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)

    # wait for the first participant to connect
    participant = await ctx.wait_for_participant()
    logger.info(f"starting voice assistant for participant {participant.identity}")

    agent = VoicePipelineAgent(
        vad=ctx.proc.userdata["vad"],
        stt=deepgram.STT(),
        llm=openai.LLM(),
        tts=openai.TTS(),
        chat_ctx=initial_ctx,
        turn_detector=turn_detector.EOUModel(),
    )

    agent.start(ctx.room, participant)

    usage_collector = metrics.UsageCollector()

    @agent.on("metrics_collected")
    def _on_metrics_collected(mtrcs: metrics.AgentMetrics):
        metrics.log_metrics(mtrcs)
        usage_collector.collect(mtrcs)

    async def log_usage():
        summary = usage_collector.get_summary()
        logger.info(f"Usage: ${summary}")

    ctx.add_shutdown_callback(log_usage)

    await agent.say("Hey, how can I help you today?", allow_interruptions=True)


if __name__ == "__main__":
    cli.run_app(
        WorkerOptions(
            entrypoint_fnc=entrypoint,
            prewarm_fnc=prewarm,
        ),
    )