hi

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

failed to get logs: The agent has shut down due to inactivity. It will automatically start again when a new session begins. why am i getting this log when i try to start my agent everyday?? and i have to redeploy to make it work, i can't keep redeploying everyday tell me what is this issue and how to fix it permanently

Thanks — I understand the frustration. You’re seeing the log “The agent has shut down due to inactivity. It will automatically start again when a new session begins.” and you’re forced to redeploy daily. I’ll explain why that happens and how to fix it so you don’t need to redeploy. Why this happens • The agent is scaling to zero when idle. That shutdown message is expected behavior on plans that allow scaling to zero — the agent stops to save resources and should cold-start when a new session begins. • Redeploying every day means the agent isn’t reliably cold-starting on demand (the shutdown itself is normal; the restart failing is the problem). Steps to fix it permanently 1. Check startup errors ◦ Inspect agent startup logs for errors when a new session should trigger a start (missing env vars, auth failures, exceptions). 1. Verify environment variables ◦ Ensure

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

, and

LIVEKIT_URL

(or your equivalent config) are set and correct in the deployment environment. 1. Confirm proper startup mode ◦ Run the agent in the recommended production startup mode (not

dev

) so it handles lifecycle and restarts correctly. 1. Configure health checks ◦ Make sure the health check endpoint used by the platform is configured and returns healthy only after the agent is ready. If health checks fail, the platform may mark the start as unsuccessful. 1. Inspect your Docker/deployment config ◦ Ensure your container or process doesn’t exit on startup (no scripts that finish immediately). ◦ Don’t suppress startup signals; let the process run in foreground for the orchestrator to manage it. 1. Reproduce a cold start manually ◦ Stop the agent, trigger a new session, and watch logs from boot to identify where startup stalls or errors occur. If after these checks the agent still won’t start without redeploying, tell me: • your deployment type (Cloud, self-hosted, container platform), • any startup logs you see when a new session tries to start, • the agent startup command or Dockerfile snippet you use. With that info I’ll help pinpoint the failing step and give exact fixes. Sources: Deployment reliability on LiveKit Cloud | LiveKit | Server options | LiveKit Documentation | Server startup modes | LiveKit Documentation, with interactive elements

C:\Users\AaronFrancis\Desktop\vscode\main tasks\livekit\appointment_bot>lk agent logs WARNING: config file C:\Users\AaronFrancis/.livekit/cli-config.yaml should have permissions 600 WARNING: config file C:\Users\AaronFrancis/.livekit/cli-config.yaml should have permissions 600 Using project [calendarbot] Using agent [CA_4HYSAxBiEp3i] failed to get logs: The agent has shut down due to inactivity. It will automatically start again when a new session begins. - map[agent_id:CA_4HYSAxBiEp3i project_id:p_58wa539xhnr] how to fix this issue?? is it cus my account is on free trial and the free trial is over?? willl it be fixed if i swithc to a new account and deploy it there??

Thanks — I see the exact logs you ran and the shutdown message. I’ll address your two questions and next steps to fix it. Short answers • That shutdown message is expected: agents on plans that scale to zero will stop when idle. The message alone is normal. • Your free trial expiring is not the cause. The agent should still cold-start when a new session begins regardless of trial status. • Creating a new account and redeploying is unlikely to fix the underlying problem — we should diagnose why the agent fails to cold-start on demand. Please provide these details so I can pinpoint the issue: • Deployment type: Cloud (LiveKit Cloud) or self-hosted / container (Docker, Kubernetes, etc.). • The agent startup command or Dockerfile entrypoint you use. • Any logs you see immediately after you trigger a new session (start the agent) — especially startup error lines. • Whether you configured a health check URL and what it returns. Quick checks you can run now • Try triggering a new session and immediately tail logs to capture startup output (don’t redeploy yet). • Confirm env vars:

LIVEKIT_API_KEY

,

LIVEKIT_API_SECRET

, and

LIVEKIT_URL

are set in your deployment environment. • Ensure you’re not running the agent in

dev

mode and that the process stays in the foreground. Give me the deployment type and a copy of the startup logs from a cold-start attempt and I’ll tell you the exact fix. , with interactive elements

1. Deployment Type:*LiveKit Cloud*. (The logs confirm connection to`calendarbot-5zanxsg2.livekit.cloud`). 2. Startup Command: The agent is run as a Python worker using`python agent_google.py dev`. 3. Startup Logs (The "Smoking Gun"): The agent was failing to cold-start because of a`NameError: name 'ClientOptions' is not defined`. This caused the agent process to crash immediately upon initialization, preventing it from ever joining the room. 4. Health Check: No custom health check URL is used; we rely on the LiveKit Worker's internal registration.

Thanks — this is helpful. I’ll help fix the

NameError: name 'ClientOptions' is not defined

so your agent can cold-start reliably. Please provide these four items so I can give the exact code fix: 1. Full Python traceback (all error lines from when the agent crashes). 2. The top of your

agent_google.py

file (imports) and the few lines where

ClientOptions

is referenced. 3. The LiveKit/agent-related packages and versions (paste output of

pip show livekit

and

pip freeze | grep google

or whole

pip freeze

). 4. Python version and whether you use a virtualenv/conda. Quick checklist you can try now: • Ensure you’re not running production on

dev

mode; use the production start command after fixing the error. • If

ClientOptions

should come from a Google library, install the correct package (often

google-api-core

or

google-auth

) and a compatible version. Send the traceback + code + package list and I’ll respond with the exact import and code change. Sources: Deployment reliability on LiveKit Cloud | LiveKit | Server options | LiveKit Documentation | Build voice, video, and physical AI | LiveKit, with interactive elements

1. The Fix: ◦ Fixed the missing`ClientOptions`import and constant ordering in the Python agent. ◦ Resolved a redirection priority conflict in`_redirects`that was causing API calls to return HTML instead of JSON. ◦ Implemented an explicit`ctx.shutdown()`handler on`participant_disconnected`(matching the pattern in your`IT-helpdesk-agent`project) to ensure the job is released immediately when a user leaves. i have done all this, what next?

Great — thanks for the clear fixes. Next steps to verify the agent will cold-start reliably and stop the daily redeploys: 1. Redeploy in production mode ◦ Start the agent with the production command (not

dev

). This ensures correct lifecycle handling. 1. Test a cold start ◦ Stop or leave the agent idle until it scales to zero. ◦ Trigger a new session and immediately tail logs to confirm the agent: ▪︎ Boots without exceptions, ▪︎ Registers with LiveKit, and ▪︎ Joins the room. 1. Verify the fixes in logs ◦ Confirm no more

NameError

or HTML-from-API responses. ◦ Confirm

_redirects

now returns JSON and

ctx.shutdown()

runs when participants disconnect. 1. Add health check (optional but recommended) ◦ If possible, expose a simple health endpoint that returns healthy only after initialization completes. This helps the platform detect successful cold starts. 1. Monitor for a few days ◦ Watch for cold-start success each time a new session begins. Capture logs if a restart fails. If you see any startup errors while testing a cold start, paste the startup traceback and the exact production start command you used and I’ll pinpoint the remaining issue. , with interactive elements