import { Buffer } from 'node:buffer';
import { existsSync, mkdirSync, readFileSync, writeFileSync } from 'node:fs';
import path from 'node:path';

const repoRoot = process.cwd();
const outDir = path.join(
  repoRoot,
  'output',
  'imagegen',
  'edutainment-toca-world-map-concepts-20260523',
);
const styleReferencePath = path.join(
  repoRoot,
  'public',
  'child-motion-demo',
  'picture-book-grass-stage.png',
);
const defaultTimeoutMs = 1000000;

const commonPrompt = [
  '横屏 16:9 寓教于乐板块玩法入口概念图。',
  '参考 Toca Life World 的地图组织方式：一个横向展开的大世界，允许向左和向右以“一屏一屏”的单位继续延伸和探索。',
  '画面必须像儿童绘本插画，明亮、干净、温暖、圆润、手绘感强，保留 Genarrative 寓教于乐现有的草地、水彩、纸张纹理和童趣气质。',
  '地图里要有清晰的道路、步道、河流、桥、分区节点和地标，但不要复制 Toca 的 logo、角色、字体、UI、建筑外形或配色。',
  '每个玩法入口都要像一个可单独进入的区域，区域之间既连贯又能独立辨认，适合后续做横向滑动或分屏探索。',
  '左右两侧都要有明显的延展感，边缘不能封死，重要场景不要都挤在画面中心。',
  '中心只保留一个轻量主枢纽，左右各留出半屏到一屏的可继续探索空间。',
  '不要出现文字、数字、字母、按钮文案、UI 面板、logo、水印、真实照片感、暗黑科技风、过度复杂的人物表情、现成商业 IP 角色。',
].join('');

const concepts = [
  {
    id: 'edutainment-toca-world-01-river-town',
    title: '河道城镇带',
    prompt: [
      commonPrompt,
      '版式方向：一条横向城镇带沿着河道和主路展开，左边是果园与识物区，中间是创作和主枢纽区，右边是音乐广场、自然观察和运动区。',
      '每个区域像独立小镇街区，房屋和设施分布在道路两侧，远处山坡和天空继续延伸，整体感觉像可以一直向左右滑动。',
      '左侧入口更偏自然与认知，右侧入口更偏探索与表演，中间保留一个安静广场作为聚合点。',
    ].join(''),
  },
  {
    id: 'edutainment-toca-world-02-mountain-arc',
    title: '山脊长廊',
    prompt: [
      commonPrompt,
      '版式方向：一条山脊和环山公路贯穿左右，地图像被拉长的山地长廊，城市、树林、草坡和小店沿山脊展开。',
      '左屏是水果农场和画画工坊，中屏是社区广场和拼图桥，右屏是音乐小剧场、动物观察和冒险步道。',
      '地形要有明显起伏，但道路必须连续、可走、可向两侧继续延伸，像同一世界的不同屏幕段落。',
    ].join(''),
  },
  {
    id: 'edutainment-toca-world-03-island-chain',
    title: '岛链世界',
    prompt: [
      commonPrompt,
      '版式方向：多个小岛通过桥梁、栈道和缆车相连，像一条横向的岛链，每个岛都像一屏可探索区域。',
      '左侧岛是识物果园岛，中间岛是绘本创作岛和主广场，右侧岛是运动草地岛、音乐舞台岛和自然探索岛。',
      '每个岛的边缘都要暗示下一岛的延伸，水面和道路自然把画面向左向右打开，不要封闭成一个圆形世界。',
    ].join(''),
  },
  {
    id: 'edutainment-toca-world-04-city-park-spine',
    title: '城市公园脊',
    prompt: [
      commonPrompt,
      '版式方向：一条城市公园主脊从左到右穿过整个画面，主脊两侧是不同功能街区，像儿童版的世界地图主干道。',
      '左边是安静学习区和果园，中央是综合广场、画画棚和拼图桥，右边是音乐广场、运动场、动物观测点和森林边界。',
      '整体更接近 Toca 式“世界菜单”感，但美术要更像绘本插画，不要扁平矢量 UI，也不要把地图画成球体。',
    ].join(''),
  },
];

function readDotenv(fileName) {
  const filePath = path.join(repoRoot, fileName);
  if (!existsSync(filePath)) {
    return {};
  }

  const values = {};
  for (const line of readFileSync(filePath, 'utf8').split(/\r?\n/u)) {
    const trimmed = line.trim();
    if (!trimmed || trimmed.startsWith('#')) {
      continue;
    }
    const match = /^([A-Za-z_][A-Za-z0-9_]*)=(.*)$/u.exec(trimmed);
    if (!match) {
      continue;
    }
    let value = match[2].trim();
    if (
      (value.startsWith('"') && value.endsWith('"')) ||
      (value.startsWith("'") && value.endsWith("'"))
    ) {
      value = value.slice(1, -1);
    }
    values[match[1]] = value;
  }
  return values;
}

function resolveEnv() {
  const loaded = {
    ...readDotenv('.env.example'),
    ...readDotenv('.env.local'),
    ...readDotenv('.env.secrets.local'),
    ...process.env,
  };
  return {
    baseUrl: String(loaded.VECTOR_ENGINE_BASE_URL || '')
      .trim()
      .replace(/\/+$/u, ''),
    apiKey: String(loaded.VECTOR_ENGINE_API_KEY || '').trim(),
    timeoutMs: Number.parseInt(
      String(loaded.VECTOR_ENGINE_IMAGE_REQUEST_TIMEOUT_MS || defaultTimeoutMs),
      10,
    ),
  };
}

function generationUrl(baseUrl) {
  return baseUrl.endsWith('/v1')
    ? `${baseUrl}/images/generations`
    : `${baseUrl}/v1/images/generations`;
}

function collectStringsByKey(value, targetKey, output) {
  if (Array.isArray(value)) {
    value.forEach((entry) => collectStringsByKey(entry, targetKey, output));
    return;
  }
  if (!value || typeof value !== 'object') {
    return;
  }

  for (const [key, nested] of Object.entries(value)) {
    if (key === targetKey) {
      if (typeof nested === 'string' && nested.trim()) {
        output.push(nested.trim());
      }
      if (Array.isArray(nested)) {
        nested.forEach((entry) => {
          if (typeof entry === 'string' && entry.trim()) {
            output.push(entry.trim());
          }
        });
      }
    }
    collectStringsByKey(nested, targetKey, output);
  }
}

function inferExtensionFromBytes(bytes) {
  if (bytes.subarray(0, 8).equals(Buffer.from('\x89PNG\r\n\x1A\n', 'binary'))) {
    return 'png';
  }
  if (bytes.subarray(0, 3).equals(Buffer.from([0xff, 0xd8, 0xff]))) {
    return 'jpg';
  }
  if (
    bytes.subarray(0, 4).toString('ascii') === 'RIFF' &&
    bytes.subarray(8, 12).toString('ascii') === 'WEBP'
  ) {
    return 'webp';
  }
  return 'png';
}

function inferExtensionFromContentType(contentType) {
  const normalized = contentType.split(';')[0]?.trim().toLowerCase();
  if (normalized === 'image/png') {
    return 'png';
  }
  if (normalized === 'image/webp') {
    return 'webp';
  }
  if (normalized === 'image/jpeg') {
    return 'jpg';
  }
  return 'png';
}

function toDataUrl(filePath) {
  if (!existsSync(filePath)) {
    return null;
  }
  const bytes = readFileSync(filePath);
  const extension = inferExtensionFromBytes(bytes);
  const mime = extension === 'jpg' ? 'image/jpeg' : `image/${extension}`;
  return `data:${mime};base64,${bytes.toString('base64')}`;
}

function buildRequestBody(concept, size, hasStyleReference) {
  const body = {
    model: 'gpt-image-2-all',
    prompt: concept.prompt,
    n: 1,
    size,
  };
  if (hasStyleReference) {
    const ref = toDataUrl(styleReferencePath);
    if (ref) {
      body.image = [ref];
    }
  }
  return body;
}

function buildDryRunRequestBody(concept, size, hasStyleReference) {
  return {
    model: 'gpt-image-2-all',
    prompt: concept.prompt,
    n: 1,
    size,
    imageReferenceCount: hasStyleReference ? 1 : 0,
  };
}

async function fetchJson(url, options, timeoutMs) {
  const abortController = new AbortController();
  const timer = setTimeout(() => abortController.abort(), timeoutMs);
  try {
    const response = await fetch(url, {
      ...options,
      signal: abortController.signal,
    });
    const text = await response.text();
    if (!response.ok) {
      throw new Error(`VectorEngine ${response.status}: ${text.slice(0, 600)}`);
    }
    return JSON.parse(text);
  } catch (error) {
    if (error?.name === 'AbortError') {
      throw new Error(`VectorEngine request timed out after ${timeoutMs}ms`);
    }
    throw error;
  } finally {
    clearTimeout(timer);
  }
}

async function downloadUrl(url, timeoutMs) {
  const abortController = new AbortController();
  const timer = setTimeout(() => abortController.abort(), timeoutMs);
  try {
    const response = await fetch(url, { signal: abortController.signal });
    if (!response.ok) {
      throw new Error(`download ${response.status}`);
    }
    return {
      bytes: Buffer.from(await response.arrayBuffer()),
      extension: inferExtensionFromContentType(
        response.headers.get('content-type') || '',
      ),
    };
  } catch (error) {
    if (error?.name === 'AbortError') {
      throw new Error(`Generated image download timed out after ${timeoutMs}ms`);
    }
    throw error;
  } finally {
    clearTimeout(timer);
  }
}

function outputPathFor(concept, extension = 'png') {
  return path.join(outDir, `${concept.id}.${extension}`);
}

function findExistingOutputPath(concept) {
  for (const extension of ['png', 'jpg', 'jpeg', 'webp']) {
    const candidate = outputPathFor(concept, extension);
    if (existsSync(candidate)) {
      return candidate;
    }
  }
  return null;
}

async function generateOne(env, concept, size) {
  const payload = await fetchJson(
    generationUrl(env.baseUrl),
    {
      method: 'POST',
      headers: {
        Authorization: `Bearer ${env.apiKey}`,
        Accept: 'application/json',
        'Content-Type': 'application/json',
      },
      body: JSON.stringify(buildRequestBody(concept, size, existsSync(styleReferencePath))),
    },
    env.timeoutMs,
  );

  const urls = [];
  const b64Images = [];
  collectStringsByKey(payload, 'url', urls);
  collectStringsByKey(payload, 'image', urls);
  collectStringsByKey(payload, 'image_url', urls);
  collectStringsByKey(payload, 'b64_json', b64Images);

  let image;
  const imageUrl = [...new Set(urls)].find((url) => /^https?:\/\//u.test(url));
  if (imageUrl) {
    image = await downloadUrl(imageUrl, env.timeoutMs);
  } else if (b64Images[0]) {
    const bytes = Buffer.from(b64Images[0], 'base64');
    image = {
      bytes,
      extension: inferExtensionFromBytes(bytes),
    };
  } else {
    throw new Error(`VectorEngine returned no image for ${concept.id}`);
  }

  mkdirSync(outDir, { recursive: true });
  const outputPath = outputPathFor(concept, image.extension);
  writeFileSync(outputPath, image.bytes);
  return outputPath;
}

const args = new Map();
for (let index = 2; index < process.argv.length; index += 1) {
  const raw = process.argv[index];
  if (raw.startsWith('--')) {
    const next = process.argv[index + 1];
    if (next && !next.startsWith('--')) {
      args.set(raw, next);
      index += 1;
    } else {
      args.set(raw, true);
    }
  }
}

const size = String(args.get('--size') || '2048x1152');
const dryRun = args.has('--dry-run') || !args.has('--live');
const selectedIds = String(args.get('--only') || '')
  .split(',')
  .map((value) => value.trim())
  .filter(Boolean);
const selectedConcepts = concepts.filter(
  (concept) => selectedIds.length === 0 || selectedIds.includes(concept.id),
);
const hasStyleReference = existsSync(styleReferencePath);

if (dryRun) {
  console.log(
    JSON.stringify(
      {
        mode: 'dry-run',
        outDir,
        size,
        hasStyleReference,
        count: selectedConcepts.length,
        requests: selectedConcepts.map((concept) => ({
          id: concept.id,
          title: concept.title,
          body: buildDryRunRequestBody(concept, size, hasStyleReference),
        })),
      },
      null,
      2,
    ),
  );
  process.exit(0);
}

const env = resolveEnv();
if (!env.baseUrl || !env.apiKey) {
  console.error(
    JSON.stringify({
      ok: false,
      error: 'Missing VECTOR_ENGINE_BASE_URL or VECTOR_ENGINE_API_KEY',
      hasBaseUrl: Boolean(env.baseUrl),
      hasApiKey: Boolean(env.apiKey),
    }),
  );
  process.exit(1);
}

const files = [];
const generatedFileById = new Map();
for (const concept of selectedConcepts) {
  console.log(`Generating ${concept.id}...`);
  const file = await generateOne(env, concept, size);
  files.push(file);
  generatedFileById.set(concept.id, file);
}

const metadataFiles = concepts
  .map((concept) => {
    const file = generatedFileById.get(concept.id) ?? findExistingOutputPath(concept);
    if (!file) {
      return null;
    }
    return {
      id: concept.id,
      title: concept.title,
      file,
      prompt: concept.prompt,
    };
  })
  .filter(Boolean);

writeFileSync(
  path.join(outDir, 'generation-metadata.json'),
  JSON.stringify(
    {
      model: 'gpt-image-2-all',
      size,
      generatedAt: new Date().toISOString(),
      styleReference: hasStyleReference ? styleReferencePath : null,
      generatedIds: selectedConcepts.map((concept) => concept.id),
      files: metadataFiles,
    },
    null,
    2,
  ),
);

console.log(JSON.stringify({ ok: true, count: files.length, files }, null, 2));