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fa72beea6cf5194940db4a317c6b1dc784f484a6
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8 Commits

Author SHA1 Message Date
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
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
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
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
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