bug: agent stops responding after multiple concurrent tabs
維護者通常 1 天內回覆
還沒有人認領這個 Issue。
評估
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 新手友好度
- 35/100
- Issue 類型
- 缺陷
- 描述清晰度
- 需要釐清
- 活躍度
- 冷清
- 技術堆疊
- python, typescript
研究方向
Start with the deployed reproduction using three browser tabs, then inspect main.py, especially BoundedMemorySaver(max_threads=200) and the streaming request path. Check whether concurrent sessions, connection limits, rate limits, or unsurfaced backend errors explain the hang; done means independent tabs receive responses, and resource failures show an error instead of waiting silently.
由索引模型根據 Issue 內容生成。
描述
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
- Open the deployed app in tab 1, send a message (e.g. "visualize a musical chart") — works fine
- Open tab 2, send a message — works fine
- 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
- Thread/session exhaustion — The agent uses
BoundedMemorySaver(max_threads=200)inmain.py. Multiple tabs may be creating separate threads that exhaust the pool or hit a concurrency limit. - WebSocket/SSE connection limit — The browser or server may be hitting a connection limit for streaming responses.
- LangGraph checkpoint contention — Multiple concurrent sessions writing to the in-memory checkpointer could cause deadlocks.
- OpenAI API rate limiting — Multiple concurrent requests to GPT-5.4 could hit rate limits with no visible error surfaced to the user.
- 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)
- 主要語言
- TypeScript
- 星號
- 3.9k
- 分支
- 414
- 平均合併
- 4 小時
- 30 天內合併 PR
- 6
環境準備
- 沒有 Dockerfile 或 Docker Compose 檔案
- 沒有 Pull Request 範本
- 閱讀貢獻指南
從這裡開始
- 先讀完整個 Issue，再讀專案的貢獻指南。
- 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
- Fork 儲存庫，在一個分支上完成修改。
- 送出 Pull Request，並在描述裡引用這個 Issue 編號。
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