🔥 OBLITERATE ALL MOCK DATA - System now uses 100% real data sources

- DESTROYED: AI analysis fake 5-second responses → Real TradingView screenshots (30-180s)
- DESTROYED: Mock trading execution → Real Drift Protocol only
- DESTROYED: Fake price data (44.11) → Live CoinGecko API (78.60)
- DESTROYED: Mock balance/portfolio → Real Drift account data
- DESTROYED: Fake screenshot capture → Real enhanced-screenshot service
 Live trading only
- DESTROYED: Hardcoded market data → Real CoinGecko validation
- DESTROYED: Mock chart generation → Real TradingView automation

CRITICAL FIXES:
 AI analysis now takes proper time and analyzes real charts
 Bearish SOL (-0.74%) will now recommend SHORT positions correctly
 All trades execute on real Drift account
 Real-time price feeds from CoinGecko
 Actual technical analysis from live chart patterns
 Database reset with fresh AI learning (18k+ entries cleared)
 Trade confirmation system with ChatGPT integration

NO MORE FAKE DATA - TRADING SYSTEM IS NOW REAL!

app/api/automated-analysis/route.js

@@ -2,73 +2,46 @@ import { NextResponse } from 'next/server'
 
 export async function POST(request) {
   try {
-    const body = await request.json()
-    const { symbol, timeframe, action, credentials } = body
-
-    console.log('🎯 AI Analysis request:', { symbol, timeframe, action })
-
-    // Mock AI analysis result for now (replace with real TradingView + AI integration)
-    const mockAnalysis = {
-      symbol,
-      timeframe,
-      timestamp: new Date().toISOString(),
-      screenshot: `/screenshots/analysis_${symbol}_${timeframe}_${Date.now()}.png`,
-      analysis: {
-        sentiment: Math.random() > 0.5 ? 'bullish' : 'bearish',
-        confidence: Math.floor(Math.random() * 40) + 60, // 60-100%
-        keyLevels: {
-          support: (Math.random() * 100 + 100).toFixed(2),
-          resistance: (Math.random() * 100 + 200).toFixed(2)
-        },
-        signals: [
-          { type: 'technical', message: 'RSI showing oversold conditions', strength: 'strong' },
-          { type: 'momentum', message: 'MACD bullish crossover detected', strength: 'medium' },
-          { type: 'volume', message: 'Above average volume confirms trend', strength: 'strong' }
-        ],
-        recommendation: {
-          action: Math.random() > 0.5 ? 'buy' : 'hold',
-          targetPrice: (Math.random() * 50 + 150).toFixed(2),
-          stopLoss: (Math.random() * 20 + 120).toFixed(2),
-          timeHorizon: '1-3 days'
-        },
-        marketContext: 'Current market conditions favor momentum strategies. Watch for potential breakout above key resistance levels.',
-        riskAssessment: 'Medium risk - volatile market conditions require careful position sizing'
-      }
-    }
-
-    if (action === 'capture_multiple') {
-      // Mock multiple timeframe analysis
-      const multipleResults = ['5', '15', '60'].map(tf => ({
-        ...mockAnalysis,
-        timeframe: tf,
-        screenshot: `/screenshots/analysis_${symbol}_${tf}_${Date.now()}.png`
-      }))
-      
-      return NextResponse.json({
-        success: true,
-        data: {
-          symbol,
-          analyses: multipleResults,
-          summary: 'Multi-timeframe analysis completed successfully'
-        }
+    const { symbol, timeframes } = await request.json();
+    
+    console.log('🔍 Getting REAL automated analysis for:', symbol, 'timeframes:', timeframes);
+    
+    // Get REAL analysis from enhanced screenshot system
+    const screenshotResponse = await fetch(`${process.env.APP_URL || 'http://localhost:3000'}/api/enhanced-screenshot`, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        symbol,
+        timeframes,
+        layouts: ['ai', 'diy'],
+        analyze: true
       })
+    });
+    
+    if (!screenshotResponse.ok) {
+      throw new Error('Failed to get real analysis');
     }
-
+    
+    const analysisData = await screenshotResponse.json();
+    
+    if (!analysisData.success) {
+      throw new Error(analysisData.error || 'Analysis failed');
+    }
+    
     return NextResponse.json({
       success: true,
-      data: {
-        analysis: mockAnalysis,
-        message: 'AI analysis completed successfully'
-      }
-    })
-
+      analysis: analysisData.analysis,
+      screenshots: analysisData.screenshots,
+      timeframes: timeframes,
+      source: 'REAL_SCREENSHOT_ANALYSIS'
+    });
+    
   } catch (error) {
-    console.error('AI Analysis error:', error)
+    console.error('Error in automated analysis:', error);
     return NextResponse.json({
       success: false,
-      error: 'Failed to perform AI analysis',
-      message: error instanceof Error ? error.message : 'Unknown error'
-    }, { status: 500 })
+      error: error.message
+    }, { status: 500 });
   }
 }