LiveKit (tracing)

pip install respan-ai respan-instrumentation-livekit livekit-agents

npm install @livekit/agents @livekit/rtc-node @respan/respan @respan/tracing @respan/instrumentation-livekit

import os

from livekit.agents import llm
from respan import Respan, workflow
from respan_instrumentation_livekit import LiveKitInstrumentor

respan = Respan(
    api_key=os.environ["RESPAN_API_KEY"],
    app_name="livekit-tracing",
    instrumentations=[LiveKitInstrumentor()],
)


@workflow(name="livekit_chat.workflow")
async def run_chat(model: llm.LLM) -> str:
    chat_ctx = llm.ChatContext.empty()
    chat_ctx.add_message(role="user", content="Say hello in one sentence.")
    response = await model.chat(chat_ctx=chat_ctx).collect()
    return response.text

respan.shutdown()

import * as LiveKit from "@livekit/agents";
import { voice } from "@livekit/agents";
import { Respan } from "@respan/respan";
import { LiveKitInstrumentor } from "@respan/instrumentation-livekit";

LiveKit.initializeLogger({ pretty: false, level: "silent" });

const respan = new Respan({
  apiKey: process.env.RESPAN_API_KEY,
  baseURL: process.env.RESPAN_BASE_URL,
  appName: "livekit-tracing",
  instrumentations: [
    new LiveKitInstrumentor({
      livekitModule: LiveKit,
    }),
  ],
});
await respan.initialize();

const session = new voice.AgentSession({
  llm: new voice.testing.FakeLLM([
    {
      input: "Give me a short welcome for a travel concierge.",
      content: "Welcome. I can help plan a focused city itinerary.",
    },
  ]),
});

const agent = new voice.Agent({
  id: "travel_concierge",
  instructions: "Answer in one concise sentence.",
});

try {
  await respan.withWorkflow({ name: "livekit_text_agent_turn" }, async () => {
    await session.start({ agent, record: false });
    const result = await session
      .run({ userInput: "Give me a short welcome for a travel concierge." })
      .wait();
    console.log(result.events);
  });
} finally {
  await session.close().catch(() => undefined);
}