trading_bot_v3/app/api/ai-analytics/route.js

import { NextResponse } from 'next/server';
import { PrismaClient } from '@prisma/client';

/**
 * AI Learning Analytics API
 * 
 * Provides real-time statistics about AI learning improvements and trading performance
 */

const prisma = new PrismaClient();

export async function GET(request) {
  try {
    const startDate = new Date('2025-07-24'); // When AI trading started
    
    // Get learning data
    const learningData = await prisma.aILearningData.findMany({
      where: {
        createdAt: {
          gte: startDate
        }
      },
      orderBy: { createdAt: 'asc' }
    });
    
    // Get trade data
    const tradeData = await prisma.trade.findMany({
      where: {
        createdAt: {
          gte: startDate
        },
        isAutomated: true
      },
      orderBy: { createdAt: 'asc' }
    });
    
    // Get automation sessions
    const automationSessions = await prisma.automationSession.findMany({
      where: {
        createdAt: {
          gte: startDate
        }
      },
      orderBy: { createdAt: 'desc' }
    });
    
    // Calculate improvements
    const improvements = calculateImprovements(learningData);
    const pnlAnalysis = calculatePnLAnalysis(tradeData);
    
    // Add real-time drift position data
    let currentPosition = null;
    try {
      const HttpUtil = require('../../../lib/http-util');
      const positionData = await HttpUtil.get('http://localhost:9001/api/automation/position-monitor');
      
      if (positionData.success && positionData.monitor) {
        currentPosition = {
          hasPosition: positionData.monitor.hasPosition,
          symbol: positionData.monitor.position?.symbol,
          side: positionData.monitor.position?.side,
          size: positionData.monitor.position?.size,
          entryPrice: positionData.monitor.position?.entryPrice,
          currentPrice: positionData.monitor.position?.currentPrice,
          unrealizedPnl: positionData.monitor.position?.unrealizedPnl,
          distanceFromStopLoss: positionData.monitor.stopLossProximity?.distancePercent,
          riskLevel: positionData.monitor.riskLevel,
          aiRecommendation: positionData.monitor.recommendation
        };
      }
    } catch (positionError) {
      console.log('Could not fetch position data:', positionError.message);
    }
    
    // Build response
    const now = new Date();
    const daysSinceStart = Math.ceil((now.getTime() - startDate.getTime()) / (1000 * 60 * 60 * 24));
    
    const response = {
      generated: now.toISOString(),
      period: {
        start: startDate.toISOString(),
        end: now.toISOString(),
        daysActive: daysSinceStart
      },
      overview: {
        totalLearningRecords: learningData.length,
        totalTrades: tradeData.length,
        totalSessions: automationSessions.length,
        activeSessions: automationSessions.filter(s => s.status === 'ACTIVE').length
      },
      improvements,
      pnl: pnlAnalysis,
      currentPosition,
      realTimeMetrics: {
        daysSinceAIStarted: daysSinceStart,
        learningRecordsPerDay: Number((learningData.length / daysSinceStart).toFixed(1)),
        tradesPerDay: Number((tradeData.length / daysSinceStart).toFixed(1)),
        lastUpdate: now.toISOString(),
        isLearningActive: automationSessions.filter(s => s.status === 'ACTIVE').length > 0
      },
      learningProof: {
        hasImprovement: improvements?.confidenceImprovement > 0,
        improvementDirection: improvements?.trend,
        confidenceChange: improvements?.confidenceImprovement,
        accuracyChange: improvements?.accuracyImprovement,
        sampleSize: learningData.length,
        isStatisticallySignificant: learningData.length > 100
      }
    };
    
    return NextResponse.json(response);
    
  } catch (error) {
    console.error('Error generating AI analytics:', error);
    return NextResponse.json({ 
      error: 'Failed to generate analytics',
      details: error.message 
    }, { status: 500 });
  } finally {
    await prisma.$disconnect();
  }
}

function calculateImprovements(learningData) {
  if (learningData.length < 10) {
    return {
      improvement: 0,
      trend: 'INSUFFICIENT_DATA',
      message: 'Need more learning data to calculate improvements',
      confidenceImprovement: 0,
      accuracyImprovement: null
    };
  }

  // Split data into early vs recent periods
  const midPoint = Math.floor(learningData.length / 2);
  const earlyData = learningData.slice(0, midPoint);
  const recentData = learningData.slice(midPoint);

  // Calculate average confidence scores
  const earlyConfidence = getAverageConfidence(earlyData);
  const recentConfidence = getAverageConfidence(recentData);

  // Calculate accuracy if outcomes are available
  const earlyAccuracy = getAccuracy(earlyData);
  const recentAccuracy = getAccuracy(recentData);

  const confidenceImprovement = ((recentConfidence - earlyConfidence) / earlyConfidence) * 100;
  const accuracyImprovement = earlyAccuracy && recentAccuracy ? 
    ((recentAccuracy - earlyAccuracy) / earlyAccuracy) * 100 : null;

  return {
    confidenceImprovement: Number(confidenceImprovement.toFixed(2)),
    accuracyImprovement: accuracyImprovement ? Number(accuracyImprovement.toFixed(2)) : null,
    earlyPeriod: {
      samples: earlyData.length,
      avgConfidence: Number(earlyConfidence.toFixed(2)),
      accuracy: earlyAccuracy ? Number(earlyAccuracy.toFixed(2)) : null
    },
    recentPeriod: {
      samples: recentData.length,
      avgConfidence: Number(recentConfidence.toFixed(2)),
      accuracy: recentAccuracy ? Number(recentAccuracy.toFixed(2)) : null
    },
    trend: confidenceImprovement > 5 ? 'IMPROVING' : 
           confidenceImprovement < -5 ? 'DECLINING' : 'STABLE'
  };
}

function calculatePnLAnalysis(tradeData) {
  const analysis = {
    totalTrades: tradeData.length,
    totalPnL: 0,
    totalPnLPercent: 0,
    winningTrades: 0,
    losingTrades: 0,
    breakEvenTrades: 0,
    avgTradeSize: 0,
    winRate: 0,
    avgWin: 0,
    avgLoss: 0,
    profitFactor: 0
  };

  if (tradeData.length === 0) {
    return analysis;
  }

  let totalProfit = 0;
  let totalLoss = 0;
  let totalAmount = 0;

  tradeData.forEach(trade => {
    const pnl = trade.profit || 0;
    const pnlPercent = trade.pnlPercent || 0;
    const amount = trade.amount || 0;

    analysis.totalPnL += pnl;
    analysis.totalPnLPercent += pnlPercent;
    totalAmount += amount;

    if (pnl > 0) {
      analysis.winningTrades++;
      totalProfit += pnl;
    } else if (pnl < 0) {
      analysis.losingTrades++;
      totalLoss += Math.abs(pnl);
    } else {
      analysis.breakEvenTrades++;
    }
  });

  analysis.avgTradeSize = totalAmount / tradeData.length;
  analysis.winRate = (analysis.winningTrades / tradeData.length) * 100;
  analysis.avgWin = analysis.winningTrades > 0 ? totalProfit / analysis.winningTrades : 0;
  analysis.avgLoss = analysis.losingTrades > 0 ? totalLoss / analysis.losingTrades : 0;
  analysis.profitFactor = analysis.avgLoss > 0 ? analysis.avgWin / analysis.avgLoss : 0;

  // Round numbers
  Object.keys(analysis).forEach(key => {
    if (typeof analysis[key] === 'number') {
      analysis[key] = Number(analysis[key].toFixed(4));
    }
  });

  return analysis;
}

function getAverageConfidence(data) {
  const confidenceScores = data
    .map(d => {
      // Handle confidence stored as percentage (75.0) vs decimal (0.75)
      let confidence = d.confidenceScore || d.analysisData?.confidence || 0.5;
      if (confidence > 1) {
        confidence = confidence / 100; // Convert percentage to decimal
      }
      return confidence;
    })
    .filter(score => score > 0);
  
  return confidenceScores.length > 0 ? 
    confidenceScores.reduce((a, b) => a + b, 0) / confidenceScores.length : 0.5;
}

function getAccuracy(data) {
  const withOutcomes = data.filter(d => d.outcome && d.accuracyScore);
  if (withOutcomes.length === 0) return null;

  const avgAccuracy = withOutcomes.reduce((sum, d) => sum + (d.accuracyScore || 0), 0) / withOutcomes.length;
  return avgAccuracy;
}

export async function POST(request) {
  return NextResponse.json({ 
    success: true, 
    message: 'Analytics refreshed',
    timestamp: new Date().toISOString()
  });
}