import { type NextRequest, NextResponse } from "next/server"
import { createOpenAI } from "@ai-sdk/openai"
import { openai } from "@ai-sdk/openai"
import { generateText } from "ai"
import { extractTextFromPDF, generateTranslatedPDF, processImageFile, processPDFWithOCR, ocrLanguageMap, isImageFile, isPDFFile } from "@/lib/pdf-processor"
import { calculateCost, estimateTokens, formatTokenCount, MODEL_PRICING } from "@/lib/pricing"
import { costTracker } from "@/lib/cost-tracker"

export async function POST(request: NextRequest) {
  try {
    // Select AI provider based on environment variable
    const aiProvider = process.env.AI_PROVIDER || "deepseek"
    
    let model
    let modelName: string
    
    if (aiProvider === "openai") {
      // Use OpenAI
      modelName = process.env.OPENAI_MODEL || "gpt-4o-mini"
      model = openai(modelName)
    } else {
      // Use DeepSeek (default)
      modelName = process.env.DEEPSEEK_MODEL || "deepseek-chat"
      const deepseek = createOpenAI({
        apiKey: process.env.DEEPSEEK_API_KEY,
        baseURL: process.env.DEEPSEEK_BASE_URL || "https://api.deepseek.com",
      })
      model = deepseek(modelName)
    }

    const formData = await request.formData()
    const file = formData.get("file") as File
    const targetLanguage = formData.get("targetLanguage") as string
    const sourceLanguage = formData.get("sourceLanguage") as string
    const returnPDF = formData.get("returnPDF") === "true"

    if (!file || !targetLanguage) {
      return NextResponse.json({ error: "缺少必要參數" }, { status: 400 })
    }

    // Validate file type
    if (!isPDFFile(file.type) && !isImageFile(file.type)) {
      return NextResponse.json({ error: "請上傳 PDF 檔案或圖片檔案" }, { status: 400 })
    }

    // Check file size (10MB limit)
    const maxSize = parseInt(process.env.MAX_FILE_SIZE || "10485760")
    if (file.size > maxSize) {
      return NextResponse.json({ error: "檔案太大，請上傳小於 10MB 的檔案" }, { status: 413 })
    }

    // Process file based on type
    const arrayBuffer = await file.arrayBuffer()
    const buffer = Buffer.from(arrayBuffer)
    
    let extractedText = ""
    let metadata: any = {}
    
    try {
      if (isImageFile(file.type)) {
        // Image file - OCR功能已停用
        console.log("Image file detected - OCR功能已停用")
        extractedText = "目前僅支援包含文字的 PDF 文件，不支援圖片檔案。"
        metadata = { title: file.name, type: 'image' }
      } else if (isPDFFile(file.type)) {
        // Process PDF file
        console.log("Processing PDF file...")
        const result = await extractTextFromPDF(buffer)
        metadata = result.metadata
        
        if (result.isScanned) {
          // PDF is scanned or text extraction failed
          console.log("Detected scanned PDF or text extraction failed")
          const message = result.metadata?.message || "此 PDF 為掃描檔案，目前僅支援包含文字的 PDF 文件。"
          
          return NextResponse.json({ 
            error: `${message}

📋 可能的原因：
• PDF 是掃描的圖片檔案
• PDF 文件已加密或受保護
• PDF 內容格式特殊，無法提取文字
• PDF 文件損壞

💡 建議：
• 嘗試其他包含純文字的 PDF 文件
• 確認 PDF 可以在其他軟體中複製文字
• 如果是掃描檔案，建議轉換為圖片格式`,
            details: {
              pageCount: result.pageCount,
              textLength: result.metadata?.extractedTextLength || 0,
              hasTextContent: result.metadata?.hasTextContent || false
            }
          }, { status: 400 })
        } else {
          // PDF has extractable text, use it directly
          console.log("PDF contains extractable text, using direct extraction")
          extractedText = result.text
        }
      }
      
      if (!extractedText || extractedText.trim().length === 0) {
        extractedText = "無法從檔案擷取文字內容。請確認檔案包含可讀取的文字或清晰的圖像。"
      }
    } catch (error) {
      console.error("File processing error:", error)
      
      // Provide helpful error message for PDF conversion issues
      if (error instanceof Error && error.message.includes('PDF 轉圖片失敗')) {
        return NextResponse.json({ 
          error: `📄 掃描 PDF 需要額外工具支援

🎯 建議解決方案：
1. 💡 立即可用：將 PDF 轉換為圖片格式（JPG/PNG）後上傳
   - 使用 PDF 閱讀器截圖
   - 或使用線上 PDF 轉圖片工具

2. 🔧 安裝系統工具：
   • Windows: 下載安裝 ImageMagick (https://imagemagick.org/script/download.php#windows)
   • Mac: brew install imagemagick  
   • Linux: apt-get install imagemagick

📸 提示：圖片格式的 OCR 識別效果通常比掃描 PDF 更好！`,
          suggestion: "convert_to_image",
          downloadLink: "https://imagemagick.org/script/download.php#windows"
        }, { status: 400 })
      }
      
      extractedText = `檔案處理過程中發生錯誤：${error instanceof Error ? error.message : '未知錯誤'}`
    }

    // Get language name for better translation context
    const languageNames: Record<string, string> = {
      "zh-TW": "繁體中文",
      "zh-CN": "簡體中文",
      en: "English",
      ja: "日本語",
      ko: "한국어",
      es: "Español",
      fr: "Français",
      de: "Deutsch",
      it: "Italiano",
      pt: "Português",
      ru: "Русский",
      ar: "العربية",
      hi: "हिन्दी",
      th: "ไทย",
      vi: "Tiếng Việt",
    }

    const targetLanguageName = languageNames[targetLanguage] || targetLanguage
    const sourceLanguageName = languageNames[sourceLanguage] || "自動偵測"

    // Prepare translation prompt
    const prompt = `You are a professional translator. Translate the following text from ${sourceLanguageName} to ${targetLanguageName}. 
Keep the original format and structure. Only translate the content, preserving line breaks and paragraphs.
If the text appears to be an error message or system message, translate it appropriately.

Text to translate:

${extractedText}`

    // Estimate input tokens
    const estimatedInputTokens = estimateTokens(prompt)
    
    let translatedText: string
    let usage: any = null
    
    try {
      // Try to translate using selected AI provider
      const result = await generateText({
        model: model,
        prompt: prompt,
        temperature: 0.3, // Lower temperature for more accurate translation
        maxTokens: 4000,
      })
      translatedText = result.text
      usage = result.usage
    } catch (error) {
      console.error("AI API Error:", error)
      // Fallback to a simple mock translation for demo purposes
      translatedText = `[模擬翻譯結果]\n\n原文內容: ${extractedText}\n\n注意: 這是模擬翻譯結果，因為 AI API 連接失敗。請檢查 API 金鑰配置。\n\n目標語言: ${targetLanguageName}\n來源語言: ${sourceLanguageName}\n\n實際應用中，這裡會顯示真正的 AI 翻譯結果。`
    }

    // Calculate token usage and cost
    const tokenUsage = {
      promptTokens: usage?.promptTokens || estimatedInputTokens,
      completionTokens: usage?.completionTokens || estimateTokens(translatedText),
      totalTokens: (usage?.promptTokens || estimatedInputTokens) + (usage?.completionTokens || estimateTokens(translatedText))
    }

    const costCalculation = calculateCost(modelName, tokenUsage)
    const modelDisplayName = MODEL_PRICING[modelName as keyof typeof MODEL_PRICING]?.displayName || modelName

    // Track cost in accumulator (client-side will handle storage)
    const costSession = {
      model: modelName,
      provider: aiProvider,
      tokenUsage: {
        promptTokens: tokenUsage.promptTokens,
        completionTokens: tokenUsage.completionTokens,
        totalTokens: tokenUsage.totalTokens
      },
      cost: {
        inputCost: costCalculation.inputCost,
        outputCost: costCalculation.outputCost,
        totalCost: costCalculation.totalCost,
        currency: costCalculation.currency
      }
    }

    // Generate translated PDF if requested
    let pdfBase64 = ""
    if (returnPDF) {
      try {
        const pdfBytes = await generateTranslatedPDF(translatedText, metadata, targetLanguage)
        pdfBase64 = Buffer.from(pdfBytes).toString('base64')
      } catch (error) {
        console.error("PDF generation error:", error)
        // Continue without PDF generation
      }
    }

    return NextResponse.json({ 
      translatedText,
      pdfBase64: pdfBase64,
      hasPDF: pdfBase64.length > 0,
      tokenUsage: {
        promptTokens: tokenUsage.promptTokens,
        completionTokens: tokenUsage.completionTokens,
        totalTokens: tokenUsage.totalTokens,
        formattedCounts: {
          prompt: formatTokenCount(tokenUsage.promptTokens),
          completion: formatTokenCount(tokenUsage.completionTokens),
          total: formatTokenCount(tokenUsage.totalTokens)
        }
      },
      cost: {
        inputCost: costCalculation.inputCost,
        outputCost: costCalculation.outputCost,
        totalCost: costCalculation.totalCost,
        formattedCost: costCalculation.formattedCost,
        currency: costCalculation.currency
      },
      model: {
        name: modelName,
        displayName: modelDisplayName,
        provider: aiProvider
      },
      costSession: costSession
    })
  } catch (error) {
    console.error("翻譯錯誤:", error)
    
    // Check for specific error types
    if (error instanceof Error) {
      if (error.message.includes("API key")) {
        return NextResponse.json({ error: "API 金鑰配置錯誤，請聯繫管理員" }, { status: 500 })
      }
      if (error.message.includes("rate limit")) {
        return NextResponse.json({ error: "API 請求過於頻繁，請稍後再試" }, { status: 429 })
      }
    }
    
    return NextResponse.json({ error: "翻譯過程中發生錯誤，請稍後再試" }, { status: 500 })
  }
}

// OPTIONS method for CORS
export async function OPTIONS(request: NextRequest) {
  return new NextResponse(null, {
    status: 200,
    headers: {
      'Access-Control-Allow-Origin': '*',
      'Access-Control-Allow-Methods': 'POST, OPTIONS',
      'Access-Control-Allow-Headers': 'Content-Type',
    },
  })
}