Summary:
- Fix methodology score display issue in task list (show score instead of 'warn')
- Add methodology_score field to database schema
- Fix report display when only methodology agent is selected
- Implement Word document export using docx library
- Update documentation to v3.0/v3.1
Backend changes:
- Add methodologyScore to Prisma schema and TaskSummary type
- Update reviewWorker to save methodologyScore
- Update getTaskList to return methodologyScore
Frontend changes:
- Install docx and file-saver libraries
- Implement handleExportReport with Word generation
- Fix activeTab auto-selection based on available data
- Add proper imports for docx components
Documentation:
- Update RVW module status to 90% (Phase 1-5 complete)
- Update system status document to v3.0
Tested: All review workflows verified, Word export functional
Summary:
- Migrate backend to modules/rvw with v2 API routes (/api/v2/rvw)
- Add new database fields: selectedAgents, editorialScore, methodologyStatus, picoExtract, isArchived
- Create frontend module in frontend-v2/src/modules/rvw
- Implement Dashboard with task list, filtering, batch operations
- Implement ReportDetail with dual tabs (editorial/methodology)
- Implement AgentModal for intelligent agent selection
- Register RVW module in moduleRegistry.ts
- Add navigation entry in TopNavigation
- Update documentation for RVW module status (v3.0)
- Update system status document (v2.9)
Features:
- User can select agents: editorial, methodology, or both
- Support batch task execution
- Task status filtering
- Replace console.log with logger service
- Maintain v1 API backward compatibility
Tested: Frontend and backend verified locally
Status: 85% complete (Phase 1-3 done)
- Frontend V3 architecture migration to modules/pkb
- Implement three work modes: full-text reading, deep reading, batch processing
- Complete batch processing: template selection, progress display, result export (CSV)
- Integrate Ant Design X Chat component with streaming support
- Add document upload modal with drag-and-drop support
- Optimize UI: multi-line table display, citation formatting, auto-scroll
- Fix 10+ technical issues: API mapping, state sync, form clearing
- Update documentation: development records and module status
Performance: 3 docs batch processing ~17-28s
Status: PKB module now production-ready (90% complete)
Summary:
- Implement PKB Dashboard and Workspace pages based on V3 prototype
- Add single-layer header with integrated Tab navigation
- Implement 3 work modes: Full Text, Deep Read, Batch Processing
- Integrate Ant Design X Chat component for AI conversations
- Create BatchModeComplete with template selection and document processing
- Add compact work mode selector with dropdown design
Backend:
- Migrate PKB controllers and services to /modules/pkb structure
- Register v2 API routes at /api/v2/pkb/knowledge
- Maintain dual API routes for backward compatibility
Technical details:
- Use Zustand for state management
- Handle SSE streaming responses for AI chat
- Support document selection for Deep Read mode
- Implement batch processing with progress tracking
Known issues:
- Batch processing API integration pending
- Knowledge assets page navigation needs optimization
Status: Frontend functional, pending refinement
Features:
- PatientWechatCallbackController for URL verification and message handling
- PatientWechatService for template and customer messages
- Support for secure mode (message encryption/decryption)
- Simplified route /wechat/patient/callback for WeChat config
- Event handlers for subscribe/unsubscribe/text messages
- Template message for visit reminders
Technical details:
- Reuse @wecom/crypto for encryption (compatible with Official Account)
- Relaxed Fastify schema validation to prevent early request blocking
- Access token caching (7000s with 5min pre-refresh)
- Comprehensive logging for debugging
Testing: Local URL verification passed, ready for SAE deployment
Status: Code complete, waiting for WeChat platform configuration
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
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
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
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
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
- 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
