- Fixed field mapping between API and frontend (amount→positionSize, entry→entryPrice, createdAt→timestamp)
- Updated API sync function to properly convert API trade format to frontend format
- Resolved display issues: 'Invalid Date', missing entry price, missing trade size
- Added trade monitoring system and automation improvements
- Enhanced automation with simple-automation.js for reliable 24/7 operation
- Working automation now detecting 85% confidence BUY signals and executing trades
- Added macro sentiment analysis to paper-trading-safe API
- Integrates Fear & Greed Index and M2 Money Supply data
- Confidence adjustments based on macro conditions
- Enhanced UI with macro sentiment panel showing F&G and M2 signals
- Displays original vs adjusted confidence with macro impact
- Shows M2 correlation timeline (3-6 month peak impact)
- Macro adjustments applied: +/-10% for extreme F&G, +/-5% for M2
- Fixed conflicting localStorage keys causing positions to disappear
- Added backward compatibility to load from both old and new key patterns
- Standardized to safePaperTrading_ prefix for consistency
- Updated reset function to clear all key patterns
- Positions should now persist when navigating between pages
Core Features:
- True 24/7 automation runs without browser dependency
- Server-side process in Docker container
- Auto-executes paper trades with ≥60% confidence
- Integrates with existing AI learning system
- Safe paper trading mode only (zero real money risk)
- working-24x7.js: Main automation process (currently running)
- check-automation.js: Status monitoring and health checks
- app/api/safe-paper-trading/create-trade/route.js: Paper trade API
- app/api/automation-24x7/route.js: Automation control API
- Fixed continuous learning state persistence issues
- Added force enable function for debugging: window.forceEnableLearning()
- Enhanced state restoration logic with immediate and delayed checks
- Auto-execute toggle now properly unlocks when continuous learning active
- System running successfully (PID: 3922502)
- Already executed first automated paper trade (80% confidence SELL)
- Scheduled to run every 60 minutes automatically
- Logs all activity for monitoring and debugging
ical Implementation:
- Uses curl for HTTP requests (no fetch dependencies)
- Background process with proper signal handling
- Comprehensive error handling and logging
- Integration with existing analysis pipeline
- Maintains compatibility with browser-based safe paper trading
This completes the 24/7 automation requirement - system now runs continuously
in Docker container without requiring browser tabs to remain open.
- Add comprehensive setup guide (VIRTUAL_TRADING_SETUP_GUIDE.md)
- Improve UI to clearly show required steps for AI learning
- Make auto-execute toggle always visible with clear instructions
- Add blue info panel explaining the learning setup process
- User can now easily enable: Continuous Learning + Auto-Execute
- Virtual trades will execute automatically and AI will learn from outcomes
Resolves issue: AI analyzing without learning due to missing virtual trade execution
- ❌ Removed unused generateMockAnalysis() function from API
- ❌ Eliminated all random/fake data generation in frontend
- ❌ Replaced mock learning status with real AI learning API integration
Real Data Integration:
- 📊 Paper trading now uses ONLY real market analysis via ai-analysis/latest
- 🧠 Learning insights fetch real data from /api/ai-learning-status
- 📈 Analysis panels display actual market data (resistance/support from keyLevels)
- 🎯 Entry/exit points use real analysis data, not hardcoded values
- 📋 Pattern recognition shows real database statistics (100 decisions)
- Market Analysis: Enhanced Screenshot Service + AI Analysis (30-180s response time)
- Learning Status: Real database with 100 total decisions, PATTERN RECOGNITION phase
- Trade Outcomes: Real PnL tracking and winner/loser determination
- Pattern Data: Actual success rates, confidence thresholds, and learning phases
- Paper trading remains completely isolated (no real trading risk)
- Real market data provides authentic learning experience
- All UI text updated to reflect 'Real market analysis for practice'
- API enforces NO FALLBACK TO MOCK DATA policy
Performance Verification:
- Real analysis confirmed taking 30+ seconds (authentic data processing)
- Learning API returns real statistics: 100 decisions, 50% win rate, PATTERN RECOGNITION phase
- Support/resistance levels pulled from actual analysis keyLevels
- Entry reasoning uses real analysis summary and reasoning
This ensures users get authentic market learning experience with zero mock data contamination.
New Features:
- 📊 Detailed Market Analysis Panel (similar to pro trading interface)
* Market sentiment, recommendation, resistance/support levels
* Detailed trading setup with entry/exit points
* Risk management with R:R ratios and confirmation triggers
* Technical indicators (RSI, OBV, VWAP) analysis
- 🧠 AI Learning Insights Panel
* Real-time learning status and success rates
* Winner/Loser trade outcome tracking
* AI reflection messages explaining what was learned
* Current thresholds and pattern recognition data
- 🔮 AI Database Integration
* Shows what AI learned from previous trades
* Current confidence thresholds and risk parameters
* Pattern recognition for symbol/timeframe combinations
* Next trade adjustments based on learning
- 🎓 Intelligent Learning from Outcomes
* Automatic trade outcome analysis (winner/loser)
* AI generates learning insights from each trade result
* Confidence adjustment based on trade performance
* Pattern reinforcement or correction based on results
- Beautiful gradient panels with color-coded sections
- Clear winner/loser indicators with visual feedback
- Expandable detailed analysis view
- Real-time learning progress tracking
- Completely isolated paper trading (no real money risk)
- Real market data integration for authentic learning
- Safe practice environment with professional analysis tools
This provides a complete AI learning trading simulation where users can:
1. Get real market analysis with detailed reasoning
2. Execute safe paper trades with zero risk
3. See immediate feedback on trade outcomes
4. Learn from AI reflections and insights
5. Understand how AI adapts and improves over time
- Replace mock data with real market analysis in paper trading
- Safe paper trading API now uses live TradingView screenshots and OpenAI analysis
- Maintain complete isolation from live trading while using real market conditions
- Fix Docker build error in automation trade route (removed unreachable code)
- Add safety redirects to prevent accidental live trading access
- Real data includes: live charts, technical indicators, current market conditions
- Analysis time: 30-180s for genuine market analysis vs 5s for mock data
- All safety blocks maintained for zero trading risk learning environment
Tested and verified:
Container builds and runs successfully
Real screenshot capture working (TradingView integration)
OpenAI analysis processing real market data
Safety systems prevent any actual trading
Paper trading provides realistic learning experience
