HaHafeng
8eef9e0544
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
105 lines
2.2 KiB
Markdown
105 lines
2.2 KiB
Markdown
# 通用能力层
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> **层级定义：** 跨业务模块共享的核心技术能力
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> **核心原则：** 可复用、高内聚、独立部署
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---
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## 📋 能力清单
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| 能力 | 说明 | 复用率 | 优先级 | 状态 |
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|------|------|-------|--------|------|
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| **01-LLM大模型网关** | 统一管理LLM调用、成本控制、模型切换 | 71% (5/7) | P0 | ⏳ 待实现 |
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| **02-文档处理引擎** | PDF/Docx/Txt提取、OCR、表格提取 | 86% (6/7) | P0 | ✅ 已实现 |
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| **03-RAG引擎** | 向量检索、语义搜索、RAG问答 | 43% (3/7) | P1 | ✅ 已实现 |
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| **04-数据ETL引擎** | Excel JOIN、数据清洗、数据转换 | 29% (2/7) | P2 | ⏳ 待实现 |
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| **05-医学NLP引擎** | 医学实体识别、术语标准化 | 14% (1/7) | P2 | ⏳ 待实现 |
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---
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## 🎯 设计原则
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### 1. 可复用性
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- 多个业务模块共享
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- 避免重复开发
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### 2. 独立部署
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- 可以独立为微服务
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- 支持独立扩展
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### 3. 高内聚
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- 每个能力职责单一
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- 接口清晰
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### 4. 领域知识
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- 包含业务领域知识
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- 不是纯技术组件
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---
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## 📊 复用率分析
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**LLM网关** - 71%复用率（最高优先级）
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- AIA（AI智能问答）
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- ASL（AI智能文献）
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- PKB（个人知识库）
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- DC（数据清洗）
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- RVW（稿件审查）
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**文档处理引擎** - 86%复用率（已实现）
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- ASL、PKB、DC、SSA、ST、RVW
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**RAG引擎** - 43%复用率（已实现）
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- AIA、ASL、PKB
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---
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## 📚 快速导航
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### 快速上下文
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- **[AI对接] 通用能力快速上下文.md** - 2-3分钟了解通用能力层
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### 核心能力
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1. [LLM大模型网关](./01-LLM大模型网关/README.md) - P0优先级 ⭐
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2. [文档处理引擎](./02-文档处理引擎/README.md) - 已实现
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3. [RAG引擎](./03-RAG引擎/README.md) - 已实现
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4. [数据ETL引擎](./04-数据ETL引擎/README.md)
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5. [医学NLP引擎](./05-医学NLP引擎/README.md)
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---
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## 🔗 相关文档
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- [系统架构分层设计](../00-系统总体设计/01-系统架构分层设计.md)
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- [平台基础层](../01-平台基础层/README.md)
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- [业务模块层](../03-业务模块/README.md)
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---
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**最后更新：** 2025-11-06
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**维护人：** 技术架构师
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