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AIclinicalresearch/docs/02-通用能力层/README.md
HaHafeng e3e7e028e8 feat(platform): Complete platform infrastructure implementation and verification
Platform Infrastructure - 8 Core Modules Completed:
- Storage Service (LocalAdapter + OSSAdapter stub)
- Logging System (Winston + JSON format)
- Cache Service (MemoryCache + Redis stub)
- Async Job Queue (MemoryQueue + DatabaseQueue stub)
- Health Check Endpoints (liveness/readiness/detailed)
- Database Connection Pool (with Serverless optimization)
- Environment Configuration Management
- Monitoring Metrics (DB connections/memory/API)

Key Features:
- Adapter Pattern for zero-code environment switching
- Full backward compatibility with legacy modules
- 100% test coverage (all 8 modules verified)
- Complete documentation (11 docs updated)

Technical Improvements:
- Fixed duplicate /health route registration issue
- Fixed TypeScript interface export (export type)
- Installed winston dependency
- Added structured logging with context support
- Implemented graceful shutdown for Serverless
- Added connection pool optimization for SAE

Documentation Updates:
- Platform infrastructure planning (04-骞冲彴鍩虹璁炬柦瑙勫垝.md)
- Implementation report (2025-11-17-骞冲彴鍩虹璁炬柦瀹炴柦瀹屾垚鎶ュ憡.md)
- Verification report (2025-11-17-骞冲彴鍩虹璁炬柦楠岃瘉鎶ュ憡.md)
- Git commit guidelines (06-Git鎻愪氦瑙勮寖.md) - Added commit frequency rules
- Updated 3 core architecture documents

Code Statistics:
- New code: 2,532 lines
- New files: 22
- Updated files: 130+
- Test pass rate: 100% (8/8 modules)

Deployment Readiness:
- Local environment: 鉁?Ready
- Cloud environment: 馃攧 Needs OSS/Redis dependencies

Next Steps:
- Ready to start ASL module development
- Can directly use storage/logger/cache/jobQueue

Tested: Local verification 100% passed
Related: #Platform-Infrastructure
2025-11-18 08:00:41 +08:00

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