HaHafeng
b64896a307
Summary: - PostgreSQL database migration to RDS completed (90MB SQL, 11 schemas) - Frontend Nginx Docker image built and pushed to ACR (v1.0, ~50MB) - Python microservice Docker image built and pushed to ACR (v1.0, 1.12GB) - Created 3 deployment documentation files Docker Configuration Files: - frontend-v2/Dockerfile: Multi-stage build with nginx:alpine - frontend-v2/.dockerignore: Optimize build context - frontend-v2/nginx.conf: SPA routing and API proxy - frontend-v2/docker-entrypoint.sh: Dynamic env injection - extraction_service/Dockerfile: Multi-stage build with Aliyun Debian mirror - extraction_service/.dockerignore: Optimize build context - extraction_service/requirements-prod.txt: Production dependencies (removed Nougat) Deployment Documentation: - docs/05-部署文档/00-部署进度总览.md: One-stop deployment status overview - docs/05-部署文档/07-前端Nginx-SAE部署操作手册.md: Frontend deployment guide - docs/05-部署文档/08-PostgreSQL数据库部署操作手册.md: Database deployment guide - docs/00-系统总体设计/00-系统当前状态与开发指南.md: Updated with deployment status Database Migration: - RDS instance: pgm-2zex1m2y3r23hdn5 (2C4G, PostgreSQL 15.0) - Database: ai_clinical_research - Schemas: 11 business schemas migrated successfully - Data: 3 users, 2 projects, 1204 literatures verified - Backup: rds_init_20251224_154529.sql (90MB) Docker Images: - Frontend: crpi-cd5ij4pjt65mweeo.cn-beijing.personal.cr.aliyuncs.com/ai-clinical/ai-clinical_frontend-nginx:v1.0 - Python: crpi-cd5ij4pjt65mweeo.cn-beijing.personal.cr.aliyuncs.com/ai-clinical/python-extraction:v1.0 Key Achievements: - Resolved Docker Hub network issues (using generic tags) - Fixed 30 TypeScript compilation errors - Removed Nougat OCR to reduce image size by 1.5GB - Used Aliyun Debian mirror to resolve apt-get network issues - Implemented multi-stage builds for optimization Next Steps: - Deploy Python microservice to SAE - Build Node.js backend Docker image - Deploy Node.js backend to SAE - Deploy frontend Nginx to SAE - End-to-end verification testing Status: Docker images ready, SAE deployment pending
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）
- AIA（AI智能问答）
- ASL（AI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
🔗 相关文档
最后更新： 2025-11-06
维护人： 技术架构师