71d32d11ee
feat(iit): V3.2 data consistency + project isolation + admin config redesign + Chinese labels
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Summary:
- Refactor timeline API to read from qc_field_status (SSOT) instead of qc_logs
- Add field-issues paginated API with severity/dimension/recordId filters
- Add LEFT JOIN field_metadata + qc_event_status for Chinese display names
- Implement per-project ChatOrchestrator cache and SessionMemory isolation
- Redesign admin IIT config tabs (REDCap -> Fields -> KB -> Rules -> Members)
- Add AI-powered QC rule generation (D3 programmatic + D1/D5/D6 LLM-based)
- Add clickable warning/critical detail Modal in ReportsPage
- Auto-dispatch eQuery after batch QC via DailyQcOrchestrator
- Update module status documentation to v3.2
Backend changes:
- iitQcCockpitController: rewrite getTimeline from qc_field_status, add getFieldIssues
- iitQcCockpitRoutes: add field-issues route
- ChatOrchestrator: per-projectId cached instances
- SessionMemory: keyed by userId::projectId
- WechatCallbackController: resolve projectId from iitUserMapping
- iitRuleSuggestionService: dimension-based suggest + generateD3Rules
- iitBatchController: call DailyQcOrchestrator after batch QC
Frontend changes:
- AiStreamPage: adapt to new timeline structure with dimension tags
- ReportsPage: clickable stats cards with issue detail Modal
- IitProjectDetailPage: reorder tabs, add AI rule generation UI
- iitProjectApi: add TimelineIssue, FieldIssueItem types and APIs
Status: TypeScript compilation verified, no new lint errors
Made-with: Cursor
2026-03-02 14:29:59 +08:00
2030ebe28f
feat(iit): Complete V3.1 QC engine + GCP business reports + AI timeline + bug fixes
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V3.1 QC Engine:
- QcExecutor unified entry + D1-D7 dimension engines + three-level aggregation
- HealthScoreEngine + CompletenessEngine + ProtocolDeviationEngine + QcAggregator
- B4 flexible cron scheduling (project-level cronExpression + pg-boss dispatcher)
- Prisma migrations for qc_field_status, event_status, project_stats
GCP Business Reports (Phase A - 4 reports):
- D1 Eligibility: record_summary full list + qc_field_status D1 overlay
- D2 Completeness: data entry rate and missing rate aggregation
- D3/D4 Query Tracking: severity distribution from qc_field_status
- D6 Protocol Deviation: D6 dimension filtering
- 4 frontend table components + ReportsPage 5-tab restructure
AI Timeline Enhancement:
- SkillRunner outputs totalRules (33 actual rules vs 1 skill)
- iitQcCockpitController severity mapping fix (critical->red, warning->yellow)
- AiStreamPage expandable issue detail table with Chinese labels
- Event label localization (eventLabel from backend)
Business-side One-click Batch QC:
- DashboardPage batch QC button with SyncOutlined icon
- Auto-refresh QcReport cache after batch execution
Bug Fixes:
- dimension_code -> rule_category in 4 SQL queries
- D1 eligibility data source: record_summary full + qc_field_status overlay
- Timezone UTC -> Asia/Shanghai (QcReportService toBeijingTime helper)
- Pass rate calculation: passed/totalEvents instead of passed/totalRecords
Docs:
- Update IIT module status with GCP reports and bug fix milestones
- Update system status doc v6.6 with IIT progress
Tested: Backend compiles, frontend linter clean, batch QC verified
Made-with: Cursor
2026-03-01 22:49:49 +08:00
0b29fe88b5
feat(iit): QC deep fix + V3.1 architecture plan + project member management
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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
9b8490b4d0
docs(iit): Update module status with frontend architecture changes
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Changes:
- Add frontend architecture adjustment milestone (admin/business side split)
- Document product positioning: ops team configures, end users use QC platform
- Add new completed feature section for routing/navigation changes
- Update current status to reflect Web AI Chat and admin IIT project management
Made-with: Cursor
2026-02-26 22:12:49 +08:00
7c3cc12b2e
feat(iit): Complete CRA Agent V3.0 P1 - ChatOrchestrator with LLM Function Calling
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P1 Architecture: Lightweight ReAct (Function Calling loop, max 3 rounds)
Core changes:
- Add ToolDefinition/ToolCall types to LLM adapters (DeepSeek + CloseAI + Claude)
- Replace 6 old tools with 4 semantic tools: read_report, look_up_data, check_quality, search_knowledge
- Create ChatOrchestrator (~160 lines) replacing ChatService (1,442 lines)
- Wire WechatCallbackController to ChatOrchestrator, deprecate ChatService
- Fix nullable content (string | null) across 12+ LLM consumer files
E2E test results: 8/8 scenarios passed (100%)
- QC report query, critical issues, patient data, trend, on-demand QC
- Knowledge base search, project overview, data modification refusal
Net code reduction: ~1,100 lines
Tested: E2E P1 chat test 8/8 passed with DeepSeek API
Made-with: Cursor
2026-02-26 14:27:09 +08:00
31b0433195
docs(iit): Add CRA Agent V3.0 development plan and update module status guide
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V3.0 Plan:
- Finalize CRA Agent V3.0 development plan (replace CRA positioning)
- Add unified CRA QC platform PRD
- Add HTML UI prototype (dashboard, AI stream, eQuery, reports)
- Architecture: report-driven + LLM Tool Use + 4 semantic tools
Module Status Update:
- Update architecture from dual-brain V2.9.1 to V3.0 Tool Use
- Update DB schema inventory (5 tables -> 18 tables)
- Update code stats (577 lines -> 15,000+ lines / 61 files)
- Update next steps to V3.0 P0 roadmap
- Archive old phase plans (ReAct engine, IntentService)
- Add V3.0 document references (plan, PRD, prototype)
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-25 22:04:00 +08:00
7a299e8562
feat(iit): Implement event-level QC architecture V3.1 with dynamic rule filtering, report deduplication and AI intent enhancement
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Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-08 21:22:11 +08:00
45c7b32dbb
docs(iit): Add QC system UI and LLM format optimization plan
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- Add development plan: 07-QC system UI and LLM format optimization
- Phase 1: PromptBuilder + XML clinical slice format (~5.5h)
- Phase 2: QC cockpit + stat cards + risk heatmap (~9.5h)
- Phase 3: Variable tagging system (~5h)
- Add CRA Agent design document and prototype
- Update module status: design 100%, code 45%
- Update system status: real-time QC complete + plan ready
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-08 09:59:44 +08:00
5db4a7064c
feat(iit): Implement real-time quality control system
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Summary:
- Add 4 new database tables: iit_field_metadata, iit_qc_logs, iit_record_summary, iit_qc_project_stats
- Implement pg-boss debounce mechanism in WebhookController
- Refactor QC Worker for dual output: QC logs + record summary
- Enhance HardRuleEngine to support form-based rule filtering
- Create QcService for QC data queries
- Optimize ChatService with new intents: query_enrollment, query_qc_status
- Add admin batch operations: one-click full QC + one-click full summary
- Create IIT Admin management module: project config, QC rules, user mapping
Status: Code complete, pending end-to-end testing
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-07 21:56:11 +08:00
0c590854b5
docs(iit): Add IIT Manager Agent V2.9 development plan with multi-agent architecture
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Features:
- Add V2.9 enhancements: Cron Skill, User Profiling, Feedback Loop, Multi-Intent Handling
- Create modular development plan documents (database, engines, services, memory, tasks)
- Add V2.5/V2.6/V2.8/V2.9 design documents for architecture evolution
- Add system design white papers and implementation guides
Architecture:
- Dual-Brain Architecture (SOP + ReAct engines)
- Three-layer memory system (Flow Log, Hot Memory, History Book)
- ProfilerService for personalized responses
- SchedulerService with Cron Skill support
Also includes:
- Frontend nginx config updates
- Backend test scripts for WeChat signature
- Database backup files
Co-authored-by: Cursor <cursoragent@cursor.com >
2026-02-05 22:33:26 +08:00
2481b786d8
deploy: Complete 0126-27 deployment - database upgrade, services update, code recovery
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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
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- 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
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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
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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
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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
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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
57fdc6ef00
feat(aia): Integrate PromptService for 10 AI agents
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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
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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
1b53ab9d52
feat(aia): Complete AIA V2.0 with universal streaming capabilities
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Major Changes:
- Add StreamingService with OpenAI Compatible format
- Upgrade Chat component V2 with Ant Design X integration
- Implement AIA module with 12 intelligent agents
- Update API routes to unified /api/v1 prefix
- Update system documentation
Backend (~1300 lines):
- common/streaming: OpenAI Compatible adapter
- modules/aia: 12 agents, conversation service, streaming integration
- Update route versions (RVW, PKB to v1)
Frontend (~3500 lines):
- modules/aia: AgentHub + ChatWorkspace (100% prototype restoration)
- shared/Chat: AIStreamChat, ThinkingBlock, useAIStream Hook
- Update API endpoints to v1
Documentation:
- AIA module status guide
- Universal capabilities catalog
- System overview updates
- All module documentation sync
Tested: Stream response verified, authentication working
Status: AIA V2.0 core completed (85%)
2026-01-14 19:15:01 +08:00
4ed67a8846
fix(admin): Fix Prompt management list not showing version info and add debug diagnostics
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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
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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
5523ef36ea
feat(admin): Complete Phase 3.5.1-3.5.4 Prompt Management System (83%)
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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
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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
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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
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- 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
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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
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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
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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
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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
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- 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
4794640f5d
feat(iit): Phase 1.5 AI对话能力集成 - 复用通用能力层LLMFactory
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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
6a567f028f
feat(iit-manager): 完成MVP闭环 - 企业微信集成与端到端测试
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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
5f089516cb
feat(iit-manager): Day 3 企业微信集成开发完成
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- 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
36ce1bbcb2
feat(iit): Complete Day 3 - WeChat Work integration and URL verification
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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
2eef7522a1
feat(iit): Complete Day 2 - REDCap real-time integration
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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
bdfca32305
docs(iit): REDCap对接技术方案完成与模块状态更新
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- 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
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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
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- 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
