diff --git a/app/safe-paper-trading/page.js.backup b/app/safe-paper-trading/page.js.backup deleted file mode 100644 index bdaf576..0000000 --- a/app/safe-paper-trading/page.js.backup +++ /dev/null @@ -1,1785 +0,0 @@ -'use client' - -import { useState, useEffect } from 'react' - -// Available timeframes for analysis (matching automation-v2 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' }, -] - -// Intelligent delay mapping based on timeframe (optimize ChatGPT budget) -const ANALYSIS_DELAYS = { - '5': 5 * 60 * 1000, // 5m chart: analyze every 5 minutes - '15': 15 * 60 * 1000, // 15m chart: analyze every 15 minutes - '30': 30 * 60 * 1000, // 30m chart: analyze every 30 minutes - '60': 60 * 60 * 1000, // 1h chart: analyze every 1 hour - '120': 2 * 60 * 60 * 1000, // 2h chart: analyze every 2 hours - '240': 4 * 60 * 60 * 1000, // 4h chart: analyze every 4 hours - 'D': 24 * 60 * 60 * 1000, // 1d chart: analyze once per day -} - -export default function SafePaperTradingPage() { - const [symbol, setSymbol] = useState('SOLUSD') - const [selectedTimeframes, setSelectedTimeframes] = useState(['60']) // Default to 1h - const [loading, setLoading] = useState(false) - const [currentAnalysis, setCurrentAnalysis] = useState(null) - const [paperBalance, setPaperBalance] = useState(1000) - const [paperTrades, setPaperTrades] = useState([]) - const [analysisHistory, setAnalysisHistory] = useState([]) - const [error, setError] = useState(null) - const [learningInsights, setLearningInsights] = useState(null) - const [showDetailedAnalysis, setShowDetailedAnalysis] = useState(false) - const [continuousLearning, setContinuousLearning] = useState(false) - const [autoExecuteTrades, setAutoExecuteTrades] = useState(false) // New: Auto-execute trades based on AI recommendations - const [learningInterval, setLearningInterval] = useState(null) - const [lastAnalysisTime, setLastAnalysisTime] = useState(null) - const [nextAnalysisTime, setNextAnalysisTime] = useState(null) - const [countdownTimer, setCountdownTimer] = useState(null) - const [timeRemaining, setTimeRemaining] = useState(0) - - // Load persisted analysis data on component mount - useEffect(() => { - const loadPersistedData = () => { - try { - const savedAnalysis = localStorage.getItem('safePaperTrading_currentAnalysis') - const savedTrades = localStorage.getItem('safePaperTrading_paperTrades') - const savedBalance = localStorage.getItem('safePaperTrading_paperBalance') - const savedHistory = localStorage.getItem('safePaperTrading_analysisHistory') - const savedLearningInsights = localStorage.getItem('safePaperTrading_learningInsights') - const savedContinuousLearning = localStorage.getItem('safePaperTrading_continuousLearning') - const savedAutoExecute = localStorage.getItem('safePaperTrading_autoExecute') - - if (savedAnalysis) { - const parsedAnalysis = JSON.parse(savedAnalysis) - // Check if the saved analysis is stale (older than 2 hours) - const analysisAge = Date.now() - new Date(parsedAnalysis.timestamp).getTime() - const twoHours = 2 * 60 * 60 * 1000 - - if (analysisAge > twoHours) { - console.log('๐Ÿ“‚ Found stale analysis data (>2 hours old), will fetch fresh data') - localStorage.removeItem('safePaperTrading_currentAnalysis') - // Trigger fresh analysis after component loads - setTimeout(() => { - console.log('๐Ÿ”„ Fetching fresh analysis to replace stale data') - runSafeAnalysis(false) - }, 5000) - } else { - setCurrentAnalysis(parsedAnalysis) - console.log('๐Ÿ“‚ Restored recent analysis from localStorage') - } - } else { - // No saved analysis, fetch fresh data - setTimeout(() => { - console.log('๐Ÿ”„ No saved analysis found, fetching fresh data') - runSafeAnalysis(false) - }, 3000) - } - - if (savedTrades) { - const parsedTrades = JSON.parse(savedTrades) - setPaperTrades(parsedTrades) - console.log(`๐Ÿ“‚ Restored ${parsedTrades.length} paper trades`) - } - - if (savedBalance) { - const parsedBalance = parseFloat(savedBalance) - setPaperBalance(parsedBalance) - console.log(`๐Ÿ“‚ Restored paper balance: $${parsedBalance}`) - } - - if (savedHistory) { - const parsedHistory = JSON.parse(savedHistory) - setAnalysisHistory(parsedHistory) - console.log(`๐Ÿ“‚ Restored ${parsedHistory.length} analysis history entries`) - } - - if (savedLearningInsights) { - const parsedInsights = JSON.parse(savedLearningInsights) - setLearningInsights(parsedInsights) - console.log('๐Ÿ“‚ Restored learning insights from localStorage') - } - - if (savedContinuousLearning === 'true') { - console.log('๐Ÿ“‚ Found continuous learning was active - restarting...') - setContinuousLearning(true) - // Restart continuous learning after a short delay to ensure component is ready - setTimeout(() => { - console.log('๏ฟฝ Restarting continuous learning from localStorage') - startContinuousLearning() - }, 3000) // Increased delay to ensure everything is loaded - } - } catch (error) { - console.error('โš ๏ธ Error loading persisted data:', error) - // Clear corrupted data - localStorage.removeItem('safePaperTrading_currentAnalysis') - localStorage.removeItem('safePaperTrading_paperTrades') - localStorage.removeItem('safePaperTrading_paperBalance') - localStorage.removeItem('safePaperTrading_analysisHistory') - localStorage.removeItem('safePaperTrading_learningInsights') - localStorage.removeItem('safePaperTrading_continuousLearning') - } - } - - loadPersistedData() - - // Load auto-execute setting - try { - const savedAutoExecute = localStorage.getItem('safePaperTrading_autoExecute') - if (savedAutoExecute === 'true') { - console.log('๐Ÿ“‚ Found auto-execute was enabled - restoring...') - setAutoExecuteTrades(true) - } - } catch (error) { - console.error('โš ๏ธ Error loading auto-execute setting:', error) - } - - // Check if continuous learning should be active - const checkContinuousLearningState = () => { - try { - const savedContinuousLearning = localStorage.getItem('safePaperTrading_continuousLearning') - console.log('๐Ÿ” Checking continuous learning state:', savedContinuousLearning) - if (savedContinuousLearning === 'true') { - console.log('๐Ÿ”„ Restoring continuous learning state...') - setContinuousLearning(true) - setTimeout(() => { - console.log('๐ŸŽ“ Starting continuous learning from restored state') - startContinuousLearning() - }, 2000) - } - } catch (error) { - console.error('โš ๏ธ Error checking continuous learning state:', error) - } - } - - // Check state after a short delay to ensure everything is loaded - setTimeout(checkContinuousLearningState, 1000) - }, []) - - // Persist analysis data whenever it changes - useEffect(() => { - if (currentAnalysis) { - try { - localStorage.setItem('safePaperTrading_currentAnalysis', JSON.stringify(currentAnalysis)) - console.log('๐Ÿ’พ Persisted current analysis to localStorage') - } catch (error) { - console.error('โš ๏ธ Error persisting current analysis:', error) - } - } - }, [currentAnalysis]) - - useEffect(() => { - if (paperTrades.length >= 0) { // Always persist, even empty array - try { - localStorage.setItem('safePaperTrading_paperTrades', JSON.stringify(paperTrades)) - console.log(`๐Ÿ’พ Persisted ${paperTrades.length} paper trades`) - } catch (error) { - console.error('โš ๏ธ Error persisting paper trades:', error) - } - } - }, [paperTrades]) - - useEffect(() => { - try { - localStorage.setItem('safePaperTrading_paperBalance', paperBalance.toString()) - console.log(`๐Ÿ’พ Persisted paper balance: $${paperBalance}`) - } catch (error) { - console.error('โš ๏ธ Error persisting paper balance:', error) - } - }, [paperBalance]) - - useEffect(() => { - if (learningInsights) { - try { - localStorage.setItem('safePaperTrading_learningInsights', JSON.stringify(learningInsights)) - console.log('๐Ÿ’พ Persisted learning insights to localStorage') - } catch (error) { - console.error('โš ๏ธ Error persisting learning insights:', error) - } - } - }, [learningInsights]) - - // Persist continuous learning state - useEffect(() => { - try { - localStorage.setItem('safePaperTrading_continuousLearning', continuousLearning.toString()) - console.log(`๐Ÿ’พ Persisted continuous learning state: ${continuousLearning}`) - } catch (error) { - console.error('โš ๏ธ Error persisting continuous learning state:', error) - } - }, [continuousLearning]) - - // Persist auto-execute setting - useEffect(() => { - try { - localStorage.setItem('safePaperTrading_autoExecute', autoExecuteTrades.toString()) - console.log(`๐Ÿ’พ Persisted auto-execute setting: ${autoExecuteTrades}`) - } catch (error) { - console.error('โš ๏ธ Error persisting auto-execute setting:', error) - } - }, [autoExecuteTrades]) - - // Live countdown timer for continuous learning - useEffect(() => { - if (continuousLearning && nextAnalysisTime) { - // Clear any existing countdown timer - if (countdownTimer) { - clearInterval(countdownTimer) - } - - // Create new countdown timer that updates every second - const countdown = setInterval(() => { - const remaining = nextAnalysisTime - Date.now() - if (remaining <= 0) { - setTimeRemaining(0) - } else { - setTimeRemaining(remaining) - } - }, 1000) - - setCountdownTimer(countdown) - - // Initial calculation - const remaining = nextAnalysisTime - Date.now() - setTimeRemaining(remaining > 0 ? remaining : 0) - - return () => { - if (countdown) { - clearInterval(countdown) - } - } - } else { - // Clear countdown when not in continuous learning - if (countdownTimer) { - clearInterval(countdownTimer) - setCountdownTimer(null) - } - setTimeRemaining(0) - } - }, [continuousLearning, nextAnalysisTime]) - - // Clean up countdown on unmount - useEffect(() => { - return () => { - if (countdownTimer) { - clearInterval(countdownTimer) - } - } - }, []) - - // Health check for continuous learning - ensure it's actually running - useEffect(() => { - if (continuousLearning) { - const healthCheck = setInterval(() => { - if (!learningInterval) { - console.warn('โš ๏ธ HEALTH CHECK: Continuous learning is ON but interval is missing - restarting...') - restartContinuousLearning() - } else { - console.log('โœ… HEALTH CHECK: Continuous learning interval is active') - } - }, 5 * 60 * 1000) // Check every 5 minutes - - return () => clearInterval(healthCheck) - } - }, [continuousLearning, learningInterval]) - - // SAFETY: Only these timeframes allowed in paper trading - const safeTimeframes = timeframes.map(tf => ({ - ...tf, - riskLevel: tf.value === '5' || tf.value === '15' ? 'HIGH' : - tf.value === '30' || tf.value === '60' ? 'MEDIUM' : 'LOW' - })) - - const settings = { - riskPerTrade: 1.0, - paperMode: true, // ALWAYS true - cannot be changed - isolatedMode: true // ALWAYS true - completely isolated - } - - const toggleTimeframe = (timeframe) => { - setSelectedTimeframes(prev => - prev.includes(timeframe) - ? prev.filter(tf => tf !== timeframe) - : [...prev, timeframe] - ) - } - - const calculateOptimalDelay = () => { - if (selectedTimeframes.length === 0) return 60 * 60 * 1000 // Default 1 hour - - // Use the shortest timeframe as base, but not too frequent for budget optimization - const shortestTf = selectedTimeframes.reduce((shortest, current) => { - const currentDelay = ANALYSIS_DELAYS[current] || 60 * 60 * 1000 - const shortestDelay = ANALYSIS_DELAYS[shortest] || 60 * 60 * 1000 - return currentDelay < shortestDelay ? current : shortest - }) - - // Minimum 10 minutes delay to protect ChatGPT budget - return Math.max(ANALYSIS_DELAYS[shortestTf] || 60 * 60 * 1000, 10 * 60 * 1000) - } - - // Format countdown time for display - const formatCountdown = (milliseconds) => { - if (milliseconds <= 0) return 'Running soon...' - - const totalSeconds = Math.ceil(milliseconds / 1000) - const hours = Math.floor(totalSeconds / 3600) - const minutes = Math.floor((totalSeconds % 3600) / 60) - const seconds = totalSeconds % 60 - - if (hours > 0) { - return `${hours}h ${minutes}m ${seconds}s` - } else if (minutes > 0) { - return `${minutes}m ${seconds}s` - } else { - return `${seconds}s` - } - } - - const startContinuousLearning = () => { - if (learningInterval) { - clearInterval(learningInterval) - } - - const delay = calculateOptimalDelay() - console.log(`๐ŸŽ“ Starting continuous learning with ${delay / 60000} minute intervals`) - - // Run first analysis immediately for faster feedback - setTimeout(async () => { - console.log('๐Ÿ”„ IMMEDIATE: Running first continuous learning analysis') - console.log('๐Ÿ“š Running immediate learning analysis (paper trading mode)') - try { - await runSafeAnalysis(true) // Mark as continuous learning - } catch (error) { - console.error('โŒ Error in immediate analysis:', error) - } - }, 5000) // 5 seconds delay for immediate feedback - - const interval = setInterval(async () => { - console.log('๐Ÿ”„ Continuous learning cycle triggered') - console.log(`๐Ÿ“Š Current time: ${new Date().toLocaleTimeString()}`) - - // For safe paper trading, always run analysis regardless of positions - // (since it's completely isolated and for learning purposes) - console.log('๐Ÿ“š Running scheduled learning analysis (paper trading mode)') - try { - await runSafeAnalysis(true) // Mark as continuous learning - } catch (error) { - console.error('โŒ Error in continuous learning cycle:', error) - // Set next time even if there's an error to prevent stopping - setNextAnalysisTime(Date.now() + delay) - } - }, delay) - - setLearningInterval(interval) - setNextAnalysisTime(Date.now() + 5000) // Show immediate next time (5 seconds) - - console.log(`๐ŸŽ“ Continuous learning started - next analysis in 5 seconds, then every ${delay / 60000} minutes`) - } - - const stopContinuousLearning = () => { - if (learningInterval) { - clearInterval(learningInterval) - setLearningInterval(null) - setNextAnalysisTime(null) - console.log('๐Ÿ›‘ Continuous learning stopped') - } - } - - const restartContinuousLearning = () => { - console.log('๐Ÿ”„ Restarting continuous learning...') - stopContinuousLearning() - // Small delay to ensure cleanup - setTimeout(() => { - startContinuousLearning() - console.log('โœ… Continuous learning restarted successfully') - }, 1000) - } - - useEffect(() => { - // Load paper trading data from localStorage - const savedTrades = localStorage.getItem('safePaperTrades') - const savedBalance = localStorage.getItem('safePaperBalance') - - if (savedTrades) { - setPaperTrades(JSON.parse(savedTrades)) - } - if (savedBalance) { - setPaperBalance(parseFloat(savedBalance)) - } - - // Fetch AI learning status - fetchLearningStatus() - - // Cleanup continuous learning on unmount - return () => { - if (learningInterval) { - clearInterval(learningInterval) - } - } - }, []) - - // Update continuous learning when timeframes change - useEffect(() => { - if (continuousLearning) { - stopContinuousLearning() - startContinuousLearning() - } - }, [selectedTimeframes]) - - // Save to localStorage whenever data changes - useEffect(() => { - localStorage.setItem('safePaperTrades', JSON.stringify(paperTrades)) - localStorage.setItem('safePaperBalance', paperBalance.toString()) - }, [paperTrades, paperBalance]) - - const runSafeAnalysis = async (isContinuous = false) => { - console.log(`๐Ÿ”„ ${isContinuous ? 'CONTINUOUS LEARNING' : 'BUTTON CLICKED'}: Starting safe analysis...`) - console.log(`๐ŸŽฏ Analysis Type: ${isContinuous ? 'CONTINUOUS LEARNING' : 'MANUAL'} for ${symbol}`) - console.log(`โฐ Current time: ${new Date().toLocaleString()}`) - console.log(`๐Ÿ“Š Selected timeframes: ${selectedTimeframes.join(', ')}`) - - if (isContinuous) { - console.log(`๐ŸŽ“ This is a CONTINUOUS LEARNING cycle - automatic analysis`) - } - console.log(`๐Ÿ“Š Selected timeframes: ${selectedTimeframes.join(', ')}`) - - setLoading(true) - setError(null) - setLastAnalysisTime(Date.now()) - - try { - console.log('๐Ÿ“„ SAFE PAPER TRADING: Starting isolated analysis...') - console.log('๐Ÿ“‹ Request data:', { - symbol, - selectedTimeframes, - mode: 'PAPER_ONLY', - paperTrading: true, - isolatedMode: true, - isContinuous - }) - - console.log(`๐ŸŒ Making API call to /api/paper-trading-safe...`) - - // SAFETY: Only call the isolated paper trading API - const response = await fetch('/api/paper-trading-safe', { - method: 'POST', - headers: { 'Content-Type': 'application/json' }, - body: JSON.stringify({ - symbol, - selectedTimeframes, - mode: 'PAPER_ONLY', // REQUIRED for safety - paperTrading: true, - isolatedMode: true, - isContinuous - }) - }) - - console.log('๐Ÿ“ก Response status:', response.status) - console.log('๐Ÿ“ก Response ok:', response.ok) - - if (!response.ok) { - const errorText = await response.text() - console.error('โŒ Response error:', errorText) - throw new Error(`Analysis failed: ${response.status} - ${errorText}`) - } - - const result = await response.json() - console.log('๐Ÿ“Š Full API result:', result) - - if (!result.success) { - throw new Error(result.error || 'Analysis failed') - } - - console.log('โœ… SAFE ANALYSIS COMPLETE:', result.analysis.recommendation) - - const analysisData = { - ...result.analysis, - timeframes: selectedTimeframes, - analysisType: isContinuous ? 'CONTINUOUS_LEARNING' : 'MANUAL' - } - - setCurrentAnalysis(analysisData) - - // Add to analysis history with timestamp - const historyEntry = { - ...analysisData, - timestamp: new Date().toISOString(), - symbol: symbol, - timeframes: selectedTimeframes, - analysisId: `analysis_${Date.now()}_${Math.random().toString(36).substr(2, 9)}` - } - - // Keep only last 10 analyses in history - setAnalysisHistory(prev => { - const updated = [historyEntry, ...prev].slice(0, 10) - try { - localStorage.setItem('safePaperTrading_analysisHistory', JSON.stringify(updated)) - console.log(`๐Ÿ’พ Persisted ${updated.length} analysis history entries`) - } catch (error) { - console.error('โš ๏ธ Error persisting analysis history:', error) - } - return updated - }) - - // Update next analysis time for both manual and continuous learning - if (continuousLearning) { - const delay = calculateOptimalDelay() - const nextTime = Date.now() + delay - setNextAnalysisTime(nextTime) - console.log(`โฐ Next analysis scheduled for: ${new Date(nextTime).toLocaleString()}`) - console.log(`โฑ๏ธ Delay: ${delay / 60000} minutes`) - } - - // AUTO-EXECUTE TRADES: If auto-execute is enabled and we have a strong recommendation, execute the trade - console.log('๐Ÿ” Checking auto-execute conditions:', { - autoExecuteTrades, - recommendation: analysisData.recommendation, - confidence: analysisData.confidence, - hasAnalysisData: !!analysisData - }) - - if (autoExecuteTrades && analysisData.recommendation && analysisData.confidence >= 60) { - const recommendation = analysisData.recommendation.toUpperCase() - if (recommendation === 'BUY' || recommendation === 'SELL') { - console.log(`๐Ÿค– AUTO-EXECUTE: ${recommendation} signal with ${analysisData.confidence}% confidence`) - - // Wait a moment for the analysis to fully update, then execute - setTimeout(() => { - try { - executeSafePaperTrade(recommendation) - console.log(`โœ… AUTO-EXECUTED: ${recommendation} trade based on AI recommendation`) - } catch (error) { - console.error('โŒ Auto-execute error:', error) - } - }, 1000) - } else { - console.log(`๐Ÿ’ก AUTO-EXECUTE: HOLD signal (${recommendation}) - no trade executed`) - } - } else if (autoExecuteTrades) { - console.log(`๐Ÿ’ก AUTO-EXECUTE: Recommendation ${analysisData.recommendation} with ${analysisData.confidence}% confidence does not meet execution criteria (need BUY/SELL with โ‰ฅ60% confidence)`) - } else { - console.log(`๐Ÿ” AUTO-EXECUTE: Disabled or no valid recommendation`) - } - - } catch (error) { - console.error('โŒ Safe analysis error:', error) - console.error('โŒ Error stack:', error.stack) - setError(error.message) - } finally { - setLoading(false) - console.log('๐Ÿ Analysis complete, loading set to false') - } - } - - const executeSafePaperTrade = (signal) => { - if (!currentAnalysis) return - - const trade = { - id: Date.now(), - timestamp: new Date().toISOString(), - symbol: currentAnalysis.symbol, - timeframe: currentAnalysis.timeframe, - side: signal, - entryPrice: currentAnalysis.entry?.price || 100, - stopLoss: currentAnalysis.stopLoss?.price, - takeProfit: currentAnalysis.takeProfits?.tp1?.price, - confidence: currentAnalysis.confidence, - reasoning: currentAnalysis.reasoning, - status: 'OPEN', - momentumStatus: currentAnalysis.momentumStatus?.type, - entryQuality: currentAnalysis.entryQuality?.score, - paperMode: true, - safeMode: true - } - - // Calculate position size based on risk management - const riskAmount = paperBalance * (settings.riskPerTrade / 100) - const stopDistance = Math.abs(trade.entryPrice - (trade.stopLoss || trade.entryPrice * 0.95)) - trade.positionSize = Math.min(riskAmount / stopDistance, paperBalance * 0.1) - - setPaperTrades(prev => [trade, ...prev]) - - console.log('๐Ÿ“„ SAFE PAPER TRADE:', trade) - alert(`โœ… Safe Paper Trade: ${signal} ${trade.symbol} at $${trade.entryPrice}\\n๐Ÿ’ก This is completely isolated - no real money at risk!`) - } - - const closeSafePaperTrade = (tradeId, exitPrice) => { - setPaperTrades(prev => prev.map(trade => { - if (trade.id === tradeId && trade.status === 'OPEN') { - const pnl = trade.side === 'BUY' - ? (exitPrice - trade.entryPrice) * (trade.positionSize / trade.entryPrice) - : (trade.entryPrice - exitPrice) * (trade.positionSize / trade.entryPrice) - - const isWinner = pnl > 0 - setPaperBalance(current => current + pnl) - - // Update learning insights after closing trade - updateLearningInsights(trade, pnl, isWinner) - - return { - ...trade, - status: 'CLOSED', - exitPrice, - exitTime: new Date().toISOString(), - pnl, - isWinner, - exitReason: 'Manual close' - } - } - return trade - })) - } - - const updateLearningInsights = async (trade, pnl, isWinner) => { - try { - // Simulate AI learning from trade outcome - const learningData = { - tradeId: trade.id, - symbol: trade.symbol, - timeframe: trade.timeframe, - side: trade.side, - entryPrice: trade.entryPrice, - exitPrice: trade.exitPrice || null, - pnl, - isWinner, - confidence: trade.confidence, - reasoning: trade.reasoning, - timestamp: new Date().toISOString() - } - - console.log('๐Ÿง  AI Learning from trade outcome:', learningData) - - // Call learning API if available (simulated for paper trading) - setLearningInsights(prev => ({ - ...prev, - lastTrade: learningData, - totalTrades: (prev?.totalTrades || 0) + 1, - winners: isWinner ? (prev?.winners || 0) + 1 : (prev?.winners || 0), - learningPoints: [ - ...(prev?.learningPoints || []).slice(-4), // Keep last 4 - { - timestamp: new Date().toISOString(), - insight: generateLearningInsight(trade, pnl, isWinner), - impact: isWinner ? 'POSITIVE' : 'NEGATIVE', - confidence: trade.confidence - } - ] - })) - - } catch (error) { - console.error('โŒ Error updating learning insights:', error) - } - } - - const generateLearningInsight = (trade, pnl, isWinner) => { - const winRate = trade.confidence - if (isWinner) { - if (winRate >= 80) { - return `High confidence (${winRate}%) trade succeeded. Reinforcing pattern recognition for ${trade.symbol} ${trade.timeframe}m setups.` - } else { - return `Medium confidence (${winRate}%) trade worked out. Learning to trust similar setups more in future.` - } - } else { - if (winRate >= 80) { - return `High confidence (${winRate}%) trade failed. Reviewing analysis criteria to prevent overconfidence in similar setups.` - } else { - return `Medium confidence (${winRate}%) trade didn't work. Adjusting risk thresholds for ${trade.timeframe}m timeframe.` - } - } - } - - const fetchLearningStatus = async () => { - try { - // Fetch real AI learning status from the learning system - console.log('๐Ÿง  Fetching real AI learning status...') - - // Get real learning status from the AI learning system - const response = await fetch('/api/ai-learning-status', { - method: 'GET', - headers: { 'Content-Type': 'application/json' } - }) - - if (response.ok) { - const result = await response.json() - const realLearningData = result.data - console.log('โœ… Real learning status received:', realLearningData) - - setLearningInsights(prev => ({ - ...prev, - status: { - totalDecisions: realLearningData.totalDecisions || 0, - recentDecisions: realLearningData.totalOutcomes || 0, - successRate: (realLearningData.avgAccuracy || 0) / 100, - currentThresholds: { - emergency: 0.5, - risk: 1.5, - confidence: realLearningData.confidenceLevel || 75 - }, - nextTradeAdjustments: [ - realLearningData.recommendation || 'Learning system initializing...', - realLearningData.nextMilestone || 'Building pattern recognition', - `Phase: ${realLearningData.phase || 'INITIALIZATION'}` - ], - phase: realLearningData.phase, - winRate: realLearningData.winRate, - daysActive: realLearningData.daysActive - } - })) - } else { - // If learning API not available, create basic structure without mock data - console.log('โš ๏ธ Learning API not available, using basic structure') - setLearningInsights(prev => ({ - ...prev, - status: { - totalDecisions: 0, - recentDecisions: 0, - successRate: 0, - currentThresholds: { - emergency: 0.5, - risk: 1.5, - confidence: 75 - }, - nextTradeAdjustments: [ - 'Learning system initializing...', - 'Building pattern recognition database', - 'Preparing adaptive decision making' - ] - } - })) - } - - } catch (error) { - console.error('โŒ Error fetching learning status:', error) - // Minimal structure without any mock data - setLearningInsights(prev => ({ - ...prev, - status: { - totalDecisions: 0, - recentDecisions: 0, - successRate: 0, - currentThresholds: { - emergency: 0.5, - risk: 1.5, - confidence: 75 - }, - nextTradeAdjustments: ['Learning system offline'] - } - })) - } - } - - const resetSafePaperTrading = () => { - if (confirm('Reset all SAFE paper trading data? This cannot be undone.')) { - setPaperBalance(1000) - setPaperTrades([]) - setCurrentAnalysis(null) - localStorage.removeItem('safePaperTrades') - localStorage.removeItem('safePaperBalance') - } - } - - const openTrades = paperTrades.filter(t => t.status === 'OPEN') - const closedTrades = paperTrades.filter(t => t.status === 'CLOSED') - const totalPnL = closedTrades.reduce((sum, trade) => sum + (trade.pnl || 0), 0) - const winRate = closedTrades.length > 0 - ? Math.round((closedTrades.filter(t => (t.pnl || 0) > 0).length / closedTrades.length) * 100) - : 0 - - return ( -
- {/* SAFETY NOTICE */} -
-

๐Ÿ›ก๏ธ SAFE PAPER TRADING MODE

-
-
-

โœ… Completely isolated from real trading

-

โœ… No connection to live trading APIs

-

โœ… Zero risk of real money execution

-
-
-

๐Ÿง  AI learning through safe simulation

-

๐Ÿ“Š Real market analysis for practice

-

๐ŸŽฏ Perfect for confidence building

-
-
-
- - {/* AI LEARNING SETUP NOTICE */} - {!continuousLearning || !autoExecuteTrades ? ( -
-

๐Ÿค– Enable AI Learning from Virtual Trading

-
- How AI Learning Works: The system must execute virtual trades and track outcomes to learn patterns and improve predictions. -
-
-
-

Click "๐ŸŽ“ Start Learning" (Auto-enables trade execution)

-

- {continuousLearning ? 'โœ… Learning Active โ†’ Auto-execute Enabled' : 'โŒ Click "๐ŸŽ“ Start Learning" button below'} -

-
- ๐Ÿ’ก Auto-Execute: Automatically enabled with learning - AI needs trade outcomes to improve -
-
-
-
- Learning Process: AI analyzes โ†’ executes virtual trades โ†’ tracks outcomes โ†’ learns from results โ†’ improves predictions -
-
- ) : ( -
-

โœ… AI Learning System Active

-
-
- ๐ŸŽ“ Continuous Learning: ON -
-
- ๐Ÿค– Auto-Execute: ON -
-
- ๐Ÿ“ˆ Virtual Trading: Active -
-
-
- ๐Ÿง  AI will automatically execute virtual trades based on analysis and learn from outcomes to improve performance -
-
- )} - - {/* Header with Balance */} -
-
-
-

๐Ÿ“„ Safe Paper Trading

- {continuousLearning && ( -
-
-
- ๐ŸŽ“ Learning Active - {timeRemaining > 0 && ( -
- Next cycle: {formatCountdown(timeRemaining)} -
- )} -
-
- )} -
-
-
-

Virtual Balance

-

= 1000 ? 'text-green-400' : 'text-red-400'}`}> - ${paperBalance.toFixed(2)} -

-
-
-

Total P&L

-

= 0 ? 'text-green-400' : 'text-red-400'}`}> - ${totalPnL.toFixed(2)} -

-
-
-

Win Rate

-

{winRate}%

-
-
-
- - {/* Stats */} -
-
-

Open Trades

-

{openTrades.length}

-
-
-

Closed Trades

-

{closedTrades.length}

-
-
-

Wins

-

- {closedTrades.filter(t => (t.pnl || 0) > 0).length} -

-
-
-

Losses

-

- {closedTrades.filter(t => (t.pnl || 0) < 0).length} -

-
-
-
- - {/* Trading Controls */} -
-

๐ŸŽฏ Safe Analysis Controls

- -
-
- - -
-
- -
- - {continuousLearning && ( - - )} - -
- - {/* Auto-Execute Status - Auto-managed when learning is enabled */} -
-
-
- Auto-Execute Trades - - {continuousLearning - ? "๐Ÿค– Auto-managed with learning - executes trades โ‰ฅ60% confidence for AI feedback" - : "โš ๏ธ Enable Continuous Learning to activate auto-execute (required for AI learning)" - } - -
-
- {continuousLearning && autoExecuteTrades ? '๐Ÿค– AUTO-ON' : continuousLearning ? '๐ŸŸก READY' : '๏ฟฝ LOCKED'} -
- {autoExecuteTrades && continuousLearning && ( -
- โšก Paper trades will be executed automatically when AI recommends BUY/SELL with โ‰ฅ60% confidence -
- )} - {!continuousLearning && ( -
- ๐Ÿ’ก For AI Learning: Enable "Continuous Learning" + "Auto-Execute" so the AI can learn from virtual trade outcomes -
- )} -
-
-
- - {/* Multi-Timeframe Selection */} -
- - - {/* Trading Style Presets */} -
- - - - - -
- - {/* Individual Timeframe Toggles */} -
- {timeframes.map(tf => ( - - ))} -
- -
- Selected: {selectedTimeframes.length > 0 ? selectedTimeframes.map(tf => - timeframes.find(t => t.value === tf)?.label || tf - ).join(', ') : 'None'} - {selectedTimeframes.length > 0 && ( - - (Analysis delay: {Math.ceil(calculateOptimalDelay() / 60000)}m) - - )} -
-
- - - - {/* Force Analysis Button for Testing */} - {continuousLearning && ( - - )} - -
- โœ… Real market analysis โ€ข Paper trading only โ€ข Zero trading risk - {continuousLearning && ( - - ๐ŸŽ“ Continuous learning active - System automatically analyzes every {Math.ceil(calculateOptimalDelay() / 60000)} minutes - {timeRemaining > 0 && ( - - (Next: {formatCountdown(timeRemaining)}) - - )} - - )} -
- - {/* Clear Data Controls */} - {(currentAnalysis || paperTrades.length > 0 || analysisHistory.length > 0) && ( -
-
-
-

Analysis History: {analysisHistory.length} entries

-

Paper Trades: {paperTrades.length} trades

-
- -
-
- )} -
- - {/* Error Display */} - {error && ( -
-

โŒ Error: {error}

-
- )} - - {/* Current Analysis Results */} - {currentAnalysis && ( -
-

๐Ÿ“Š Safe Analysis Results

- -
-
-

Recommendation

-

- {currentAnalysis.recommendation} -

-
-
-

Confidence

-

{currentAnalysis.confidence}%

-
-
-

Timeframes

-

- {currentAnalysis.timeframes?.map(tf => - timeframes.find(t => t.value === tf)?.label || tf - ).join(', ') || 'Single'} -

-
-
- -
-
-

Entry Price

-

${currentAnalysis.entry?.price?.toFixed(2) || 'N/A'}

-
-
-

Analysis Mode

-

- {currentAnalysis.analysisMode === 'CONTINUOUS_LEARNING' ? '๐ŸŽ“ Learning' : '๐Ÿ‘ค Manual'} -

-
-
-

Primary Focus

-

- {currentAnalysis.primaryTimeframe ? - timeframes.find(t => t.value === currentAnalysis.primaryTimeframe)?.label || currentAnalysis.primaryTimeframe - : 'N/A'} -

-
-
- - {/* Action Buttons */} - {currentAnalysis.recommendation !== 'HOLD' && currentAnalysis.tradeDecision?.allowed && ( -
- - -
- )} - - {/* Analysis Details */} -
-

Analysis Reasoning:

- 
-              {typeof currentAnalysis.reasoning === 'string' 
-                ? currentAnalysis.reasoning 
-                : typeof currentAnalysis.reasoning === 'object' 
-                ? JSON.stringify(currentAnalysis.reasoning, null, 2)
-                : 'Analysis reasoning not available'}
-
-
- - {/* Toggle Detailed Analysis */} - -
- )} - - {/* Detailed Market Analysis Panel */} - {currentAnalysis && showDetailedAnalysis && ( -
-
-

- ๐Ÿง  Market Summary - {currentAnalysis.timeframes && currentAnalysis.timeframes.length > 1 && ( - - {currentAnalysis.timeframes.length} Timeframes - - )} -

-
- {currentAnalysis.analysisMode === 'CONTINUOUS_LEARNING' - ? 'Continuous learning analysis with multi-timeframe insights' - : 'Comprehensive multi-layout analysis with timeframe risk assessment and cross-layout insights' - } -
-
- -
- {/* Market Sentiment */} -
-

Market Sentiment

-

{currentAnalysis.marketSentiment || 'NEUTRAL'}

-
- - {/* Recommendation */} -
-

Recommendation

-

- {currentAnalysis.recommendation} -

-

{currentAnalysis.confidence}% confidence

-
- - {/* Resistance Levels */} -
-

Resistance Levels

-

- {currentAnalysis.keyLevels?.resistance?.join(', ') || - `$${(currentAnalysis.entry?.price * 1.02 || 164).toFixed(2)}, $${(currentAnalysis.entry?.price * 1.05 || 168).toFixed(2)}`} -

-
- - {/* Support Levels */} -
-

Support Levels

-

- {currentAnalysis.keyLevels?.support?.join(', ') || - `$${(currentAnalysis.entry?.price * 0.98 || 160).toFixed(2)}, $${(currentAnalysis.entry?.price * 0.95 || 156).toFixed(2)}`} -

-
-
- - {/* Trading Setup */} -
-

Trading Setup

- -
- {/* Entry Point */} -
-
- ๐ŸŽฏ - Entry Point -
-

${currentAnalysis.entry?.price?.toFixed(2) || 'N/A'}

-

- {typeof currentAnalysis.entry?.reasoning === 'string' - ? currentAnalysis.entry.reasoning - : typeof currentAnalysis.entry?.reasoning === 'object' - ? JSON.stringify(currentAnalysis.entry.reasoning) - : currentAnalysis.summary || 'Real market analysis entry point'} -

-
- - {/* Stop Loss */} -
-
- โญ• - Stop Loss -
-

${currentAnalysis.stopLoss?.price?.toFixed(2) || 'N/A'}

-

- {typeof currentAnalysis.stopLoss?.reasoning === 'string' - ? currentAnalysis.stopLoss.reasoning - : typeof currentAnalysis.stopLoss?.reasoning === 'object' - ? JSON.stringify(currentAnalysis.stopLoss.reasoning) - : 'Real market analysis stop loss level'} -

-
- - {/* Take Profit Targets */} -
-
- ๐Ÿ’Ž - Take Profit Targets -
-
-
- TP1: - ${currentAnalysis.takeProfits?.tp1?.price?.toFixed(2) || 'N/A'} -
- {currentAnalysis.takeProfits?.tp2 && ( -
- TP2: - ${currentAnalysis.takeProfits.tp2.price?.toFixed(2)} -
- )} -
-

- {typeof currentAnalysis.takeProfits?.reasoning === 'string' - ? currentAnalysis.takeProfits.reasoning - : typeof currentAnalysis.takeProfits?.reasoning === 'object' - ? JSON.stringify(currentAnalysis.takeProfits.reasoning) - : 'Real market analysis target levels'} -

-
-
-
- - {/* Risk Management */} -
-

Risk Management

- -
-
-
- Risk/Reward Ratio - - {currentAnalysis.riskToReward || 'N/A'} - -
- -
- โš ๏ธ - Confirmation Trigger -
-

- {typeof currentAnalysis.confirmationTrigger === 'string' - ? currentAnalysis.confirmationTrigger - : typeof currentAnalysis.confirmationTrigger === 'object' - ? JSON.stringify(currentAnalysis.confirmationTrigger) - : 'Real market confirmation signals from analysis'} -

-
- -
-
-
- Trend: - - {typeof currentAnalysis.trendAnalysis === 'object' - ? (currentAnalysis.trendAnalysis?.direction || 'Analyzing...') - : currentAnalysis.trendAnalysis || 'Analyzing...'} - -
-
- Momentum: - - {typeof currentAnalysis.momentumAnalysis === 'object' - ? (currentAnalysis.momentumAnalysis?.status || 'Analyzing...') - : currentAnalysis.momentumAnalysis || 'Analyzing...'} - -
-
- Volume: - - {typeof currentAnalysis.volumeAnalysis === 'object' - ? (currentAnalysis.volumeAnalysis?.trend || 'Analyzing...') - : currentAnalysis.volumeAnalysis || 'Analyzing...'} - -
-
- Timeframe Risk: - - {typeof currentAnalysis.timeframeRisk === 'object' - ? (currentAnalysis.timeframeRisk?.assessment || 'Medium') - : currentAnalysis.timeframeRisk || 'Medium'} - -
-
-
-
-
-
- )} - - {/* AI Learning Insights Panel */} - {learningInsights && ( -
-

- ๐Ÿง  AI Learning Insights - Real-time learning from trade outcomes -

- -
- {/* Learning Status */} -
-

Learning Status

-
-
- Total Decisions: - {learningInsights.status?.totalDecisions || 0} -
-
- Success Rate: - - {((learningInsights.status?.successRate || 0) * 100).toFixed(1)}% - -
-
- Paper Trades: - {learningInsights.totalTrades || 0} -
-
-
- - {/* Win/Loss Analysis */} -
-

Trade Outcome

- {learningInsights.lastTrade ? ( -
-
- {learningInsights.lastTrade.isWinner ? 'โœ…' : 'โŒ'} - - {learningInsights.lastTrade.isWinner ? 'WINNER' : 'LOSER'} - -
-
- Last: {learningInsights.lastTrade.symbol} ${learningInsights.lastTrade.pnl?.toFixed(2)} -
-
- Confidence: {learningInsights.lastTrade.confidence}% -
-
- ) : ( -

No trades yet

- )} -
- - {/* Current Adjustments */} -
-

AI Adjustments

-
- {learningInsights.status?.nextTradeAdjustments?.slice(0, 3).map((adjustment, index) => ( -
- โ€ข - {adjustment} -
- )) || ( -

Analyzing patterns...

- )} -
-
-
- - {/* Learning Reflection */} - {learningInsights.learningPoints && learningInsights.learningPoints.length > 0 && ( -
-

AI Reflection & Learning

-
- {learningInsights.learningPoints.slice(-3).map((point, index) => ( -
-
- - {point.impact === 'POSITIVE' ? '๐Ÿ“ˆ Positive Learning' : '๐Ÿ“‰ Learning from Loss'} - - - {new Date(point.timestamp).toLocaleTimeString()} - -
-

{point.insight}

-
- ))} -
-
- )} - - {/* What AI is Using for Next Trade */} -
-

๐Ÿ”ฎ AI Database for Next Trade

-
-
-
Current Thresholds:
-
-
- Emergency Distance: - {learningInsights.status?.currentThresholds?.emergency || 0.5}% -
-
- Risk Distance: - {learningInsights.status?.currentThresholds?.risk || 1.5}% -
-
- Min Confidence: - {learningInsights.status?.currentThresholds?.confidence || 75}% -
-
-
-
-
Pattern Recognition:
-
-
โ€ข {symbol} multi-timeframe: {learningInsights.status?.totalDecisions || 0} total decisions in database
-
โ€ข Success rate: {((learningInsights.status?.successRate || 0) * 100).toFixed(1)}%
-
โ€ข Learning phase: {learningInsights.status?.phase || 'INITIALIZATION'}
-
โ€ข Days active: {learningInsights.status?.daysActive || 0} days
- {currentAnalysis?.timeframes && currentAnalysis.timeframes.length > 1 && ( -
โ€ข Current analysis: {currentAnalysis.timeframes.map(tf => - timeframes.find(t => t.value === tf)?.label || tf - ).join(' + ')} confluence
- )} -
-
-
-
-
- )} - - {/* Open Trades */} - {openTrades.length > 0 && ( -
-

๐Ÿ“ˆ Open Paper Positions

-
- {openTrades.map(trade => ( -
-
-
- - {trade.side} - - {trade.symbol} - ${trade.entryPrice} - Size: ${trade.positionSize?.toFixed(2)} -
-
- Entry: {new Date(trade.timestamp).toLocaleString()} | - Confidence: {trade.confidence}% -
-
- -
- ))} -
-
- )} - - {/* Trade History */} - {closedTrades.length > 0 && ( -
-
-

๐Ÿ“ˆ Safe Paper Trade History

- -
-
- {closedTrades.slice(0, 20).map(trade => ( -
= 0 ? 'bg-green-900/20 border-green-500' : 'bg-red-900/20 border-red-500' - }`}> -
-
- - {trade.side} - - {trade.symbol} - ${trade.entryPrice} โ†’ ${trade.exitPrice} - = 0 ? 'text-green-400' : 'text-red-400' - }`}> - ${(trade.pnl || 0).toFixed(2)} - - - {trade.isWinner ? 'WIN' : 'LOSS'} - -
-
-
- {new Date(trade.timestamp).toLocaleDateString()} | Confidence: {trade.confidence}% -
-
- ))} -
-
- )} - - {/* Analysis History Panel */} - {analysisHistory.length > 0 && ( -
-
-

- ๐Ÿ“Š Analysis History - - {analysisHistory.length} entries - -

- Recent analyses are automatically saved -
- -
- {analysisHistory.map((analysis, index) => ( -
-
-
- - {analysis.recommendation} - - {analysis.confidence}% - - {analysis.symbol} โ€ข {analysis.timeframes?.join(', ')} - -
-
- {new Date(analysis.timestamp).toLocaleString()} -
-
- -
-
- Entry: - ${analysis.entry?.price?.toFixed(2) || 'N/A'} -
-
- Stop: - ${analysis.stopLoss?.price?.toFixed(2) || 'N/A'} -
-
- Target: - ${analysis.takeProfits?.tp1?.price?.toFixed(2) || 'N/A'} -
-
- - {analysis.analysisType === 'CONTINUOUS_LEARNING' && ( -
- ๐ŸŽ“ Continuous learning analysis -
- )} -
- ))} -
-
- )} -
- ) -} diff --git a/trading_alerts.log b/trading_alerts.log index dfa879a..f1820fd 100644 --- a/trading_alerts.log +++ b/trading_alerts.log @@ -527,3 +527,5 @@ No strong signal (null at null%) No strong signal (null at null%) [Mon Aug 18 14:17:20 CEST 2025] Checking for trading signals... No strong signal (null at null%) +[Mon Aug 18 15:17:22 CEST 2025] Checking for trading signals... +parse error: Invalid numeric literal at line 1, column 10