Thanks — I hear that your self-hosted LiveKit app uses Silero VAD for turn detection and that when a long-running workflow is started the flow "breaks" and the agent never gets the workflow response. I can help troubleshoot — a few clarifying questions and some targeted checks will narrow this down. Please provide: • Where the workflow runs (in-process with the agent, separate service, or serverless function?) and approx. how long it takes. • Which component is expected to send the workflow response back to the agent (your app server, a webhook, the client) and how that response is delivered (RTC data channel, REST callback, websocket, etc.). • Any error logs or messages from the agent, your app server, LiveKit server, or the workflow service around the time the workflow starts and when it should respond. • Whether turn detection stops working only when the workflow is running, or whether the VAD stops detecting turns entirely afterward. • Your LiveKit version and relevant parts of your configuration (timeouts, participant permissions, and whether you use a proxy/load-balancer). Quick checks you can run now: • Verify the workflow service actually completes and emits its response (check its logs or add temporary logging for success/failure and timing). • Confirm the mechanism delivering the response to the agent is reachable and not timing out or blocked (test the endpoint with a simple request). • Check LiveKit and client-side connection logs for dropped connections, data channel closures, or permission errors when the workflow runs. • If the workflow runs long, confirm any request timeouts (HTTP client, reverse proxy, load balancer) are longer than the workflow runtime. • Ensure your VAD processing thread/process is not being blocked by the workflow (CPU, synchronous calls). If the workflow is CPU- or I/O-heavy, run it asynchronously so VAD stays responsive. If you can share the answers above plus a short snippet of the relevant logs (no secrets), I’ll suggest concrete next steps and configuration changes to keep turn detection stable while the workflow runs. , with interactive elements

Thanks — that helps. I’m responding to the part where you said the workflow runs in your main application and LiveKit runs as a microservice. A few targeted questions to diagnose this quickly: • How is the workflow invoked from the agent? (sync function call, background job, HTTP request to the app, etc.) • How does the workflow return its result to the agent? (RTC data channel, REST callback, websocket, updating DB + client poll, etc.) • How long does the workflow typically take, and does the agent call block while waiting? • Is Silero VAD running in the same thread/process as the workflow or in a separate worker/process? • Do you see any errors or timeouts in your app logs, LiveKit server logs, or client console when the workflow runs? Please paste short relevant log snippets (no secrets). • Are there any proxies/load-balancers or request timeouts (NGINX, Envoy, API gateway) between LiveKit, your app, and clients? Immediate suggestions you can try now: • Run the workflow asynchronously (background job, task queue) so VAD and request handlers remain non-blocking. • Ensure responses are delivered via a reliable channel that doesn’t depend on the original request staying open (e.g., send results over the RTC data channel or push via websocket). • Increase relevant timeouts on HTTP clients, reverse proxies, and load balancers if the workflow must be synchronous. • Move Silero VAD into its own thread/process or worker so CPU or I/O from the workflow can’t block turn detection. • Add logging around invocation, start/finish times, and delivery attempts to confirm the workflow completes and the response path is reachable. Share the answers to the questions above and a few log lines and I’ll give concrete code/config changes tailored to your setup. , with interactive elements

You're asking how to "sideline" the async workflow so the agent doesn't block waiting for its output while Silero VAD and the call continue. Good goal — you can decouple the workflow result from the agent's immediate flow so turn detection and media remain responsive. Below are practical options and the minimal next steps to implement them. Quick options (pick one based on how your app delivers results): • Send workflow results back over the LiveKit RTC data channel. ◦ Fire the workflow asynchronously and immediately resume the call. ◦ When the workflow finishes, have your app server send the result to the agent participant using LiveKit data messages. This doesn't require the original request to remain open. • Push via a dedicated websocket or server-sent events (SSE). ◦ Agent subscribes to a websocket/SSE channel for workflow completions. Workflow completes → push message → agent consumes and continues. • Persist result + notify (DB + pub/sub). ◦ Workflow writes result to DB or cache and publishes an event (Redis pub/sub, Kafka). ◦ Agent receives event (or polls short-interval) and fetches the result. Use this when reliability and retries are important. • Use a background job queue with callbacks (e.g., Celery, Sidekiq, RQ). ◦ Enqueue long jobs; workers process them separately. ◦ On completion, callback the agent via data channel/websocket or publish an event. Implementation notes to keep VAD stable: • Run Silero VAD in a separate thread/process or worker so CPU/I/O from the workflow cannot block audio processing. • Keep the audio/video media path independent of the workflow request lifecycle (no synchronous waits on long-running tasks in the media handling thread). • If using HTTP callbacks, ensure client/proxy timeouts are longer than workflow runtime, or prefer push channels that don't require open requests. Concrete next step I recommend: 1. Which delivery channel do you prefer for results: LiveKit data channel, websocket, or DB+pubsub? 2. Share one short log snippet showing how the agent currently waits (no secrets) or the code path that blocks, and I’ll give the specific code/architecture changes for that approach. Tell me your preferred channel and paste the blocking code or logs and I’ll provide focused steps you can apply immediately. , with interactive elements