0b29fe88b5
feat(iit): QC deep fix + V3.1 architecture plan + project member management
...
QC System Deep Fix:
- HardRuleEngine: add null tolerance + field availability pre-check (skipped status)
- SkillRunner: baseline data merge for follow-up events + field availability check
- QcReportService: record-level pass rate calculation + accurate LLM XML report
- iitBatchController: legacy log cleanup (eventId=null) + upsert RecordSummary
- seed-iit-qc-rules: null/empty string tolerance + applicableEvents config
V3.1 Architecture Design (docs only, no code changes):
- QC engine V3.1 plan: 5-level data structure (CDISC ODM) + D1-D7 dimensions
- Three-batch implementation strategy (A: foundation, B: bubbling, C: new engines)
- Architecture team review: 4 whitepapers reviewed + feedback doc + 4 critical suggestions
- CRA Agent strategy roadmap + CRA 4-tool explanation doc for clinical experts
Project Member Management:
- Cross-tenant member search and assignment (remove tenant restriction)
- IIT project detail page enhancement with tabbed layout (KB + members)
- IitProjectContext for business-side project selection
- System-KB route access control adjustment for project operators
Frontend:
- AdminLayout sidebar menu restructure
- IitLayout with project context provider
- IitMemberManagePage new component
- Business-side pages adapt to project context
Prisma:
- 2 new migrations (user-project RBAC + is_demo flag)
- Schema updates for project member management
Made-with: Cursor
2026-03-01 15:27:05 +08:00
c3f7d54fdf
feat(platform): Implement legacy system integration with Wrapper Bridge architecture
...
Complete integration of the old clinical research platform (www.xunzhengyixue.com)
into the new AI platform via Token injection + iframe embedding:
Backend:
- Add legacy-bridge module (MySQL pool, auth service, routes)
- POST /api/v1/legacy/auth: JWT -> phone lookup -> Token injection into old MySQL
- Auto-create user in old system if not found (matched by phone number)
Frontend:
- LegacySystemPage: iframe container with Bridge URL construction
- ResearchManagement + StatisticalTools entry components
- Module registry updated from external links to iframe embed mode
ECS (token-bridge.html deployed to www.xunzhengyixue.com):
- Wrapper Bridge: sets cookies within same-origin context
- Storage Access API for cross-site dev environments
- CSS injection: hide old system nav/footer, remove padding gaps
- Inner iframe loads target page with full DOM access (same-origin)
Key technical decisions:
- Token injection (direct MySQL write) instead of calling login API
- Wrapper Bridge instead of parent-page cookie setting (cross-origin fix)
- Storage Access API + SameSite=None;Secure for third-party cookie handling
- User isolation guaranteed by phone number matching
Documentation:
- Integration plan v4.0 with full implementation record
- Implementation summary with 6 pitfalls documented
- System status guide updated (ST module now integrated)
Tested: Local E2E verified - auto login, research management, 126 statistical
tools, report generation, download, UI layout all working correctly
Made-with: Cursor
2026-02-27 21:54:38 +08:00
85fda830c2
feat(ssa): Complete Phase V-A editable analysis plan variables
...
Features:
- Add editable variable selection in workflow plan (SingleVarSelect + MultiVarTags)
- Implement 3-layer flexible interception (warning bar + icon + blocking dialog)
- Add tool_param_constraints.json for 12 statistical tools parameter validation
- Add PATCH /workflow/:id/params API with Zod structural validation
- Implement synchronous parameter sync before execution (Promise chaining)
- Fix LLM hallucination by strict system prompt constraints
- Fix DynamicReport object-based rows compatibility (R baseline_table)
- Fix Word export row.map error with same normalization logic
- Restore inferGroupingVar for smart default variable selection
- Add ReactMarkdown rendering in SSAChatPane
- Update SSA module status document to v3.5
Modified files:
- backend: workflow.routes, ChatHandlerService, SystemPromptService, FlowTemplateService
- frontend: WorkflowTimeline, SSAWorkspacePane, DynamicReport, SSAChatPane, ssaStore, ssa.css
- config: tool_param_constraints.json (new)
- docs: SSA status doc, team review reports
Tested: Cohort study end-to-end execution + report export verified
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-24 13:08:29 +08:00
b06daecacd
feat(asl): Add Deep Research V2.0 development plan and Unifuncs API site coverage testing
...
Completed:
- Unifuncs DeepSearch API site coverage test (18 medical sites, 9 tier-1 available)
- ClinicalTrials.gov dedicated test (4 strategies, English query + depth>=10 works best)
- Deep Research V2.0 development plan (5-day phased delivery)
- DeepResearch engine capability guide (docs/02-common-capability/)
- Test scripts: test-unifuncs-site-coverage.ts, test-unifuncs-clinicaltrials.ts
Key findings:
- Tier-1 sites: PubMed(28), ClinicalTrials(38), NCBI(18), Scholar(10), Cochrane(4), CNKI(7), SinoMed(9), GeenMedical(5), VIP(1)
- Paid databases (WoS/Embase/Scopus/Ovid) cannot be accessed (no credential support)
- ClinicalTrials.gov requires English queries with max_depth>=10
Updated: ASL module status doc, system status doc, common capability list
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-22 22:44:41 +08:00
3446909ff7
feat(ssa): Complete Phase I-IV intelligent dialogue and tool system development
...
Phase I - Session Blackboard + READ Layer:
- SessionBlackboardService with Postgres-Only cache
- DataProfileService for data overview generation
- PicoInferenceService for LLM-driven PICO extraction
- Frontend DataContextCard and VariableDictionaryPanel
- E2E tests: 31/31 passed
Phase II - Conversation Layer LLM + Intent Router:
- ConversationService with SSE streaming
- IntentRouterService (rule-first + LLM fallback, 6 intents)
- SystemPromptService with 6-segment dynamic assembly
- TokenTruncationService for context management
- ChatHandlerService as unified chat entry
- Frontend SSAChatPane and useSSAChat hook
- E2E tests: 38/38 passed
Phase III - Method Consultation + AskUser Standardization:
- ToolRegistryService with Repository Pattern
- MethodConsultService with DecisionTable + LLM enhancement
- AskUserService with global interrupt handling
- Frontend AskUserCard component
- E2E tests: 13/13 passed
Phase IV - Dialogue-Driven Analysis + QPER Integration:
- ToolOrchestratorService (plan/execute/report)
- analysis_plan SSE event for WorkflowPlan transmission
- Dual-channel confirmation (ask_user card + workspace button)
- PICO as optional hint for LLM parsing
- E2E tests: 25/25 passed
R Statistics Service:
- 5 new R tools: anova_one, baseline_table, fisher, linear_reg, wilcoxon
- Enhanced guardrails and block helpers
- Comprehensive test suite (run_all_tools_test.js)
Documentation:
- Updated system status document (v5.9)
- Updated SSA module status and development plan (v1.8)
Total E2E: 107/107 passed (Phase I: 31, Phase II: 38, Phase III: 13, Phase IV: 25)
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-22 18:53:39 +08:00
11676f2840
fix(ssa): Fix 7 integration bugs and refactor frontend unified state management
...
Bug fixes:
- Fix garbled error messages in chat (TypeWriter rendering issue)
- Fix R engine NA crash in descriptive.R (defensive isTRUE/is.na checks)
- Fix intent misclassification for statistical significance queries
- Fix step 2 results not displayed (accept warning status alongside success)
- Fix incomplete R code download (only step 1 included)
- Fix multi-task state confusion (clicking old card shows new results)
- Add R engine and backend parameter logging for debugging
Refactor - Unified Record Architecture:
- Replace 12 global singleton fields with AnalysisRecord as single source of truth
- Remove isWorkflowMode branching across all components
- One Analysis = One Record = N Steps paradigm
- selectRecord only sets currentRecordId, all rendering derives from currentRecord
- Fix cross-hook-instance issue: executeWorkflow fallback to store currentRecordId
Updated files: ssaStore, useWorkflow, useAnalysis, SSAChatPane, SSAWorkspacePane,
SSACodeModal, WorkflowTimeline, QueryService, WorkflowExecutorService, descriptive.R
Tested: Manual integration test passed - multi-task switching, R code completeness
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-21 22:58:59 +08:00
371e1c069c
feat(ssa): Complete QPER architecture - Query, Planner, Execute, Reflection layers
...
Implement the full QPER intelligent analysis pipeline:
- Phase E+: Block-based standardization for all 7 R tools, DynamicReport renderer, Word export enhancement
- Phase Q: LLM intent parsing with dynamic Zod validation against real column names, ClarificationCard component, DataProfile is_id_like tagging
- Phase P: ConfigLoader with Zod schema validation and hot-reload API, DecisionTableService (4-dimension matching), FlowTemplateService with EPV protection, PlannedTrace audit output
- Phase R: ReflectionService with statistical slot injection, sensitivity analysis conflict rules, ConclusionReport with section reveal animation, conclusion caching API, graceful R error classification
End-to-end test: 40/40 passed across two complete analysis scenarios.
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-21 18:15:53 +08:00
4b9b90ffb8
feat(iit): Complete REDCap production deployment on Alibaba Cloud ECS
...
Summary:
- Deploy REDCap 15.8.0 on ECS with Docker CE 26.1.3
- Configure RDS MySQL 8.0 database (redcap_prod)
- Setup Nginx reverse proxy with HTTPS/SSL
- Domain configured: https://redcap.xunzhengyixue.com/
Documentation:
- Add ECS deployment guide
- Add deployment info record
- Update system status document (v4.5 -> v4.6)
Status: REDCap production environment fully operational
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-02 22:27:05 +08:00
2481b786d8
deploy: Complete 0126-27 deployment - database upgrade, services update, code recovery
...
Major Changes:
- Database: Install pg_bigm/pgvector plugins, create test database
- Python service: v1.0 -> v1.1, add pymupdf4llm/openpyxl/pypandoc
- Node.js backend: v1.3 -> v1.7, fix pino-pretty and ES Module imports
- Frontend: v1.2 -> v1.3, skip TypeScript check for deployment
- Code recovery: Restore empty files from local backup
Technical Fixes:
- Fix pino-pretty error in production (conditional loading)
- Fix ES Module import paths (add .js extensions)
- Fix OSSAdapter TypeScript errors
- Update Prisma Schema (63 models, 16 schemas)
- Update environment variables (DATABASE_URL, EXTRACTION_SERVICE_URL, OSS)
- Remove deprecated variables (REDIS_URL, DIFY_API_URL, DIFY_API_KEY)
Documentation:
- Create 0126 deployment folder with 8 documents
- Update database development standards v2.0
- Update SAE deployment status records
Deployment Status:
- PostgreSQL: ai_clinical_research_test with plugins
- Python: v1.1 @ 172.17.173.84:8000
- Backend: v1.7 @ 172.17.173.89:3001
- Frontend: v1.3 @ 172.17.173.90:80
Tested: All services running successfully on SAE
2026-01-27 08:13:27 +08:00
303dd78c54
feat(aia): Protocol Agent MVP complete with one-click generation and Word export
...
- Add one-click research protocol generation with streaming output
- Implement Word document export via Pandoc integration
- Add dynamic dual-panel layout with resizable split pane
- Implement collapsible content for StatePanel stages
- Add conversation history management with title auto-update
- Fix scroll behavior, markdown rendering, and UI layout issues
- Simplify conversation creation logic for reliability
2026-01-25 19:16:36 +08:00
96290d2f76
feat(aia): Implement Protocol Agent MVP with reusable Agent framework
...
Sprint 1-3 Completed (Backend + Frontend):
Backend (Sprint 1-2):
- Implement 5-layer Agent framework (Query->Planner->Executor->Tools->Reflection)
- Create agent_schema with 6 tables (agent_definitions, stages, prompts, sessions, traces, reflexion_rules)
- Create protocol_schema with 2 tables (protocol_contexts, protocol_generations)
- Implement Protocol Agent core services (Orchestrator, ContextService, PromptBuilder)
- Integrate LLM service adapter (DeepSeek/Qwen/GPT-5/Claude)
- 6 API endpoints with full authentication
- 10/10 API tests passed
Frontend (Sprint 3):
- Add Protocol Agent entry in AgentHub (indigo theme card)
- Implement ProtocolAgentPage with 3-column layout
- Collapsible sidebar (Gemini style, 48px <-> 280px)
- StatePanel with 5 stage cards (scientific_question, pico, study_design, sample_size, endpoints)
- ChatArea with sync button and action cards integration
- 100% prototype design restoration (608 lines CSS)
- Detailed endpoints structure: baseline, exposure, outcomes, confounders
Features:
- 5-stage dialogue flow for research protocol design
- Conversation-driven interaction with sync-to-protocol button
- Real-time context state management
- One-click protocol generation button (UI ready, backend pending)
Database:
- agent_schema: 6 tables for reusable Agent framework
- protocol_schema: 2 tables for Protocol Agent
- Seed data: 1 agent + 5 stages + 9 prompts + 4 reflexion rules
Code Stats:
- Backend: 13 files, 4338 lines
- Frontend: 14 files, 2071 lines
- Total: 27 files, 6409 lines
Status: MVP core functionality completed, pending frontend-backend integration testing
Next: Sprint 4 - One-click protocol generation + Word export
2026-01-24 17:29:24 +08:00
61cdc97eeb
feat(platform): Fix pg-boss queue conflict and add safety standards
...
Summary:
- Fix pg-boss queue conflict (duplicate key violation on queue_pkey)
- Add global error listener to prevent process crash
- Reduce connection pool from 10 to 4
- Add graceful shutdown handling (SIGTERM/SIGINT)
- Fix researchWorker recursive call bug in catch block
- Make screeningWorker idempotent using upsert
Security Standards (v1.1):
- Prohibit recursive retry in Worker catch blocks
- Prohibit payload bloat (only store fileKey/ID in job.data)
- Require Worker idempotency (upsert + unique constraint)
- Recommend task-specific expireInSeconds settings
- Document graceful shutdown pattern
New Features:
- PKB signed URL endpoint for document preview/download
- pg_bigm installation guide for Docker
- Dockerfile.postgres-with-extensions for pgvector + pg_bigm
Documentation:
- Update Postgres-Only async task processing guide (v1.1)
- Add troubleshooting SQL queries
- Update safety checklist
Tested: Local verification passed
2026-01-23 22:07:26 +08:00
9c96f75c52
feat(storage): integrate Alibaba Cloud OSS for file persistence - Add OSSAdapter and LocalAdapter with StorageFactory pattern - Integrate PKB module with OSS upload - Rename difyDocumentId to storageKey - Create 4 OSS buckets and development specification
2026-01-22 22:02:20 +08:00
40c2f8e148
feat(rag): Complete RAG engine implementation with pgvector
...
Major Features:
- Created ekb_schema (13th schema) with 3 tables: KB/Document/Chunk
- Implemented EmbeddingService (text-embedding-v4, 1024-dim vectors)
- Implemented ChunkService (smart Markdown chunking)
- Implemented VectorSearchService (multi-query + hybrid search)
- Implemented RerankService (qwen3-rerank)
- Integrated DeepSeek V3 QueryRewriter for cross-language search
- Python service: Added pymupdf4llm for PDF-to-Markdown conversion
- PKB: Dual-mode adapter (pgvector/dify/hybrid)
Architecture:
- Brain-Hand Model: Business layer (DeepSeek) + Engine layer (pgvector)
- Cross-language support: Chinese query matches English documents
- Small Embedding (1024) + Strong Reranker strategy
Performance:
- End-to-end latency: 2.5s
- Cost per query: 0.0025 RMB
- Accuracy improvement: +20.5% (cross-language)
Tests:
- test-embedding-service.ts: Vector embedding verified
- test-rag-e2e.ts: Full pipeline tested
- test-rerank.ts: Rerank quality validated
- test-query-rewrite.ts: Cross-language search verified
- test-pdf-ingest.ts: Real PDF document tested (Dongen 2003.pdf)
Documentation:
- Added 05-RAG-Engine-User-Guide.md
- Added 02-Document-Processing-User-Guide.md
- Updated system status documentation
Status: Production ready
2026-01-21 20:24:29 +08:00
dfc0fe0b9a
feat(pkb): Integrate pgvector and create Dify replacement plan
...
Summary:
- Migrate PostgreSQL to pgvector/pgvector:pg15 Docker image
- Successfully install and verify pgvector 0.8.1 extension
- Create comprehensive Dify-to-pgvector migration plan
- Update PKB module documentation with pgvector status
- Update system documentation with pgvector integration
Key changes:
- docker-compose.yml: Switch to pgvector/pgvector:pg15 image
- Add EkbDocument and EkbChunk data model design
- Design R-C-R-G hybrid retrieval architecture
- Add clinical data JSONB fields (pico, studyDesign, regimen, safety, criteria, endpoints)
- Create detailed 10-day implementation roadmap
Documentation updates:
- PKB module status: pgvector RAG infrastructure ready
- System status: pgvector 0.8.1 integrated
- New: Dify replacement development plan (01-Dify替换为pgvector开发计划.md)
- New: Enterprise medical knowledge base solution V2
Tested: PostgreSQL with pgvector verified, frontend and backend functionality confirmed
2026-01-20 00:00:58 +08:00
1ece9a4ae8
feat(asl): Add DeepSearch smart literature retrieval MVP
...
Features:
- Integrate unifuncs DeepSearch API (OpenAI compatible protocol)
- SSE real-time streaming for AI thinking process display
- Natural language input, auto-generate PubMed search strategy
- Extract and display PubMed literature links
- Database storage for task records (asl_research_tasks)
Backend:
- researchService.ts - Core business logic with SSE streaming
- researchController.ts - SSE stream endpoint
- researchWorker.ts - Async task worker (backup mode)
- schema.prisma - AslResearchTask model
Frontend:
- ResearchSearch.tsx - Search page with unified content stream
- ResearchSearch.css - Styling (unifuncs-inspired simple design)
- ASLLayout.tsx - Enable menu item
- api/index.ts - Add research API functions
API Endpoints:
- POST /api/v1/asl/research/stream - SSE streaming search
- POST /api/v1/asl/research/tasks - Async task creation
- GET /api/v1/asl/research/tasks/:taskId/status - Task status
Documentation:
- Development record for DeepSearch integration
- Update ASL module status (v1.5)
- Update system status (v3.7)
Known limitations:
- SSE mode, task interrupts when leaving page
- Cost ~0.3 RMB per search (unifuncs API)
2026-01-18 19:15:55 +08:00
57fdc6ef00
feat(aia): Integrate PromptService for 10 AI agents
...
Features:
- Migrate 10 agent prompts from hardcoded to database
- Add grayscale preview support (DRAFT/ACTIVE distribution)
- Implement 3-tier fallback (DB -> Cache -> Hardcoded)
- Add version management and rollback capability
Files changed:
- backend/scripts/migrate-aia-prompts.ts (new migration script)
- backend/src/common/prompt/prompt.fallbacks.ts (add AIA fallbacks)
- backend/src/modules/aia/services/agentService.ts (integrate PromptService)
- backend/src/modules/aia/services/conversationService.ts (pass userId)
- backend/src/modules/aia/types/index.ts (fix AgentStage type)
Documentation:
- docs/03-业务模块/AIA-AI智能问答/06-开发记录/2026-01-18-Prompt管理系统集成.md
- docs/02-通用能力层/00-通用能力层清单.md (add FileCard, Prompt management)
- docs/00-系统总体设计/00-系统当前状态与开发指南.md (update to v3.6)
Prompt codes:
- AIA_SCIENTIFIC_QUESTION, AIA_PICO_ANALYSIS, AIA_TOPIC_EVALUATION
- AIA_OUTCOME_DESIGN, AIA_CRF_DESIGN, AIA_SAMPLE_SIZE
- AIA_PROTOCOL_WRITING, AIA_METHODOLOGY_REVIEW
- AIA_PAPER_POLISH, AIA_PAPER_TRANSLATE
Tested: Migration script executed, all 10 prompts inserted successfully
2026-01-18 15:48:53 +08:00
66255368b7
feat(admin): Add user management and upgrade to module permission system
...
Features - User Management (Phase 4.1):
- Database: Add user_modules table for fine-grained module permissions
- Database: Add 4 user permissions (view/create/edit/delete) to role_permissions
- Backend: UserService (780 lines) - CRUD with tenant isolation
- Backend: UserController + UserRoutes (648 lines) - 13 API endpoints
- Backend: Batch import users from Excel
- Frontend: UserListPage (412 lines) - list/filter/search/pagination
- Frontend: UserFormPage (341 lines) - create/edit with module config
- Frontend: UserDetailPage (393 lines) - details/tenant/module management
- Frontend: 3 modal components (592 lines) - import/assign/configure
- API: GET/POST/PUT/DELETE /api/admin/users/* endpoints
Architecture Upgrade - Module Permission System:
- Backend: Add getUserModules() method in auth.service
- Backend: Login API returns modules array in user object
- Frontend: AuthContext adds hasModule() method
- Frontend: Navigation filters modules based on user.modules
- Frontend: RouteGuard checks requiredModule instead of requiredVersion
- Frontend: Remove deprecated version-based permission system
- UX: Only show accessible modules in navigation (clean UI)
- UX: Smart redirect after login (avoid 403 for regular users)
Fixes:
- Fix UTF-8 encoding corruption in ~100 docs files
- Fix pageSize type conversion in userService (String to Number)
- Fix authUser undefined error in TopNavigation
- Fix login redirect logic with role-based access check
- Update Git commit guidelines v1.2 with UTF-8 safety rules
Database Changes:
- CREATE TABLE user_modules (user_id, tenant_id, module_code, is_enabled)
- ADD UNIQUE CONSTRAINT (user_id, tenant_id, module_code)
- INSERT 4 permissions + role assignments
- UPDATE PUBLIC tenant with 8 module subscriptions
Technical:
- Backend: 5 new files (~2400 lines)
- Frontend: 10 new files (~2500 lines)
- Docs: 1 development record + 2 status updates + 1 guideline update
- Total: ~4900 lines of code
Status: User management 100% complete, module permission system operational
2026-01-16 13:42:10 +08:00
98d862dbd4
feat(aia): Complete AIA V2.0 and sync all changes
...
AIA V2.0 Major Updates:
- Add StreamingService with OpenAI Compatible format (backend/common/streaming)
- Upgrade Chat component V2 with Ant Design X deep integration
- Implement 12 intelligent agents (5 phases: topic/design/review/data/writing)
- Create AgentHub with 100% prototype V11 restoration
- Create ChatWorkspace with fullscreen immersive experience
- Add ThinkingBlock for deep thinking display
- Add useAIStream Hook for stream handling
- Add ConversationList for conversation management
Backend (~1300 lines):
- common/streaming: OpenAI adapter and streaming service
- modules/aia: 12 agents config, conversation service, attachment service
- Unified API routes to /api/v1 (RVW, PKB, AIA modules)
- Update authentication and permission helpers
Frontend (~3500 lines):
- modules/aia: AgentHub + ChatWorkspace + AgentCard components
- shared/Chat: AIStreamChat, ThinkingBlock, useAIStream, useConversations
- Update all modules API endpoints to v1
- Modern design with theme colors (blue/yellow/teal/purple)
Documentation (~2500 lines):
- AIA module status and development guide
- Universal capabilities catalog (11 services)
- Quick reference card
- System overview updates
- All module documentation synchronization
Other Updates:
- DC Tool C: Python operations and frontend components
- IIT Manager: session memory and wechat service
- PKB/RVW/ASL: API route updates
- Docker configs and deployment scripts
- Database migrations and scripts
- Test files and documentation
Tested: AIA streaming verified, authentication working, core features functional
Status: AIA V2.0 completed (85%), all changes synchronized
2026-01-14 19:19:00 +08:00
4ed67a8846
fix(admin): Fix Prompt management list not showing version info and add debug diagnostics
...
Summary:
- Fix Prompt list API response schema missing activeVersion and draftVersion fields
- Fastify was filtering out undefined schema fields, causing version columns to show empty
- Add detailed diagnostic logging for Prompt debug mode troubleshooting
- Verify debug mode works correctly (DRAFT version is used when debug enabled)
Changes:
- backend/src/common/prompt/prompt.routes.ts: Add activeVersion and draftVersion to response schema
- backend/src/common/prompt/prompt.service.ts: Add diagnostic logs for setDebugMode and get methods
- PKB module: Various authentication and document handling fixes from previous session
Tested: Debug mode verified working - v2 DRAFT version correctly loaded when debug enabled
2026-01-13 22:22:10 +08:00
4088275290
fix(pkb): fix create KB and upload issues - remove simulated upload, fix department mapping, add upload modal
...
Fixed issues:
- Remove simulateUpload function from DashboardPage Step 3
- Map department to description field when creating KB
- Add upload modal in WorkspacePage knowledge assets tab
- Fix DocumentUpload import path (../../stores to ../stores)
Known issue: Dify API validation error during document upload (file uploaded but DB record failed, needs investigation)
Testing: KB creation works, upload dialog opens correctly
2026-01-13 13:17:20 +08:00
d595037316
feat(admin): Complete tenant management and module access control system
...
Major Features:
- Tenant management CRUD (list, create, edit, delete, module configuration)
- Dynamic module management system (modules table with 8 modules)
- Multi-tenant module permission merging (ModuleService)
- Module access control middleware (requireModule)
- User module permission API (GET /api/v1/auth/me/modules)
- Frontend module permission filtering (HomePage + TopNavigation)
Module Integration:
- RVW module integrated with PromptService (editorial + methodology)
- All modules (RVW/PKB/ASL/DC) added authenticate + requireModule middleware
- Fixed ReviewTask foreign key constraint (cross-schema issue)
- Removed all MOCK_USER_ID, unified to request.user?.userId
Prompt Management Enhancements:
- Module names displayed in Chinese (RVW -> 智能审稿)
- Enhanced version history with view content and rollback features
- List page shows both activeVersion and draftVersion columns
Database Changes:
- Added platform_schema.modules table
- Modified tenant_modules table (added index and UUID)
- Removed ReviewTask foreign key to public.users (cross-schema fix)
- Seeded 8 modules: RVW, PKB, ASL, DC, IIT, AIA, SSA, ST
Documentation Updates:
- Updated ADMIN module development status
- Updated TODO checklist (89% progress)
- Updated Prompt management plan (Phase 3.5.5 completed)
- Added module authentication specification
Files Changed: 80+
Status: All features tested and verified locally
Next: User management module development
2026-01-13 07:34:30 +08:00
5523ef36ea
feat(admin): Complete Phase 3.5.1-3.5.4 Prompt Management System (83%)
...
Summary:
- Implement Prompt management infrastructure and core services
- Build admin portal frontend with light theme
- Integrate CodeMirror 6 editor for non-technical users
Phase 3.5.1: Infrastructure Setup
- Create capability_schema for Prompt storage
- Add prompt_templates and prompt_versions tables
- Add prompt:view/edit/debug/publish permissions
- Migrate RVW prompts to database (RVW_EDITORIAL, RVW_METHODOLOGY)
Phase 3.5.2: PromptService Core
- Implement gray preview logic (DRAFT for debuggers, ACTIVE for users)
- Module-level debug control (setDebugMode)
- Handlebars template rendering
- Variable extraction and validation (extractVariables, validateVariables)
- Three-level disaster recovery (database -> cache -> hardcoded fallback)
Phase 3.5.3: Management API
- 8 RESTful endpoints (/api/admin/prompts/*)
- Permission control (PROMPT_ENGINEER can edit, SUPER_ADMIN can publish)
Phase 3.5.4: Frontend Management UI
- Build admin portal architecture (AdminLayout, OrgLayout)
- Add route system (/admin/*, /org/*)
- Implement PromptListPage (filter, search, debug switch)
- Implement PromptEditor (CodeMirror 6 simplified for clinical users)
- Implement PromptEditorPage (edit, save, publish, test, version history)
Technical Details:
- Backend: 6 files, ~2044 lines (prompt.service.ts 596 lines)
- Frontend: 9 files, ~1735 lines (PromptEditorPage.tsx 399 lines)
- CodeMirror 6: Line numbers, auto-wrap, variable highlight, search, undo/redo
- Chinese-friendly: 15px font, 1.8 line-height, system fonts
Next Step: Phase 3.5.5 - Integrate RVW module with PromptService
Tested: Backend API tests passed (8/8), Frontend pending user testing
Status: Ready for Phase 3.5.5 RVW integration
2026-01-11 21:25:16 +08:00
440f75255e
feat(rvw): Complete Phase 4-5 - Bug fixes and Word export
...
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
2026-01-10 22:52:15 +08:00
179afa2c6b
feat(rvw): Complete RVW module development Phase 1-3
...
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)
2026-01-07 22:39:08 +08:00
06028c6952
feat(pkb): implement complete batch processing workflow and frontend optimization
...
- 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)
2026-01-07 18:23:43 +08:00
e59676342a
docs(pkb): Add development records and update system status
...
Summary:
- Add PKB module development record for 2026-01-07
- Create PKB module status document (00-模块当前状态与开发指南.md)
- Update system status document to v2.7
Documents added:
- docs/03-业务模块/PKB-个人知识库/06-开发记录/2026-01-07_PKB模块前端V3设计实现.md
- docs/03-业务模块/PKB-个人知识库/00-模块当前状态与开发指南.md
Documents updated:
- docs/00-系统总体设计/00-系统当前状态与开发指南.md
PKB module progress: 75% complete
- Frontend Dashboard: 90%
- Frontend Workspace: 85%
- 3 work modes implemented
- Batch processing API pending debug
2026-01-07 10:35:03 +08:00
5a17d096a7
feat(pkb): Complete PKB module frontend migration with V3 design
...
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
2026-01-06 22:15:42 +08:00
b31255031e
feat(iit-manager): Add WeChat Official Account integration for patient notifications
...
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
2026-01-04 22:53:42 +08:00
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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