import { NextRequest, NextResponse } from 'next/server'
import { photoService } from '@/lib/photo-service'
import { imageClassifier } from '@/lib/image-classifier'
import { existsSync } from 'fs'

interface BatchClassifyRequest {
  directory?: string
  limit?: number
  offset?: number
  minConfidence?: number
  onlyUntagged?: boolean
  dryRun?: boolean
  customLabels?: string[]
  maxResults?: number
  comprehensive?: boolean // Use both ViT + CLIP for more tags
  categories?: {
    general?: string[]
    time?: string[]
    weather?: string[]
    subjects?: string[]
    locations?: string[]
    style?: string[]
    seasons?: string[]
  }
}

export async function POST(request: NextRequest) {
  try {
    const body: BatchClassifyRequest = await request.json()
    
    const {
      directory,
      limit = 50, // Process 50 photos at a time to avoid memory issues
      offset = 0,
      minConfidence = 0.3,
      onlyUntagged = false,
      dryRun = false,
      customLabels,
      maxResults,
      comprehensive = false,
      categories
    } = body

    // Build classifier configuration for this batch
    const classifierConfig = {
      minConfidence: comprehensive ? 0.05 : minConfidence, // Lower threshold for comprehensive mode
      maxResults: comprehensive ? 25 : (maxResults || 10), // More results for comprehensive mode
      customLabels,
      categories
    }

    // Initialize classifier(s)
    if (comprehensive) {
      console.log('[BATCH CLASSIFY] Initializing comprehensive classifiers (ViT + CLIP)...')
      await Promise.all([
        imageClassifier.initialize(),
        imageClassifier.initializeZeroShot()
      ])
    } else {
      console.log('[BATCH CLASSIFY] Initializing image classifier...')
      await imageClassifier.initialize()
    }

    // Get photos to process
    console.log('[BATCH CLASSIFY] Getting photos to classify...')
    let photos = photoService.getPhotos({
      directory,
      limit,
      offset,
      sortBy: 'created_at',
      sortOrder: 'ASC'
    })

    // Filter to only untagged photos if requested
    if (onlyUntagged) {
      photos = photos.filter(photo => {
        const tags = photoService.getPhotoTags(photo.id)
        return tags.length === 0
      })
    }

    console.log(`[BATCH CLASSIFY] Processing ${photos.length} photos...`)

    const results = []
    let processed = 0
    let successful = 0
    let failed = 0
    let totalTagsAdded = 0

    for (const photo of photos) {
      try {
        processed++
        console.log(`[BATCH CLASSIFY] Processing ${processed}/${photos.length}: ${photo.filename}`)

        // Try to get cached thumbnail first, fall back to file path
        let imageSource: string | Buffer = photo.filepath
        let usingThumbnail = false
        const thumbnailBlob = photoService.getCachedThumbnail(photo.id, 200) // Use 200px thumbnail
        
        if (thumbnailBlob) {
          console.log(`[BATCH CLASSIFY] Using cached thumbnail: ${photo.filename}`)
          imageSource = thumbnailBlob
          usingThumbnail = true
        } else {
          // Check if file exists for fallback
          if (!existsSync(photo.filepath)) {
            console.warn(`[BATCH CLASSIFY] File not found and no thumbnail: ${photo.filepath}`)
            failed++
            continue
          }
          console.log(`[BATCH CLASSIFY] Using original file (no thumbnail): ${photo.filename}`)
        }

        // Get existing tags if any
        const existingTags = photoService.getPhotoTags(photo.id)

        // Classify the image with fallback handling
        let classifications
        try {
          if (comprehensive) {
            const comprehensiveResult = await imageClassifier.classifyImageComprehensive(imageSource, classifierConfig)
            classifications = comprehensiveResult.combinedResults
            console.log(`[BATCH CLASSIFY] Comprehensive: ${comprehensiveResult.objectClassification.length} object + ${comprehensiveResult.styleClassification.length} style tags`)
          } else {
            classifications = await imageClassifier.classifyImage(imageSource, customLabels, classifierConfig)
          }
        } catch (error) {
          if (usingThumbnail && existsSync(photo.filepath)) {
            console.warn(`[BATCH CLASSIFY] Thumbnail failed for ${photo.filename}, falling back to original file:`, error)
            try {
              // Fallback to original file
              if (comprehensive) {
                const comprehensiveResult = await imageClassifier.classifyImageComprehensive(photo.filepath, classifierConfig)
                classifications = comprehensiveResult.combinedResults
              } else {
                classifications = await imageClassifier.classifyImage(photo.filepath, customLabels, classifierConfig)
              }
              console.log(`[BATCH CLASSIFY] Fallback to original file successful: ${photo.filename}`)
            } catch (fallbackError) {
              console.error(`[BATCH CLASSIFY] Both thumbnail and original file failed for ${photo.filename}:`, fallbackError)
              throw fallbackError
            }
          } else {
            throw error
          }
        }
        
        // Filter by confidence and exclude existing tags
        // Note: classifications are already filtered by confidence in classifyImage
        const existingTagNames = existingTags.map(tag => tag.name.toLowerCase())
        const newTags = classifications
          .filter(result => !existingTagNames.includes(result.label.toLowerCase()))
          .map(result => ({ name: result.label, confidence: result.score }))

        if (dryRun) {
          // Just log what would be added
          results.push({
            photoId: photo.id,
            filename: photo.filename,
            existingTags: existingTags.length,
            newClassifications: newTags,
            wouldAdd: newTags.length
          })
        } else {
          // Actually add the tags
          const addedCount = photoService.addPhotoTags(photo.id, newTags)
          totalTagsAdded += addedCount
          
          results.push({
            photoId: photo.id,
            filename: photo.filename,
            existingTags: existingTags.length,
            classificationsFound: classifications.length,
            newTagsAdded: addedCount,
            topTags: newTags.slice(0, 5) // Show top 5 tags for logging
          })
        }

        successful++

        // Log progress every 10 photos
        if (processed % 10 === 0) {
          console.log(`[BATCH CLASSIFY] Progress: ${processed}/${photos.length} (${successful} successful, ${failed} failed)`)
        }

      } catch (error) {
        console.error(`[BATCH CLASSIFY] Error processing ${photo.filename}:`, error)
        failed++
        
        results.push({
          photoId: photo.id,
          filename: photo.filename,
          error: error instanceof Error ? error.message : 'Unknown error'
        })
      }
    }

    console.log(`[BATCH CLASSIFY] Completed: ${successful} successful, ${failed} failed, ${totalTagsAdded} total tags added`)

    return NextResponse.json({
      summary: {
        processed,
        successful,
        failed,
        totalTagsAdded,
        config: classifierConfig,
        dryRun,
        onlyUntagged
      },
      results: dryRun ? results : results.slice(0, 10), // Limit results in response for performance
      hasMore: photos.length === limit // Indicate if there might be more photos to process
    })

  } catch (error) {
    console.error('[BATCH CLASSIFY] Error:', error)
    return NextResponse.json(
      { error: 'Failed to batch classify images' },
      { status: 500 }
    )
  }
}

// Get classification status
export async function GET(request: NextRequest) {
  try {
    const { searchParams } = new URL(request.url)
    const directory = searchParams.get('directory') || undefined

    // Get total photos
    const allPhotos = photoService.getPhotos({ directory })
    
    // Get photos with tags
    const photosWithTags = allPhotos.filter(photo => {
      const tags = photoService.getPhotoTags(photo.id)
      return tags.length > 0
    })

    // Get most common tags
    const tagCounts: { [tagName: string]: number } = {}
    allPhotos.forEach(photo => {
      const tags = photoService.getPhotoTags(photo.id)
      tags.forEach(tag => {
        tagCounts[tag.name] = (tagCounts[tag.name] || 0) + 1
      })
    })

    const topTags = Object.entries(tagCounts)
      .sort(([,a], [,b]) => b - a)
      .slice(0, 20)
      .map(([name, count]) => ({ name, count }))

    return NextResponse.json({
      total: allPhotos.length,
      tagged: photosWithTags.length,
      untagged: allPhotos.length - photosWithTags.length,
      taggedPercentage: Math.round((photosWithTags.length / allPhotos.length) * 100),
      topTags,
      classifierReady: imageClassifier.isReady()
    })

  } catch (error) {
    console.error('[BATCH CLASSIFY STATUS] Error:', error)
    return NextResponse.json(
      { error: 'Failed to get classification status' },
      { status: 500 }
    )
  }
}