AI Clinical Dev Team 84bf1c86ab feat: Day 14-17 - Frontend Chat Interface completed
Frontend:
- Create MessageList component with streaming animation
- Create MessageInput component with @knowledge base support
- Create ModelSelector component (DeepSeek/Qwen/Gemini)
- Implement conversationApi with SSE streaming
- Update AgentChatPage integrate all components
- Add Markdown rendering (react-markdown + remark-gfm)
- Add code highlighting (react-syntax-highlighter)
- Add vite-env.d.ts for environment variables

Features:
- Real-time streaming output with cursor animation
- Markdown and code block rendering
- Model switching (DeepSeek-V3, Qwen3-72B, Gemini Pro)
- @Knowledge base selector (UI ready)
- Auto-scroll to bottom
- Shift+Enter for new line, Enter to send
- Beautiful message bubble design

Build: Frontend build successfully (7.94s, 1.9MB)

New Files:
- components/chat/MessageList.tsx (170 lines)
- components/chat/MessageList.css (150 lines)
- components/chat/MessageInput.tsx (145 lines)
- components/chat/MessageInput.css (60 lines)
- components/chat/ModelSelector.tsx (110 lines)
- components/chat/ModelSelector.css (35 lines)
- api/conversationApi.ts (170 lines)
- src/vite-env.d.ts (9 lines)

Total: ~850 lines of new code
2025-10-10 20:52:30 +08:00
2025-10-10 15:58:14 +08:00

AI科研助手

专注于赋能临床及科研人员的智能化平台

📚 项目文档

📖 文档导航中心

🔗 快速链接

🛠️ 子项目文档

🏗️ 技术栈

前端

  • React 18 + TypeScript
  • Vite
  • TailwindCSS
  • Zustand
  • LobeChat组件

后端

  • Node.js + Fastify + TypeScript
  • Prisma ORM
  • PostgreSQL
  • Redis

第三方服务

  • DifyRAG知识库
  • DeepSeek-V3主力LLM
  • Qwen3备用LLM

🚀 快速开始

1. 启动基础服务

# 启动PostgreSQL和Redis
docker-compose up -d

2. 后端开发

cd backend
npm install
npm run dev

3. 前端开发

cd frontend
npm install
npm run dev

📦 目录结构

AIclinicalresearch/
├── frontend/           # 前端项目
├── backend/            # 后端项目
├── docs/               # 项目文档
├── docker-compose.yml  # Docker配置
└── README.md           # 本文件

🔑 环境变量

请参考 .env.example 文件配置环境变量。

📖 开发指南

请查看 开发里程碑 了解详细的开发计划。

📄 License

MIT


🔗 相关链接


当前开发阶段: 里程碑1 - Day 6前端基础架构
开发进度: 50% - 前后端基础架构已完成

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