Thanks — I see you’re hitting this assertion: AssertionError: end_of_utterance prediction should always returns a result You asked “What happened to the EOU plugin?” — short answer: the EOU (turn detector) plugin is still supported and active. The assertion means the turn detector did not return any prediction for the call to

predict_end_of_turn

. That can happen even though the plugin itself still exists and is being maintained. What likely caused this in your run • Model inference didn’t return before the method’s checks. This can happen if the model is still loading or there was a timeout during inference. • Model weights were not available or failed to download on first use (the multilingual model requires a large weights download). • Insufficient CPU/RAM or other resource constraints causing the model to fail to produce a result. • The

chat_ctx

passed into

predict_end_of_turn

was empty or malformed, so the model had no valid input to produce a result. Quick troubleshooting steps to try now 1. Confirm agent/library version ◦ Make sure you’re running Agents Python 1.3.0 or later (contains stability improvements for the turn detector). 1. Check model weights/download ◦ On first run the multilingual model will download large weights (~396MB). Ensure the environment allows outbound downloads and has enough disk space. If the download was interrupted, retry or clear partial files and run again. 1. Re-run with observability/logging enabled ◦ Look for any

eou_detection

traces or logs that show model input, time-to-inference or errors during model load. 1. Validate

chat_ctx

◦ Ensure

chat_ctx

contains recent transcript history (typically several prior turns). Send a minimal known-good context to test whether a prediction is returned. 1. Resource check & timeouts ◦ If running on a constrained VM/container, try reproducing locally on a machine with more CPU/RAM or increase any inference timeout values you control. 1. Reproduce with a simple test ◦ Create a minimal script that calls

predict_end_of_turn

with a small, well-formed

chat_ctx

to see if the plugin returns any result outside your full agent pipeline. If you want, I can help narrow this down — please tell me: • Which Agents Python version you’re using (exact package version). • Whether this is the first time running on this machine (did you see a model download progress?). • A snippet (sanitized) of the

chat_ctx

you pass in, or confirm whether it ever contains recent transcript turns. • Any logs around model load/inference time or network errors during first run. I can then suggest the next targeted step (for example, how to force a fresh download of model weights, increase timeouts, or adjust the

chat_ctx

format). Sources: Improving voice AI's turn detection with transformers | LiveKit turn detector plugin | LiveKit Documentation | Improved End-of-Turn Model Cuts Voice AI Interruptions 39%