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
ASL - AI智能文献
模块代号: ASL (AI Smart Literature)
开发状态: ⏳ 下一步开发(Week 2-4)
商业价值: ⭐⭐⭐⭐⭐ 可独立售卖
独立性: ⭐⭐⭐⭐⭐
优先级: P0
📋 模块概述
AI智能文献筛选系统,帮助研究者快速筛选和分析文献。
核心价值: 核心差异化功能,可独立售卖
🎯 核心功能(6个模块)
- ✅ 标题摘要初筛 - 双模型AI判断
- ✅ 全文复筛 - PDF全文分析
- ⏳ 全文解析与数据提取
- ⏳ 数据分析与报告生成
- ⏳ 系统评价与Meta分析
- ⏳ 文献管理
本周重点: 标题摘要初筛 + 全文复筛
📂 文档结构
ASL-AI智能文献/
├── [AI对接] ASL快速上下文.md # ⏳ 待创建
├── 00-项目概述/
│ ├── 01-产品需求文档(PRD).md # ⏳ 待合并(3个PRD)
│ └── ...
├── 01-设计文档/
│ ├── 02-数据库设计.md
│ ├── 03-API设计.md
│ └── 07-UI设计/
│ ├── 标题摘要初筛原型.html
│ └── 全文复筛原型.html
└── README.md # ✅ 当前文档
🔗 依赖的通用能力
- LLM网关 - 双模型AI判断
- 文档处理引擎 - PDF全文提取
- RAG引擎 - 文献内容检索
🎯 商业模式
目标客户: 系统评价研究者、循证医学中心
售卖方式: 独立产品
定价策略: 按项目数或按月订阅
最后更新: 2025-11-06
维护人: 技术架构师