- Modified _ensure_initialized() to run in background thread (non-blocking)
- Added _ensure_initialized_async() for truly async initialization
- Updated index_content() to return immediately without waiting for initialization
- Weights now load in background thread instead of blocking event loop
- Added initialization tracking to prevent duplicate initialization
- Modified today_workflow API to handle non-blocking indexing gracefully
- This prevents dashboard refresh from blocking other services
When a user accesses the dashboard, the indexing now happens in background
instead of blocking the HTTP response, allowing other services to function
normally while weights are being loaded.
- Added generation_mode column (VARCHAR, default: 'llm_generation')
- Added committee_agent_count column (INTEGER, default: 0)
- Added fallback_used column (BOOLEAN, default: 0)
Also fixed:
- Imported daily_workflow_models in services/database.py to ensure models are registered
- Added _create_daily_workflow_tables() to database setup
- Created migration script to add columns to 35 existing databases
- Fixed WorkflowError type in frontend to use constructor for proper 'name' property
This resolves the 'no such column' sqlite3 errors when accessing the today-workflow API.
get_all_user_ids now checks if DB file exists before calling get_session_for_user. This prevents get_engine_for_user from triggering init_user_database and creating tables for stale workspace folders. Without this fix, a read-only ID scan creates/initializes SQLite databases and default tables as a side effect, which can silently create fresh DBs for stale workspace folders and hide missing/corrupt-database states that discovery previously surfaced.
Avoid filtering loader queries by canonical user_id. Calling loaders with user_id=user_id introduces an exact-ID filter path that can drop valid legacy tasks: several loaders (e.g., load_due_market_trends_tasks) apply ...where task.user_id == user_id, but this commit also shifts discovery toward canonical IDs, so tasks persisted earlier with workspace-safe/sanitized IDs in the same per-user DB will no longer be returned and therefore never execute. Before this change, loaders were invoked as task_loader(db) and did not regress on mixed ID formats.
- Use canonical Clerk user id (clerk_user_id) across all onboarding entrypoints to ensure consistent OnboardingSession.user_id lookup
- Fix API key persistence in api_key_manager.py to use correct APIKey model columns (session_id, provider, key)
- Increase Node heap for frontend build to 8GB and add build:nomap script to disable sourcemaps and reduce memory usage
- Update onboarding endpoints (endpoints_core.py, onboarding_control_service.py, step_management_service.py) to prefer clerk_user_id over id
- Fix frontend workflowStore.ts TypeScript error by returning WorkflowError instance
- Add website_automation_service.py for onboarding automation
- Fix missing user_id parameter in analyze_content_style() call
- Fix missing user_id parameter in analyze_style_patterns() call
- Fix missing user_id parameter in generate_style_guidelines() call
- user_id is required for subscription checking in llm_text_gen()
- Resolves errors: 'user_id is required for subscription checking'
- All style detection functions now properly pass user_id from executor context
- Replace provenance-based quality with contextuality validation framework
- Add evidence link tracking system (onboarding:key and alert:id formats)
- Implement plan contextuality validation function with configurable thresholds
- Calculate task-level context scores based on evidence link density
- Define contextual workflows (>65% threshold) vs low-context workflows (<65%)
- Add validation in plan persistence layer before database commit
- Integrate contextuality metrics into release readiness checks
- Add recovery strategies for low-context workflows (regeneration with guidance)
- Track evidence link validity against grounding context (onboarding data, alerts)
- Provide detailed contextuality reports in quality assessments
- Maintain backward compatibility while enabling contextual workflow detection
- Add POST /api/today-workflow/regenerate endpoint for on-demand plan regeneration
- Implement rate limiting (3 requests per 60 seconds) to prevent abuse
- Add regeneration quality score tracking and onboarding completion status
- Compute task hashes for deduplication and change detection
- Extract plan metadata from plan_json for cleaner API responses
- Integrate onboarding progress service to track completion status
- Return quality_score and generated_with_agents metadata in responses
- Enable manual workflow refresh in degraded mode scenarios
- Maintain backward compatibility with simplified schema
- Simplify workflow generation by removing complex dependency coercion and metadata normalization functions
- Add committee health precheck to detect insufficient active agents before proposal gathering
- Add orchestrator initialization state metadata tracking for observability
- Downgrade fastapi to 0.104.0 for stability
- Simplify database schema (remove generation_mode, committee_agent_count, fallback_used columns from DailyWorkflowPlan)
- Remove 'skipped' from suppressed task statuses in memory service (keep only dismissed, rejected)
- Update task status normalization logic for clarity
- Return simplified metadata structure with generation_path and degradation tracking
- Resolve merge conflicts in backend/services/today_workflow_service.py and frontend/src/stores/workflowStore.ts
- Backend: Keep robust handling for both dict and object types in TaskProposal conversion
- Backend: Combine dependencies coercion with task metadata normalization
- Frontend: Implement graceful fallback pattern (try server first, then local generation on unavailability)
- Add provenanceSummary integration from server responses
- Ensure degraded mode handling with appropriate messaging
