Features: - Backend statistics API (cloud-native Prisma aggregation) - Results page with hybrid solution (AI consensus + human final decision) - Excel export (frontend generation, zero disk write, cloud-native) - PRISMA-style exclusion reason analysis with bar chart - Batch selection and export (3 export methods) - Fixed logic contradiction (inclusion does not show exclusion reason) - Optimized table width (870px, no horizontal scroll) Components: - Backend: screeningController.ts - add getProjectStatistics API - Frontend: ScreeningResults.tsx - complete results page (hybrid solution) - Frontend: excelExport.ts - Excel export utility (40 columns full info) - Frontend: ScreeningWorkbench.tsx - add navigation button - Utils: get-test-projects.mjs - quick test tool Architecture: - Cloud-native: backend aggregation reduces network transfer - Cloud-native: frontend Excel generation (zero file persistence) - Reuse platform: global prisma instance, logger - Performance: statistics API < 500ms, Excel export < 3s (1000 records) Documentation: - Update module status guide (add Week 4 features) - Update task breakdown (mark Week 4 completed) - Update API design spec (add statistics API) - Update database design (add field usage notes) - Create Week 4 development plan - Create Week 4 completion report - Create technical debt list Test: - End-to-end flow test passed - All features verified - Performance test passed - Cloud-native compliance verified Ref: Week 4 Development Plan Scope: ASL Module MVP - Title Abstract Screening Results Cloud-Native: Backend aggregation + Frontend Excel generation
1.2 KiB
1.2 KiB
AIA - AI智能问答
模块代号: AIA (AI Intelligent Answer)
开发状态: ✅ 已完成
商业价值: ⭐⭐⭐⭐
独立性: ⭐⭐⭐
📋 模块概述
AI智能问答模块提供10+个专业AI智能体,覆盖科研关键节点。
核心价值: 差异化AI能力,覆盖科研全流程
🎯 核心功能
已完成功能
- ✅ 12个智能体 - YAML配置框架
- ✅ 多轮对话 - 上下文管理、历史记录
- ✅ 流式输出 - SSE打字机效果
- ✅ 模型切换 - DeepSeek、Qwen3、Qwen-Long
- ✅ @知识库问答 - RAG增强
主要智能体
- 选题评价智能体(四维度评价)
- PICO梳理智能体
- 样本量计算智能体
- 研究方案制定智能体
- 文章润色与翻译智能体
📂 文档结构
AIA-AI智能问答/
├── [AI对接] AIA快速上下文.md # ⏳ 待创建
├── 00-项目概述/
├── 01-设计文档/
└── README.md # ✅ 当前文档
🔗 依赖的通用能力
- LLM网关 - 模型调用和切换
- RAG引擎 - @知识库问答
最后更新: 2025-11-06
维护人: 技术架构师