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'
        }
      })
    }

    return NextResponse.json({
      success: true,
      data: {
        analysis: mockAnalysis,
        message: 'AI analysis completed successfully'
      }
    })

  } catch (error) {
    console.error('AI Analysis error:', error)
    return NextResponse.json({
      success: false,
      error: 'Failed to perform AI analysis',
      message: error instanceof Error ? error.message : 'Unknown error'
    }, { status: 500 })
  }
}

export async function GET() {
  return NextResponse.json({
    message: 'AI Analysis endpoint - Use POST to perform analysis',
    supportedActions: ['capture_and_analyze', 'capture_multiple'],
    requiredFields: ['symbol', 'timeframe', 'action'],
    optionalFields: ['credentials']
  })
}