Thanks — I’m sorry you’re seeing the agent repeatedly enter an infinite “thinking” loop. I’m responding to your question about whether old imports could cause this and how to troubleshoot it. Quick summary of likely causes you can check now • Agents can get stuck in thinking when tool calls are delayed, fail, or the agent never generates a final reply. • Common causes: missing or incorrect tool arguments, poorly defined tool descriptions (agent keeps retrying), or very verbose/recursive reasoning. • A known mitigation is enforcing a maximum iteration/tool-call limit so the agent stops after a few cycles and returns an error or fallback response. About your question on “old imports” • Old or incorrect imports are not described as a documented cause. The docs do not confirm imports/version conflicts cause infinite thinking. • That said, if an import change caused a tool to error or return unexpected results, that could indirectly trigger repeated thinking (the agent keeps calling a tool that fails). So check whether any code changes affected tool behavior. Actions to try next (please run or check) 1. Verify tool behavior ◦ Confirm each tool returns quickly and returns the expected shape/parameters. ◦ Ensure required parameters are validated and the tool raises a clear

ToolError

when inputs are missing. 1. Add limits and observability ◦ Set a maximum iteration or tool-call limit (e.g., 3–5) so the agent stops instead of looping. ◦ Add logging for AgentSession events (including

thinking

) and tool calls to see where it gets stuck. 1. Reproduce with minimal config ◦ Run the agent with a minimal set of tools / a lightweight model to see if the loop still happens. If it stops, gradually re-enable tools to find the culprit. 1. Inspect recent changes ◦ Check recent code or dependency changes (including imports). If a change altered tool behavior or exceptions, revert or test without it. What I need from you to dig deeper • A short reproduction: agent logs around the

thinking

events and the sequence of tool calls (or a log snippet). • Any recent code changes or dependency updates (including imports) you rolled out before this started. • Which model and tool set you’re using, and whether you’ve set an iteration limit. If you share the logs/snippets and recent changes I’ll analyze them and suggest the next targeted fix. Sources: The ReAct Pattern for Voice Agents and How AI Agents Think, Act, and Respon... | The ReAct Pattern for Voice Agents and How AI Agents Think, Act, and Respon... | Turns overview | LiveKit Documentation, with interactive elements