We have been working very hard to improve the open-weights End of Turn detection model. Our ML team has made substantial improvements. One big problem we have seen is when agents need to collect specific data like phone numbers, email addresses, etc, they often stumble and add a lot of friction to the human-to-machine interaction experience. Also, you no longer need to pick an English or a multilingual model. You should use multilingual from now on. Check out our visualization tool that will let you compare the open weights models side by side: https://huggingface.co/spaces/livekit/eot-visualization?ref=blog.livekit.io I can hardly keep from spilling the beans on some other huge improvements we have in the lab right now but realtime AI is getting much better. Updated Model Blog Post with demo: https://blog.livekit.io/improved-end-of-turn-model-cuts-voice-ai-interruptions-39/ Plugin Code: https://github.com/livekit/agents/tree/main/livekit-plugins/livekit-plugins-turn-detector?ref=blog.livekit.io

Hello everyone, I want to build a dashboard where the client can see the logs of their calls: the type of call (inbound or outbound), the time and date, and other important information such as the transcription. My question is: in LiveKit, what would be the best approach to send this information to the backend? Should I rely on LiveKit webhooks/events, send everything when the session closes, or use another option?