Files
course-agent-od/backend
pengxiao 51d6fd22c0 feat: capture reasoning content from thinking models, improve thinking UI
- Backend: intercept reasoning_content from DeepSeek-R1/QwQ streaming
  chunks and emit as thinking events (stage=reasoning)
- RAG chain: show retrieved document titles/previews in thinking steps
- Conversation chain: directly stream from LLM to capture reasoning
- Frontend: collapsible thinking panel with reasoning section,
  document details, and time summary
- Replace relative time with HH:mm format for message timestamps

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-27 11:47:14 +08:00
..

国土空间规划课程智能体后端服务

基于FastAPI和LangGraph的智能问答系统后端服务。

技术栈

  • 框架: FastAPI + Uvicorn
  • AI框架: LangChain + LangGraph
  • 大模型: 硅基流动API (Qwen3-30B)
  • 向量数据库: Chroma
  • 数据库: PostgreSQL

快速开始

使用Docker(推荐)

docker-compose up -d

本地开发

uv sync
uv run main.py

API文档

启动服务后访问:http://localhost:8000/docs