import { NextResponse } from 'next/server'
import OpenAI from 'openai'
import fs from 'fs'
import path from 'path'

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY
})

// Helper function to convert image file to base64
function imageToBase64(imagePath) {
  try {
    const fullPath = path.join(process.cwd(), 'screenshots', imagePath)
    if (fs.existsSync(fullPath)) {
      const imageBuffer = fs.readFileSync(fullPath)
      return imageBuffer.toString('base64')
    }
    return null
  } catch (error) {
    console.error('Error converting image to base64:', error)
    return null
  }
}

export async function POST(request) {
  try {
    const { message, position, screenshots, chatHistory } = await request.json()

    if (!message || !position) {
      return NextResponse.json({
        success: false,
        error: 'Message and position are required'
      }, { status: 400 })
    }

    // Build context about the current position
    const positionContext = `
CURRENT POSITION DETAILS:
- Symbol: ${position.symbol}
- Side: ${position.side}
- Entry Price: $${position.entryPrice}
- Current Price: $${position.currentPrice || 'Unknown'}
- Position Size: ${position.size}
- Current P&L: ${position.pnl > 0 ? '+' : ''}$${position.pnl?.toFixed(2) || 'Unknown'}
- Stop Loss: ${position.stopLoss ? `$${position.stopLoss}` : 'Not set'}
- Take Profit: ${position.takeProfit ? `$${position.takeProfit}` : 'Not set'}
- Entry Time: ${position.entryTime}
- Entry Analysis: ${position.entryAnalysis || 'Not available'}
`

    // Build chat history context
    const chatContext = chatHistory?.length > 0 
      ? `\n\nRECENT CONVERSATION:\n${chatHistory.map((msg) => 
          `${msg.type === 'user' ? 'TRADER' : 'ASSISTANT'}: ${msg.content}`
        ).join('\n')}`
      : ''

    // Analyze screenshots if provided
    let screenshotAnalysis = ''
    if (screenshots && screenshots.length > 0) {
      console.log('📸 Processing screenshots for analysis:', screenshots.length)
      
      const screenshotMessages = []
      
      for (const screenshot of screenshots) {
        // Extract filename from screenshot path/URL
        const filename = screenshot.split('/').pop() || screenshot
        console.log('🔍 Processing screenshot:', filename)
        
        // Convert to base64
        const base64Image = imageToBase64(filename)
        if (base64Image) {
          screenshotMessages.push({
            type: "image_url",
            image_url: {
              url: `data:image/png;base64,${base64Image}`,
              detail: "high"
            }
          })
        } else {
          console.warn('⚠️ Failed to convert screenshot to base64:', filename)
        }
      }

      if (screenshotMessages.length > 0) {
        console.log('🤖 Sending screenshots to OpenAI for analysis...')
        const analysisResponse = await openai.chat.completions.create({
          model: "gpt-4o-mini",
          messages: [
            {
              role: "system",
              content: `You are a professional trading analyst. Analyze this chart for an active ${position.side} position at $${position.entryPrice}.

Current P&L: ${position.pnl > 0 ? '+' : ''}$${position.pnl?.toFixed(2)}

PROVIDE CONCISE ANALYSIS (Max 100 words):
• Current price action vs entry
• Key levels to watch
• Risk assessment
• Immediate action needed

Be direct. Give exact price levels only.`
            },
            {
              role: "user",
              content: [
                {
                  type: "text",
                  text: `Analyze these current chart screenshots for my ${position.side} position in ${position.symbol}. What should I do now?`
                },
                ...screenshotMessages
              ]
            }
          ],
          max_tokens: 150,
          temperature: 0.1
        })

        screenshotAnalysis = analysisResponse.choices[0]?.message?.content || ''
        console.log('✅ Screenshot analysis completed')
      }
    }

    // Generate conversational response
    const systemPrompt = `You are a professional trading coach with the precision of a top proprietary desk trader. No vagueness, no fluff.

CURRENT POSITION:
${positionContext}

${screenshotAnalysis ? `LATEST CHART ANALYSIS:\n${screenshotAnalysis}\n` : ''}

RESPONSE STYLE:
- Be direct and actionable
- Give EXACT price levels only
- Use bullet points for clarity
- Maximum 150 words total
- Focus on immediate action needed

TRADER QUESTION: "${message}"

Provide concise, specific guidance.`

    const response = await openai.chat.completions.create({
      model: "gpt-4o-mini",
      messages: [
        {
          role: "system",
          content: systemPrompt
        },
        {
          role: "user",
          content: message
        }
      ],
      max_tokens: 200,
      temperature: 0.1
    })

    const assistantResponse = response.choices[0]?.message?.content

    return NextResponse.json({
      success: true,
      response: assistantResponse,
      analysis: screenshotAnalysis ? {
        timestamp: new Date().toISOString(),
        content: screenshotAnalysis
      } : null
    })

  } catch (error) {
    console.error('Trade follow-up error:', error)
    return NextResponse.json({
      success: false,
      error: 'Failed to process trade follow-up request'
    }, { status: 500 })
  }
}