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
68 lines
1.6 KiB
PowerShell
68 lines
1.6 KiB
PowerShell
# DC模块代码恢复脚本运行器
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Write-Host "==================================================================================" -ForegroundColor Cyan
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Write-Host "DC模块代码恢复工具" -ForegroundColor Cyan
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Write-Host "==================================================================================" -ForegroundColor Cyan
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# 检查Python是否安装
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try {
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$pythonVersion = python --version 2>&1
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Write-Host "✅ Python版本: $pythonVersion" -ForegroundColor Green
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} catch {
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Write-Host "❌ 错误: Python未安装或不在PATH中" -ForegroundColor Red
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exit 1
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}
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# 运行恢复脚本
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Write-Host "`n📦 开始运行恢复脚本..." -ForegroundColor Yellow
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$output = python recover_dc_code.py 2>&1 | Out-String
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Write-Host $output
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# 保存输出到文件
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$output | Out-File "recovery_output.log" -Encoding UTF8
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Write-Host "`n💾 输出已保存到: recovery_output.log" -ForegroundColor Green
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# 检查恢复结果
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if (Test-Path "recovered_dc_code") {
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Write-Host "`n✅ 恢复目录已创建!" -ForegroundColor Green
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Write-Host "📁 恢复的文件:" -ForegroundColor Cyan
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Get-ChildItem "recovered_dc_code" | Format-Table Name, Length, LastWriteTime
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} else {
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Write-Host "`n⚠️ 未创建恢复目录,可能未找到DC代码" -ForegroundColor Yellow
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}
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Write-Host "`n==================================================================================" -ForegroundColor Cyan
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Write-Host "完成!请查看 recovered_dc_code 目录" -ForegroundColor Cyan
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Write-Host "==================================================================================" -ForegroundColor Cyan
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