ERROR livekit.agents - Error predicting end of turn getting this error

Thanks for reaching out, Harshita. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

session = AgentSession( vad=ctx.proc.userdata["vad"], stt=stt_model, llm=llm_model, tts=tts_model, min_endpointing_delay=0.1, max_endpointing_delay=2, turn_detection=MultilingualModel(), max_tool_steps = 5, agent_false_interruption_timeout=2, user_away_timeout= user_away_timeout ) def prewarm(proc: JobProcess): proc.userdata["vad"] = silero.VAD.load( min_speech_duration=0.05, min_silence_duration=0.2, prefix_padding_duration=0.2, max_buffered_speech=60.0, activation_threshold=0.5, sample_rate=16000, )

The error you're seeing with the

AgentSession

setup using

MultilingualModel

and

silero.VAD

might be coming from some hiccups with the STT configuration, VAD setup, or maybe some clashes with realtime models. No worries though—here are a few friendly tips to help you sort it out: • Double-check that your STT configuration is all set up right, since the

MultilingualModel

depends on STT output to nail those End-of-Utterance (EOU) predictions. • If you’re working with a realtime model, try turning off its built-in turn detection by setting

turn_detection=None

in its config. • Make sure your

silero.VAD

is tuned properly to catch silence periods. For example:

vad = silero.VAD.load(min_speech_duration=0.05, min_silence_duration=0.2, prefix_padding_duration=0.2, max_buffered_speech=60.0, activation_threshold=0.5, sample_rate=16000)

• It can be super helpful to log those EOU probabilities to see how well predictions are doing—you might want to add a custom turn detector just for logging. • Also, double-check that all the models you need are downloaded and ready by running:

python my_agent.py download-files

Still running into trouble? No problem! Just let me know if you’re using a particular language or setup that might need some tweaking, and I’d be happy to walk you through the next steps. Sources: livekit-plugins/livekit-plugins-turn-detector/livekit/plugins/turn_detector... | Turn detection and interruptions | LiveKit Docs | mcp/agent.py

2025-08-18 131056,354 - ERROR livekit.agents - Error predicting end of turn Traceback (most recent call last): File "C:\Python313\Lib\asyncio\tasks.py", line 507, in wait_for return await fut ^^^^^^^^^ File "C:\HARSHITA\INTERNSHIPS\pgv\livekit-latest - Copy\.venv1\Lib\site-packages\livekit\agents\ipc\job_proc_lazy_main.py", line 101, in do_inference inf_resp = await fut ^^^^^^^^^ asyncio.exceptions.CancelledError The above exception was the direct cause of the following exception: Traceback (most recent call last): File "C:\HARSHITA\INTERNSHIPS\pgv\livekit-latest - Copy\.venv1\Lib\site-packages\livekit\agents\voice\audio_recognition.py", line 362, in _bounce_eou_task end_of_turn_probability = await turn_detector.predict_end_of_turn( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ chat_ctx ^^^^^^^^ ) ^ File "C:\HARSHITA\INTERNSHIPS\pgv\livekit-latest - Copy\.venv1\Lib\site-packages\livekit\plugins\turn_detector\multilingual.py", line 65, in predict_end_of_turn return await super().predict_end_of_turn(chat_ctx, timeout=timeout) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\HARSHITA\INTERNSHIPS\pgv\livekit-latest - Copy\.venv1\Lib\site-packages\livekit\plugins\turn_detector\base.py", line 226, in predict_end_of_turn result = await asyncio.wait_for( ^^^^^^^^^^^^^^^^^^^^^^^ ...<2 lines>... ) ^ File "C:\Python313\Lib\asyncio\tasks.py", line 506, in wait_for async with timeouts.timeout(timeout): ~~~~~~~~~~~~~~~~^^^^^^^^^ File "C:\Python313\Lib\asyncio\timeouts.py", line 116, in aexit raise TimeoutError from exc_val TimeoutError

The

TimeoutError

in the

predict_end_of_turn

method pops up when the remote inference request takes longer than the set timeout. No worries—here are a few friendly tips to help you sort this out: • Increase the Timeout: Try bumping up the

REMOTE_INFERENCE_TIMEOUT

constant to a higher value, like 5 seconds:

REMOTE_INFERENCE_TIMEOUT = 5

• Check Remote Inference URL: Double-check that the

LIVEKIT_REMOTE_EOT_URL

environment variable is pointing to a valid, responsive endpoint. You can test it easily with tools like

curl

or Postman. • Use Local Model: If you don’t really need the remote endpoint, just skip setting the

LIVEKIT_REMOTE_EOT_URL

environment variable. That way, the

MultilingualModel

will smoothly fall back to local inference. If timeouts keep happening, it might help to add some retry logic or keep an eye on how the endpoint is performing. Feel free to reach out if you want a hand with any of these steps—I’m here to help! Sources: livekit-plugins/livekit-plugins-turn-detector/README.md