ROOT CAUSE IDENTIFIED:
- Database schema error: Prisma ai_learning_data missing 'id' field
- Missing function: generateLearningReport() not in SimplifiedStopLossLearner
- Memory leaks: Unhandled errors causing EventEmitter overflow
- Next.js config: Deprecated serverComponentsExternalPackages warning
FIXES APPLIED:
- Added unique ID generation for Prisma ai_learning_data records
- Commented out problematic generateLearningReport calls in risk manager
- Updated next.config.ts to use serverExternalPackages (new format)
- Prevented cascading unhandled errors that led to MaxListeners warnings
- Container now starts without crashes
- No more unhandled error floods
- Orphaned order cleanup integration preserved and working
- Superior parallel screenshot system still operational
This fixes the instability issues that were causing trader_dev to crash and restart.
- Fixed ai-analytics API: Created missing endpoint and corrected model names
- Fixed ai-learning-status.ts: Updated to use ai_learning_data and trades models
- Fixed batch-analysis route: Corrected ai_learning_data model references
- Fixed analysis-details route: Updated automation_sessions and trades models
- Fixed test scripts: Updated model names in check-learning-data.js and others
- Disabled conflicting route files to prevent Next.js confusion
All APIs now use correct snake_case model names matching Prisma schema:
- ai_learning_data (not aILearningData)
- automation_sessions (not automationSession)
- trades (not trade)
This resolves 'Unable to load REAL AI analytics' frontend errors.
LEARNING INTEGRATION:
- Enhanced AI analysis service feeds historical data into OpenAI prompts
- Symbol/timeframe specific learning optimization
- Pattern recognition from past trade outcomes
- Confidence adjustment based on success rates
HTTP COMPATIBILITY SYSTEM:
- HttpUtil with automatic curl/no-curl detection
- Node.js fallback for Docker environments without curl
- Updated all automation systems to use HttpUtil
- Production-ready error handling
AUTONOMOUS RISK MANAGEMENT:
- Enhanced risk manager with learning integration
- Simplified learners using existing AILearningData schema
- Real-time position monitoring every 30 seconds
- Smart stop-loss decisions with AI learning
INFRASTRUCTURE:
- Database utility for shared Prisma connections
- Beach mode status display system
- Complete error handling and recovery
- Docker container compatibility tested
Historical performance flows into OpenAI prompts before every trade.
- Fixed network connectivity and live trading mode
- Updated Drift SDK integration with proper API methods
- Fixed BN type conversions and minimum order size
- Fixed stop loss & take profit conditional orders
- Complete risk management system now functional
Fixed automation v2 start button (relative API URLs)
Fixed batch analysis API endpoint in simple-automation
Fixed AI learning storage with correct userId
Implemented comprehensive learning data storage
Fixed parallel analysis system working correctly
- Changed frontend API calls from localhost:9001 to relative URLs
- Updated simple-automation to use localhost:3000 for batch analysis
- Fixed learning integration with 'default-user' instead of 'system'
- AI learning now stores analysis results with confidence/recommendations
- Batch analysis working: 35s completion, 85% confidence, learning stored
- True parallel screenshot system operational (6 screenshots when multi-timeframe)
- Automation start/stop functionality fully working
- Replace time-based cleanup with on-demand cleanup in development mode
- Cleanup is triggered immediately after AI analysis completes
- Added runPostAnalysisCleanup() method to aggressive-cleanup service
- Cleanup triggers added to both single and batch analysis endpoints
- More efficient: cleanup happens only when needed, not on timer
- Prevents zombie processes without interfering with active analysis
- Production mode still uses periodic cleanup as backup (10 min intervals)
- Gentle cleanup in development: SIGTERM first, then SIGKILL if needed
- Create /api/batch-analysis endpoint that collects ALL screenshots first
- Then sends all screenshots to AI for comprehensive analysis
- Fixes issue where individual timeframes were analyzed immediately
- Multi-timeframe analysis now provides cross-timeframe consensus
- Update AIAnalysisPanel to use batch analysis for multiple timeframes
- Maintains backward compatibility with single timeframe analysis
