#!/usr/bin/env node
/**
 * 批量封面生成 - 为执黑先行旧草稿补生成封面
 * 从剪映草稿目录提取首帧 → GPT Image edit → Sharp 文字叠加 → OSS 上传
 *
 * 用法: node gen-covers-batch.js
 */

const fs = require('fs')
const path = require('path')
const https = require('https')
const { execSync } = require('child_process')
const sharp = require('sharp')
const OSS = require('ali-oss')

// ============================================================================
// Config
// ============================================================================

const configPath = path.join(__dirname, '..', '..', 'config.json')
const cfg = JSON.parse(fs.readFileSync(configPath, 'utf-8'))

const DRAFT_BASE = cfg.jianyingDraftPath || path.join(require('os').homedir(), 'Movies/JianyingPro/User Data/Projects/com.lveditor.draft')

// Output dir for covers
const OUTPUT_BASE = path.join(__dirname, '..', '..', '..', 'output', '执黑先行_补封面')
fs.mkdirSync(OUTPUT_BASE, { recursive: true })

// OSS client
const ossClient = new OSS({
  region: cfg.ossRegion,
  accessKeyId: cfg.ossAccessKeyId,
  accessKeySecret: cfg.ossAccessKeySecret,
  bucket: cfg.ossBucket,
  secure: true,
})

// ============================================================================
// 8 drafts to process
// ============================================================================

const DRAFTS = [
  { dir: '执黑先行_0513_01_闭嘴搞钱', topicA: '闭嘴做事·才是狠人', seq: '01' },
  { dir: '执黑先行_0513_02_穷是原罪',    topicA: '你只是没钱罢了',      seq: '02' },
  { dir: '执黑先行_0513_03_别跪',        topicA: '别跪了·你配的上',    seq: '03' },
  { dir: '执黑先行_0513_04_阶层密码',    topicA: '没人说的·阶层真相',  seq: '04' },
  { dir: '执黑先行_0513_05_能量掠夺',    topicA: '出轨真相·不是道德',  seq: '05' },
  { dir: '执黑先行_0513_06_不凑合',      topicA: '不凑合·最好的风水',  seq: '06' },
  { dir: '执黑先行_0513_07_真领导',      topicA: '跟对人·只管赢',      seq: '07' },
  { dir: '执黑先行_0513_10_榨你最狠',    topicA: '哭惨的人·榨你最狠',  seq: '10' },
]

// 执黑先行 cover style (locked)
const COVER_STYLE = `Dynamic cinematic scene with a powerful figure occupying 60-70% of the frame, semi-realistic Marvel-tone style, dramatic warm orange and cool blue dual-lighting from opposing sides creating tension, dark atmospheric background, cinematic composition with strong focal point, film-grain texture, high contrast, poster-like framing`

// ============================================================================
// Utils
// ============================================================================

function fetch(url, options = {}) {
  const method = options.method || 'GET'
  const headers = options.headers || {}
  const body = options.body

  return new Promise((resolve, reject) => {
    const u = new URL(url)
    const req = https.request({
      hostname: u.hostname, port: 443, path: u.pathname + u.search,
      method, headers, timeout: 120000,
    }, (res) => {
      const chunks = []
      res.on('data', c => chunks.push(c))
      res.on('end', () => {
        const data = Buffer.concat(chunks)
        resolve({ status: res.statusCode, data, json: () => JSON.parse(data.toString()) })
      })
    })
    req.on('error', reject)
    req.on('timeout', () => { req.destroy(); reject(new Error('timeout')) })
    if (body) req.write(body)
    req.end()
  })
}

function getFirstVideoPath(draftDir) {
  const contentPath = path.join(draftDir, 'draft_content.json')
  const data = JSON.parse(fs.readFileSync(contentPath, 'utf-8'))
  const videos = data.materials.videos
  const tracks = data.tracks

  let firstVidId = null
  for (const track of tracks) {
    if (track.type === 'video') {
      const segs = track.segments || []
      if (segs.length > 0) {
        firstVidId = segs[0].material_id
        break
      }
    }
  }

  if (!firstVidId) return null

  for (const v of videos) {
    if (v.id === firstVidId) return v.path
  }
  return null
}

function sleep(ms) {
  return new Promise(resolve => setTimeout(resolve, ms))
}

async function gptImageEdit(prompt, imagePath, size, retries = 3) {
  const boundary = '----FormBoundary' + Math.random().toString(36).slice(2)
  const imgBuf = fs.readFileSync(imagePath)
  const imgName = path.basename(imagePath)

  const parts = []
  const addField = (name, value) => {
    parts.push(Buffer.from(`--${boundary}\r\nContent-Disposition: form-data; name="${name}"\r\n\r\n${value}\r\n`))
  }
  const addFile = (name, filename, buf, mime) => {
    parts.push(Buffer.from(`--${boundary}\r\nContent-Disposition: form-data; name="${name}"; filename="${filename}"\r\nContent-Type: ${mime}\r\n\r\n`))
    parts.push(buf)
    parts.push(Buffer.from('\r\n'))
  }

  const model = cfg.gptImageModel || 'gpt-image-2'
  addField('model', model)
  addField('prompt', prompt)
  if (size) addField('size', size)
  addFile('image', imgName, imgBuf, 'image/png')

  parts.push(Buffer.from(`--${boundary}--\r\n`))
  const body = Buffer.concat(parts)

  const baseUrl = cfg.gptImageApiBaseUrl || 'https://yunwu.ai'
  const apiKey = cfg.gptImageApiKey || ''

  let lastError = null
  for (let attempt = 0; attempt <= retries; attempt++) {
    if (attempt > 0) {
      const delay = [5, 15, 30][attempt - 1] || 30
      console.log(`  ⏳ Retry ${attempt}/${retries} after ${delay}s...`)
      await sleep(delay * 1000)
    }

    const res = await fetch(`${baseUrl}/v1/images/edits`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${apiKey}`,
        'Content-Type': `multipart/form-data; boundary=${boundary}`,
        'Content-Length': String(body.length),
      },
      body,
    })

    if (res.status === 200) {
      return res.json()
    }

    const errText = res.data.toString().substring(0, 500)
    if (res.status === 429) {
      console.log(`  ⚠️  Rate limited (429), attempt ${attempt + 1}/${retries + 1}`)
      lastError = new Error(`GPT Image edit rate limited after ${retries + 1} attempts: ${errText}`)
    } else {
      throw new Error(`GPT Image edit failed: ${res.status} ${errText}`)
    }
  }

  throw lastError
}

async function download(url, dest) {
  return new Promise((resolve, reject) => {
    const file = fs.createWriteStream(dest)
    https.get(url, (res) => {
      if (res.statusCode >= 300 && res.statusCode < 400 && res.headers.location) {
        file.close()
        try { fs.unlinkSync(dest) } catch (_) {}
        return download(res.headers.location, dest).then(resolve, reject)
      }
      res.pipe(file)
      file.on('finish', () => { file.close(); resolve() })
    }).on('error', (err) => { try { fs.unlinkSync(dest) } catch (_) {}; reject(err) })
  })
}

async function addTextOverlay(imagePath, text, outputPath) {
  const metadata = await sharp(imagePath).metadata()
  const { width, height } = metadata

  const fontSize = Math.round(width * 0.10)
  const parts = text.split('·')
  const lines = parts.length === 2 ? parts : [text]

  const lineHeight = fontSize * 1.3
  const totalHeight = lines.length * lineHeight
  const startY = (height - totalHeight) / 2 + fontSize * 0.8

  let textElements = ''
  lines.forEach((line, i) => {
    const y = startY + i * lineHeight
    textElements += `<text x="${width / 2}" y="${y}" text-anchor="middle" font-size="${fontSize}" font-family="'PingFang SC', 'Heiti SC', 'STHeiti', 'Arial', sans-serif" font-weight="900" fill="white" stroke="#C8960C" stroke-width="${Math.round(fontSize * 0.06)}" paint-order="stroke fill" letter-spacing="${Math.round(fontSize * 0.05)}">${line}</text>`
  })

  const svg = `<svg xmlns="http://www.w3.org/2000/svg" width="${width}" height="${height}">
    <style>
      text {
        filter: drop-shadow(0 ${Math.round(fontSize * 0.04)} ${Math.round(fontSize * 0.08)} rgba(0,0,0,0.7));
      }
    </style>
    ${textElements}
  </svg>`

  await sharp(imagePath)
    .composite([{ input: Buffer.from(svg), top: 0, left: 0 }])
    .png({ quality: 95 })
    .toFile(outputPath)
}

async function uploadToOSS(filePath, ossName) {
  const result = await ossClient.put(ossName, filePath)
  // Generate signed URL
  const url = await ossClient.signatureUrl(ossName, { expires: cfg.ossExpires || 31536000 })
  return url
}

// ============================================================================
// Process one draft
// ============================================================================

async function processDraft(draft, index) {
  const { dir, topicA, seq } = draft
  const draftDir = path.join(DRAFT_BASE, dir)
  const coverDir = path.join(OUTPUT_BASE, `covers_${seq}`)
  fs.mkdirSync(coverDir, { recursive: true })

  console.log(`\n${'='.repeat(60)}`)
  console.log(`[${index + 1}/8] ${dir}`)
  console.log(`Topic: ${topicA}`)
  console.log(`${'='.repeat(60)}`)

  // Step 1: Extract first frame
  const videoPath = getFirstVideoPath(draftDir)
  if (!videoPath || !fs.existsSync(videoPath)) {
    throw new Error(`Video not found: ${videoPath}`)
  }

  const framePath = path.join(coverDir, '_first_frame.png')
  console.log(`  Extracting first frame from: ${path.basename(videoPath)}`)
  execSync(`ffmpeg -y -i "${videoPath}" -vframes 1 -q:v 2 "${framePath}" 2>/dev/null`, { timeout: 10000 })
  console.log(`  Frame saved: ${framePath}`)

  // Step 2: Generate covers in both sizes
  const sizes = [
    { label: '抖音', size: '1088x1920', suffix: `cover_${seq}_抖音` },
    { label: '小红书', size: '1152x1536', suffix: `cover_${seq}_小红书` },
  ]

  const results = []

  for (const { label, size, suffix } of sizes) {
    console.log(`\n  🎨 Generating ${label} cover (${size})...`)

    const editPrompt = `Create a vertical social media cover in ${size} aspect ratio. Style reference: ${COVER_STYLE}. Take the visual aesthetic from the reference image (color palette, lighting mood, character style) and recompose it into a tighter, more poster-like cover composition. The composition should have a strong focal point. NO text, NO watermark, NO letters, NO words whatsoever.`

    const result = await gptImageEdit(editPrompt, framePath, size)
    let coverUrl
    if (result.data?.[0]?.url) {
      coverUrl = result.data[0].url
    } else if (result.data?.[0]?.b64_json) {
      const buf = Buffer.from(result.data[0].b64_json, 'base64')
      const rawPath = path.join(coverDir, `${suffix}_raw.png`)
      fs.writeFileSync(rawPath, buf)
      coverUrl = rawPath
    } else {
      throw new Error(`GPT Image no URL: ${JSON.stringify(result).substring(0, 300)}`)
    }

    // Download if URL
    const coverRawPath = path.join(coverDir, `${suffix}_raw.png`)
    if (coverUrl.startsWith('http')) {
      console.log(`  Downloading generated cover...`)
      await download(coverUrl, coverRawPath)
    }

    // Add text overlay
    const coverFinalPath = path.join(coverDir, `${suffix}.png`)
    console.log(`  Adding text overlay: "${topicA}"`)
    await addTextOverlay(coverRawPath, topicA, coverFinalPath)

    // Upload to OSS
    const ossName = `covers/执黑先行/${suffix}.png`
    console.log(`  Uploading to OSS...`)
    const url = await uploadToOSS(coverFinalPath, ossName)

    console.log(`  ✅ ${label}: ${url.substring(0, 80)}...`)
    results.push({ label, size, url, localPath: coverFinalPath })

    // Small delay between covers to avoid rate limits
    await sleep(2000)
  }

  return results
}

// ============================================================================
// Main
// ============================================================================

async function main() {
  const allResults = []

  for (let i = 0; i < DRAFTS.length; i++) {
    try {
      const results = await processDraft(DRAFTS[i], i)
      allResults.push({ draft: DRAFTS[i], results, error: null })

      // Delay between drafts to avoid rate limits
      if (i < DRAFTS.length - 1) {
        console.log(`\n  ⏸️  Waiting 3s before next draft...`)
        await sleep(3000)
      }
    } catch (err) {
      console.error(`\n❌ Failed [${DRAFTS[i].dir}]: ${err.message}`)
      allResults.push({ draft: DRAFTS[i], results: [], error: err.message })
    }
  }

  // Summary
  console.log(`\n\n${'='.repeat(60)}`)
  console.log(`SUMMARY`)
  console.log(`${'='.repeat(60)}`)

  // Save JSON results
  const summaryPath = path.join(OUTPUT_BASE, 'cover_results.json')
  fs.writeFileSync(summaryPath, JSON.stringify(allResults, null, 2), 'utf-8')
  console.log(`Results saved to: ${summaryPath}`)

  // Print table
  console.log(`\n| # | 草稿 | 选题 | 抖音封面 | 小红书封面 |`)
  console.log(`|---|------|------|---------|-----------|`)

  for (const item of allResults) {
    const d = item.draft
    const douyin = item.results.find(r => r.label === '抖音')
    const xhs = item.results.find(r => r.label === '小红书')
    const dyUrl = douyin ? douyin.url : (item.error || 'FAILED')
    const xhsUrl = xhs ? xhs.url : (item.error || 'FAILED')
    console.log(`| ${d.seq} | ${d.dir} | ${d.topicA} | ${dyUrl.substring(0, 60)}... | ${xhsUrl.substring(0, 60)}... |`)
  }

  // Cleanup temp files
  for (const item of allResults) {
    if (item.error) continue
    // Keep final covers, remove raw/frames
  }

  console.log(`\nDone. ${allResults.filter(r => !r.error).length}/${DRAFTS.length} succeeded.`)
}

main().catch(err => {
  console.error('Batch cover generation failed:', err.message)
  process.exit(1)
})