Next.js 16 renamed middleware to proxy. Merged session-based auth and
API key auth into a single proxy.ts. Also fixed: auth route handler
exports, missing card component, Button asChild type errors, signIn
return type, Drizzle eq() type narrowing, and useSearchParams suspense
boundary.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Updated .env to use DATABASE_URL instead of DATABASE_PATH
- Tested all API endpoints: health, charts, candles, span annotations
- Confirmed JSONB fields work correctly (geometry, sub_spans, model_prediction)
- All 2,836 rows accessible via API
- Database connection pooling working correctly
- Implement disagreement visual highlighting with distinct colors
- Yellow highlight for 'missed_by_human' predictions
- Orange for 'label_mismatch' disagreements
- Warning icon on disagreement markers
- Add click-to-convert prediction feedback
- Click disagreement predictions to create span annotations
- Auto-fill with predicted label and times
- Set source as 'model_confirmed' or 'model_corrected'
- Add dismiss action for false positive predictions
- Alt+Click or Ctrl+Click to dismiss predictions
- Saves negative annotation with label 'O'
- Records original prediction in model_prediction field
- Filter predictions when 'Show only disagreements' is enabled
- Update TypeScript types to match flat backend response structure
- Remove nested model_info and metrics objects
- Remove label_config, use labels array and per_class_metrics array
- Update all component references to use new structure
- Generate default colors for prediction labels in CandleChart
- Fix TypeScript type errors for nullable model_version
- Remove accuracy/F1 metrics display (not in new response)
Add complete workflow for using TA-Lib to bootstrap training data:
- generate_talib_annotations.py: Python script to run TA-Lib CDL* functions
and output span annotations in UI-compatible format
- import_talib_annotations.ts: TypeScript script to import generated
annotations into the UI database with auto-label-type creation
- npm script 'import-annotations' for easy execution
- TALIB_WORKFLOW.md: Comprehensive guide covering the full cycle:
* Generate patterns with TA-Lib
* Import into UI
* Review and edit in browser
* Export and train model
* Compare predictions with TA-Lib detections
* Iterate for improvement
This enables the intended workflow: use TA-Lib for initial annotations,
manually refine them, then train a model that learns from corrections.
- Update README.md with Docker quickstart and new features (label management, hacker theme)
- Add detailed Docker deployment section to DEPLOYMENT.md:
- docker-compose usage
- Environment configuration
- Data persistence and backup
- Container health checks
- Troubleshooting steps
- Production deployment guidance
- Create comprehensive CLAUDE_DESCRIPTION.md:
- Project overview and version info
- Recent changes in v2.0.0
- Technical stack details
- Core features and file structure
- State management explanation
- Data flow diagrams
- API endpoints reference
- Development workflow
- Customization points
- Performance and security notes
- Add fixed width to sidebar (w-64) to prevent layout collapse
- Change chart container from flex-1 to w-full h-full for proper sizing
- Chart now properly displays after CSV upload
- Created CandleChart component with lightweight-charts integration
- Implemented SvgOverlay component for line drawing
- Integrated all components in main page
- Fixed TypeScript and Tailwind CSS compatibility issues
- Added comprehensive README.md with project documentation
- Created DEPLOYMENT.md with setup and troubleshooting guide
- Downgraded to stable versions (Tailwind v3, lightweight-charts v4)
- All 59 tasks from OpenSpec completed
