bug: agent stops responding after multiple concurrent tabs

[jerelvelarde]

Bug

The agent stops responding when multiple browser tabs are open against the deployed app. On the third tab, the agent hangs after the user sends a message — no response, no streaming indicator, no error.

Steps to reproduce

1. Open the deployed app in tab 1, send a message (e.g. "visualize a musical chart") — works fine
2. Open tab 2, send a message — works fine
3. Open tab 3, send a message (e.g. "I want to understand the difference between BFS and DFS...") — agent never responds

The UI shows the user messages and suggestion chips ("Try these Prompts") but no assistant response arrives. No loading indicator, no error state.

Screenshot


The chat shows:

• "visualize a musical chart"
• "Create a 3D animation of a sphere turning into an icosahedron..."
• "I want to understand the difference between BFS and DFS. Create an interactive comparison on a node graph."

None received a response. Suggestion chips are visible but the agent is unresponsive.

Possible causes

1. Thread/session exhaustion — The agent uses BoundedMemorySaver(max_threads=200) in main.py. Multiple tabs may be creating separate threads that exhaust the pool or hit a concurrency limit.
2. WebSocket/SSE connection limit — The browser or server may be hitting a connection limit for streaming responses.
3. LangGraph checkpoint contention — Multiple concurrent sessions writing to the in-memory checkpointer could cause deadlocks.
4. OpenAI API rate limiting — Multiple concurrent requests to GPT-5.4 could hit rate limits with no visible error surfaced to the user.
5. Missing error handling — The frontend may not surface backend errors, making it look like the agent is "thinking" forever.

Expected behavior

Each tab should operate as an independent session. If a resource limit is reached, the user should see an error message rather than silent failure.

Environment

• Deployed on Render
• Agent: LangGraph + CopilotKit middleware
• Model: GPT-5.4 via langchain_openai
• Checkpointer: BoundedMemorySaver(max_threads=200)