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b64896a307
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feat(deploy): Complete PostgreSQL migration and Docker image build
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
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2025-12-24 18:21:55 +08:00 |
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f729699510
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feat(dc): Complete Tool C quick action buttons Phase 1-2 - 7 functions
Summary:
- Implement 7 quick action functions (filter, recode, binning, conditional, dropna, compute, pivot)
- Refactor to pre-written Python functions architecture (stable and secure)
- Add 7 Python operations modules with full type hints
- Add 7 frontend Dialog components with user-friendly UI
- Fix NaN serialization issues and auto type conversion
- Update all related documentation
Technical Details:
- Python: operations/ module (filter.py, recode.py, binning.py, conditional.py, dropna.py, compute.py, pivot.py)
- Backend: QuickActionService.ts with 7 execute methods
- Frontend: 7 Dialog components with complete validation
- Toolbar: Enable 7 quick action buttons
Status: Phase 1-2 completed, basic testing passed, ready for further testing
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2025-12-08 17:38:08 +08:00 |
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af325348b8
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feat(dc): Complete Tool C Day 5 - AI Chat + Ant Design X Integration
Summary:
- Upgrade to Ant Design 6.0.1 + install Ant Design X (2.1.0) + X SDK (2.1.0)
- Develop frontend common capability layer: Chat component library (~968 lines)
* ChatContainer.tsx - Core container component
* MessageRenderer.tsx - Message renderer
* CodeBlockRenderer.tsx - Code block renderer with syntax highlighting
* Complete TypeScript types and documentation
- Integrate ChatContainer into Tool C
- Fix 7 critical UI issues:
* AG Grid module registration error
* UI refinement (borders, shadows, gradients)
* Add AI welcome message
* Auto-clear input field after sending
* Remove page scrollbars
* Manual code execution (not auto-run)
* Support simple Q&A (new /ai/chat API)
- Complete end-to-end testing
- Update all documentation (4 status docs + 6 dev logs)
Technical Stack:
- Frontend: React 19 + Ant Design 6.0 + Ant Design X 2.1
- Components: Bubble, Sender from @ant-design/x
- Total code: ~5418 lines
Status: Tool C MVP completed, production ready
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2025-12-07 22:02:14 +08:00 |
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