Add persistent learning data and PnL display

- Created persistent learning status API with trading statistics
- Added comprehensive PnL and win rate display to AI Learning panel
- Implemented trading stats tracking with win/loss ratios
- Added persistent data storage for historical trading performance
- Enhanced learning panel with real-time trading metrics
- Fixed learning data visibility when bot is not running
- Added sample trading data for demonstration

lib/persistent-learning-data.js

@@ -0,0 +1,132 @@
+// Helper functions for updating persistent learning data
+import fs from 'fs/promises';
+import path from 'path';
+
+const PERSISTENT_DATA_FILE = path.join(process.cwd(), 'data', 'learning-persistent.json');
+
+async function loadPersistentData() {
+  try {
+    const data = await fs.readFile(PERSISTENT_DATA_FILE, 'utf8');
+    return JSON.parse(data);
+  } catch (error) {
+    // Return default structure if file doesn't exist
+    return {
+      totalTrades: 0,
+      winningTrades: 0,
+      losingTrades: 0,
+      totalPnL: 0,
+      winRate: 0,
+      avgWinAmount: 0,
+      avgLossAmount: 0,
+      bestTrade: 0,
+      worstTrade: 0,
+      learningDecisions: 0,
+      aiEnhancements: 0,
+      riskThresholds: {
+        emergency: 1,
+        risk: 2,
+        mediumRisk: 5
+      },
+      lastUpdated: new Date().toISOString(),
+      systemStatus: 'learning',
+      dataCollected: true
+    };
+  }
+}
+
+async function savePersistentData(data) {
+  try {
+    await fs.writeFile(PERSISTENT_DATA_FILE, JSON.stringify(data, null, 2));
+    return true;
+  } catch (error) {
+    console.error('Error saving persistent data:', error);
+    return false;
+  }
+}
+
+export async function updateTradingStats(tradeData) {
+  try {
+    const persistentData = await loadPersistentData();
+    
+    // Update trade counts
+    persistentData.totalTrades += 1;
+    
+    // Determine if trade was winning or losing
+    const isWin = tradeData.pnl > 0;
+    if (isWin) {
+      persistentData.winningTrades += 1;
+    } else {
+      persistentData.losingTrades += 1;
+    }
+    
+    // Update PnL
+    persistentData.totalPnL += tradeData.pnl;
+    
+    // Update best/worst trades
+    if (tradeData.pnl > persistentData.bestTrade) {
+      persistentData.bestTrade = tradeData.pnl;
+    }
+    if (tradeData.pnl < persistentData.worstTrade) {
+      persistentData.worstTrade = tradeData.pnl;
+    }
+    
+    // Recalculate averages and win rate
+    persistentData.winRate = (persistentData.winningTrades / persistentData.totalTrades) * 100;
+    
+    if (persistentData.winningTrades > 0) {
+      // Calculate average win amount (we need to track this separately for accuracy)
+      const winTrades = persistentData.winTrades || [];
+      winTrades.push(isWin ? tradeData.pnl : null);
+      const wins = winTrades.filter(t => t !== null && t > 0);
+      persistentData.avgWinAmount = wins.reduce((sum, win) => sum + win, 0) / wins.length;
+    }
+    
+    if (persistentData.losingTrades > 0) {
+      // Calculate average loss amount
+      const lossTrades = persistentData.lossTrades || [];
+      lossTrades.push(!isWin ? tradeData.pnl : null);
+      const losses = lossTrades.filter(t => t !== null && t < 0);
+      persistentData.avgLossAmount = losses.reduce((sum, loss) => sum + loss, 0) / losses.length;
+    }
+    
+    // Update timestamp
+    persistentData.lastUpdated = new Date().toISOString();
+    persistentData.systemStatus = 'active';
+    
+    // Save updated data
+    await savePersistentData(persistentData);
+    
+    console.log(`📊 Persistent data updated: Trade PnL ${tradeData.pnl}, Total: ${persistentData.totalTrades} trades, ${persistentData.winRate.toFixed(1)}% win rate`);
+    
+    return persistentData;
+  } catch (error) {
+    console.error('Error updating trading stats:', error);
+    return null;
+  }
+}
+
+export async function updateLearningDecision() {
+  try {
+    const persistentData = await loadPersistentData();
+    persistentData.learningDecisions += 1;
+    persistentData.lastUpdated = new Date().toISOString();
+    await savePersistentData(persistentData);
+    return persistentData;
+  } catch (error) {
+    console.error('Error updating learning decision count:', error);
+    return null;
+  }
+}
+
+export async function updateAIEnhancement() {
+  try {
+    const persistentData = await loadPersistentData();
+    persistentData.aiEnhancements += 1;
+    persistentData.lastUpdated = new Date().toISOString();
+    await savePersistentData(persistentData);
+    return persistentData;
+  } catch (error) {
+    console.error('Error updating AI enhancement count:', error);
+    return null;
+  }
+}