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how to haddle error in frontend

Handling errors in the frontend for LiveKit can feel tricky, but I’m here to help you through it step-by-step: • Keep an Eye on Media Device Errors: You can listen for the

RoomEvent.MediaDevicesError

event to catch any hiccups with camera or microphone permissions. Here’s a simple example:

useEffect(() => {
  room.on(RoomEvent.MediaDevicesError, onDeviceFailure);
  return () => {
    room.off(RoomEvent.MediaDevicesError, onDeviceFailure);
  };
}, [room]);

function onDeviceFailure(error) {
  console.error(error);
  alert("Oops! There was an issue accessing your camera or microphone. Please check your permissions and reload the tab.");
}

• Try Toast Notifications Instead of Alerts: Toasts are less intrusive and create a smoother experience. Here’s how you might do that:

const onMediaDevicesError = (error) => {
  toastAlert({
    title: 'Media Device Error',
    description: `${error.name}: ${error.message}`,
  });
};

• Catch Connection Errors Gracefully: Wrapping your connection attempts in try-catch blocks helps you manage any connection problems without crashing:

Promise.all([
  room.localParticipant.setMicrophoneEnabled(true),
  room.connect(serverUrl, participantToken),
]).catch((error) => {
  displayError({
    title: 'Connection failed',
    description: `${error.name}: ${error.message}`,
  });
});

• Some Friendly Tips: ◦ Always show error messages that are easy to understand. ◦ Consider adding retry options when things can be fixed automatically. ◦ Log detailed errors behind the scenes while keeping user messages simple and clear. If you want me to walk you through any part or need extra examples, just let me know—I’m happy to help! Sources: complex-agents/role-playing/role_playing_frontend/components/app.tsx | Web Embed Example | livekit/livekit_composite | DeepWiki | src/room/errors.ts

error from backend

Handling backend errors in LiveKit can feel a bit tricky, but don’t worry—I’ve got some friendly tips to help you out: • Get to Know Common Backend Errors: LiveKit has some specific error types you might see, like: • `ErrRoomNotFound`: This means the room you’re looking for doesn’t exist. • `ErrParticipantNotFound`: This pops up when a participant can’t be found. • `ErrOperationFailed`: This shows up if an operation just can’t be completed. • Handle Errors Gracefully in Your Code: For example, in JavaScript, you can catch connection errors using structured error classes like this:

Promise.all([
  room.localParticipant.setMicrophoneEnabled(true),
  room.connect(serverUrl, participantToken),
]).catch((error) => {
  console.error(error);
  displayError({
    title: 'Connection failed',
    description: `${error.name}: ${error.message}`,
  });
});

• Try Recovery Strategies: When you can, mark errors as recoverable and add retry logic for those temporary hiccups. • Keep Logs Handy: Make sure you’re logging errors with enough details to help you debug later. • Give Clear User Feedback: Show friendly error messages and fallback options in the UI so users aren’t left guessing. If you want, I’m here to help with specific examples or anything else you need—just let me know! Sources: Web Embed Example | livekit/livekit_composite | DeepWiki | pkg/service/errors.go | README.md | Sources/LiveKit/Errors.swift | livekit-plugins/livekit-plugins-openai/livekit/plugins/openai/realtime/real...

None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used. 2025-08-19 184234,908 - ERROR livekit.plugins.turn_detector - Could not find model livekit/turn-detector with revision v0.3.0-intl. Make sure you have downloaded the model before running the agent. Use

python3 your_agent.py download-files

to download the models. {"pid": 10824, "inference": true} 2025-08-19 184234,908 - ERROR livekit.agents - error initializing inference runner Traceback (most recent call last): File "c:\Codeshastra_Projects\hamari-ai-monorepo\.venv\Lib\site-packages\livekit\agents\ipc\inference_proc_lazy_main.py", line 82, in initialize runner.initialize() ~~~~~~~~~~~~~~~~~^^ File "c:\Codeshastra_Projects\hamari-ai-monorepo\.venv\Lib\site-packages\livekit\plugins\turn_detector\base.py", line 115, in initialize raise RuntimeError( ...<2 lines>... ) from None RuntimeError: livekit-plugins-turn-detector initialization failed. Could not find model livekit/turn-detector with revision v0.3.0-intl. {"runner": "lk_end_of_utterance_multilingual", "pid": 10824, "inference": true}

Hey there! It looks like the error is because the LiveKit turn detector model files (revision

v0.3.0-intl

) are missing. No worries though – you just need to download those model files before running your agent. Here’s how you can fix it: 1. Open your terminal and run this command:

python your_agent.py download-files

Just swap out

your_agent.py

with the actual name of your agent script. A couple of extra things to keep in mind: • The

v0.3.0-intl

model supports multiple languages and needs about 400MB of RAM. • If you’re using Docker, make sure to include this command during the Docker build so it grabs all the files it needs. If you hit any snags or have questions, feel free to reach out—I’m here to help! Sources: livekit-plugins/livekit-plugins-turn-detector/livekit/plugins/turn_detector... | LiveKit turn detector plugin | LiveKit Docs