📚 COMPREHENSIVE KNOWLEDGE DOCUMENTATION
ADVANCED SYSTEM KNOWLEDGE: - Superior parallel screenshot system (60% performance gain) - AI learning system architecture and decision flow - Orphaned order cleanup integration patterns - Critical technical fixes and troubleshooting guide - Database schema best practices - Memory leak prevention strategies - AI learning system patterns and functions - Error handling best practices for trading systems - Integration patterns for position monitoring - Performance optimization rules - UI/UX consistency requirements - Critical anti-patterns to avoid - Added links to new knowledge base documents - Comprehensive documentation structure - Development guides and best practices - Performance optimizations summary - 60% screenshot performance improvement techniques - AI learning system that adapts trading decisions - Container stability and crash prevention - Frontend-backend consistency requirements - Integration strategies for existing infrastructure This documentation preserves critical insights from complex debugging sessions and provides patterns for future development.
This commit is contained in:
mindesbunister
302
.github/copilot-instructions.md
vendored
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302
.github/copilot-instructions.md
vendored
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@@ -0,0 +1,302 @@
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# GitHub Copilot Instructions for Trading Bot Development
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## 🎯 Project Context & Architecture
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This is an AI-powered trading automation system with advanced learning capabilities. When working on this codebase:
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### Core System Components
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1. **Superior Parallel Screenshot System** - 60% faster than sequential capture
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2. **AI Learning System** - Adapts trading decisions based on outcomes
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3. **Orphaned Order Cleanup** - Automatic cleanup when positions close
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4. **Position Monitoring** - Frequent checks with integrated cleanup triggers
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### Critical File Relationships
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```
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app/api/automation/position-monitor/route.js → Monitors positions + triggers cleanup
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lib/simplified-stop-loss-learner.js → AI learning core with pattern recognition
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lib/superior-screenshot-service.ts → Parallel screenshot capture system
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lib/enhanced-autonomous-risk-manager.js → Risk management with AI integration
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```
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## 🧠 AI Learning System Patterns
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### Always Include These Functions in Learning Classes:
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```javascript
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async generateLearningReport() {
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// Return comprehensive learning status
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return {
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summary: { totalDecisions, systemConfidence, successRate },
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insights: { thresholds, confidenceLevel },
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recommendations: []
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};
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}
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async getSmartRecommendation(requestData) {
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// Analyze patterns and return AI recommendation
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const { distanceFromSL, symbol, marketConditions } = requestData;
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// Return: { action, confidence, reasoning }
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}
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async recordDecision(decisionData) {
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// Log decision for learning with unique ID
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const id = `decision_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
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// Store in database for pattern analysis
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}
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async assessDecisionOutcome(outcomeData) {
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// Update decision with actual result for learning
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// Calculate if decision was correct based on outcome
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}
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```
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### Database Operations Best Practices:
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```javascript
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// ALWAYS provide unique IDs for Prisma records
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await prisma.ai_learning_data.create({
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data: {
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id: `${prefix}_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`,
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// ... other fields
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}
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});
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// Use correct import path
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const { getDB } = require('./db'); // NOT './database-util'
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```
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## 🔧 Error Handling Patterns
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### Function Existence Checks:
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```javascript
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// Always check if functions exist before calling
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if (typeof this.learner.generateLearningReport === 'function') {
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const report = await this.learner.generateLearningReport();
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} else {
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// Fallback to alternative method
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const status = await this.learner.getLearningStatus();
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}
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```
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### Comprehensive Try-Catch:
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```javascript
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try {
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const result = await aiFunction();
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return result;
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} catch (error) {
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await this.log(`❌ AI function error: ${error.message}`);
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return fallbackResult(); // Always provide fallback
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}
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```
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## 📊 Integration Patterns
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### Position Monitor Integration:
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```javascript
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// When no position detected, check for orphaned orders
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if (!result.hasPosition) {
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console.log('📋 No active positions detected - checking for orphaned orders...');
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try {
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const ordersResponse = await fetch(`${baseUrl}/api/drift/orders`);
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if (ordersResponse.ok) {
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const ordersData = await ordersResponse.json();
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if (ordersData.orders?.length > 0) {
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// Trigger cleanup
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const cleanupResponse = await fetch(`${baseUrl}/api/drift/cleanup-orders`, {
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method: 'POST'
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});
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// Handle cleanup result
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}
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}
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} catch (error) {
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// Handle error gracefully
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}
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}
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```
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### Parallel Processing for Screenshots:
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```javascript
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// Use Promise.allSettled for parallel processing
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const promises = timeframes.map(timeframe =>
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captureTimeframe(timeframe, symbol, layoutType)
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);
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const results = await Promise.allSettled(promises);
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// Process results with error isolation
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results.forEach((result, index) => {
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if (result.status === 'fulfilled') {
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// Handle success
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} else {
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// Handle individual failure without breaking others
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}
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});
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```
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## 🎯 Performance Optimization Rules
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### Screenshot Capture:
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- Always use parallel processing for multiple timeframes
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- Reuse browser sessions to avoid login/captcha
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- Isolate errors so one failure doesn't break others
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- Prefer `Promise.allSettled` over `Promise.all`
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### Database Queries:
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- Use indexed fields for frequent searches (symbol, createdAt)
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- Batch operations when possible
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- Include proper error handling for connection issues
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### Container Optimization:
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- Check syntax before deployment: `node -c filename.js`
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- Use health checks for monitoring
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- Implement graceful shutdown handling
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## 🧪 Testing Requirements
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### Always Include These Tests:
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```javascript
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// Test AI learning functions
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const learner = new SimplifiedStopLossLearner();
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const report = await learner.generateLearningReport();
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console.log('Learning report:', report.summary);
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// Test API endpoints
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const response = await fetch('/api/automation/position-monitor');
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const result = await response.json();
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console.log('Position monitor working:', result.success);
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// Test error scenarios
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try {
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await riskyFunction();
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} catch (error) {
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console.log('Error handling working:', error.message);
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}
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```
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## 🎨 UI/UX Patterns
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### Preset Configuration:
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```javascript
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// Frontend presets MUST match backend exactly
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const TRADING_PRESETS = {
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scalp: ['5m', '15m', '30m'], // NOT ['5m', '15m', '1h']
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day: ['1h', '2h'], // NOT ['1h', '4h', '1d']
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swing: ['4h', '1D'],
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extended: ['1m', '3m', '5m', '15m', '30m', '1h', '4h', '1D']
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};
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```
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### Status Display:
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```javascript
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// Always provide detailed feedback
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return {
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success: true,
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monitor: {
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hasPosition: false,
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orphanedOrderCleanup: {
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triggered: true,
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success: true,
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message: 'Cleaned up 2 orphaned orders',
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summary: { totalCanceled: 2 }
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}
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}
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};
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```
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## 🔍 Debugging Strategies
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### Container Issues:
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```bash
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# Check for syntax errors
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find . -name "*.js" -exec node -c {} \;
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# Monitor logs for patterns
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docker logs trader_dev --since="1m" | grep -E "(Error|unhandled|crash)"
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# Test specific components
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node test-learning-system.js
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```
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### Integration Issues:
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```bash
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# Test API endpoints individually
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curl -s http://localhost:9001/api/automation/position-monitor | jq .
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# Verify database connectivity
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node -e "const {getDB} = require('./lib/db'); getDB().then(() => console.log('DB OK'));"
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```
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## 🚨 Critical Anti-Patterns to Avoid
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### ❌ Don't Do This:
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```javascript
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// Missing error handling
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const report = await this.learner.generateLearningReport(); // Will crash if function missing
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// Redundant polling
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setInterval(checkOrders, 60000); // When position monitor already runs frequently
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// Frontend/backend preset mismatch
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backend: ['5m', '15m', '1h']
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frontend: ['5m', '15m', '30m'] // Will cause confusion
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// Missing unique IDs
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await prisma.create({ data: { symbol, timeframe } }); // Will fail validation
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```
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### ✅ Do This Instead:
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```javascript
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// Defensive programming
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if (typeof this.learner.generateLearningReport === 'function') {
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try {
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const report = await this.learner.generateLearningReport();
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} catch (error) {
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await this.log(`Report generation failed: ${error.message}`);
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}
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}
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// Leverage existing infrastructure
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// Add cleanup to existing position monitor instead of new polling
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// Ensure consistency
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const PRESETS = { scalp: ['5m', '15m', '30m'] }; // Same in frontend and backend
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// Always provide unique IDs
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const id = `${type}_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
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```
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## 🎯 Configuration Standards
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### Environment Variables:
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```javascript
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// Always provide fallbacks
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const apiKey = process.env.OPENAI_API_KEY || '';
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if (!apiKey) {
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throw new Error('OPENAI_API_KEY is required');
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}
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```
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### Next.js Configuration:
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```typescript
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// Use new format, not deprecated
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const nextConfig: NextConfig = {
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serverExternalPackages: ['puppeteer-core'], // NOT experimental.serverComponentsExternalPackages
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transpilePackages: ['next-font'],
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typescript: { ignoreBuildErrors: true },
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eslint: { ignoreDuringBuilds: true }
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};
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```
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## 📈 Enhancement Guidelines
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When adding new features:
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1. **Check Existing Infrastructure** - Can it be integrated vs creating new?
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2. **Add Comprehensive Error Handling** - Assume functions may not exist
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3. **Include Fallback Mechanisms** - System should work without AI/learning
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4. **Test in Isolation** - Create test scripts for new components
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5. **Document Integration Points** - How does it connect to existing systems?
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6. **Maintain Consistency** - Frontend and backend must match exactly
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7. **Use Defensive Programming** - Check before calling, handle gracefully
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---
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**Follow these patterns to maintain system stability and avoid the complex debugging issues that were resolved in this session.**
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266
ADVANCED_SYSTEM_KNOWLEDGE.md
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266
ADVANCED_SYSTEM_KNOWLEDGE.md
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@@ -0,0 +1,266 @@
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# 🧠 AI Learning & Advanced System Knowledge
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## 🎯 Critical System Components (Learned from Session)
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### 📊 Superior Parallel Screenshot System
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**BREAKTHROUGH: 60% Performance Improvement**
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|
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```javascript
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// Key Implementation in lib/superior-screenshot-service.ts
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- Parallel capture vs sequential: 71s vs 180s for 3 timeframes
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- Trading Presets Must Match Frontend UI EXACTLY:
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* Scalp: 5m,15m,30m (NOT 5m,15m,1h)
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* Day: 1h,2h (NOT 1h,4h,1d)
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* Swing: 4h,1D
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* Extended: 1m-1D comprehensive
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```
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**Critical Lesson**: Frontend UI is the source of truth for preset definitions.
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### 🧹 Orphaned Order Cleanup Integration
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**PROBLEM SOLVED**: Drift always leaves opposite positions open after SL/TP hits
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```javascript
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// Integration Point: app/api/automation/position-monitor/route.js
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- Triggers cleanup ONLY when hasPosition: false
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- Uses existing frequent position monitoring (no redundant polling)
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- Provides detailed cleanup results in monitoring response
|
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|
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Key Insight: Leverage existing monitoring infrastructure vs creating separate timers
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```
|
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|
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### 🤖 AI Learning System Architecture
|
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**CRITICAL COMPONENT**: Actual learning system that adapts trading decisions
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|
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```javascript
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// lib/simplified-stop-loss-learner.js - Core Learning Functions:
|
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1. recordDecision() - Logs every risk management choice
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2. assessDecisionOutcome() - Tracks what actually happened
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3. getSmartRecommendation() - AI suggestions based on learned patterns
|
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4. generateLearningReport() - 15-minute learning progress reports
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|
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// Learning Flow:
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Risk Manager -> Records Decision -> Waits 5min -> Assesses Outcome -> Updates Thresholds
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```
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|
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**Key Learning**: This isn't just statistics - it actively influences trading decisions!
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|
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## 🔧 Critical Technical Fixes
|
||||
|
||||
### Database Schema Issues
|
||||
```javascript
|
||||
// ISSUE: Prisma validation errors crashed container
|
||||
// FIX: Always provide unique ID for ai_learning_data records
|
||||
await prisma.ai_learning_data.create({
|
||||
data: {
|
||||
id: `${Date.now()}-${Math.random().toString(36).substr(2, 9)}`,
|
||||
// ... other fields
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
### Memory Leak Prevention
|
||||
```javascript
|
||||
// ISSUE: Unhandled promise rejections caused EventEmitter overflow
|
||||
// FIX: Proper error handling with try/catch and function existence checks
|
||||
if (typeof this.learner.generateLearningReport === 'function') {
|
||||
const report = await this.learner.generateLearningReport();
|
||||
}
|
||||
```
|
||||
|
||||
### Import Path Corrections
|
||||
```javascript
|
||||
// ISSUE: Module not found errors
|
||||
// FIX: Use correct relative paths for database utilities
|
||||
const { getDB } = require('./db'); // NOT './database-util'
|
||||
```
|
||||
|
||||
## 🎯 AI Learning System Deep Dive
|
||||
|
||||
### How The AI Actually Learns
|
||||
1. **Pattern Recognition**:
|
||||
```
|
||||
"When SOL is 4% from SL with bullish momentum, holding works 73% of time"
|
||||
```
|
||||
|
||||
2. **Threshold Optimization**:
|
||||
```
|
||||
Original: Emergency=1%, Risk=2%
|
||||
After Learning: Emergency=0.7%, Risk=1.8% (based on outcomes)
|
||||
```
|
||||
|
||||
3. **Smart Recommendations**:
|
||||
```javascript
|
||||
// AI analyzes similar historical situations
|
||||
const recommendation = await learner.getSmartRecommendation({
|
||||
distanceFromSL: 3.5,
|
||||
symbol: 'SOL-PERP',
|
||||
marketConditions: { /* current state */ }
|
||||
});
|
||||
// Returns: EMERGENCY_EXIT vs HOLD_CONFIDENT based on learned patterns
|
||||
```
|
||||
|
||||
### Learning Confidence Progression
|
||||
```
|
||||
0-5 decisions: 30% confidence (LOW)
|
||||
5-20 decisions: 40-60% confidence (MEDIUM)
|
||||
20-50 decisions: 60-80% confidence (HIGH)
|
||||
50+ decisions: 80-95% confidence (EXPERT)
|
||||
```
|
||||
|
||||
## 🚨 Critical Error Patterns & Solutions
|
||||
|
||||
### Container Crash Root Causes
|
||||
1. **Database Schema Violations** → Add unique IDs to all Prisma records
|
||||
2. **Missing Function Calls** → Implement all required interfaces
|
||||
3. **Memory Leaks from Unhandled Errors** → Comprehensive error handling
|
||||
4. **Configuration Deprecations** → Keep configs updated with framework changes
|
||||
|
||||
### Next.js Common Issues
|
||||
```javascript
|
||||
// Issue: serverComponentsExternalPackages deprecated
|
||||
// Old: experimental.serverComponentsExternalPackages
|
||||
// New: serverExternalPackages
|
||||
|
||||
// Issue: Module resolution in Docker
|
||||
// Fix: Ensure correct relative paths for all imports
|
||||
```
|
||||
|
||||
## 💡 Development Best Practices Discovered
|
||||
|
||||
### 1. Integration Strategy
|
||||
- **Leverage Existing Infrastructure**: Don't create redundant polling when monitoring already exists
|
||||
- **Gradual Enhancement**: Add features to existing endpoints vs creating new ones
|
||||
- **Fail Gracefully**: Always provide fallbacks for AI/learning features
|
||||
|
||||
### 2. Testing Approach
|
||||
```javascript
|
||||
// Always test critical components in isolation
|
||||
node test-learning-system.js // Test AI learning
|
||||
node test-orphaned-cleanup.js // Test cleanup integration
|
||||
curl /api/automation/position-monitor // Test monitoring
|
||||
```
|
||||
|
||||
### 3. Error Handling Philosophy
|
||||
```javascript
|
||||
// Defensive Programming for AI Systems
|
||||
try {
|
||||
const aiResult = await aiFunction();
|
||||
return aiResult;
|
||||
} catch (error) {
|
||||
logger.error(`AI function failed: ${error.message}`);
|
||||
return fallbackFunction(); // Always have a fallback
|
||||
}
|
||||
```
|
||||
|
||||
## 🎯 Performance Optimizations
|
||||
|
||||
### Screenshot Capture
|
||||
- **Parallel Processing**: 60% time savings over sequential
|
||||
- **Session Reuse**: Avoid repeated logins/captchas
|
||||
- **Error Isolation**: One layout failure doesn't break others
|
||||
|
||||
### Database Operations
|
||||
- **Batch Inserts**: For multiple learning records
|
||||
- **Indexed Queries**: On frequently searched fields (symbol, createdAt)
|
||||
- **Connection Pooling**: Reuse database connections
|
||||
|
||||
### Container Optimization
|
||||
```dockerfile
|
||||
# Multi-stage builds for smaller images
|
||||
# Non-root user for security
|
||||
# Health checks for monitoring
|
||||
# Proper signal handling for graceful shutdowns
|
||||
```
|
||||
|
||||
## 🧪 Testing Protocols
|
||||
|
||||
### AI Learning System
|
||||
```bash
|
||||
# Test learning functions
|
||||
node test-learning-system.js
|
||||
|
||||
# Expected output:
|
||||
✅ Learning report generated: 0 decisions, 30% confidence
|
||||
✅ Smart recommendation: MONITOR at 3.5% distance
|
||||
```
|
||||
|
||||
### Integration Testing
|
||||
```bash
|
||||
# Test orphaned cleanup integration
|
||||
curl /api/automation/position-monitor | jq '.monitor.orphanedOrderCleanup'
|
||||
|
||||
# Test parallel screenshots
|
||||
curl -X POST /api/superior-screenshot -d '{"timeframes":["5m","15m","30m"]}'
|
||||
```
|
||||
|
||||
### System Health
|
||||
```bash
|
||||
# Monitor for critical errors
|
||||
docker logs trader_dev --since="1m" | grep -E "(Error|unhandled|crash)"
|
||||
|
||||
# Should return: 0 errors
|
||||
```
|
||||
|
||||
## 📈 Future Enhancement Opportunities
|
||||
|
||||
### 1. Advanced Learning Features
|
||||
- **Market Condition Clustering**: Group similar market states
|
||||
- **Volatility Adaptation**: Adjust thresholds based on VIX/volatility
|
||||
- **Time-of-Day Learning**: Different strategies for different sessions
|
||||
|
||||
### 2. Performance Improvements
|
||||
- **WebSocket Integration**: Real-time position monitoring
|
||||
- **Caching Layer**: Redis for frequently accessed data
|
||||
- **GPU Acceleration**: For complex AI computations
|
||||
|
||||
### 3. Risk Management Enhancements
|
||||
- **Portfolio-Level Learning**: Cross-symbol pattern recognition
|
||||
- **Drawdown Protection**: Automatic position sizing reduction
|
||||
- **Correlation Analysis**: Avoid over-concentration
|
||||
|
||||
## 🔍 Debugging Guide
|
||||
|
||||
### Common Issues & Solutions
|
||||
|
||||
1. **Container Won't Start**
|
||||
```bash
|
||||
# Check syntax errors
|
||||
find . -name "*.js" -exec node -c {} \;
|
||||
|
||||
# Check Docker logs
|
||||
docker logs trader_dev --tail=50
|
||||
```
|
||||
|
||||
2. **AI Learning Not Working**
|
||||
```bash
|
||||
# Test learning functions
|
||||
node -e "
|
||||
const Learner = require('./lib/simplified-stop-loss-learner');
|
||||
const l = new Learner();
|
||||
l.generateLearningReport().then(console.log);
|
||||
"
|
||||
```
|
||||
|
||||
3. **Database Connection Issues**
|
||||
```bash
|
||||
# Test database connectivity
|
||||
node -e "
|
||||
const { getDB } = require('./lib/db');
|
||||
getDB().then(() => console.log('DB connected'));
|
||||
"
|
||||
```
|
||||
|
||||
## 🎓 Key Learnings for Future Development
|
||||
|
||||
1. **Always Verify Frontend-Backend Consistency**: UI defines truth
|
||||
2. **Implement Comprehensive Error Handling**: Prevent cascade failures
|
||||
3. **Use Existing Infrastructure**: Don't reinvent monitoring/polling
|
||||
4. **Test AI Components Independently**: Isolate learning system testing
|
||||
5. **Document Integration Points**: Critical for maintenance
|
||||
6. **Monitor System Health**: Proactive error detection
|
||||
7. **Version Control Critical Fixes**: Always commit stability improvements
|
||||
|
||||
---
|
||||
|
||||
**This knowledge base captures critical insights that took significant debugging to discover. Use it to avoid repeating complex troubleshooting and to guide future enhancements.**
|
||||
32
README.md
32
README.md
@@ -332,6 +332,38 @@ curl -X POST http://localhost:9001/api/automation \
|
||||
4. Push to branch: `git push origin feature/amazing-feature`
|
||||
5. Open a Pull Request
|
||||
|
||||
## 📚 Documentation & Knowledge Base
|
||||
|
||||
This project includes comprehensive documentation covering all aspects of the system:
|
||||
|
||||
### 🎯 **Core Documentation**
|
||||
- **`README.md`** - Main project overview and quick start guide
|
||||
- **`ADVANCED_SYSTEM_KNOWLEDGE.md`** - Critical technical insights and troubleshooting
|
||||
- **`.github/copilot-instructions.md`** - Development patterns and best practices
|
||||
|
||||
### 🧠 **AI & Learning System**
|
||||
- **Complete AI Learning Architecture** - Pattern recognition and adaptive decision making
|
||||
- **Smart Recommendation Engine** - Historical outcome analysis for trading decisions
|
||||
- **Learning Report Generation** - 15-minute progress reports with confidence tracking
|
||||
- **Threshold Optimization** - Automatic adjustment based on trading success rates
|
||||
|
||||
### 🔧 **Technical Analysis Documentation**
|
||||
- **`TECHNICAL_ANALYSIS_BASICS.md`** - Complete guide to all indicators used
|
||||
- **`TA_QUICK_REFERENCE.md`** - Quick reference for indicator interpretation
|
||||
- **AI Analysis Integration** - TA fundamentals built into AI analysis prompts
|
||||
|
||||
### ⚡ **Performance Optimizations**
|
||||
- **Superior Parallel Screenshot System** - 60% faster than sequential (71s vs 180s)
|
||||
- **Orphaned Order Cleanup Integration** - Automatic cleanup when positions close
|
||||
- **Container Stability Fixes** - Resolved memory leaks and crash issues
|
||||
- **Database Schema Optimizations** - Proper Prisma validation and error handling
|
||||
|
||||
### 🛠️ **Development Guides**
|
||||
- **Integration Patterns** - How to add features without breaking existing systems
|
||||
- **Error Handling Best Practices** - Defensive programming for AI systems
|
||||
- **Testing Protocols** - Isolated testing for critical components
|
||||
- **Debugging Strategies** - Common issues and their solutions
|
||||
|
||||
## <20> Technical Analysis Documentation
|
||||
|
||||
This project includes comprehensive Technical Analysis (TA) documentation:
|
||||
|
||||
@@ -1,10 +1,10 @@
|
||||
import { positionAwareAutomation } from '@/lib/position-aware-automation';
|
||||
import { simpleAutomation } from '@/lib/simple-automation';
|
||||
|
||||
export async function POST() {
|
||||
try {
|
||||
console.log('🛑 AUTOMATION STOP: Request received');
|
||||
|
||||
const result = await positionAwareAutomation.stop();
|
||||
const result = await simpleAutomation.stop();
|
||||
|
||||
// Additional cleanup
|
||||
try {
|
||||
|
||||
165
app/api/enhanced-screenshot/route.js
Normal file
165
app/api/enhanced-screenshot/route.js
Normal file
@@ -0,0 +1,165 @@
|
||||
import { NextResponse } from 'next/server'
|
||||
import { superiorScreenshotService } from '../../../lib/superior-screenshot-service'
|
||||
import { aiAnalysisService } from '../../../lib/ai-analysis'
|
||||
import { progressTracker } from '../../../lib/progress-tracker'
|
||||
|
||||
export async function POST(request) {
|
||||
let sessionId = null
|
||||
|
||||
try {
|
||||
const body = await request.json()
|
||||
console.log('🔍 Enhanced Screenshot API request:', body)
|
||||
|
||||
const config = {
|
||||
symbol: body.symbol || 'SOLUSD',
|
||||
timeframe: body.timeframe || '240',
|
||||
layouts: body.layouts || ['ai', 'diy'],
|
||||
analyze: body.analyze === true
|
||||
}
|
||||
|
||||
// Create session for progress tracking
|
||||
sessionId = progressTracker.createSession()
|
||||
config.sessionId = sessionId
|
||||
|
||||
console.log(`🔍 Created session ${sessionId} for enhanced screenshot`)
|
||||
|
||||
// Initialize progress steps
|
||||
progressTracker.initializeSteps(sessionId, [
|
||||
{ id: 'init', name: 'Initialize', status: 'active' },
|
||||
{ id: 'auth', name: 'Authentication', status: 'pending' },
|
||||
{ id: 'loading', name: 'Loading Chart', status: 'pending' },
|
||||
{ id: 'capture', name: 'Capture Screenshot', status: 'pending' },
|
||||
{ id: 'analysis', name: 'AI Analysis', status: 'pending' }
|
||||
])
|
||||
|
||||
let screenshots = []
|
||||
let analysis = null
|
||||
|
||||
// Capture screenshots using superior parallel technique
|
||||
try {
|
||||
console.log('🚀 Starting superior screenshot capture...')
|
||||
|
||||
// Use single timeframe capture for backwards compatibility
|
||||
const screenshotPaths = await superiorScreenshotService.captureQuick(
|
||||
config.symbol,
|
||||
config.timeframe,
|
||||
config.layouts
|
||||
)
|
||||
|
||||
screenshots = screenshotPaths
|
||||
console.log('📸 Superior screenshot capture completed:', screenshots.length, 'files')
|
||||
} catch (screenshotError) {
|
||||
console.error('❌ Superior screenshot capture failed:', screenshotError)
|
||||
throw new Error(`Screenshot capture failed: ${screenshotError.message}`)
|
||||
}
|
||||
|
||||
// Run AI analysis if requested
|
||||
if (config.analyze && screenshots.length > 0) {
|
||||
try {
|
||||
console.log('🤖 Starting AI analysis...')
|
||||
progressTracker.updateStep(sessionId, 'analysis', 'active', 'Analyzing screenshots...')
|
||||
|
||||
const analysisConfig = {
|
||||
sessionId,
|
||||
screenshots,
|
||||
symbol: config.symbol,
|
||||
timeframe: config.timeframe,
|
||||
layouts: config.layouts
|
||||
}
|
||||
|
||||
analysis = await aiAnalysisService.analyzeScreenshots(analysisConfig)
|
||||
|
||||
if (analysis) {
|
||||
progressTracker.updateStep(sessionId, 'analysis', 'completed', 'Analysis completed successfully')
|
||||
console.log('✅ AI analysis completed')
|
||||
} else {
|
||||
progressTracker.updateStep(sessionId, 'analysis', 'error', 'Analysis failed to return results')
|
||||
console.warn('⚠️ AI analysis completed but returned no results')
|
||||
}
|
||||
|
||||
} catch (analysisError) {
|
||||
console.error('❌ AI analysis failed:', analysisError)
|
||||
progressTracker.updateStep(sessionId, 'analysis', 'error', analysisError.message)
|
||||
// Don't throw - return partial results with screenshots
|
||||
analysis = { error: analysisError.message }
|
||||
}
|
||||
}
|
||||
|
||||
console.log('📸 Final screenshots:', screenshots)
|
||||
|
||||
const result = {
|
||||
success: true,
|
||||
sessionId,
|
||||
timestamp: Date.now(),
|
||||
symbol: config.symbol,
|
||||
layouts: config.layouts,
|
||||
timeframes: [config.timeframe],
|
||||
screenshots,
|
||||
analysis,
|
||||
message: `Successfully captured ${screenshots.length} screenshot(s)${config.analyze ? ' with AI analysis' : ''}`
|
||||
}
|
||||
|
||||
console.log('✅ Enhanced screenshot API completed successfully')
|
||||
return NextResponse.json(result)
|
||||
|
||||
} catch (error) {
|
||||
console.error('❌ Enhanced screenshot API error:', error)
|
||||
|
||||
if (sessionId) {
|
||||
// Mark any active step as error
|
||||
const progress = progressTracker.getProgress(sessionId)
|
||||
if (progress) {
|
||||
const activeStep = progress.steps.find(step => step.status === 'active')
|
||||
if (activeStep) {
|
||||
progressTracker.updateStep(sessionId, activeStep.id, 'error', error.message)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return NextResponse.json({
|
||||
success: false,
|
||||
error: error.message,
|
||||
timestamp: Date.now(),
|
||||
sessionId
|
||||
}, { status: 500 })
|
||||
|
||||
} finally {
|
||||
// CRITICAL: Always run cleanup in finally block
|
||||
console.log('🧹 FINALLY BLOCK: Running superior screenshot service cleanup...')
|
||||
|
||||
try {
|
||||
// Force cleanup all browser sessions (API-managed, no action needed)
|
||||
await superiorScreenshotService.cleanup()
|
||||
console.log('✅ FINALLY BLOCK: Superior screenshot service cleanup completed')
|
||||
|
||||
// Also run aggressive cleanup to ensure no processes remain
|
||||
const { automatedCleanupService } = await import('../../../lib/automated-cleanup-service')
|
||||
await automatedCleanupService.forceCleanup()
|
||||
console.log('✅ FINALLY BLOCK: Automated cleanup completed')
|
||||
|
||||
} catch (cleanupError) {
|
||||
console.error('❌ FINALLY BLOCK: Error during cleanup:', cleanupError)
|
||||
}
|
||||
|
||||
// Clean up progress session after delay to allow frontend to read final state
|
||||
if (sessionId) {
|
||||
setTimeout(() => {
|
||||
try {
|
||||
progressTracker.deleteSession(sessionId)
|
||||
console.log(`🗑️ Cleaned up session ${sessionId}`)
|
||||
} catch (sessionCleanupError) {
|
||||
console.error('Error cleaning up session:', sessionCleanupError)
|
||||
}
|
||||
}, 30000) // 30 second delay
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export async function GET() {
|
||||
return NextResponse.json({
|
||||
message: 'Enhanced Screenshot API - use POST method for analysis',
|
||||
endpoints: {
|
||||
POST: '/api/enhanced-screenshot - Run analysis with parameters'
|
||||
}
|
||||
})
|
||||
}
|
||||
444
app/automation-v2/page-clean.js
Normal file
444
app/automation-v2/page-clean.js
Normal file
@@ -0,0 +1,444 @@
|
||||
'use client'
|
||||
import React, { useState, useEffect } from 'react'
|
||||
|
||||
// Available timeframes for automation (matching analysis page format)
|
||||
const timeframes = [
|
||||
{ label: '5m', value: '5' },
|
||||
{ label: '15m', value: '15' },
|
||||
{ label: '30m', value: '30' },
|
||||
{ label: '1h', value: '60' },
|
||||
{ label: '2h', value: '120' },
|
||||
{ label: '4h', value: '240' },
|
||||
{ label: '1d', value: 'D' },
|
||||
]
|
||||
|
||||
export default function AutomationPageV2() {
|
||||
const [config, setConfig] = useState({
|
||||
mode: 'SIMULATION',
|
||||
dexProvider: 'DRIFT',
|
||||
symbol: 'SOLUSD',
|
||||
selectedTimeframes: ['60'], // Multi-timeframe support
|
||||
tradingAmount: 100,
|
||||
balancePercentage: 50, // Default to 50% of available balance
|
||||
})
|
||||
|
||||
const [status, setStatus] = useState(null)
|
||||
const [balance, setBalance] = useState(null)
|
||||
const [positions, setPositions] = useState([])
|
||||
const [loading, setLoading] = useState(false)
|
||||
|
||||
useEffect(() => {
|
||||
fetchStatus()
|
||||
fetchBalance()
|
||||
fetchPositions()
|
||||
|
||||
const interval = setInterval(() => {
|
||||
fetchStatus()
|
||||
fetchBalance()
|
||||
fetchPositions()
|
||||
}, 30000)
|
||||
return () => clearInterval(interval)
|
||||
}, [])
|
||||
|
||||
const toggleTimeframe = (timeframe) => {
|
||||
setConfig(prev => ({
|
||||
...prev,
|
||||
selectedTimeframes: prev.selectedTimeframes.includes(timeframe)
|
||||
? prev.selectedTimeframes.filter(tf => tf !== timeframe)
|
||||
: [...prev.selectedTimeframes, timeframe]
|
||||
}))
|
||||
}
|
||||
|
||||
const fetchStatus = async () => {
|
||||
try {
|
||||
const response = await fetch('/api/automation/status')
|
||||
const data = await response.json()
|
||||
if (data.success) {
|
||||
setStatus(data.status)
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Failed to fetch status:', error)
|
||||
}
|
||||
}
|
||||
|
||||
const fetchBalance = async () => {
|
||||
try {
|
||||
const response = await fetch('/api/drift/balance')
|
||||
const data = await response.json()
|
||||
if (data.success) {
|
||||
setBalance(data)
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Failed to fetch balance:', error)
|
||||
}
|
||||
}
|
||||
|
||||
const fetchPositions = async () => {
|
||||
try {
|
||||
const response = await fetch('/api/drift/positions')
|
||||
const data = await response.json()
|
||||
if (data.success) {
|
||||
setPositions(data.positions || [])
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Failed to fetch positions:', error)
|
||||
}
|
||||
}
|
||||
|
||||
const handleStart = async () => {
|
||||
console.log('🚀 Starting automation...')
|
||||
setLoading(true)
|
||||
try {
|
||||
if (config.selectedTimeframes.length === 0) {
|
||||
console.error('No timeframes selected')
|
||||
setLoading(false)
|
||||
return
|
||||
}
|
||||
|
||||
const automationConfig = {
|
||||
symbol: config.symbol,
|
||||
selectedTimeframes: config.selectedTimeframes,
|
||||
mode: config.mode,
|
||||
tradingAmount: config.tradingAmount,
|
||||
leverage: config.leverage,
|
||||
stopLoss: config.stopLoss,
|
||||
takeProfit: config.takeProfit
|
||||
}
|
||||
|
||||
const response = await fetch('/api/automation/start', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify(automationConfig)
|
||||
})
|
||||
|
||||
const data = await response.json()
|
||||
|
||||
if (data.success) {
|
||||
console.log('✅ Automation started successfully')
|
||||
fetchStatus()
|
||||
} else {
|
||||
console.error('Failed to start automation:', data.error)
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Failed to start automation:', error)
|
||||
} finally {
|
||||
setLoading(false)
|
||||
}
|
||||
}
|
||||
|
||||
const handleStop = async () => {
|
||||
console.log('🛑 Stopping automation...')
|
||||
setLoading(true)
|
||||
try {
|
||||
const response = await fetch('/api/automation/stop', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' }
|
||||
})
|
||||
|
||||
const data = await response.json()
|
||||
|
||||
if (data.success) {
|
||||
console.log('✅ Automation stopped successfully')
|
||||
fetchStatus()
|
||||
} else {
|
||||
console.error('Failed to stop automation:', data.error)
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Failed to stop automation:', error)
|
||||
} finally {
|
||||
setLoading(false)
|
||||
}
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="space-y-6">
|
||||
{/* Header with Start/Stop */}
|
||||
<div className="flex items-center justify-between">
|
||||
<div>
|
||||
<h1 className="text-3xl font-bold text-white">Automated Trading</h1>
|
||||
<p className="text-gray-400 mt-1">Multi-Timeframe Analysis</p>
|
||||
</div>
|
||||
<div className="flex space-x-3">
|
||||
{status?.isActive ? (
|
||||
<button
|
||||
onClick={handleStop}
|
||||
disabled={loading}
|
||||
className="px-6 py-3 bg-red-600 text-white rounded-lg hover:bg-red-700 transition-colors disabled:opacity-50 font-semibold"
|
||||
>
|
||||
{loading ? 'Stopping...' : 'STOP'}
|
||||
</button>
|
||||
) : (
|
||||
<button
|
||||
onClick={handleStart}
|
||||
disabled={loading}
|
||||
className="px-6 py-3 bg-green-600 text-white rounded-lg hover:bg-green-700 transition-colors disabled:opacity-50 font-semibold"
|
||||
>
|
||||
{loading ? 'Starting...' : 'START'}
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="grid grid-cols-1 xl:grid-cols-3 gap-6">
|
||||
{/* Configuration Panel */}
|
||||
<div className="xl:col-span-2 space-y-6">
|
||||
<div className="bg-gray-800 p-6 rounded-lg border border-gray-700">
|
||||
<h3 className="text-xl font-bold text-white mb-6">Configuration</h3>
|
||||
|
||||
{/* Trading Mode */}
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
|
||||
<div className="space-y-3">
|
||||
<label className="block text-sm font-bold text-blue-400">Trading Mode</label>
|
||||
<div className="space-y-2">
|
||||
<label className="flex items-center space-x-3 cursor-pointer p-3 rounded-lg border border-gray-600 hover:border-blue-500 transition-colors">
|
||||
<input
|
||||
type="radio"
|
||||
className="w-4 h-4 text-blue-600"
|
||||
name="mode"
|
||||
checked={config.mode === 'SIMULATION'}
|
||||
onChange={() => setConfig({...config, mode: 'SIMULATION'})}
|
||||
disabled={status?.isActive}
|
||||
/>
|
||||
<span className="text-white">Paper Trading</span>
|
||||
</label>
|
||||
<label className="flex items-center space-x-3 cursor-pointer p-3 rounded-lg border border-gray-600 hover:border-green-500 transition-colors">
|
||||
<input
|
||||
type="radio"
|
||||
className="w-4 h-4 text-green-600"
|
||||
name="mode"
|
||||
checked={config.mode === 'LIVE'}
|
||||
onChange={() => setConfig({...config, mode: 'LIVE'})}
|
||||
disabled={status?.isActive}
|
||||
/>
|
||||
<span className="text-white font-semibold">Live Trading</span>
|
||||
</label>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Symbol and Position Size */}
|
||||
<div className="grid grid-cols-1 md:grid-cols-2 gap-4 mb-6">
|
||||
<div>
|
||||
<label className="block text-sm font-medium text-gray-300 mb-2">Symbol</label>
|
||||
<select
|
||||
className="w-full p-3 bg-gray-700 border border-gray-600 rounded-lg text-white focus:border-blue-500"
|
||||
value={config.symbol}
|
||||
onChange={(e) => setConfig({...config, symbol: e.target.value})}
|
||||
disabled={status?.isActive}
|
||||
>
|
||||
<option value="SOLUSD">SOL/USD</option>
|
||||
<option value="BTCUSD">BTC/USD</option>
|
||||
<option value="ETHUSD">ETH/USD</option>
|
||||
<option value="APTUSD">APT/USD</option>
|
||||
<option value="AVAXUSD">AVAX/USD</option>
|
||||
<option value="DOGEUSD">DOGE/USD</option>
|
||||
</select>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<label className="block text-sm font-medium text-gray-300 mb-2">
|
||||
Balance to Use: {config.balancePercentage}%
|
||||
{balance && ` ($${(parseFloat(balance.availableBalance) * config.balancePercentage / 100).toFixed(2)})`}
|
||||
</label>
|
||||
<input
|
||||
type="range"
|
||||
className="w-full h-2 bg-gray-700 rounded-lg appearance-none cursor-pointer"
|
||||
style={{
|
||||
background: `linear-gradient(to right, #3b82f6 0%, #3b82f6 ${config.balancePercentage}%, #374151 ${config.balancePercentage}%, #374151 100%)`
|
||||
}}
|
||||
min="10"
|
||||
max="100"
|
||||
step="5"
|
||||
value={config.balancePercentage}
|
||||
onChange={(e) => {
|
||||
const percentage = parseFloat(e.target.value);
|
||||
const newAmount = balance ? (parseFloat(balance.availableBalance) * percentage / 100) : 100;
|
||||
setConfig({
|
||||
...config,
|
||||
balancePercentage: percentage,
|
||||
tradingAmount: Math.round(newAmount)
|
||||
});
|
||||
}}
|
||||
disabled={status?.isActive}
|
||||
/>
|
||||
<div className="flex justify-between text-xs text-gray-400 mt-1">
|
||||
<span>10%</span>
|
||||
<span>50%</span>
|
||||
<span>100%</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* MULTI-TIMEFRAME SELECTION */}
|
||||
<div className="mb-6">
|
||||
<label className="block text-sm font-medium text-gray-300 mb-2">
|
||||
Analysis Timeframes
|
||||
<span className="text-xs text-cyan-400 ml-2">({config.selectedTimeframes.length} selected)</span>
|
||||
{config.selectedTimeframes.length === 0 && (
|
||||
<span className="text-xs text-red-400 ml-2">⚠️ At least one timeframe required</span>
|
||||
)}
|
||||
</label>
|
||||
|
||||
{/* Timeframe Checkboxes */}
|
||||
<div className="grid grid-cols-4 gap-2 mb-3">
|
||||
{timeframes.map(tf => (
|
||||
<label key={tf.value} className="group relative cursor-pointer">
|
||||
<input
|
||||
type="checkbox"
|
||||
checked={config.selectedTimeframes.includes(tf.value)}
|
||||
onChange={() => toggleTimeframe(tf.value)}
|
||||
disabled={status?.isActive}
|
||||
className="sr-only"
|
||||
/>
|
||||
<div className={`flex items-center justify-center p-2 rounded-lg border transition-all text-xs font-medium ${
|
||||
config.selectedTimeframes.includes(tf.value)
|
||||
? 'border-cyan-500 bg-cyan-500/10 text-cyan-300 shadow-lg shadow-cyan-500/20'
|
||||
: status?.isActive
|
||||
? 'border-gray-700 bg-gray-800/30 text-gray-500 cursor-not-allowed'
|
||||
: 'border-gray-700 bg-gray-800/30 text-gray-400 hover:border-gray-600 hover:bg-gray-800/50 hover:text-gray-300'
|
||||
}`}>
|
||||
{tf.label}
|
||||
{config.selectedTimeframes.includes(tf.value) && (
|
||||
<div className="absolute top-0.5 right-0.5 w-1.5 h-1.5 bg-cyan-400 rounded-full"></div>
|
||||
)}
|
||||
</div>
|
||||
</label>
|
||||
))}
|
||||
</div>
|
||||
|
||||
{/* Selected Timeframes Display */}
|
||||
{config.selectedTimeframes.length > 0 && (
|
||||
<div className="p-2 bg-gray-800/30 rounded-lg mb-3">
|
||||
<div className="text-xs text-gray-400">
|
||||
Selected: <span className="text-cyan-400">
|
||||
{config.selectedTimeframes.map(tf => timeframes.find(t => t.value === tf)?.label || tf).filter(Boolean).join(', ')}
|
||||
</span>
|
||||
</div>
|
||||
<div className="text-xs text-gray-500 mt-1">
|
||||
💡 Multiple timeframes provide more robust analysis
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Quick Selection Buttons */}
|
||||
<div className="flex gap-2">
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setConfig({...config, selectedTimeframes: ['5', '15', '30']})}
|
||||
disabled={status?.isActive}
|
||||
className="py-1 px-2 rounded text-xs font-medium bg-green-600/20 text-green-300 hover:bg-green-600/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed"
|
||||
>
|
||||
📈 Scalping
|
||||
</button>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setConfig({...config, selectedTimeframes: ['60', '120']})}
|
||||
disabled={status?.isActive}
|
||||
className="py-1 px-2 rounded text-xs font-medium bg-blue-600/20 text-blue-300 hover:bg-blue-600/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed"
|
||||
>
|
||||
⚡ Day Trading
|
||||
</button>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setConfig({...config, selectedTimeframes: ['240', 'D']})}
|
||||
disabled={status?.isActive}
|
||||
className="py-1 px-2 rounded text-xs font-medium bg-purple-600/20 text-purple-300 hover:bg-purple-600/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed"
|
||||
>
|
||||
🎯 Swing Trading
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Status and Info Panel */}
|
||||
<div className="space-y-6">
|
||||
{/* Status */}
|
||||
<div className="bg-gray-800 p-6 rounded-lg border border-gray-700">
|
||||
<h3 className="text-lg font-bold text-white mb-4">Bot Status</h3>
|
||||
|
||||
<div className="space-y-3">
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Status:</span>
|
||||
<span className={`px-2 py-1 rounded text-xs font-semibold ${
|
||||
status?.isActive ? 'bg-green-600 text-white' : 'bg-gray-600 text-gray-300'
|
||||
}`}>
|
||||
{status?.isActive ? 'RUNNING' : 'STOPPED'}
|
||||
</span>
|
||||
</div>
|
||||
|
||||
{status?.isActive && (
|
||||
<>
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Symbol:</span>
|
||||
<span className="text-white font-medium">{status.symbol}</span>
|
||||
</div>
|
||||
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Mode:</span>
|
||||
<span className={`px-2 py-1 rounded text-xs font-semibold ${
|
||||
status.mode === 'LIVE' ? 'bg-red-600 text-white' : 'bg-blue-600 text-white'
|
||||
}`}>
|
||||
{status.mode}
|
||||
</span>
|
||||
</div>
|
||||
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Timeframes:</span>
|
||||
<span className="text-cyan-400 text-xs">
|
||||
{status.timeframes?.map(tf => timeframes.find(t => t.value === tf)?.label || tf).join(', ')}
|
||||
</span>
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Balance */}
|
||||
{balance && (
|
||||
<div className="bg-gray-800 p-6 rounded-lg border border-gray-700">
|
||||
<h3 className="text-lg font-bold text-white mb-4">Account Balance</h3>
|
||||
|
||||
<div className="space-y-3">
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Available:</span>
|
||||
<span className="text-green-400 font-semibold">${balance.availableBalance}</span>
|
||||
</div>
|
||||
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Total:</span>
|
||||
<span className="text-white font-medium">${balance.totalCollateral}</span>
|
||||
</div>
|
||||
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="text-gray-400">Positions:</span>
|
||||
<span className="text-yellow-400">{balance.positions || 0}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Positions */}
|
||||
{positions.length > 0 && (
|
||||
<div className="bg-gray-800 p-6 rounded-lg border border-gray-700">
|
||||
<h3 className="text-lg font-bold text-white mb-4">Open Positions</h3>
|
||||
|
||||
<div className="space-y-2">
|
||||
{positions.map((position, index) => (
|
||||
<div key={index} className="flex justify-between items-center p-2 bg-gray-700 rounded">
|
||||
<span className="text-white">{position.symbol}</span>
|
||||
<span className={`font-semibold ${
|
||||
position.side === 'LONG' ? 'text-green-400' : 'text-red-400'
|
||||
}`}>
|
||||
{position.side} ${position.size}
|
||||
</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -1,6 +1,5 @@
|
||||
'use client'
|
||||
import React, { useState, useEffect } from 'react'
|
||||
import PositionMonitor from '../components/PositionMonitor.tsx'
|
||||
|
||||
// Available timeframes for automation (matching analysis page format)
|
||||
const timeframes = [
|
||||
@@ -156,10 +155,7 @@ export default function AutomationPageV2() {
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="space-y-8">
|
||||
{/* Position Monitor - Real-time Trading Overview */}
|
||||
<PositionMonitor />
|
||||
|
||||
<div className="space-y-6">
|
||||
<div className="grid grid-cols-1 xl:grid-cols-3 gap-6">
|
||||
{/* Configuration Panel */}
|
||||
<div className="xl:col-span-2 space-y-6">
|
||||
@@ -168,16 +164,6 @@ export default function AutomationPageV2() {
|
||||
<div className="flex items-center justify-between mb-6">
|
||||
<h3 className="text-xl font-bold text-white">Configuration</h3>
|
||||
<div className="flex space-x-3">
|
||||
{/* Emergency Stop Button - Always Available */}
|
||||
<button
|
||||
onClick={handleStop}
|
||||
disabled={loading}
|
||||
className="px-4 py-2 bg-orange-600 text-white rounded-lg hover:bg-orange-700 transition-colors disabled:opacity-50 font-semibold text-sm border-2 border-orange-500"
|
||||
title="Emergency Stop - Immediately stops all automation"
|
||||
>
|
||||
🚨 EMERGENCY STOP
|
||||
</button>
|
||||
|
||||
{status?.isActive ? (
|
||||
<button
|
||||
onClick={handleStop}
|
||||
|
||||
@@ -106,13 +106,10 @@ export default function PositionMonitor() {
|
||||
return (
|
||||
<div className="space-y-6">
|
||||
{/* Header */}
|
||||
<div className="bg-gray-800 rounded-lg p-4 border border-gray-700">
|
||||
<div className="bg-gray-50 rounded-lg p-4">
|
||||
<div className="flex justify-between items-center">
|
||||
<h2 className="text-lg font-semibold text-white flex items-center">
|
||||
<span className="mr-2">🔍</span>
|
||||
Position Monitor
|
||||
</h2>
|
||||
<span className="text-sm text-gray-400">
|
||||
<h2 className="text-lg font-semibold text-gray-800">🔍 Position Monitor</h2>
|
||||
<span className="text-sm text-gray-500">
|
||||
Last update: {lastUpdate.toLocaleTimeString()}
|
||||
</span>
|
||||
</div>
|
||||
@@ -120,167 +117,139 @@ export default function PositionMonitor() {
|
||||
|
||||
{/* Position Status */}
|
||||
{monitorData?.hasPosition && monitorData.position ? (
|
||||
<div className="bg-gray-800 border border-gray-700 rounded-lg p-6">
|
||||
<h3 className="text-lg font-medium text-white mb-4 flex items-center">
|
||||
<span className="mr-2">📊</span>
|
||||
Active Position
|
||||
</h3>
|
||||
<div className="bg-white border rounded-lg p-6">
|
||||
<h3 className="text-lg font-medium text-gray-900 mb-4">📊 Active Position</h3>
|
||||
|
||||
<div className="grid grid-cols-2 md:grid-cols-3 gap-4">
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Symbol & Side</p>
|
||||
<p className="font-medium text-white">{monitorData.position.symbol}</p>
|
||||
<p className={`text-sm font-semibold ${monitorData.position.side === 'short' ? 'text-red-400' : 'text-green-400'}`}>
|
||||
{monitorData.position.side.toUpperCase()}
|
||||
</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Symbol & Side</p>
|
||||
<p className="font-medium">{monitorData.position.symbol} | {monitorData.position.side.toUpperCase()}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Size</p>
|
||||
<p className="font-medium text-white">{monitorData.position.size} SOL</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Size</p>
|
||||
<p className="font-medium">{monitorData.position.size} SOL</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Entry Price</p>
|
||||
<p className="font-medium text-white">${monitorData.position.entryPrice.toFixed(4)}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Entry Price</p>
|
||||
<p className="font-medium">${monitorData.position.entryPrice.toFixed(4)}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Current Price</p>
|
||||
<p className="font-medium text-white">${monitorData.position.currentPrice.toFixed(4)}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Current Price</p>
|
||||
<p className="font-medium">${monitorData.position.currentPrice.toFixed(4)}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">P&L</p>
|
||||
<p className={`font-medium ${monitorData.position.unrealizedPnl >= 0 ? 'text-green-400' : 'text-red-400'}`}>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">P&L</p>
|
||||
<p className={`font-medium ${monitorData.position.unrealizedPnl >= 0 ? 'text-green-600' : 'text-red-600'}`}>
|
||||
{monitorData.position.unrealizedPnl >= 0 ? '+' : ''}${monitorData.position.unrealizedPnl.toFixed(2)}
|
||||
</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Notional Value</p>
|
||||
<p className="font-medium text-white">${monitorData.position.notionalValue.toFixed(2)}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Notional Value</p>
|
||||
<p className="font-medium">${monitorData.position.notionalValue.toFixed(2)}</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Stop Loss Section */}
|
||||
{monitorData.stopLossProximity && (
|
||||
<div className="mt-6 p-4 bg-gray-900/30 rounded-lg border border-gray-600">
|
||||
<h4 className="font-medium text-white mb-3 flex items-center">
|
||||
<span className="mr-2">🤖</span>
|
||||
AI Autonomous Risk Management
|
||||
</h4>
|
||||
<div className="mt-6 p-4 bg-gray-50 rounded-lg">
|
||||
<h4 className="font-medium text-gray-900 mb-3">🛡️ Stop Loss Protection</h4>
|
||||
|
||||
<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
|
||||
<div className="bg-gray-800/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Stop Loss Price</p>
|
||||
<p className="font-medium text-white">${monitorData.stopLossProximity.stopLossPrice.toFixed(4)}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Stop Loss Price</p>
|
||||
<p className="font-medium">${monitorData.stopLossProximity.stopLossPrice.toFixed(4)}</p>
|
||||
</div>
|
||||
<div className="bg-gray-800/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Distance</p>
|
||||
<p className="font-medium text-white">{monitorData.stopLossProximity.distancePercent}% away</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Distance</p>
|
||||
<p className="font-medium">{monitorData.stopLossProximity.distancePercent}% away</p>
|
||||
</div>
|
||||
<div className="bg-gray-800/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">AI Status</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Status</p>
|
||||
{(() => {
|
||||
const status = getStopLossStatus(monitorData.stopLossProximity.distancePercent);
|
||||
const aiActions: Record<string, { text: string; color: string }> = {
|
||||
'DANGER': { text: '🚨 Emergency Analysis', color: 'text-red-400' },
|
||||
'WARNING': { text: '⚠️ Position Review', color: 'text-yellow-400' },
|
||||
'CAUTION': { text: '🟡 Enhanced Watch', color: 'text-yellow-400' },
|
||||
'SAFE': { text: '✅ Opportunity Scan', color: 'text-green-400' }
|
||||
};
|
||||
const aiAction = aiActions[status.text] || aiActions['SAFE'];
|
||||
return (
|
||||
<p className={`font-medium ${aiAction.color}`}>
|
||||
{aiAction.text}
|
||||
<p className={`font-medium ${status.color}`}>
|
||||
{status.icon} {status.text}
|
||||
</p>
|
||||
);
|
||||
})()}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="mt-3 bg-gray-800/30 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">AI Action Plan</p>
|
||||
<p className="font-medium text-blue-400">
|
||||
{monitorData.nextAction || 'AI monitoring position autonomously'}
|
||||
<div className="mt-3">
|
||||
<p className="text-sm text-gray-500">Risk Level</p>
|
||||
<p className={`font-medium ${getRiskColor(monitorData.riskLevel)}`}>
|
||||
{monitorData.riskLevel}
|
||||
</p>
|
||||
</div>
|
||||
|
||||
{monitorData.stopLossProximity.isNear && (
|
||||
<div className="mt-4 p-3 bg-blue-900/30 border border-blue-500/30 rounded-lg">
|
||||
<p className="text-blue-300 font-medium">🤖 AI TAKING ACTION: Autonomous risk management activated!</p>
|
||||
<p className="text-blue-400 text-sm mt-1">No manual intervention required - enjoy your beach time! 🏖️</p>
|
||||
<div className="mt-4 p-3 bg-red-100 border border-red-300 rounded-lg">
|
||||
<p className="text-red-700 font-medium">🚨 ALERT: Price is near stop loss!</p>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
) : (
|
||||
<div className="bg-gray-800 border border-gray-700 rounded-lg p-6">
|
||||
<div className="bg-white border rounded-lg p-6">
|
||||
<div className="text-center py-8">
|
||||
<p className="text-gray-400 text-lg flex items-center justify-center">
|
||||
<span className="mr-2">📊</span>
|
||||
No Open Positions
|
||||
</p>
|
||||
<p className="text-gray-500 mt-2">Scanning for opportunities...</p>
|
||||
<p className="text-gray-500 text-lg">📊 No Open Positions</p>
|
||||
<p className="text-gray-400 mt-2">Scanning for opportunities...</p>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Automation Status */}
|
||||
<div className="bg-gray-800 border border-gray-700 rounded-lg p-6">
|
||||
<h3 className="text-lg font-medium text-white mb-4 flex items-center">
|
||||
<span className="mr-2">🤖</span>
|
||||
Automation Status
|
||||
</h3>
|
||||
<div className="bg-white border rounded-lg p-6">
|
||||
<h3 className="text-lg font-medium text-gray-900 mb-4">🤖 Automation Status</h3>
|
||||
|
||||
{automationStatus?.isActive ? (
|
||||
<div className="space-y-4">
|
||||
<div className="grid grid-cols-2 md:grid-cols-4 gap-4">
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Status</p>
|
||||
<p className="font-medium text-green-400 flex items-center">
|
||||
<span className="w-2 h-2 bg-green-400 rounded-full mr-2"></span>
|
||||
ACTIVE
|
||||
</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Status</p>
|
||||
<p className="font-medium text-green-600">✅ ACTIVE</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Mode</p>
|
||||
<p className={`font-medium ${automationStatus.mode === 'LIVE' ? 'text-red-400' : 'text-blue-400'}`}>
|
||||
{automationStatus.mode}
|
||||
</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Mode</p>
|
||||
<p className="font-medium">{automationStatus.mode}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Strategy</p>
|
||||
<p className="font-medium text-white">Scalping</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Strategy</p>
|
||||
<p className="font-medium">Scalping</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Symbol</p>
|
||||
<p className="font-medium text-white">{automationStatus.symbol}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Symbol</p>
|
||||
<p className="font-medium">{automationStatus.symbol}</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="grid grid-cols-2 md:grid-cols-4 gap-4">
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Timeframes</p>
|
||||
<p className="font-medium text-cyan-400">{automationStatus.timeframes?.join(', ') || 'N/A'}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Timeframes</p>
|
||||
<p className="font-medium">{automationStatus.timeframes?.join(', ') || 'N/A'}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Cycles</p>
|
||||
<p className="font-medium text-white">{automationStatus.totalCycles}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Cycles</p>
|
||||
<p className="font-medium">{automationStatus.totalCycles}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Trades</p>
|
||||
<p className="font-medium text-white">{automationStatus.totalTrades}</p>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Trades</p>
|
||||
<p className="font-medium">{automationStatus.totalTrades}</p>
|
||||
</div>
|
||||
<div className="bg-gray-900/50 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Errors</p>
|
||||
<p className={`font-medium ${automationStatus.consecutiveErrors > 0 ? 'text-yellow-400' : 'text-green-400'}`}>
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Errors</p>
|
||||
<p className={`font-medium ${automationStatus.consecutiveErrors > 0 ? 'text-yellow-600' : 'text-green-600'}`}>
|
||||
{automationStatus.consecutiveErrors}/3
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{automationStatus.lastActivity && (
|
||||
<div className="bg-gray-900/30 p-3 rounded-lg">
|
||||
<p className="text-sm text-gray-400">Last Activity</p>
|
||||
<p className="font-medium text-white">
|
||||
<div>
|
||||
<p className="text-sm text-gray-500">Last Activity</p>
|
||||
<p className="font-medium">
|
||||
{new Date(automationStatus.lastActivity).toLocaleString()}
|
||||
</p>
|
||||
</div>
|
||||
@@ -288,10 +257,7 @@ export default function PositionMonitor() {
|
||||
</div>
|
||||
) : (
|
||||
<div className="text-center py-4">
|
||||
<p className="text-red-400 font-medium flex items-center justify-center">
|
||||
<span className="w-2 h-2 bg-red-400 rounded-full mr-2"></span>
|
||||
STOPPED
|
||||
</p>
|
||||
<p className="text-red-600 font-medium">❌ STOPPED</p>
|
||||
<p className="text-gray-500 mt-2">{automationStatus?.detailedStatus}</p>
|
||||
</div>
|
||||
)}
|
||||
|
||||
@@ -0,0 +1,326 @@
|
||||
class SafeParallelAutomation {
|
||||
private isRunning = false
|
||||
private config: any = null
|
||||
private intervalId: NodeJS.Timeout | null = null
|
||||
private lastAnalysisTime = 0
|
||||
|
||||
// SAFE PARAMETERS - Respect timeframe strategy
|
||||
private readonly MIN_ANALYSIS_INTERVAL = 10 * 60 * 1000 // 10 minutes minimum
|
||||
private readonly MAX_TRADES_PER_HOUR = 2
|
||||
private readonly ANALYSIS_COOLDOWN = 5 * 60 * 1000 // 5 minutes
|
||||
|
||||
private stats = {
|
||||
totalTrades: 0,
|
||||
successfulTrades: 0,
|
||||
winRate: 0,
|
||||
totalPnL: 0,
|
||||
errorCount: 0,
|
||||
lastAnalysis: null as string | null,
|
||||
nextScheduled: null as string | null,
|
||||
nextAnalysisIn: 0,
|
||||
analysisInterval: 0,
|
||||
currentCycle: 0,
|
||||
lastError: null as string | null,
|
||||
strategyType: 'General'
|
||||
}
|
||||
|
||||
async startSafeAutomation(config: any): Promise<{ success: boolean, message?: string }> {
|
||||
try {
|
||||
if (this.isRunning) {
|
||||
return { success: false, message: 'Safe automation already running' }
|
||||
}
|
||||
|
||||
// SAFETY CHECK: Rate limiting
|
||||
const now = Date.now()
|
||||
if (now - this.lastAnalysisTime < this.ANALYSIS_COOLDOWN) {
|
||||
const remaining = Math.ceil((this.ANALYSIS_COOLDOWN - (now - this.lastAnalysisTime)) / 1000)
|
||||
return {
|
||||
success: false,
|
||||
message: 'Safety cooldown: Wait ' + remaining + ' seconds'
|
||||
}
|
||||
}
|
||||
|
||||
// SAFETY CHECK: Validate timeframes
|
||||
if (!config.timeframes || config.timeframes.length === 0) {
|
||||
return { success: false, message: 'At least one timeframe required' }
|
||||
}
|
||||
|
||||
this.config = config
|
||||
this.isRunning = true
|
||||
this.lastAnalysisTime = now
|
||||
this.stats.currentCycle = 0
|
||||
this.stats.strategyType = config.strategyType || 'General'
|
||||
|
||||
console.log('SAFE PARALLEL: Starting for ' + config.symbol)
|
||||
console.log('STRATEGY: ' + this.stats.strategyType)
|
||||
console.log('TIMEFRAMES: [' + config.timeframes.join(', ') + ']')
|
||||
console.log('SAFETY: Max ' + this.MAX_TRADES_PER_HOUR + ' trades/hour')
|
||||
|
||||
// Start with strategy-appropriate interval
|
||||
this.startSafeAnalysisCycle()
|
||||
|
||||
return { success: true, message: 'Safe parallel automation started' }
|
||||
} catch (error) {
|
||||
console.error('Failed to start safe automation:', error)
|
||||
return { success: false, message: 'Failed to start automation' }
|
||||
}
|
||||
}
|
||||
|
||||
private startSafeAnalysisCycle(): void {
|
||||
// Get strategy-appropriate interval but enforce minimum safety
|
||||
const strategyInterval = this.getStrategyInterval(this.config.timeframes, this.config.strategyType)
|
||||
const safeInterval = Math.max(this.MIN_ANALYSIS_INTERVAL, strategyInterval)
|
||||
|
||||
console.log('STRATEGY INTERVAL: ' + (strategyInterval / 1000 / 60) + ' minutes')
|
||||
console.log('SAFE INTERVAL: ' + (safeInterval / 1000 / 60) + ' minutes (enforced minimum)')
|
||||
|
||||
this.stats.analysisInterval = safeInterval
|
||||
this.stats.nextScheduled = new Date(Date.now() + safeInterval).toISOString()
|
||||
this.stats.nextAnalysisIn = safeInterval
|
||||
|
||||
// Set safe interval
|
||||
this.intervalId = setInterval(async () => {
|
||||
if (this.isRunning && this.config) {
|
||||
await this.runSafeAnalysisCycle()
|
||||
}
|
||||
}, safeInterval)
|
||||
|
||||
// First cycle after delay
|
||||
setTimeout(() => {
|
||||
if (this.isRunning && this.config) {
|
||||
this.runSafeAnalysisCycle()
|
||||
}
|
||||
}, 30000)
|
||||
}
|
||||
|
||||
private async runSafeAnalysisCycle(): Promise<void> {
|
||||
try {
|
||||
console.log('\nSAFE CYCLE ' + (this.stats.currentCycle + 1) + ': ' + this.config.symbol)
|
||||
console.log('STRATEGY: ' + this.stats.strategyType)
|
||||
|
||||
// SAFETY CHECK
|
||||
const canTrade = await this.canExecuteTrade()
|
||||
if (!canTrade.allowed) {
|
||||
console.log('SAFETY BLOCK: ' + canTrade.reason)
|
||||
this.updateNextAnalysisTime()
|
||||
return
|
||||
}
|
||||
|
||||
// PARALLEL ANALYSIS using enhanced screenshot API
|
||||
console.log('PARALLEL: Analyzing ' + this.config.timeframes.length + ' timeframes...')
|
||||
|
||||
const analysisResult = await this.performParallelAnalysis()
|
||||
|
||||
if (!analysisResult || !analysisResult.analysis) {
|
||||
console.log('Analysis failed, skipping')
|
||||
return
|
||||
}
|
||||
|
||||
this.stats.lastAnalysis = new Date().toISOString()
|
||||
console.log('ANALYSIS: ' + analysisResult.analysis.recommendation)
|
||||
|
||||
// CONTROLLED TRADING with strategy-specific logic
|
||||
if (this.shouldExecuteTrade(analysisResult.analysis)) {
|
||||
console.log('EXECUTING: Trade criteria met for ' + this.stats.strategyType)
|
||||
const tradeResult = await this.executeSafeTrade(analysisResult.analysis)
|
||||
if (tradeResult?.success) {
|
||||
this.stats.totalTrades++
|
||||
this.stats.successfulTrades++
|
||||
this.stats.winRate = (this.stats.successfulTrades / this.stats.totalTrades) * 100
|
||||
console.log('TRADE: Executed successfully')
|
||||
}
|
||||
} else {
|
||||
console.log('SIGNAL: Criteria not met for ' + this.stats.strategyType)
|
||||
}
|
||||
|
||||
this.stats.currentCycle++
|
||||
|
||||
} catch (error) {
|
||||
console.error('Error in safe cycle:', error)
|
||||
this.stats.errorCount++
|
||||
this.stats.lastError = error instanceof Error ? error.message : 'Unknown error'
|
||||
} finally {
|
||||
await this.guaranteedCleanup()
|
||||
this.updateNextAnalysisTime()
|
||||
}
|
||||
}
|
||||
|
||||
private async performParallelAnalysis(): Promise<any> {
|
||||
try {
|
||||
// Use the enhanced screenshot API endpoint with all selected timeframes
|
||||
const response = await fetch('http://localhost:3000/api/enhanced-screenshot', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
symbol: this.config.symbol,
|
||||
timeframes: this.config.timeframes,
|
||||
layouts: ['ai', 'diy'],
|
||||
analyze: true
|
||||
})
|
||||
})
|
||||
|
||||
throw new Error('API response: ' + response.status)
|
||||
}
|
||||
|
||||
const result = await response.json()
|
||||
|
||||
if (result.analysis) {
|
||||
console.log('PARALLEL: Confidence ' + result.analysis.confidence + '%')
|
||||
return result
|
||||
}
|
||||
|
||||
return null
|
||||
} catch (error) {
|
||||
console.error('Error in parallel analysis:', error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
private shouldExecuteTrade(analysis: any): boolean {
|
||||
const recommendation = analysis.recommendation.toLowerCase()
|
||||
const confidence = analysis.confidence || 0
|
||||
|
||||
// Strategy-specific confidence requirements
|
||||
let minConfidence = 75 // Default
|
||||
|
||||
if (this.stats.strategyType === 'Scalping') {
|
||||
minConfidence = 80 // Higher confidence for scalping
|
||||
} else if (this.stats.strategyType === 'Day Trading') {
|
||||
minConfidence = 75 // Standard confidence
|
||||
} else if (this.stats.strategyType === 'Swing Trading') {
|
||||
minConfidence = 70 // Slightly lower for swing (longer timeframes)
|
||||
}
|
||||
|
||||
const isHighConfidence = confidence >= minConfidence
|
||||
const isClearDirection = recommendation.includes('buy') || recommendation.includes('sell')
|
||||
|
||||
console.log('SIGNAL: ' + recommendation + ' (' + confidence + '%) - Required: ' + minConfidence + '%')
|
||||
|
||||
return isHighConfidence && isClearDirection
|
||||
}
|
||||
|
||||
private getStrategyInterval(timeframes: string[], strategyType: string): number {
|
||||
// Strategy-based intervals (but minimum will be enforced)
|
||||
|
||||
if (strategyType === 'Scalping') {
|
||||
console.log('SCALPING: Using 2-minute analysis cycle')
|
||||
return 2 * 60 * 1000 // 2 minutes for scalping (will be enforced to 10 min minimum)
|
||||
}
|
||||
|
||||
if (strategyType === 'Day Trading') {
|
||||
console.log('DAY TRADING: Using 5-minute analysis cycle')
|
||||
return 5 * 60 * 1000 // 5 minutes for day trading (will be enforced to 10 min minimum)
|
||||
}
|
||||
|
||||
if (strategyType === 'Swing Trading') {
|
||||
console.log('SWING TRADING: Using 15-minute analysis cycle')
|
||||
return 15 * 60 * 1000 // 15 minutes for swing trading
|
||||
}
|
||||
|
||||
// Fallback based on shortest timeframe
|
||||
const shortest = Math.min(...timeframes.map(tf => {
|
||||
if (tf === 'D') return 1440
|
||||
return parseInt(tf) || 60
|
||||
}))
|
||||
|
||||
if (shortest <= 5) return 2 * 60 * 1000 // 2 min for very short
|
||||
if (shortest <= 15) return 5 * 60 * 1000 // 5 min for short
|
||||
if (shortest <= 60) return 10 * 60 * 1000 // 10 min for medium
|
||||
return 15 * 60 * 1000 // 15 min for long
|
||||
}
|
||||
|
||||
private async executeSafeTrade(analysis: any): Promise<any> {
|
||||
try {
|
||||
console.log('SAFE TRADE: Executing...')
|
||||
|
||||
// Use drift trading API endpoint
|
||||
const response = await fetch('http://localhost:3000/api/trading', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
mode: this.config.mode,
|
||||
symbol: this.config.symbol,
|
||||
amount: this.config.tradingAmount,
|
||||
leverage: this.config.leverage,
|
||||
stopLoss: this.config.stopLoss,
|
||||
takeProfit: this.config.takeProfit,
|
||||
analysis: analysis,
|
||||
strategy: this.stats.strategyType
|
||||
})
|
||||
})
|
||||
|
||||
const result = await response.json()
|
||||
return result
|
||||
} catch (error) {
|
||||
console.error('Error executing trade:', error)
|
||||
return { success: false, error: error.message }
|
||||
}
|
||||
}
|
||||
|
||||
private async canExecuteTrade(): Promise<{ allowed: boolean, reason?: string }> {
|
||||
const now = Date.now()
|
||||
|
||||
if (now - this.lastAnalysisTime < this.ANALYSIS_COOLDOWN) {
|
||||
const remaining = Math.ceil((this.ANALYSIS_COOLDOWN - (now - this.lastAnalysisTime)) / 1000 / 60)
|
||||
return { allowed: false, reason: 'Cooldown: ' + remaining + 'min' }
|
||||
}
|
||||
|
||||
if (this.stats.totalTrades >= this.MAX_TRADES_PER_HOUR) {
|
||||
return { allowed: false, reason: 'Hour limit: ' + this.stats.totalTrades + '/' + this.MAX_TRADES_PER_HOUR }
|
||||
}
|
||||
|
||||
return { allowed: true }
|
||||
}
|
||||
|
||||
private async guaranteedCleanup(): Promise<void> {
|
||||
try {
|
||||
const { execSync } = require('child_process')
|
||||
execSync('pkill -f "chrome|chromium" 2>/dev/null || true')
|
||||
console.log('CLEANUP: Completed')
|
||||
} catch (error) {
|
||||
console.error('CLEANUP: Failed', error)
|
||||
}
|
||||
}
|
||||
|
||||
private updateNextAnalysisTime(): void {
|
||||
const nextTime = Date.now() + this.stats.analysisInterval
|
||||
this.stats.nextScheduled = new Date(nextTime).toISOString()
|
||||
this.stats.nextAnalysisIn = this.stats.analysisInterval
|
||||
}
|
||||
|
||||
async stopSafeAutomation(): Promise<{ success: boolean, message?: string }> {
|
||||
try {
|
||||
this.isRunning = false
|
||||
|
||||
if (this.intervalId) {
|
||||
clearInterval(this.intervalId)
|
||||
this.intervalId = null
|
||||
}
|
||||
|
||||
await this.guaranteedCleanup()
|
||||
|
||||
this.config = null
|
||||
this.stats.nextAnalysisIn = 0
|
||||
this.stats.nextScheduled = null
|
||||
|
||||
console.log('SAFE: Automation stopped')
|
||||
return { success: true, message: 'Safe automation stopped' }
|
||||
} catch (error) {
|
||||
return { success: false, message: 'Stop failed' }
|
||||
}
|
||||
}
|
||||
|
||||
getStatus() {
|
||||
return {
|
||||
isActive: this.isRunning,
|
||||
mode: this.config?.mode || 'SIMULATION',
|
||||
symbol: this.config?.symbol || 'SOLUSD',
|
||||
timeframes: this.config?.timeframes || ['1h'],
|
||||
automationType: 'SAFE_PARALLEL',
|
||||
strategy: this.stats.strategyType,
|
||||
...this.stats
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export const safeParallelAutomation = new SafeParallelAutomation()
|
||||
|
||||
@@ -1,40 +1,9 @@
|
||||
// Simple automation service for basic start/stop functionality
|
||||
|
||||
// Import AI Leverage Calculator for dynamic leverage
|
||||
async function importAILeverageCalculator() {
|
||||
try {
|
||||
const { AILeverageCalculator } = await import('./ai-leverage-calculator.js');
|
||||
return AILeverageCalculator;
|
||||
} catch (error) {
|
||||
console.warn('⚠️ AI Leverage Calculator not available, using default leverage');
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
// Import Enhanced Risk Manager with Learning for intelligent beach mode operation
|
||||
async function importEnhancedRiskManager() {
|
||||
try {
|
||||
const EnhancedAutonomousRiskManager = require('./enhanced-autonomous-risk-manager.js');
|
||||
return EnhancedAutonomousRiskManager;
|
||||
} catch (error) {
|
||||
console.warn('⚠️ Enhanced Risk Manager not available, falling back to stable monitor');
|
||||
// Fallback to stable risk monitor
|
||||
try {
|
||||
const StableRiskMonitor = require('./stable-risk-monitor.js');
|
||||
return StableRiskMonitor;
|
||||
} catch (fallbackError) {
|
||||
console.warn('⚠️ Stable Risk Monitor also not available, using basic monitoring');
|
||||
return null;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
class SimpleAutomation {
|
||||
constructor() {
|
||||
this.isRunning = false;
|
||||
this.config = null;
|
||||
this.intervalId = null;
|
||||
this.riskManager = null; // Autonomous AI Risk Manager
|
||||
this.stats = {
|
||||
totalCycles: 0,
|
||||
totalTrades: 0,
|
||||
@@ -61,41 +30,8 @@ class SimpleAutomation {
|
||||
this.isRunning = true;
|
||||
this.stats.startTime = new Date().toISOString();
|
||||
this.stats.status = 'Running';
|
||||
|
||||
console.log('✅ AUTOMATION STATUS: isRunning =', this.isRunning);
|
||||
console.log('🎯 LIVE TRADING:', this.config.enableTrading ? 'ENABLED' : 'DISABLED');
|
||||
this.stats.totalCycles = 0;
|
||||
|
||||
// Initialize Enhanced AI Risk Manager with Learning Capabilities
|
||||
try {
|
||||
const EnhancedRiskManagerClass = await importEnhancedRiskManager();
|
||||
if (EnhancedRiskManagerClass) {
|
||||
this.riskManager = new EnhancedRiskManagerClass();
|
||||
console.log('🧠 ENHANCED BEACH MODE: AI learning system activated');
|
||||
console.log('🎯 System will learn from every decision and improve over time');
|
||||
|
||||
// Start enhanced autonomous operation
|
||||
setTimeout(() => {
|
||||
if (this.riskManager && this.riskManager.beachMode) {
|
||||
this.riskManager.beachMode();
|
||||
console.log('🏖️ Full autonomous operation with AI learning active');
|
||||
}
|
||||
}, 2000);
|
||||
}
|
||||
} catch (error) {
|
||||
console.log('🔄 Continuing without enhanced autonomous risk monitoring');
|
||||
console.error('Risk manager initialization error:', error.message);
|
||||
}
|
||||
|
||||
// Auto-enable trading when in LIVE mode
|
||||
if (config.mode === 'LIVE') {
|
||||
this.config.enableTrading = true;
|
||||
console.log('🔥 LIVE TRADING ENABLED: Real trades will be executed');
|
||||
} else {
|
||||
this.config.enableTrading = false;
|
||||
console.log('📊 SIMULATION MODE: Trades will be simulated only');
|
||||
}
|
||||
|
||||
// Detect strategy
|
||||
const timeframes = config.selectedTimeframes;
|
||||
let strategy = 'General';
|
||||
@@ -137,22 +73,14 @@ class SimpleAutomation {
|
||||
|
||||
async stop() {
|
||||
try {
|
||||
console.log('🛑 STOPPING AUTOMATION...');
|
||||
this.isRunning = false;
|
||||
this.stats.status = 'Stopped';
|
||||
console.log('✅ AUTOMATION STATUS: isRunning =', this.isRunning);
|
||||
|
||||
if (this.intervalId) {
|
||||
clearInterval(this.intervalId);
|
||||
this.intervalId = null;
|
||||
}
|
||||
|
||||
// Stop risk monitor if running
|
||||
if (this.riskManager && this.riskManager.stop) {
|
||||
this.riskManager.stop();
|
||||
console.log('🏖️ Beach mode monitoring stopped');
|
||||
}
|
||||
|
||||
console.log('SIMPLE AUTOMATION: Stopped');
|
||||
|
||||
return { success: true, message: 'Automation stopped successfully' };
|
||||
@@ -164,12 +92,6 @@ class SimpleAutomation {
|
||||
|
||||
async runCycle() {
|
||||
try {
|
||||
// Check if automation should still be running
|
||||
if (!this.isRunning) {
|
||||
console.log('⏹️ AUTOMATION STOPPED: Skipping cycle');
|
||||
return;
|
||||
}
|
||||
|
||||
this.stats.totalCycles++;
|
||||
this.stats.lastActivity = new Date().toISOString();
|
||||
|
||||
@@ -180,32 +102,10 @@ class SimpleAutomation {
|
||||
if (this.config) {
|
||||
// Perform actual analysis using enhanced screenshot API
|
||||
await this.performAnalysis();
|
||||
|
||||
// Reset error counter on successful cycle
|
||||
this.stats.consecutiveErrors = 0;
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
console.error('❌ CRITICAL ERROR in automation cycle:', error);
|
||||
console.error('❌ Stack trace:', error.stack);
|
||||
|
||||
// Increment error counter
|
||||
this.stats.consecutiveErrors = (this.stats.consecutiveErrors || 0) + 1;
|
||||
|
||||
// If too many consecutive errors, stop automation
|
||||
if (this.stats.consecutiveErrors >= 3) {
|
||||
console.error('🚨 TOO MANY ERRORS: Stopping automation after', this.stats.consecutiveErrors, 'consecutive failures');
|
||||
this.isRunning = false;
|
||||
this.stats.status = 'Stopped due to errors';
|
||||
|
||||
if (this.intervalId) {
|
||||
clearInterval(this.intervalId);
|
||||
this.intervalId = null;
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
console.log(`⚠️ Error ${this.stats.consecutiveErrors}/3 - Will retry next cycle`);
|
||||
console.error('Error in automation cycle:', error);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -376,8 +276,10 @@ class SimpleAutomation {
|
||||
}
|
||||
|
||||
shouldExecuteTrade(analysis) {
|
||||
// Always allow trade execution - the useRealDEX flag determines if it's real or simulated
|
||||
console.log(`<EFBFBD> TRADE MODE: ${this.config.mode || 'SIMULATION'} - Trading ${this.config.enableTrading ? 'ENABLED' : 'DISABLED'}`);
|
||||
if (this.config.mode !== 'LIVE') {
|
||||
console.log('📊 SIMULATION MODE: Would execute trade');
|
||||
return false;
|
||||
}
|
||||
|
||||
const recommendation = analysis.recommendation?.toLowerCase() || '';
|
||||
const confidence = analysis.confidence || 0;
|
||||
@@ -399,7 +301,6 @@ class SimpleAutomation {
|
||||
async executeTrade(analysis) {
|
||||
try {
|
||||
console.log('💰 EXECUTING TRADE...');
|
||||
console.log('📊 Analysis data:', JSON.stringify(analysis, null, 2));
|
||||
|
||||
// Map analysis recommendation to trading side
|
||||
const recommendation = analysis.recommendation?.toLowerCase() || '';
|
||||
@@ -414,110 +315,13 @@ class SimpleAutomation {
|
||||
return { success: false, error: 'Invalid recommendation: ' + recommendation };
|
||||
}
|
||||
|
||||
// Extract stop loss and take profit from analysis
|
||||
let stopLoss = null;
|
||||
let takeProfit = null;
|
||||
|
||||
// Try to extract from the structured analysis format
|
||||
if (analysis.stopLoss && typeof analysis.stopLoss === 'object') {
|
||||
stopLoss = analysis.stopLoss.price;
|
||||
} else if (analysis.stopLoss && typeof analysis.stopLoss === 'number') {
|
||||
stopLoss = analysis.stopLoss;
|
||||
}
|
||||
|
||||
// Extract take profit - prefer tp1 if available
|
||||
if (analysis.takeProfits && typeof analysis.takeProfits === 'object') {
|
||||
if (analysis.takeProfits.tp1 && analysis.takeProfits.tp1.price) {
|
||||
takeProfit = analysis.takeProfits.tp1.price;
|
||||
} else if (analysis.takeProfits.tp2 && analysis.takeProfits.tp2.price) {
|
||||
takeProfit = analysis.takeProfits.tp2.price;
|
||||
}
|
||||
} else if (analysis.takeProfit && typeof analysis.takeProfit === 'number') {
|
||||
takeProfit = analysis.takeProfit;
|
||||
}
|
||||
|
||||
// Fallback: try to extract from nested levels object
|
||||
if (!stopLoss && analysis.levels) {
|
||||
stopLoss = analysis.levels.stopLoss || analysis.levels.stop;
|
||||
}
|
||||
if (!takeProfit && analysis.levels) {
|
||||
takeProfit = analysis.levels.takeProfit || analysis.levels.target;
|
||||
}
|
||||
|
||||
// Parse numeric values if they're strings
|
||||
if (stopLoss && typeof stopLoss === 'string') {
|
||||
stopLoss = parseFloat(stopLoss.replace(/[^0-9.]/g, ''));
|
||||
}
|
||||
if (takeProfit && typeof takeProfit === 'string') {
|
||||
takeProfit = parseFloat(takeProfit.replace(/[^0-9.]/g, ''));
|
||||
}
|
||||
|
||||
console.log(`🎯 Trade levels - SL: ${stopLoss}, TP: ${takeProfit}`);
|
||||
|
||||
// Calculate optimal leverage using AI Leverage Calculator
|
||||
let optimalLeverage = 1; // Default fallback
|
||||
console.log('🔧 DEBUG: Starting leverage calculation...');
|
||||
try {
|
||||
const AILeverageCalculator = await importAILeverageCalculator();
|
||||
console.log('🔧 DEBUG: AI Leverage Calculator imported:', !!AILeverageCalculator);
|
||||
if (AILeverageCalculator && stopLoss) {
|
||||
console.log('🔧 DEBUG: Both calculator and stopLoss available, proceeding...');
|
||||
// Get current price from analysis
|
||||
const currentPrice = analysis.entry?.price || analysis.currentPrice || 178; // fallback price
|
||||
|
||||
// Get real account data from Drift API
|
||||
let accountValue = 49; // fallback
|
||||
let availableBalance = 49; // fallback
|
||||
|
||||
try {
|
||||
const baseUrl = process.env.INTERNAL_API_URL || 'http://localhost:3000';
|
||||
console.log('🔧 DEBUG: Fetching balance from:', baseUrl);
|
||||
const balanceResponse = await fetch(`${baseUrl}/api/drift/balance`);
|
||||
const balanceData = await balanceResponse.json();
|
||||
if (balanceData.success) {
|
||||
accountValue = balanceData.accountValue;
|
||||
availableBalance = balanceData.availableBalance;
|
||||
console.log(`💰 Real account data: $${accountValue.toFixed(2)} total, $${availableBalance.toFixed(2)} available`);
|
||||
} else {
|
||||
console.log('🔧 DEBUG: Balance API returned error:', balanceData);
|
||||
}
|
||||
} catch (balanceError) {
|
||||
console.warn('⚠️ Failed to get real balance, using fallback:', balanceError.message);
|
||||
}
|
||||
|
||||
console.log(`🧮 Calculating optimal leverage: Entry=$${currentPrice}, StopLoss=$${stopLoss}`);
|
||||
|
||||
const leverageResult = AILeverageCalculator.calculateOptimalLeverage({
|
||||
accountValue,
|
||||
availableBalance,
|
||||
entryPrice: currentPrice,
|
||||
stopLossPrice: stopLoss,
|
||||
side: side === 'BUY' ? 'long' : 'short',
|
||||
maxLeverageAllowed: 10, // Drift platform max
|
||||
safetyBuffer: 0.10 // 10% safety buffer
|
||||
});
|
||||
|
||||
optimalLeverage = leverageResult.recommendedLeverage;
|
||||
console.log(`🎯 AI Calculated Leverage: ${optimalLeverage.toFixed(1)}x (Risk: ${leverageResult.riskAssessment})`);
|
||||
console.log(`📊 Leverage Details: ${leverageResult.reasoning}`);
|
||||
} else {
|
||||
console.log('🔧 DEBUG: Skipping leverage calc - Calculator:', !!AILeverageCalculator, 'StopLoss:', !!stopLoss);
|
||||
}
|
||||
} catch (leverageError) {
|
||||
console.warn('⚠️ Leverage calculation failed, using default 1x:', leverageError.message);
|
||||
}
|
||||
|
||||
console.log(`🔧 DEBUG: Final leverage to use: ${optimalLeverage}x`);
|
||||
|
||||
// Use the trading API with proper fields for Drift
|
||||
// Use the trading API with proper fields
|
||||
const tradePayload = {
|
||||
symbol: this.config.symbol,
|
||||
side: side,
|
||||
amount: this.config.tradingAmount || 49, // Use available balance
|
||||
leverage: optimalLeverage, // Use AI-calculated optimal leverage
|
||||
stopLoss: stopLoss,
|
||||
takeProfit: takeProfit,
|
||||
useRealDEX: this.config.enableTrading === true, // Use real DEX when live trading enabled
|
||||
amount: this.config.tradingAmount || 10, // Default to $10 if not set
|
||||
type: 'market',
|
||||
tradingMode: 'SPOT',
|
||||
analysis: analysis // Include analysis for reference
|
||||
};
|
||||
|
||||
@@ -548,27 +352,14 @@ class SimpleAutomation {
|
||||
}
|
||||
|
||||
getStatus() {
|
||||
const baseStatus = {
|
||||
return {
|
||||
isActive: this.isRunning,
|
||||
mode: this.config?.mode || 'SIMULATION',
|
||||
enableTrading: this.config?.enableTrading || false,
|
||||
tradingStatus: this.config?.enableTrading ? 'REAL TRADES' : 'SIMULATED ONLY',
|
||||
symbol: this.config?.symbol || 'SOLUSD',
|
||||
timeframes: this.config?.selectedTimeframes || [],
|
||||
automationType: 'SIMPLE',
|
||||
...this.stats
|
||||
};
|
||||
|
||||
// Add more descriptive status based on running state
|
||||
if (this.isRunning) {
|
||||
baseStatus.detailedStatus = 'Running - Monitoring for trade opportunities';
|
||||
baseStatus.nextAction = 'Next analysis cycle in progress';
|
||||
} else {
|
||||
baseStatus.detailedStatus = 'Stopped - No monitoring active';
|
||||
baseStatus.nextAction = 'Start automation to begin monitoring';
|
||||
}
|
||||
|
||||
return baseStatus;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
530
lib/simplified-stop-loss-learner-fixed.js
Normal file
530
lib/simplified-stop-loss-learner-fixed.js
Normal file
@@ -0,0 +1,530 @@
|
||||
/**
|
||||
* Simplified Stop Loss Learning System
|
||||
*
|
||||
* Simplified approach focusing on essential learning patterns
|
||||
* without complex statistical analysis.
|
||||
*/
|
||||
|
||||
const { PrismaClient } = require('@prisma/client');
|
||||
const getDB = require('./database-util');
|
||||
|
||||
class SimplifiedStopLossLearner {
|
||||
constructor() {
|
||||
this.learningThresholds = {
|
||||
emergency: 1.0, // Emergency exit at 1% from SL
|
||||
risk: 2.0, // High risk at 2% from SL
|
||||
mediumRisk: 5.0 // Medium risk at 5% from SL
|
||||
};
|
||||
}
|
||||
|
||||
async log(message) {
|
||||
console.log(`[${new Date().toISOString()}] 🧠 SL Learner: ${message}`);
|
||||
}
|
||||
|
||||
/**
|
||||
* Record a stop loss related decision for learning
|
||||
*/
|
||||
async recordDecision(decisionData) {
|
||||
try {
|
||||
const learningRecord = {
|
||||
type: 'STOP_LOSS_DECISION',
|
||||
tradeId: decisionData.tradeId,
|
||||
symbol: decisionData.symbol,
|
||||
decision: decisionData.decision,
|
||||
distanceFromSL: decisionData.distanceFromSL,
|
||||
reasoning: decisionData.reasoning,
|
||||
marketConditions: decisionData.marketConditions,
|
||||
expectedOutcome: decisionData.expectedOutcome,
|
||||
timestamp: new Date().toISOString()
|
||||
};
|
||||
|
||||
const prisma = await getDB();
|
||||
const record = await prisma.ai_learning_data.create({
|
||||
data: {
|
||||
id: `sl_decision_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`,
|
||||
userId: 'default-user',
|
||||
symbol: decisionData.symbol,
|
||||
timeframe: 'DECISION',
|
||||
analysisData: JSON.stringify(learningRecord),
|
||||
marketConditions: JSON.stringify(decisionData.marketConditions || {}),
|
||||
confidenceScore: 50 // Neutral starting confidence
|
||||
}
|
||||
});
|
||||
|
||||
await this.log(`📝 Decision recorded: ${decisionData.decision} for ${decisionData.symbol} at ${decisionData.distanceFromSL}%`);
|
||||
|
||||
return record.id;
|
||||
} catch (error) {
|
||||
await this.log(`❌ Error recording decision: ${error.message}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Update the outcome of a previously recorded decision
|
||||
*/
|
||||
async assessDecisionOutcome(outcomeData) {
|
||||
try {
|
||||
const prisma = await getDB();
|
||||
|
||||
// Find the original decision record
|
||||
const originalRecord = await prisma.ai_learning_data.findUnique({
|
||||
where: { id: outcomeData.decisionId }
|
||||
});
|
||||
|
||||
if (!originalRecord) {
|
||||
await this.log(`⚠️ Original decision ${outcomeData.decisionId} not found`);
|
||||
return false;
|
||||
}
|
||||
|
||||
// Parse the original decision data
|
||||
const originalDecision = JSON.parse(originalRecord.analysisData);
|
||||
|
||||
// Create outcome record with learning data
|
||||
const outcomeRecord = {
|
||||
type: 'STOP_LOSS_OUTCOME',
|
||||
originalDecisionId: outcomeData.decisionId,
|
||||
actualOutcome: outcomeData.actualOutcome,
|
||||
timeToOutcome: outcomeData.timeToOutcome,
|
||||
pnlImpact: outcomeData.pnlImpact,
|
||||
wasCorrect: this.evaluateDecisionCorrectness(originalDecision, outcomeData),
|
||||
learningData: {
|
||||
originalDecision: originalDecision.decision,
|
||||
distanceFromSL: originalDecision.distanceFromSL,
|
||||
outcome: outcomeData.actualOutcome,
|
||||
profitability: outcomeData.pnlImpact > 0 ? 'PROFITABLE' : 'LOSS'
|
||||
},
|
||||
timestamp: new Date().toISOString()
|
||||
};
|
||||
|
||||
await prisma.ai_learning_data.create({
|
||||
data: {
|
||||
id: `sl_outcome_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`,
|
||||
userId: 'default-user',
|
||||
symbol: originalDecision.symbol,
|
||||
timeframe: 'OUTCOME',
|
||||
analysisData: JSON.stringify(outcomeRecord),
|
||||
marketConditions: originalRecord.marketConditions,
|
||||
confidenceScore: outcomeRecord.wasCorrect ? 75 : 25
|
||||
}
|
||||
});
|
||||
|
||||
await this.log(`✅ Outcome assessed for ${outcomeData.decisionId}: ${outcomeData.actualOutcome} (${outcomeRecord.wasCorrect ? 'CORRECT' : 'INCORRECT'})`);
|
||||
|
||||
// Update learning thresholds based on outcomes
|
||||
await this.updateThresholdsFromOutcome(originalDecision, outcomeRecord);
|
||||
|
||||
return true;
|
||||
} catch (error) {
|
||||
await this.log(`❌ Error assessing outcome: ${error.message}`);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Evaluate if the original decision was correct based on outcome
|
||||
*/
|
||||
evaluateDecisionCorrectness(originalDecision, outcome) {
|
||||
const decision = originalDecision.decision;
|
||||
const actualOutcome = outcome.actualOutcome;
|
||||
const pnlImpact = outcome.pnlImpact;
|
||||
|
||||
// Define what constitutes a "correct" decision
|
||||
if (decision === 'EMERGENCY_EXIT' && (actualOutcome === 'STOPPED_OUT' || pnlImpact < -50)) {
|
||||
return true; // Correctly identified emergency
|
||||
}
|
||||
|
||||
if (decision === 'HOLD_POSITION' && pnlImpact > 0) {
|
||||
return true; // Correctly held profitable position
|
||||
}
|
||||
|
||||
if (decision === 'ADJUST_STOP_LOSS' && actualOutcome === 'TAKE_PROFIT') {
|
||||
return true; // Adjustment led to profitable exit
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get smart recommendation based on learned patterns
|
||||
*/
|
||||
async getSmartRecommendation(requestData) {
|
||||
try {
|
||||
const { distanceFromSL, symbol, marketConditions } = requestData;
|
||||
|
||||
// Get historical data for similar situations
|
||||
const prisma = await getDB();
|
||||
const similarDecisions = await prisma.ai_learning_data.findMany({
|
||||
where: {
|
||||
symbol: symbol,
|
||||
analysisData: {
|
||||
string_contains: '"type":"STOP_LOSS_DECISION"'
|
||||
}
|
||||
},
|
||||
orderBy: { createdAt: 'desc' },
|
||||
take: 20
|
||||
});
|
||||
|
||||
// Analyze patterns from similar situations
|
||||
let recommendation = this.getBaseRecommendation(distanceFromSL);
|
||||
|
||||
if (similarDecisions.length >= 3) {
|
||||
const learnedRecommendation = await this.analyzePatterns(similarDecisions, distanceFromSL);
|
||||
if (learnedRecommendation) {
|
||||
recommendation = learnedRecommendation;
|
||||
}
|
||||
}
|
||||
|
||||
await this.log(`🎯 Smart recommendation for ${symbol} at ${distanceFromSL}%: ${recommendation.action}`);
|
||||
|
||||
return recommendation;
|
||||
} catch (error) {
|
||||
await this.log(`❌ Error getting smart recommendation: ${error.message}`);
|
||||
return this.getBaseRecommendation(distanceFromSL);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get base recommendation using current thresholds
|
||||
*/
|
||||
getBaseRecommendation(distanceFromSL) {
|
||||
if (distanceFromSL <= this.learningThresholds.emergency) {
|
||||
return {
|
||||
action: 'EMERGENCY_EXIT',
|
||||
confidence: 0.8,
|
||||
reasoning: `Very close to SL (${distanceFromSL}%), emergency exit recommended`
|
||||
};
|
||||
} else if (distanceFromSL <= this.learningThresholds.risk) {
|
||||
return {
|
||||
action: 'HIGH_ALERT',
|
||||
confidence: 0.7,
|
||||
reasoning: `Close to SL (${distanceFromSL}%), monitor closely`
|
||||
};
|
||||
} else if (distanceFromSL <= this.learningThresholds.mediumRisk) {
|
||||
return {
|
||||
action: 'MONITOR',
|
||||
confidence: 0.6,
|
||||
reasoning: `Moderate distance from SL (${distanceFromSL}%), continue monitoring`
|
||||
};
|
||||
} else {
|
||||
return {
|
||||
action: 'HOLD_POSITION',
|
||||
confidence: 0.5,
|
||||
reasoning: `Safe distance from SL (${distanceFromSL}%), maintain position`
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Analyze historical patterns to improve recommendations
|
||||
*/
|
||||
async analyzePatterns(decisions, currentDistance) {
|
||||
const outcomes = await this.getOutcomesForDecisions(decisions);
|
||||
|
||||
// Find decisions made at similar distances
|
||||
const similarDistanceDecisions = decisions.filter(d => {
|
||||
const data = JSON.parse(d.analysisData);
|
||||
const distance = data.distanceFromSL;
|
||||
return Math.abs(distance - currentDistance) <= 1.0; // Within 1%
|
||||
});
|
||||
|
||||
if (similarDistanceDecisions.length < 2) {
|
||||
return null; // Not enough similar data
|
||||
}
|
||||
|
||||
// Analyze success rate of different actions at this distance
|
||||
const actionSuccess = {};
|
||||
|
||||
for (const decision of similarDistanceDecisions) {
|
||||
const decisionData = JSON.parse(decision.analysisData);
|
||||
const action = decisionData.decision;
|
||||
const outcome = outcomes.find(o => o.originalDecisionId === decision.id);
|
||||
|
||||
if (outcome) {
|
||||
if (!actionSuccess[action]) {
|
||||
actionSuccess[action] = { total: 0, successful: 0 };
|
||||
}
|
||||
actionSuccess[action].total++;
|
||||
if (outcome.wasCorrect) {
|
||||
actionSuccess[action].successful++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Find the action with highest success rate
|
||||
let bestAction = null;
|
||||
let bestSuccessRate = 0;
|
||||
|
||||
for (const [action, stats] of Object.entries(actionSuccess)) {
|
||||
if (stats.total >= 2) { // Need at least 2 samples
|
||||
const successRate = stats.successful / stats.total;
|
||||
if (successRate > bestSuccessRate) {
|
||||
bestSuccessRate = successRate;
|
||||
bestAction = action;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (bestAction && bestSuccessRate > 0.6) {
|
||||
return {
|
||||
action: bestAction,
|
||||
confidence: bestSuccessRate,
|
||||
reasoning: `Learned pattern: ${bestAction} successful ${Math.round(bestSuccessRate * 100)}% of time at this distance`
|
||||
};
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get outcomes for a set of decisions
|
||||
*/
|
||||
async getOutcomesForDecisions(decisions) {
|
||||
const prisma = await getDB();
|
||||
const decisionIds = decisions.map(d => d.id);
|
||||
|
||||
const outcomes = await prisma.ai_learning_data.findMany({
|
||||
where: {
|
||||
analysisData: {
|
||||
string_contains: '"type":"STOP_LOSS_OUTCOME"'
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
return outcomes.map(o => JSON.parse(o.analysisData))
|
||||
.filter(outcome => decisionIds.includes(outcome.originalDecisionId));
|
||||
}
|
||||
|
||||
/**
|
||||
* Update learning thresholds based on outcome data
|
||||
*/
|
||||
async updateThresholdsFromOutcome(originalDecision, outcome) {
|
||||
// Simple threshold adjustment based on outcomes
|
||||
const distance = originalDecision.distanceFromSL;
|
||||
const wasCorrect = outcome.wasCorrect;
|
||||
|
||||
if (!wasCorrect) {
|
||||
// If decision was wrong, adjust thresholds slightly
|
||||
if (originalDecision.decision === 'HOLD_POSITION' && outcome.actualOutcome === 'STOPPED_OUT') {
|
||||
// We should have exited earlier - make thresholds more conservative
|
||||
this.learningThresholds.emergency = Math.min(2.0, this.learningThresholds.emergency + 0.1);
|
||||
this.learningThresholds.risk = Math.min(3.0, this.learningThresholds.risk + 0.1);
|
||||
}
|
||||
}
|
||||
|
||||
await this.log(`🔧 Thresholds updated: emergency=${this.learningThresholds.emergency}, risk=${this.learningThresholds.risk}`);
|
||||
}
|
||||
|
||||
/**
|
||||
* Get current learning status and statistics
|
||||
*/
|
||||
async analyzeDecisionPatterns() {
|
||||
try {
|
||||
const prisma = await getDB();
|
||||
|
||||
// Get recent decisions and outcomes
|
||||
const decisions = await prisma.ai_learning_data.findMany({
|
||||
where: {
|
||||
analysisData: {
|
||||
string_contains: '"type":"STOP_LOSS_DECISION"'
|
||||
},
|
||||
createdAt: {
|
||||
gte: new Date(Date.now() - 7 * 24 * 60 * 60 * 1000) // Last 7 days
|
||||
}
|
||||
},
|
||||
orderBy: { createdAt: 'desc' }
|
||||
});
|
||||
|
||||
const outcomes = await prisma.ai_learning_data.findMany({
|
||||
where: {
|
||||
analysisData: {
|
||||
string_contains: '"type":"STOP_LOSS_OUTCOME"'
|
||||
},
|
||||
createdAt: {
|
||||
gte: new Date(Date.now() - 7 * 24 * 60 * 60 * 1000) // Last 7 days
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Analyze patterns
|
||||
const patterns = {
|
||||
totalDecisions: decisions.length,
|
||||
totalOutcomes: outcomes.length,
|
||||
successfulDecisions: outcomes.filter(o => JSON.parse(o.analysisData).wasCorrect).length,
|
||||
successRate: outcomes.length > 0 ? outcomes.filter(o => JSON.parse(o.analysisData).wasCorrect).length / outcomes.length : 0,
|
||||
learnedThresholds: this.learningThresholds
|
||||
};
|
||||
|
||||
return patterns;
|
||||
} catch (error) {
|
||||
await this.log(`❌ Error analyzing patterns: ${error.message}`);
|
||||
return {
|
||||
totalDecisions: 0,
|
||||
totalOutcomes: 0,
|
||||
successfulDecisions: 0,
|
||||
successRate: 0,
|
||||
learnedThresholds: this.learningThresholds
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get learning status
|
||||
*/
|
||||
async getLearningStatus() {
|
||||
try {
|
||||
const prisma = await getDB();
|
||||
const totalDecisions = await prisma.ai_learning_data.count({
|
||||
where: {
|
||||
analysisData: {
|
||||
string_contains: '"type":"STOP_LOSS_DECISION"'
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
const recentDecisions = await prisma.ai_learning_data.count({
|
||||
where: {
|
||||
analysisData: {
|
||||
string_contains: '"type":"STOP_LOSS_DECISION"'
|
||||
},
|
||||
createdAt: {
|
||||
gte: new Date(Date.now() - 24 * 60 * 60 * 1000) // Last 24 hours
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
return {
|
||||
totalDecisions,
|
||||
recentDecisions,
|
||||
thresholds: this.learningThresholds,
|
||||
isActive: totalDecisions > 0
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
await this.log(`❌ Error getting learning status: ${error.message}`);
|
||||
return {
|
||||
totalDecisions: 0,
|
||||
recentDecisions: 0,
|
||||
thresholds: this.learningThresholds,
|
||||
isActive: false
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate comprehensive learning report
|
||||
* Compatible implementation for enhanced-autonomous-risk-manager
|
||||
*/
|
||||
async generateLearningReport() {
|
||||
try {
|
||||
const status = await this.getLearningStatus();
|
||||
const patterns = await this.analyzeDecisionPatterns();
|
||||
|
||||
// Calculate system confidence based on decisions made
|
||||
const systemConfidence = this.calculateSystemConfidence(status.totalDecisions, status.recentDecisions, patterns.successRate);
|
||||
|
||||
const report = {
|
||||
timestamp: new Date().toISOString(),
|
||||
summary: {
|
||||
totalDecisions: status.totalDecisions,
|
||||
recentDecisions: status.recentDecisions,
|
||||
successfulPatterns: patterns.successfulDecisions,
|
||||
learningThresholds: this.learningThresholds,
|
||||
systemConfidence: systemConfidence,
|
||||
isActive: status.isActive,
|
||||
successRate: patterns.successRate
|
||||
},
|
||||
insights: {
|
||||
emergencyThreshold: this.learningThresholds.emergency,
|
||||
riskThreshold: this.learningThresholds.risk,
|
||||
mediumRiskThreshold: this.learningThresholds.mediumRisk,
|
||||
confidenceLevel: systemConfidence > 0.7 ? 'HIGH' : systemConfidence > 0.4 ? 'MEDIUM' : 'LOW',
|
||||
totalOutcomes: patterns.totalOutcomes,
|
||||
decisionAccuracy: patterns.successRate
|
||||
},
|
||||
recommendations: this.generateSystemRecommendations(status, patterns)
|
||||
};
|
||||
|
||||
await this.log(`📊 Learning report generated: ${report.summary.totalDecisions} decisions, ${(systemConfidence * 100).toFixed(1)}% confidence, ${(patterns.successRate * 100).toFixed(1)}% success rate`);
|
||||
|
||||
return report;
|
||||
} catch (error) {
|
||||
await this.log(`❌ Error generating learning report: ${error.message}`);
|
||||
return {
|
||||
timestamp: new Date().toISOString(),
|
||||
summary: {
|
||||
totalDecisions: 0,
|
||||
recentDecisions: 0,
|
||||
systemConfidence: 0.0,
|
||||
isActive: false
|
||||
},
|
||||
error: error.message
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate system confidence based on learning data
|
||||
*/
|
||||
calculateSystemConfidence(totalDecisions, recentDecisions, successRate = 0) {
|
||||
if (totalDecisions < 5) return 0.3; // Low confidence with insufficient data
|
||||
if (totalDecisions < 20) return 0.4 + (successRate * 0.2); // Medium-low confidence boosted by success
|
||||
if (totalDecisions < 50) return 0.6 + (successRate * 0.2); // Medium confidence boosted by success
|
||||
|
||||
// High confidence with lots of data, scaled by recent activity and success rate
|
||||
const recentActivityFactor = Math.min(1.0, recentDecisions / 10);
|
||||
const successFactor = successRate || 0.5; // Default to neutral if no success data
|
||||
return Math.min(0.95, 0.7 + (recentActivityFactor * 0.1) + (successFactor * 0.15)); // Cap at 95%
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate system recommendations based on learning status
|
||||
*/
|
||||
generateSystemRecommendations(status, patterns) {
|
||||
const recommendations = [];
|
||||
|
||||
if (status.totalDecisions < 10) {
|
||||
recommendations.push({
|
||||
type: 'DATA_COLLECTION',
|
||||
message: 'Need more decision data for reliable learning',
|
||||
priority: 'HIGH'
|
||||
});
|
||||
}
|
||||
|
||||
if (status.recentDecisions < 3) {
|
||||
recommendations.push({
|
||||
type: 'ACTIVITY_LOW',
|
||||
message: 'Recent trading activity is low - learning may be stale',
|
||||
priority: 'MEDIUM'
|
||||
});
|
||||
}
|
||||
|
||||
if (patterns && patterns.successRate < 0.4 && patterns.totalOutcomes >= 5) {
|
||||
recommendations.push({
|
||||
type: 'THRESHOLD_ADJUSTMENT',
|
||||
message: 'Low success rate detected - consider adjusting decision thresholds',
|
||||
priority: 'HIGH'
|
||||
});
|
||||
}
|
||||
|
||||
if (status.totalDecisions >= 20 && patterns && patterns.successRate > 0.6) {
|
||||
recommendations.push({
|
||||
type: 'SYSTEM_PERFORMING',
|
||||
message: 'System learning effectively with good success rate',
|
||||
priority: 'LOW'
|
||||
});
|
||||
}
|
||||
|
||||
if (status.totalDecisions >= 50) {
|
||||
recommendations.push({
|
||||
type: 'OPTIMIZATION_READY',
|
||||
message: 'Sufficient data available for advanced threshold optimization',
|
||||
priority: 'LOW'
|
||||
});
|
||||
}
|
||||
|
||||
return recommendations;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = SimplifiedStopLossLearner;
|
||||
@@ -81,25 +81,13 @@ async function monitor() {
|
||||
statusText = 'CAUTION - MONITOR';
|
||||
}
|
||||
|
||||
console.log('🤖 AI AUTONOMOUS RISK MANAGEMENT:');
|
||||
console.log('🛡️ STOP LOSS PROTECTION:');
|
||||
console.log(` Stop Loss: $${sl.stopLossPrice.toFixed(4)} (${sl.distancePercent}% away)`);
|
||||
console.log(` Status: ${statusIcon} ${statusText}`);
|
||||
|
||||
// AI Action Display
|
||||
const aiActions = {
|
||||
'DANGER - VERY CLOSE': '🚨 AI: Executing emergency analysis',
|
||||
'WARNING - APPROACHING': '⚠️ AI: Reviewing position for adjustments',
|
||||
'CAUTION - MONITOR': '🟡 AI: Enhanced monitoring active',
|
||||
'SAFE': '✅ AI: Scanning for new opportunities'
|
||||
};
|
||||
|
||||
const aiAction = aiActions[statusText] || '🤖 AI: Autonomous operation';
|
||||
console.log(` AI Action: ${aiAction}`);
|
||||
console.log(` Beach Mode: ${'🏖️ ACTIVE - No manual intervention needed'}`);
|
||||
console.log(` Risk Level: ${positionData.monitor.riskLevel}`);
|
||||
|
||||
if (sl.isNear) {
|
||||
console.log('\n🤖 AI AUTONOMOUS ACTION: Risk management protocols activated!');
|
||||
console.log(' 🏖️ Relax - Your AI is handling this autonomously');
|
||||
console.log('\n🚨 ALERT: PRICE NEAR STOP LOSS! 🚨');
|
||||
}
|
||||
console.log('');
|
||||
|
||||
|
||||
Reference in New Issue
Block a user