Develop/AIclinicalresearch
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
173 Commits 1 Branch 0 Tags
bf10dec4c876b3d4214c47dee67df3140df0ef3f
Commit Graph

125 Commits

Author SHA1 Message Date
HaHafeng
dfc472810b feat(iit-manager): Integrate Dify knowledge base for hybrid retrieval 
Completed features:
- Created Dify dataset (Dify_test0102) with 2 processed documents
- Linked test0102 project with Dify dataset ID
- Extended intent detection to recognize query_protocol intent
- Implemented queryDifyKnowledge method (semantic search Top 5)
- Integrated hybrid retrieval (REDCap data + Dify documents)
- Fixed AI hallucination bugs (intent detection + API field path)
- Developed debugging scripts
- Completed end-to-end testing (5 scenarios passed)
- Generated comprehensive documentation (600+ lines)
- Updated development plans and module status

Technical highlights:
- Single project single knowledge base architecture
- Smart routing based on user intent
- Prevent AI hallucination by injecting real data/documents
- Session memory for multi-turn conversations
- Reused LLMFactory for DeepSeek-V3 integration

Bug fixes:
- Fixed intent detection missing keywords
- Fixed Dify API response field path error

Testing: All scenarios verified in WeChat production environment

Status: Fully tested and deployed
 2026-01-04 15:44:11 +08:00
HaHafeng
b47079b387 feat(iit): Phase 1.5 AI对话集成REDCap真实数据完成 
- feat: ChatService集成DeepSeek-V3实现AI对话（390行）
- feat: SessionMemory实现上下文记忆（最近3轮对话，170行）
- feat: 意图识别支持REDCap数据查询（关键词匹配）
- feat: REDCap数据注入LLM（queryRedcapRecord, countRedcapRecords, getProjectInfo）
- feat: 解决LLM幻觉问题（基于真实数据回答，明确system prompt）
- feat: 即时反馈（正在查询...提示）
- test: REDCap查询测试通过（test0102项目，10条记录，ID 7患者详情）
- docs: 创建Phase1.5开发完成记录（313行）
- docs: 更新Phase1.5开发计划（标记完成）
- docs: 更新MVP开发任务清单（Phase 1.5完成）
- docs: 更新模块当前状态（60%完成度）
- docs: 更新系统总体设计文档（v2.6）
- chore: 删除测试脚本（test-redcap-query-for-ai.ts, check-env-config.ts）
- chore: 移除REDCap测试环境变量（REDCAP_TEST_*）

技术亮点：
- AI基于REDCap真实数据对话，不编造信息
- 从数据库读取项目配置，不使用环境变量
- 企业微信端测试通过，用户体验良好

测试通过：
-  查询项目记录总数（10条）
-  查询特定患者详情（ID 7）
-  项目信息查询
-  上下文记忆（3轮对话）
-  即时反馈提示

影响范围：IIT Manager Agent模块
 2026-01-03 22:48:10 +08:00
HaHafeng
4794640f5d feat(iit): Phase 1.5 AI对话能力集成 - 复用通用能力层LLMFactory 
新增功能
- SessionMemory: 会话记忆管理器（存储最近3轮对话）
- ChatService: AI对话服务（复用LLMFactory，支持DeepSeek-V3）
- WechatCallbackController: 集成AI对话 + '正在查询'即时反馈

 技术亮点
- 复用通用能力层LLMFactory（零配置，单例模式）
- 上下文记忆（SessionMemory，Node.js内存，自动清理过期会话）
- 即时反馈（立即回复'正在查询，请稍候...'，规避5秒超时）
- 极简MVP（<300行代码，1天完成）

 文档更新
- Phase1.5开发计划文档（反映通用能力层复用优势）

 完成度
- Phase 1.5核心功能：100%
- 预估工作量：2-3天  实际：1天（LLM调用层已完善）

Scope: iit-manager
 2026-01-03 16:42:46 +08:00
HaHafeng
6a567f028f feat(iit-manager): 完成MVP闭环 - 企业微信集成与端到端测试 
核心交付物:
- WechatService (314行): Access Token缓存 + 消息推送
- WechatCallbackController (501行): URL验证 + 消息接收
- 质控Worker完善: 质控逻辑 + 企业微信推送 + 审计日志
- Worker注册修复: initIitManager() 在启动时调用
- 数据库字段修复: action -> action_type
- 端到端测试通过: <2秒延迟, 100%成功率

性能指标:
- Webhook响应: 5.8ms (目标<10ms)
- Worker执行: ~50ms (目标<100ms)
- 端到端延迟: <2秒 (目标<5秒)
- 消息成功率: 100% (测试5次)

临时措施:
- UserID从环境变量获取 (Phase 2改进)
- 定时轮询暂时禁用 (Phase 2添加)
- 质控逻辑简化 (Phase 1.5集成Dify)

Closes #IIT-MVP-Day3
 2026-01-03 14:19:08 +08:00
HaHafeng
5f089516cb feat(iit-manager): Day 3 企业微信集成开发完成 
- 新增WechatService（企业微信推送服务，支持文本/卡片/Markdown消息）
- 新增WechatCallbackController（异步回复模式，5秒内响应）
- 完善iit_quality_check Worker（调用WechatService推送通知）
- 新增企业微信回调路由（GET验证+POST接收消息）
- 实现LLM意图识别（query_weekly_summary/query_patient_info等）
- 安装依赖：@wecom/crypto, xml2js
- 更新开发记录文档和MVP开发计划

技术要点：
- 使用异步回复模式规避企业微信5秒超时限制
- 使用@wecom/crypto官方库处理XML加解密
- 使用setImmediate实现后台异步处理
- 支持主动推送消息返回LLM处理结果
- 完善审计日志记录（WECHAT_NOTIFICATION_SENT/WECHAT_INTERACTION）

相关文档：
- docs/03-业务模块/IIT Manager Agent/06-开发记录/Day3-企业微信集成开发完成记录.md
- docs/03-业务模块/IIT Manager Agent/04-开发计划/最小MVP闭环开发计划.md
- docs/03-业务模块/IIT Manager Agent/00-模块当前状态与开发指南.md
 2026-01-03 09:39:39 +08:00
HaHafeng
36ce1bbcb2 feat(iit): Complete Day 3 - WeChat Work integration and URL verification 
Summary:
- Implement WechatService (314 lines, push notifications)
- Implement WechatCallbackController (501 lines, async reply mode)
- Complete iit_quality_check Worker with WeChat notifications
- Configure WeChat routes (GET + POST /wechat/callback)
- Configure natapp tunnel for local development
- WeChat URL verification test passed

Technical Highlights:
- Async reply mode to avoid 5-second timeout
- Message encryption/decryption using @wecom/crypto
- Signature verification using getSignature
- natapp tunnel: https://iit.nat100.top
- Environment variables configuration completed

Technical Challenges Solved:
- Fix environment variable naming (WECHAT_CORP_SECRET)
- Fix @wecom/crypto import (createRequire for CommonJS)
- Fix decrypt function parameters (2 params, not 4)
- Fix Token character recognition (lowercase l vs digit 1)
- Regenerate EncodingAESKey (43 chars, correct format)
- Configure natapp for internal network penetration

Test Results:
- WeChat developer tool verification: PASSED
- Return status: request success
- HTTP 200, decrypted 23 characters correctly
- Backend logs: URL verification successful

Documentation:
- Add Day3 WeChat integration development record
- Update MVP development task list (Day 2-3 completed)
- Update module status guide (v1.2 -> v1.3)
- Overall completion: 35% -> 50%

Progress:
- Module completion: 35% -> 50%
- Day 3 development: COMPLETED
- Ready for end-to-end testing (REDCap -> WeChat)
 2026-01-03 00:13:36 +08:00
HaHafeng
2eef7522a1 feat(iit): Complete Day 2 - REDCap real-time integration 
Summary:
- Implement RedcapAdapter (271 lines, 7 API methods)
- Implement WebhookController (327 lines, <10ms response)
- Implement SyncManager (398 lines, incremental/full sync)
- Register Workers (iit_quality_check + iit_redcap_poll)
- Configure routes with form-urlencoded parser
- Add 3 integration test scripts (912 lines total)
- Complete development documentation

Technical Highlights:
- REDCap DET real-time trigger (0ms delay)
- Webhook + scheduled polling dual mechanism
- Form-urlencoded format support for REDCap DET
- Postgres-Only architecture with pg-boss queue
- Full compliance with team development standards

Test Results:
- Integration tests: 12/12 passed
- Real scenario validation: PASSED
- Performance: Webhook response <10ms
- Data accuracy: 100%

Progress:
- Module completion: 18% -> 35%
- Day 2 development: COMPLETED
- Production ready: YES
 2026-01-02 18:20:18 +08:00
HaHafeng
bdfca32305 docs(iit): REDCap对接技术方案完成与模块状态更新 
- 新增《REDCap对接技术方案与实施指南》(1070行)
  - 确定DET+REST API技术方案(不使用External Module)
  - 完整RedcapAdapter/WebhookController/SyncManager代码设计
  - Day 2详细实施步骤与验收标准
- 更新《IIT Manager Agent模块当前状态与开发指南》
  - 记录REDCap本地环境部署完成(15.8.0)
  - 记录对接方案确定过程与技术决策
  - 更新Day 2工作计划(6个阶段详细清单)
  - 整体进度18%(Day 1完成+REDCap环境就绪)
- REDCap环境准备完成
  - 测试项目test0102(PID 16)创建成功
  - DET功能源码验证通过
  - 本地Docker环境稳定运行

技术方案:
- 实时触发: Data Entry Trigger (0秒延迟)
- 数据拉取: REST API exportRecords (增量同步)
- 轮询补充: pg-boss定时任务 (每30分钟)
- 可靠性: Webhook幂等性 + 轮询补充机制
 2026-01-02 14:30:38 +08:00
HaHafeng
dbca1615b5 docs(redcap): 重构REDCap文档体系并创建Docker部署操作手册 
核心成果:
 创建REDCap模块文档体系（4个分类目录）
 完成《REDCap Docker部署操作手册》- 最核心文档
 梳理从0到1的完整部署流程
 明确Docker文件的可复用性

文档体系:
- 00-模块概览/     系统介绍、方案设计、决策报告
- 01-部署与配置/   部署手册、问题排查（核心）
- 02-系统配置与运维/ 日常管理（规划中）
- 03-API对接与开发/ API开发、二次开发
- 04-参考资料/     旧版文档存档

核心文档:
 10-REDCap_Docker部署操作手册.md（最重要）
  - 完整的从0到1部署流程
  - Docker文件复用说明和可复用性分析
  - 3种环境差异配置（本地/ECS/医院）
  - 5大常见问题与解决方案
  - 部署检查清单
  - 日常维护命令

 13-部署问题排查手册.md
  - 基于实际踩坑经验
  - ERR_CONTENT_DECODING_FAILED
  - CRLF污染问题
  - Base URL配置错误
  - MySQL连接问题

Docker文件可复用性:
 100%可复用（无需修改）:
  - Dockerfile.redcap
  - docker-entrypoint.sh
  - config/php/php.ini
  - .gitattributes

 需根据环境调整:
  - docker-compose.yml（端口、卷路径）
  - config/apache/redcap.conf（域名）
  - config/database.php（数据库连接）

文档重组:
- 移动文档到对应分类目录
- 重命名为标准格式（数字前缀）
- 旧版文档归档到参考资料
- 创建README快速入口

下一步:
- Day 2: 开发REDCap API Adapter
- 创建API使用指南
- 创建对接设计文档
 2026-01-02 10:17:00 +08:00
HaHafeng
38d9bf99d6 feat(redcap): REDCap 15.8.0 Docker本地开发环境部署完成 
核心成果:
- REDCap 15.8.0成功部署在Docker环境
- 登录功能正常，管理员账户: Admin/Admin123!
- MySQL 8.0 + PHP 8.1 + Apache 2.4环境验证通过

问题解决:
1. 修复ERR_CONTENT_DECODING_FAILED错误
   - 强制禁用Apache deflate模块
   - PHP配置关闭zlib.output_compression
   - 自动注释REDCap源码中的压缩设置

2. 修复Base URL配置错误
   - 更新redcap_config表中的redcap_base_url
   - 统一DocumentRoot与访问路径

3. 修复登录失败问题(CRLF污染)
   - 删除database.php末尾的PHP结束标签
   - 创建.gitattributes规范换行符
   - 验证REDCap官方源码无此问题

技术改进:
- 添加密码重置工具脚本
- 完善docker-entrypoint.sh启动脚本
- 创建详细的部署问题解决记录
- 建立PHP配置文件最佳实践

部署文档:
- REDCap本地Docker开发环境部署方案
- REDCap生产环境部署决策报告(ECS vs SAE)
- 部署问题解决记录(含根因分析)

下一步:
- Day 2: 开发REDCap API Adapter
- 实现与IIT Manager Agent的数据对接
 2026-01-02 10:02:46 +08:00
HaHafeng
dac3cecf78 feat(iit): Complete IIT Manager Agent Day 1 - Environment initialization and WeChat integration 
Summary:
- Complete IIT Manager Agent MVP Day 1 (12.5% progress)
- Database: Create iit_schema with 5 tables (IitProject, IitPendingAction, IitTaskRun, IitUserMapping, IitAuditLog)
- Backend: Add module structure (577 lines) and types (223 lines)
- WeChat: Configure Enterprise WeChat app (CorpID, AgentID, Secret)
- WeChat: Obtain web authorization and JS-SDK authorization
- WeChat: Configure trusted domain (iit.xunzhengyixue.com)
- Frontend: Deploy v1.2 with WeChat domain verification file
- Frontend: Fix CRLF issue in docker-entrypoint.sh (CRLF -> LF)
- Testing: 11/11 database CRUD tests passed
- Testing: Access Token retrieval test passed
- Docs: Create module status and development guide
- Docs: Update MVP task list with Day 1 completion
- Docs: Rename deployment doc to SAE real-time status record
- Deployment: Update frontend internal IP to 172.17.173.80

Technical Details:
- Prisma: Multi-schema support (iit_schema)
- pg-boss: Job queue integration prepared
- Taro 4.x: Framework selected for WeChat Mini Program
- Shadow State: Architecture foundation laid
- Docker: Fix entrypoint script line endings for Linux container

Status: Day 1/14 complete, ready for Day 2 REDCap integration
 2026-01-01 14:32:58 +08:00
HaHafeng
4c5bb3d174 feat(iit): Initialize IIT Manager Agent MVP - Day 1 complete 
- Add iit_schema with 5 tables
- Create module structure and types (223 lines)
- WeChat integration verified (Access Token success)
- Update system docs to v2.4
- Add REDCap source folders to .gitignore
- Day 1/14 complete (11/11 tasks)
 2025-12-31 18:35:05 +08:00
HaHafeng
decff0bb1f docs(deploy): Complete full system deployment to Aliyun SAE 
Summary:
- Successfully deployed complete system to Aliyun SAE (2025-12-25)
- All services running: Python microservice + Node.js backend + Frontend Nginx + CLB
- Public access available at http://8.140.53.236/

Major Achievements:
1. Python microservice deployed (v1.0, internal IP: 172.17.173.66:8000)
2. Node.js backend deployed (v1.3, internal IP: 172.17.173.73:3001)
   - Fixed 4 critical issues: bash path, config directory, pino-pretty, ES Module
3. Frontend Nginx deployed (v1.0, internal IP: 172.17.173.72:80)
4. CLB load balancer configured (public IP: 8.140.53.236)

New Documentation (9 docs):
- 11-Node.js backend SAE deployment config checklist (21 env vars)
- 12-Node.js backend SAE deployment operation manual
- 13-Node.js backend image fix record (config directory)
- 14-Node.js backend pino-pretty fix
- 15-Node.js backend deployment success summary
- 16-Frontend Nginx deployment success summary
- 17-Complete deployment practical manual 2025 edition (1800 lines)
- 18-Deployment documentation usage guide
- 19-Daily update quick operation manual (670 lines)

Key Fixes:
- Environment variable name correction: EXTRACTION_SERVICE_URL (not PYTHON_SERVICE_URL)
- Dockerfile fix: added COPY config ./config
- Logger configuration: conditional pino-pretty for dev only
- Health check fix: ES Module compatibility (require -> import)

Updated Files:
- System status document updated with full deployment info
- Deployment progress overview updated with latest IPs
- All 3 Docker services' Dockerfiles and configs refined

Verification:
- All health checks passed
- Tool C 7 features working correctly
- Literature screening module functional
- Response time < 1 second

BREAKING CHANGE: Node.js backend internal IP changed from 172.17.173.71 to 172.17.173.73

Closes #deployment-milestone
 2025-12-25 21:24:37 +08:00
HaHafeng
691dc2bc98 docs(deploy): Update deployment documentation for Node.js backend 
Summary:
- Created Node.js backend Docker image build guide
- Updated deployment progress overview with backend status
- Updated system status documentation

Backend build achievements:
- Fixed 200+ TypeScript compilation errors (200+ to 0)
- Completed Prisma reverse sync (32 models from RDS)
- Manually added 30+ Prisma relation fields
- Successfully built Docker image (838MB)
- Pushed image to ACR (v1.0 + latest tags)

Documentation updates:
- Added 10-Node.js后端-Docker镜像构建手册.md
- Updated 00-部署进度总览.md with backend deployment status
- Updated 00-系统当前状态与开发指南.md with latest progress
- Fixed date format (2024 -> 2025)

Next steps:
- Deploy Node.js backend to SAE
- Configure environment variables
- Test end-to-end functionality

Status: Backend Docker image ready for SAE deployment
 2025-12-25 08:21:21 +08:00
HaHafeng
ef967d7d7c build(backend): Complete Node.js backend deployment preparation 
Major changes:
- Add Docker configuration (Dockerfile, .dockerignore)
- Fix 200+ TypeScript compilation errors
- Add Prisma schema relations for all models (30+ relations)
- Update tsconfig.json to relax non-critical checks
- Optimize Docker build with local dist strategy

Technical details:
- Exclude test files from TypeScript compilation
- Add manual relations for ASL, PKB, DC, AIA modules
- Use type assertions for JSON/Buffer compatibility
- Fix pg-boss, extractionWorker, and other legacy code issues

Build result:
- Docker image: 838MB (compressed ~186MB)
- Successfully pushed to ACR
- Zero TypeScript compilation errors

Related docs:
- Update deployment documentation
- Add Python microservice SAE deployment guide
 2025-12-24 22:12:00 +08:00
HaHafeng
b64896a307 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
 2025-12-24 18:21:55 +08:00
HaHafeng
5fa7b0bbe1 docs(common): Add platform infrastructure technical debt list 
Summary:
- Document future optimization opportunities based on Tool C practice
- 7 technical debts identified with priority and effort estimation
- Focus on: Clean data service, Data version management, Generic polling Hook

Content:
- TD-COMMON-001: Generic polling Hook for frontend (P2, 0.5d)
- TD-COMMON-002: Clean data caching service (P1, 1d, High priority)
- TD-COMMON-003: Generic data cleaning algorithms (P2, 0.5d)
- TD-COMMON-004: Worker registration helper (P3, 0.3d)
- TD-COMMON-005: Data version management system (P1, 3d, High priority)
- TD-COMMON-006: Ghost column/row detection library (P2, 0.5d)
- TD-COMMON-007: Generic progress bar component (P2, 0.3d)

Recommendation:
- Priority 1: Clean data service + Data version management
- Priority 2: Generic polling Hook
- Current architecture is already good, these are enhancements

Status: Documentation complete, ready for future implementation
 2025-12-22 21:39:35 +08:00
HaHafeng
4c6eaaecbf feat(dc): Implement Postgres-Only async architecture and performance optimization 
Summary:
- Implement async file upload processing (Platform-Only pattern)
- Add parseExcelWorker with pg-boss queue
- Implement React Query polling mechanism
- Add clean data caching (avoid duplicate parsing)
- Fix pivot single-value column tuple issue
- Optimize performance by 99 percent

Technical Details:

1. Async Architecture (Postgres-Only):
   - SessionService.createSession: Fast upload + push to queue (3s)
   - parseExcelWorker: Background parsing + save clean data (53s)
   - SessionController.getSessionStatus: Status query API for polling
   - React Query Hook: useSessionStatus (auto-serial polling)
   - Frontend progress bar with real-time feedback

2. Performance Optimization:
   - Clean data caching: Worker saves processed data to OSS
   - getPreviewData: Read from clean data cache (0.5s vs 43s, -99 percent)
   - getFullData: Read from clean data cache (0.5s vs 43s, -99 percent)
   - Intelligent cleaning: Boundary detection + ghost column/row removal
   - Safety valve: Max 3000 columns, 5M cells

3. Bug Fixes:
   - Fix pivot column name tuple issue for single value column
   - Fix queue name format (colon to underscore: asl:screening -> asl_screening)
   - Fix polling storm (15+ concurrent requests -> 1 serial request)
   - Fix QUEUE_TYPE environment variable (memory -> pgboss)
   - Fix logger import in PgBossQueue
   - Fix formatSession to return cleanDataKey
   - Fix saveProcessedData to update clean data synchronously

4. Database Changes:
   - ALTER TABLE dc_tool_c_sessions ADD COLUMN clean_data_key VARCHAR(1000)
   - ALTER TABLE dc_tool_c_sessions ALTER COLUMN total_rows DROP NOT NULL
   - ALTER TABLE dc_tool_c_sessions ALTER COLUMN total_cols DROP NOT NULL
   - ALTER TABLE dc_tool_c_sessions ALTER COLUMN columns DROP NOT NULL

5. Documentation:
   - Create Postgres-Only async task processing guide (588 lines)
   - Update Tool C status document (Day 10 summary)
   - Update DC module status document
   - Update system overview document
   - Update cloud-native development guide

Performance Improvements:
- Upload + preview: 96s -> 53.5s (-44 percent)
- Filter operation: 44s -> 2.5s (-94 percent)
- Pivot operation: 45s -> 2.5s (-94 percent)
- Concurrent requests: 15+ -> 1 (-93 percent)
- Complete workflow (upload + 7 ops): 404s -> 70.5s (-83 percent)

Files Changed:
- Backend: 15 files (Worker, Service, Controller, Schema, Config)
- Frontend: 4 files (Hook, Component, API)
- Docs: 4 files (Guide, Status, Overview, Spec)
- Database: 4 column modifications
- Total: ~1388 lines of new/modified code

Status: Fully tested and verified, production ready
 2025-12-22 21:30:31 +08:00
HaHafeng
9b81aef9a7 feat(dc): Add multi-metric transformation feature (direction 1+2) 
Summary:
- Implement intelligent multi-metric grouping detection algorithm
- Add direction 1: timepoint-as-row, metric-as-column (analysis format)
- Add direction 2: timepoint-as-column, metric-as-row (display format)
- Fix column name pattern detection (FMA___ issue)
- Maintain original Record ID order in output
- Add full-select/clear buttons in UI
- Integrate into TransformDialog with Radio selection
- Update 3 documentation files

Technical Details:
- Python: detect_metric_groups(), apply_multi_metric_to_long(), apply_multi_metric_to_matrix()
- Backend: 3 new methods in QuickActionService
- Frontend: MultiMetricPanel.tsx (531 lines)
- Total: ~1460 lines of new code

Status: Fully tested and verified, ready for production
 2025-12-21 15:06:15 +08:00
HaHafeng
8be8cdcf53 docs(deploy): Update quick deployment SOP with real ACR configuration 
Summary:
- Add complete ACR personal registry information (namespace, credentials, endpoints)
- Update all 3 image repositories with real addresses (frontend-nginx, python-extraction, nodejs-backend)
- Update docker login/tag/push commands with actual registry domain
- Add security warnings for credential management

Files changed:
- docs/05-部署文档/01-快速部署SOP-零基础版.md

Status: ACR configuration section completed, ready for Docker image build phase
 2025-12-18 21:30:01 +08:00
HaHafeng
19f9c5ea93 docs(deployment): Fix 8 critical deployment issues and enhance documentation 
Summary of fixes:
- Fix service discovery address (change .sae domain to internal IP)
- Unify timezone configuration (Asia/Shanghai for all services)
- Enhance ECS security group configuration (Redis/Weaviate port binding)
- Add image pull strategy best practices
- Add Python service memory management guidelines
- Update Dify API Key deployment strategy (avoid deadlock)
- Add SSH tunnel for RDS database access
- Add NAT gateway cost optimization explanation

Modified files (7 docs):
- 00-部署架构总览.md (enhanced with 7 sections)
- 03-Dify-ECS部署完全指南.md (security hardening)
- 04-Python微服务-SAE容器部署指南.md (timezone + service discovery)
- 05-Node.js后端-SAE容器部署指南.md (timezone configuration)
- PostgreSQL部署策略-摸底报告.md (timezone best practice)
- 07-关键配置补充说明.md (3 new sections)
- 08-部署检查清单.md (service address fix)

New files:
- 文档修正报告-20251214.md (comprehensive fix report)
- Review documents from technical team

Impact:
- Fixed 3 P0/P1 critical issues (100% connection failure risk)
- Fixed 3 P2 important issues (stability and maintainability)
- Added 2 P3 best practices (developer convenience)

Status: All deployment documents reviewed and corrected, ready for production deployment
 2025-12-14 13:25:28 +08:00
HaHafeng
fa72beea6c feat(platform): Complete Postgres-Only architecture refactoring (Phase 1-7) 
Major Changes:
- Implement Platform-Only architecture pattern (unified task management)
- Add PostgresCacheAdapter for unified caching (platform_schema.app_cache)
- Add PgBossQueue for job queue management (platform_schema.job)
- Implement CheckpointService using job.data (generic for all modules)
- Add intelligent threshold-based dual-mode processing (THRESHOLD=50)
- Add task splitting mechanism (auto chunk size recommendation)
- Refactor ASL screening service with smart mode selection
- Refactor DC extraction service with smart mode selection
- Register workers for ASL and DC modules

Technical Highlights:
- All task management data stored in platform_schema.job.data (JSONB)
- Business tables remain clean (no task management fields)
- CheckpointService is generic (shared by all modules)
- Zero code duplication (DRY principle)
- Follows 3-layer architecture principle
- Zero additional cost (no Redis needed, save 8400 CNY/year)

Code Statistics:
- New code: ~1750 lines
- Modified code: ~500 lines
- Test code: ~1800 lines
- Documentation: ~3000 lines

Testing:
- Unit tests: 8/8 passed
- Integration tests: 2/2 passed
- Architecture validation: passed
- Linter errors: 0

Files:
- Platform layer: PostgresCacheAdapter, PgBossQueue, CheckpointService, utils
- ASL module: screeningService, screeningWorker
- DC module: ExtractionController, extractionWorker
- Tests: 11 test files
- Docs: Updated 4 key documents

Status: Phase 1-7 completed, Phase 8-9 pending
 2025-12-13 16:10:04 +08:00
HaHafeng
200eab5c2e feat(dc-tool-c): Tool C UX重大改进 - 列头筛选/行号/滚动条/全量数据 
新功能
- 列头筛选：Excel风格筛选功能（Community版本，中文本地化，显示唯一值及计数）
- 行号列：添加固定行号列（#列头，灰色背景，左侧固定）
- 全量数据加载：不再限制50行预览，Session加载全量数据
- 全量数据返回：所有快速操作（筛选/映射/分箱/条件/删NA/计算/Pivot）全量返回结果

 Bug修复
- 滚动条终极修复：修改MainLayout为固定高度（h-screen + overflow-hidden），整个浏览器窗口无滚动条，只有AG Grid内部滚动
- 计算列全角字符修复：自动转换中文括号等全角字符为半角
- 计算列特殊字符列名修复：完善列别名机制，支持任意特殊字符列名

 UI优化
- 删除'表格仅展示前50行'提示条，减少干扰
- 筛选对话框美化：白色背景，圆角，阴影
- 列头筛选图标优化：清晰可见，易于点击

 文档更新
- 工具C_功能按钮开发计划_V1.0.md：添加V1.5版本记录
- 工具C_MVP开发_TODO清单.md：添加Day 8 UX优化内容
- 00-工具C当前状态与开发指南.md：更新进度为98%
- 00-模块当前状态与开发指南.md：更新DC模块状态
- 00-系统当前状态与开发指南.md：更新系统整体状态

 影响范围
- Python微服务：无修改
- Node.js后端：5处代码修改（SessionService + QuickActionController + AICodeService）
- 前端：MainLayout + DataGrid + ag-grid-custom.css + index.tsx
- 完成度：Tool C整体完成度提升至98%

 代码统计
- 修改文件：~15个文件
- 新增行数：~200行
- 修改行数：~150行

Co-authored-by: AI Assistant <assistant@example.com>
 2025-12-10 18:02:42 +08:00
HaHafeng
74cf346453 feat(dc/tool-c): Add missing value imputation feature with 6 methods and MICE 
Major features:
1. Missing value imputation (6 simple methods + MICE):
   - Mean/Median/Mode/Constant imputation
   - Forward fill (ffill) and Backward fill (bfill) for time series
   - MICE multivariate imputation (in progress, shape issue to fix)

2. Auto precision detection:
   - Automatically match decimal places of original data
   - Prevent false precision (e.g. 13.57 instead of 13.566716417910449)

3. Categorical variable detection:
   - Auto-detect and skip categorical columns in MICE
   - Show warnings for unsuitable columns
   - Suggest mode imputation for categorical data

4. UI improvements:
   - Rename button: "Delete Missing" to "Missing Value Handling"
   - Remove standalone "Dedup" and "MICE" buttons
   - 3-tab dialog: Delete / Fill / Advanced Fill
   - Display column statistics and recommended methods
   - Extended warning messages (8 seconds for skipped columns)

5. Bug fixes:
   - Fix sessionService.updateSessionData -> saveProcessedData
   - Fix OperationResult interface (add message and stats)
   - Fix Toolbar button labels and removal

Modified files:
Python: operations/fillna.py (new, 556 lines), main.py (3 new endpoints)
Backend: QuickActionService.ts, QuickActionController.ts, routes/index.ts
Frontend: MissingValueDialog.tsx (new, 437 lines), Toolbar.tsx, index.tsx
Tests: test_fillna_operations.py (774 lines), test scripts and docs
Docs: 5 documentation files updated

Known issues:
- MICE imputation has DataFrame shape mismatch issue (under debugging)
- Workaround: Use 6 simple imputation methods first

Status: Development complete, MICE debugging in progress
Lines added: ~2000 lines across 3 tiers
 2025-12-10 13:06:00 +08:00
HaHafeng
f4f1d09837 feat(dc/tool-c): Add pivot column ordering and NA handling features 
Major features:
1. Pivot transformation enhancements:
   - Add option to keep unselected columns with 3 aggregation methods
   - Maintain original column order after pivot (aligned with source file)
   - Preserve pivot value order (first appearance order)

2. NA handling across 4 core functions:
   - Recode: Support keep/map/drop for NA values
   - Filter: Already supports is_null/not_null operators
   - Binning: Support keep/label/assign for NA values (fix nan display)
   - Conditional: Add is_null/not_null operators

3. UI improvements:
   - Enable column header tooltips with custom header component
   - Add closeable alert for 50-row preview
   - Fix page scrollbar issues

Modified files:
Python: pivot.py, recode.py, binning.py, conditional.py, main.py
Backend: SessionController, QuickActionController, QuickActionService
Frontend: PivotDialog, RecodeDialog, BinningDialog, ConditionalDialog, DataGrid, index

Status: Ready for testing
 2025-12-09 14:40:14 +08:00
HaHafeng
75ceeb0653 hotfix(dc/tool-c): Fix compute formula validation and binning NaN serialization 
Critical fixes:
1. Compute column: Add Chinese comma support in formula validation
   - Problem: Formula with Chinese comma failed validation
   - Fix: Add Chinese comma character to allowed_chars regex
   - Example: Support formulas like 'col1（kg）+ col2，col3'

2. Binning operation: Fix NaN serialization error
   - Problem: 'Out of range float values are not JSON compliant: nan'
   - Fix: Enhanced NaN/inf handling in binning endpoint
   - Added np.inf/-np.inf replacement before JSON serialization
   - Added manual JSON serialization with NaN->null conversion

3. Enhanced all operation endpoints for consistency
   - Updated conditional, dropna endpoints with same NaN/inf handling
   - Ensures all operations return JSON-compliant data

Modified files:
- extraction_service/operations/compute.py: Add Chinese comma to regex
- extraction_service/main.py: Enhanced NaN handling in binning/conditional/dropna

Status: Hotfix complete, ready for testing
 2025-12-09 08:45:27 +08:00
HaHafeng
91cab452d1 fix(dc/tool-c): Fix special character handling and improve UX 
Major fixes:
- Fix pivot transformation with special characters in column names
- Fix compute column validation for Chinese punctuation
- Fix recode dialog to fetch unique values from full dataset via new API
- Add column mapping mechanism to handle special characters

Database migration:
- Add column_mapping field to dc_tool_c_sessions table
- Migration file: 20251208_add_column_mapping

UX improvements:
- Darken table grid lines for better visibility
- Reduce column width by 40% with tooltip support
- Insert new columns next to source columns
- Preserve original row order after operations
- Add notice about 50-row preview limit

Modified files:
- Backend: SessionService, SessionController, QuickActionService, routes
- Python: pivot.py, compute.py, recode.py, binning.py, conditional.py
- Frontend: DataGrid, RecodeDialog, index.tsx, ag-grid-custom.css
- Database: schema.prisma, migration SQL

Status: Code complete, database migrated, ready for testing
 2025-12-08 23:20:55 +08:00
HaHafeng
f729699510 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
 2025-12-08 17:38:08 +08:00
HaHafeng
af325348b8 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
 2025-12-07 22:02:14 +08:00
HaHafeng
2c7ed94161 feat(dc/tool-c): 完成前端基础框架（Day 4 MVP） 
核心功能：
- 新增Tool C主入口（index.tsx, 258行）：状态管理+布局
- 新增Header组件（91行）：顶栏+返回按钮+导出
- 新增Toolbar组件（104行）：7个快捷按钮+搜索框
- 新增DataGrid组件（111行）：AG Grid Community集成
- 新增Sidebar组件（149行）：右侧栏骨架版
- 新增API封装（toolC.ts, 218行）：8个API方法
- 新增类型定义（types/index.ts, 62行）

AG Grid集成：
- 安装ag-grid-community + ag-grid-react
- Excel风格表格渲染
- 列排序、过滤、调整宽度
- 缺失值高亮显示（红色斜体）
- 数值右对齐
- 自定义Emerald绿色主题（ag-grid-custom.css, 113行）
- 虚拟滚动支持大数据

路由配置：
- 更新dc/index.tsx：新增ToolCModule懒加载
- 更新Portal.tsx：Tool C状态改为ready
- 路径：/data-cleaning/tool-c

API封装（8个方法）：
- uploadFile（上传CSV/Excel）
- getSession（获取Session元数据）
- getPreviewData（获取预览数据）
- updateHeartbeat（延长10分钟）
- generateCode（生成代码，不执行）
- executeCode（执行代码）
- processMessage（生成+执行，一步到位）核心API
- getChatHistory（对话历史）

文档更新：
- 新增Day 4前端基础完成总结（213行）
- 更新工具C当前状态文档
- 更新TODO清单（Day 1-4标记完成）
- 更新系统总体设计文档

测试数据准备：
- cqol-demo.csv（21列x313行真实医疗数据）
- G鼓膜穿孔数据.xlsx（备用）

Day 5待完成：
- MessageItem组件（消息渲染）
- CodeBlock组件（Prism.js代码高亮）
- InputArea组件（输入框交互）
- InsightsPanel组件（数据洞察）
- 完善Sidebar（完整Chat交互）
- 端到端测试

影响范围：
- frontend-v2/src/modules/dc/pages/tool-c/*（新增11个文件）
- frontend-v2/src/modules/dc/api/toolC.ts（新增）
- frontend-v2/src/modules/dc/index.tsx（更新路由）
- frontend-v2/src/modules/dc/pages/Portal.tsx（启用Tool C）
- docs/03-业务模块/DC-数据清洗整理/*（文档更新）
- package.json（新增依赖）

Breaking Changes: 无

总代码行数：+1106行（前端基础框架）

Refs: #Tool-C-Day4
 2025-12-07 17:40:07 +08:00
HaHafeng
f01981bf78 feat(dc/tool-c): 完成AI代码生成服务（Day 3 MVP） 
核心功能：
- 新增AICodeService（550行）：AI代码生成核心服务
- 新增AIController（257行）：4个API端点
- 新增dc_tool_c_ai_history表：存储对话历史
- 实现自我修正机制：最多3次智能重试
- 集成LLMFactory：复用通用能力层
- 10个Few-shot示例：覆盖Level 1-4场景

技术优化：
- 修复NaN序列化问题（Python端转None）
- 修复数据传递问题（从Session获取真实数据）
- 优化System Prompt（明确环境信息）
- 调整Few-shot示例（移除import语句）

测试结果：
- 通过率：9/11（81.8%） 达到MVP标准
- 成功场景：缺失值处理、编码、分箱、BMI、筛选、填补、统计、分类
- 待优化：数值清洗、智能去重（已记录技术债务TD-C-006）

API端点：
- POST /api/v1/dc/tool-c/ai/generate（生成代码）
- POST /api/v1/dc/tool-c/ai/execute（执行代码）
- POST /api/v1/dc/tool-c/ai/process（生成并执行，一步到位）
- GET /api/v1/dc/tool-c/ai/history/:sessionId（对话历史）

文档更新：
- 新增Day 3开发完成总结（770行）
- 新增复杂场景优化技术债务（TD-C-006）
- 更新工具C当前状态文档
- 更新技术债务清单

影响范围：
- backend/src/modules/dc/tool-c/*（新增2个文件，更新1个文件）
- backend/scripts/create-tool-c-ai-history-table.mjs（新增）
- backend/prisma/schema.prisma（新增DcToolCAiHistory模型）
- extraction_service/services/dc_executor.py（NaN序列化修复）
- docs/03-业务模块/DC-数据清洗整理/*（5份文档更新）

Breaking Changes: 无

总代码行数：+950行

Refs: #Tool-C-Day3
 2025-12-07 16:21:32 +08:00
HaHafeng
2348234013 feat(dc/tool-c): Day 2 - Session管理与数据处理完成 
核心功能:
- 数据库: 创建dc_tool_c_sessions表 (12字段, 3索引)
- 服务层: SessionService (383行), DataProcessService (303行)
- 控制器: SessionController (300行, 6个API端点)
- 路由: 新增6个Session管理路由
- 测试: 7个API测试全部通过 (100%)

技术亮点:
- 零落盘架构: Excel内存解析, OSS存储
- Session管理: 10分钟过期, 心跳延长机制
- 云原生规范: storage/logger/prisma全平台复用
- 完整测试: 上传/预览/完整数据/删除/心跳

文件清单:
- backend/prisma/schema.prisma (新增DcToolCSession模型)
- backend/prisma/migrations/create_tool_c_session.sql
- backend/scripts/create-tool-c-table.mjs
- backend/src/modules/dc/tool-c/services/ (SessionService, DataProcessService)
- backend/src/modules/dc/tool-c/controllers/SessionController.ts
- backend/src/modules/dc/tool-c/routes/index.ts
- backend/test-tool-c-day2.mjs
- docs/03-业务模块/DC-数据清洗整理/00-工具C当前状态与开发指南.md
- docs/03-业务模块/DC-数据清洗整理/06-开发记录/2025-12-06_工具C_Day2开发完成总结.md

代码统计: ~1900行
测试结果: 7/7 通过 (100%)
云原生规范: 完全符合
 2025-12-06 22:12:47 +08:00
HaHafeng
8be741cd52 docs(dc/tool-c): Complete Tool C MVP planning and TODO list 
Summary:
- Update Tool C MVP Development Plan (V1.3)
  * Clarify Python execution as core feature
  * Add 15 real medical data cleaning scenarios (basic/medium/advanced)
  * Enhance System Prompt with 10 Few-shot examples
  * Discover existing Python service (extraction_service)
  * Update to extend existing service instead of rebuilding
- Create Tool C MVP Development TODO List
  * 3-week plan with 30 tasks (Day 1-15)
  * 4 core milestones with clear acceptance criteria
  * Daily checklist and risk management
  * Detailed task breakdown for each day

Key Changes:
- Python service: Extend existing extraction_service instead of new setup
- Test scenarios: 15 scenarios (5 basic + 5 medium + 5 advanced)
- Success criteria: Basic >90%, Medium >80%, Advanced >60%, Total >80%
- Development time: Reduced from 3 weeks to 2 weeks (reuse infrastructure)

Status: Planning complete, ready to start Day 1 development
 2025-12-06 11:00:44 +08:00
HaHafeng
8a17369138 feat(dc): Complete Tool B MVP with full API integration and bug fixes 
Phase 5: Export Feature
- Add Excel export API endpoint (GET /tasks/:id/export)
- Fix Content-Disposition header encoding for Chinese filenames
- Fix export field order to match template definition
- Export finalResult or resultA as fallback

API Integration Fixes (Phase 1-5):
- Fix API response parsing (return result.data consistently)
- Fix field name mismatch (fileKey -> sourceFileKey)
- Fix Excel parsing bug (range:99 -> slice(0,100))
- Add file upload with Excel parsing (columns, totalRows)
- Add detailed error logging for debugging

LLM Integration Fixes:
- Fix LLM call method: LLMFactory.createLLM -> getAdapter
- Fix adapter interface: generateText -> chat([messages])
- Fix response fields: text -> content, tokensUsed -> usage.totalTokens
- Fix model names: qwen-max -> qwen3-72b

React Infinite Loop Fixes:
- Step2: Remove updateState from useEffect deps
- Step3: Add useRef to prevent Strict Mode double execution
- Step3: Clear interval on API failure (max 3 retries)
- Step4: Add useRef to prevent infinite data loading
- Add cleanup functions to all useEffect hooks

Frontend Enhancements:
- Add comprehensive error handling with user-friendly messages
- Remove debug console.logs (production ready)
- Fix TypeScript type definitions (TaskProgress, ExtractionItem)
- Improve Step4Verify data transformation logic

Backend Enhancements:
- Add detailed logging at each step for debugging
- Add parameter validation in controllers
- Improve error messages with stack traces (dev mode)
- Add export field ordering by template definition

Documentation Updates:
- Update module status: Tool B MVP completed
- Create MVP completion summary (06-开发记录)
- Create technical debt document (07-技术债务)
- Update API documentation with test status
- Update database documentation with verified status
- Update system overview with DC module status
- Document 4 known issues (Excel preprocessing, progress display, etc.)

Testing Results:
- File upload: 9 rows parsed successfully
- Health check: Column validation working
- Dual model extraction: DeepSeek-V3 + Qwen-Max both working
- Processing time: ~49s for 9 records (~5s per record)
- Token usage: ~10k tokens total (~1.1k per record)
- Conflict detection: 1 clean, 8 conflicts (88.9% conflict rate)
- Excel export: Working with proper encoding

Files Changed:
Backend (~500 lines):
- ExtractionController.ts: Add upload endpoint, improve logging
- DualModelExtractionService.ts: Fix LLM call methods, add detailed logs
- HealthCheckService.ts: Fix Excel range parsing
- routes/index.ts: Add upload route

Frontend (~200 lines):
- toolB.ts: Fix API response parsing, add error handling
- Step1Upload.tsx: Integrate upload and health check APIs
- Step2Schema.tsx: Fix infinite loop, load templates from API
- Step3Processing.tsx: Fix infinite loop, integrate progress polling
- Step4Verify.tsx: Fix infinite loop, transform backend data correctly
- Step5Result.tsx: Integrate export API
- index.tsx: Add file metadata to state

Scripts:
- check-task-progress.mjs: Database inspection utility

Docs (~8 files):
- 00-模块当前状态与开发指南.md: Update to v2.0
- API设计文档.md: Mark all endpoints as tested
- 数据库设计文档.md: Update verification status
- DC模块Tool-B开发计划.md: Add MVP completion notice
- DC模块Tool-B开发任务清单.md: Update progress to 100%
- Tool-B-MVP完成总结.md: New completion summary
- Tool-B技术债务清单.md: New technical debt document
- 00-系统当前状态与开发指南.md: Update DC module status

Status: Tool B MVP complete and production ready
 2025-12-03 15:07:39 +08:00
HaHafeng
5f1e7af92c feat(dc): Complete Tool B frontend development with UI optimization 
- Implement Tool B 5-step workflow (upload, schema, processing, verify, result)
- Add back navigation button to Portal
- Optimize Step 2 field list styling to match prototype
- Fix step 3 label: 'dual-blind' to 'dual-model'
- Create API service layer with 7 endpoints
- Integrate Tool B route into DC module
- Add comprehensive TypeScript types

Components (~1100 lines):
- index.tsx: Main Tool B entry with state management
- Step1Upload.tsx: File upload and health check
- Step2Schema.tsx: Smart template configuration
- Step3Processing.tsx: Dual-model extraction progress
- Step4Verify.tsx: Conflict verification workbench
- Step5Result.tsx: Result display
- StepIndicator.tsx: Step progress component
- api/toolB.ts: API service layer

Status: Frontend complete, ready for API integration
 2025-12-03 09:36:35 +08:00
HaHafeng
33db2687b9 docs(dc): Add 2025-12-02 daily work summary 2025-12-02 21:54:53 +08:00
HaHafeng
d4d33528c7 feat(dc): Complete Phase 1 - Portal workbench page development 
Summary:
- Implement DC module Portal page with 3 tool cards
- Create ToolCard component with decorative background and hover animations
- Implement TaskList component with table layout and progress bars
- Implement AssetLibrary component with tab switching and file cards
- Complete database verification (4 tables confirmed)
- Complete backend API verification (6 endpoints ready)
- Optimize UI to match prototype design (V2.html)

Frontend Components (~715 lines):
- components/ToolCard.tsx - Tool cards with animations
- components/TaskList.tsx - Recent tasks table view
- components/AssetLibrary.tsx - Data asset library with tabs
- hooks/useRecentTasks.ts - Task state management
- hooks/useAssets.ts - Asset state management
- pages/Portal.tsx - Main portal page
- types/portal.ts - TypeScript type definitions

Backend Verification:
- Backend API: 1495 lines code verified
- Database: dc_schema with 4 tables verified
- API endpoints: 6 endpoints tested (templates API works)

Documentation:
- Database verification report
- Backend API test report
- Phase 1 completion summary
- UI optimization report
- Development task checklist
- Development plan for Tool B

Status: Phase 1 completed (100%), ready for browser testing
Next: Phase 2 - Tool B Step 1 and 2 development
 2025-12-02 21:53:24 +08:00
HaHafeng
f240aa9236 docs(asl): Update module and system status documentation 
ASL Module Status Update (v1.2 -> v1.3):
- Update development stage: backend completed (Day 2-5)
- Add fulltext-screening backend structure (controllers, services, routes, tests)
- Add 5 new API endpoints for fulltext screening
- Update milestone: Day 4-5 completed (database + batch service + API)
- Mark Day 6-8 as pending (frontend development)

System Status Update (v2.4.0 -> v2.5.0):
- Update ASL module progress across all sections
- Update database schema: 4 tables -> 6 tables (add fulltext screening tables)
- Update API endpoints: 10 -> 15 (add 5 fulltext screening APIs)
- Update backend structure to include fulltext-screening module
- Reflect 2500+ lines of code added in Day 2-5
 2025-11-23 11:36:30 +08:00
HaHafeng
e28617ab89 docs(asl): Add fulltext screening frontend development plan and technical debt 
- Create comprehensive frontend development plan (05-全文复筛前端开发计划.md)
  - 4 core pages design (Settings, Progress, Workbench, Results)
  - 10 feature components and 3 reused components
  - Detailed UI/UX specifications with wireframes
  - 2.5-day development schedule (Day 6-8)
  - Technical implementation guide (PDF upload, progress polling, PDF preview)
  - Testing plan (functional, performance, compatibility)

- Update technical debt list (v1.1 -> v1.2)
  - Add 10 frontend-related technical debts (debt 11-20)
  - PDF annotation feature (medium priority)
  - Literature note-taking (medium priority)
  - Knowledge base integration (low priority)
  - Auto-fetch PDF by PMID/DOI (low priority)
  - Highlight AI-cited text in PDF (medium priority)
  - WebSocket real-time push (low priority)
  - Virtual scrolling optimization (low priority)
  - Batch operations (low priority)
  - Offline PDF preview (low priority)
  - Mobile responsive design (lowest priority)
 2025-11-23 11:17:33 +08:00
HaHafeng
88cc049fb3 feat(asl): Complete Day 5 - Fulltext Screening Backend API Development 
- Implement 5 core API endpoints (create task, get progress, get results, update decision, export Excel)
- Add FulltextScreeningController with Zod validation (652 lines)
- Implement ExcelExporter service with 4-sheet report generation (352 lines)
- Register routes under /api/v1/asl/fulltext-screening
- Create 31 REST Client test cases
- Add automated integration test script
- Fix PDF extraction fallback mechanism in LLM12FieldsService
- Update API design documentation to v3.0
- Update development plan to v1.2
- Create Day 5 development record
- Clean up temporary test files
 2025-11-23 10:52:07 +08:00
HaHafeng
08aa3f6c28 docs: Enforce English-only commit messages to prevent encoding issues 
Changes:
- Add prominent warning at the beginning of Commit Message section
- Update all commit message examples to English
- Change 'recommended' to 'mandatory' for English usage
- Update best practices section with stronger requirement
- Update all scenario examples (feature/bugfix/architecture)
- Update version history to v1.1

Reason:
- Chinese characters in commit messages cause garbled text in Windows PowerShell
- No encoding configuration can fully resolve this issue
- English commit messages are standard practice in open source projects

Reference: Fixed commit beb7f7f which had garbled Chinese text
 2025-11-22 22:27:27 +08:00
HaHafeng
beb7f7f559 feat(asl): Implement full-text screening core LLM service and validation system (Day 1-3) 
Core Components:
- PDFStorageService with Dify/OSS adapters
- LLM12FieldsService with Nougat-first + dual-model + 3-layer JSON parsing
- PromptBuilder for dynamic prompt assembly
- MedicalLogicValidator with 5 rules + fault tolerance
- EvidenceChainValidator for citation integrity
- ConflictDetectionService for dual-model comparison

Prompt Engineering:
- System Prompt (6601 chars, Section-Aware strategy)
- User Prompt template (PICOS context injection)
- JSON Schema (12 fields constraints)
- Cochrane standards (not loaded in MVP)

Key Innovations:
- 3-layer JSON parsing (JSON.parse + json-repair + code block extraction)
- Promise.allSettled for dual-model fault tolerance
- safeGetFieldValue for robust field extraction
- Mixed CN/EN token calculation

Integration Tests:
- integration-test.ts (full test)
- quick-test.ts (quick test)
- cached-result-test.ts (fault tolerance test)

Documentation Updates:
- Development record (Day 2-3 summary)
- Quality assurance strategy (full-text screening)
- Development plan (progress update)
- Module status (v1.1 update)
- Technical debt (10 new items)

Test Results:
- JSON parsing success rate: 100%
- Medical logic validation: 5/5 passed
- Dual-model parallel processing: OK
- Cost per PDF: CNY 0.10

Files: 238 changed, 14383 insertions(+), 32 deletions(-)
Docs: docs/03-涓氬姟妯″潡/ASL-AI鏅鸿兘鏂囩尞/05-寮€鍙戣褰?2025-11-22_Day2-Day3_LLM鏈嶅姟涓庨獙璇佺郴缁熷紑鍙?md
 2025-11-22 22:21:12 +08:00
HaHafeng
8eef9e0544 feat(asl): Complete Week 4 - Results display and Excel export with hybrid solution 
Features:
- Backend statistics API (cloud-native Prisma aggregation)
- Results page with hybrid solution (AI consensus + human final decision)
- Excel export (frontend generation, zero disk write, cloud-native)
- PRISMA-style exclusion reason analysis with bar chart
- Batch selection and export (3 export methods)
- Fixed logic contradiction (inclusion does not show exclusion reason)
- Optimized table width (870px, no horizontal scroll)

Components:
- Backend: screeningController.ts - add getProjectStatistics API
- Frontend: ScreeningResults.tsx - complete results page (hybrid solution)
- Frontend: excelExport.ts - Excel export utility (40 columns full info)
- Frontend: ScreeningWorkbench.tsx - add navigation button
- Utils: get-test-projects.mjs - quick test tool

Architecture:
- Cloud-native: backend aggregation reduces network transfer
- Cloud-native: frontend Excel generation (zero file persistence)
- Reuse platform: global prisma instance, logger
- Performance: statistics API < 500ms, Excel export < 3s (1000 records)

Documentation:
- Update module status guide (add Week 4 features)
- Update task breakdown (mark Week 4 completed)
- Update API design spec (add statistics API)
- Update database design (add field usage notes)
- Create Week 4 development plan
- Create Week 4 completion report
- Create technical debt list

Test:
- End-to-end flow test passed
- All features verified
- Performance test passed
- Cloud-native compliance verified

Ref: Week 4 Development Plan
Scope: ASL Module MVP - Title Abstract Screening Results
Cloud-Native: Backend aggregation + Frontend Excel generation
 2025-11-21 20:12:38 +08:00
HaHafeng
2e8699c217 feat(asl): Week 2 Day 2 - Excel import with template download and intelligent dedup 
Features:
- feat: Excel template generation and download (with examples)
- feat: Excel file parsing in memory (cloud-native, no disk write)
- feat: Field validation (title + abstract required)
- feat: Smart deduplication (DOI priority + Title fallback)
- feat: Literature preview table with statistics
- feat: Complete submission flow (create project + import literatures)

Components:
- feat: Create excelUtils.ts with full Excel processing toolkit
- feat: Enhance TitleScreeningSettings page with upload/preview/submit
- feat: Update API interface signatures and export unified aslApi object

Dependencies:
- chore: Add xlsx library for Excel file processing

Ref: Week 2 Frontend Development - Day 2
Scope: ASL Module MVP - Title Abstract Screening
Cloud-Native: Memory parsing, no file persistence
 2025-11-19 10:24:47 +08:00
HaHafeng
3634933ece refactor(asl): ASL frontend architecture refactoring with left navigation 
- feat: Create ASLLayout component with 7-module left navigation
- feat: Implement Title Screening Settings page with optimized PICOS layout
- feat: Add placeholder pages for Workbench and Results
- fix: Fix nested routing structure for React Router v6
- fix: Resolve Spin component warning in MainLayout
- fix: Add QueryClientProvider to App.tsx
- style: Optimize PICOS form layout (P+I left, C+O+S right)
- style: Align Inclusion/Exclusion criteria side-by-side
- docs: Add architecture refactoring and routing fix reports

Ref: Week 2 Frontend Development
Scope: ASL module MVP - Title Abstract Screening
 2025-11-18 21:51:51 +08:00
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
HaHafeng
31d555f7bb docs: Update architecture docs with platform infrastructure details 
- Add platform infrastructure chapter to frontend-backend architecture design
- Update system architecture document with 6 new infrastructure modules
- Update AI onboarding guide with infrastructure overview
- Link to backend/src/common/README.md for detailed usage guide

Key Updates:
- Storage service (LocalAdapter + OSSAdapter)
- Logging system (Winston + JSON format)
- Cache service (Memory + Redis)
- Async job queue (Memory + Database)
- Health check endpoints
- Monitoring metrics
- Database connection pool
- Environment config management

All modules support zero-code switching between local and cloud environments.

Related: #Platform-Infrastructure
 2025-11-17 08:36:10 +08:00
HaHafeng
8bba33ac89 feat(platform): Implement platform infrastructure with cloud-native support 
- Add storage service (LocalAdapter + OSSAdapter stub)
- Add database connection pool with graceful shutdown
- Add logging system with winston (JSON format)
- Add environment config management
- Add async job queue (MemoryQueue + DatabaseQueue stub)
- Add cache service (MemoryCache + RedisCache stub)
- Add health check endpoints for SAE
- Add monitoring metrics for DB, memory, API

Key Features:
- Zero-code switching between local and cloud environments
- Adapter pattern for multi-environment support
- Backward compatible with legacy modules
- Ready for Aliyun Serverless deployment

Related: Platform Infrastructure Planning (docs/09-鏋舵瀯瀹炴柦/04-骞冲彴鍩虹璁炬柦瑙勫垝.md)
 2025-11-17 08:31:23 +08:00
HaHafeng
a79abf88db docs(platform): Complete platform infrastructure planning 
- Create platform infrastructure planning core document (766 lines)
- Update architecture design to support cloud-native deployment
- Update development specs and operations documentation
- Simplify ASL module docs by removing duplicate implementations

New Documents:
- Platform Infrastructure Planning (04-骞冲彴鍩虹璁炬柦瑙勫垝.md)
- Cloud-Native Development Standards (08-浜戝師鐢熷紑鍙戣鑼?md)
- Git Commit Standards (06-Git鎻愪氦瑙勮寖.md)
- Cloud-Native Deployment Guide (03-浜戝師鐢熼儴缃叉灦鏋勬寚鍗?md)
- Daily Summary (2025-11-16 work summary)

Updated Documents (11 files):
- System architecture design docs (3 files)
- Implementation and standards docs (4 files)
- Operations documentation (1 file)
- ASL module planning docs (3 files)

Key Achievements:
- Platform-level infrastructure architecture established
- Zero-code switching between local/cloud environments
- 100% support for 4 PRD deployment modes
- Support for modular product combinations
- 99% efficiency improvement for module development
- Net +1426 lines of quality documentation

Implementation: 2.5 days (20 hours) for 8 infrastructure modules
 2025-11-16 21:36:57 +08:00
HaHafeng
e52020409c docs: complete documentation system (250+ files) 
- System architecture and design documentation
- Business module docs (ASL/AIA/PKB/RVW/DC/SSA/ST)
- ASL module complete design (quality assurance, tech selection)
- Platform layer and common capabilities docs
- Development standards and API specifications
- Deployment and operations guides
- Project management and milestone tracking
- Architecture implementation reports
- Documentation templates and guides
 2025-11-16 15:43:55 +08:00