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

const repoRoot = process.cwd();
const outputDir = path.join(
  repoRoot,
  'public',
  'branding',
  'taonier-logo-squish-concepts',
);
const defaultTimeoutMs = 420000;

const concepts = [
  {
    id: 'taonier-squish-v2-pulse',
    title: '软泥合拍',
    prompt:
      '无文字扁平矢量 Logo，产品名“陶泥儿”。参考方向：上下两团抽象软泥轻快合拍，中间一颗星点被捏出来。不要画手、手指、掌纹，不要聊天气泡、笑脸、眼睛、花朵、播放键。整体年轻、主流、抽象、生动、像娱乐创作 App icon。上方珊瑚红软形，下方青绿软形，中央奶油白或金色星点，最多 3 色。形状简洁，小尺寸清晰。',
  },
  {
    id: 'taonier-squish-v2-bounce',
    title: '弹力成型',
    prompt:
      '无文字扁平矢量 Logo，产品名“陶泥儿”。图形由上下两块弹性的软泥豆形组成，中间留出弯曲的白色空间和一颗小星点，表达脑洞被轻轻一压就成型。要抽象、有动感、亲和，不像手、不像眼睛、不像聊天气泡。主流 App icon 风格，简洁、高识别。配色：亮珊瑚、薄荷青、奶油白，最多 3 色。禁止文字、字母、3D、褐色、碎元素。',
  },
  {
    id: 'taonier-squish-v2-spark-gap',
    title: '星隙合拍',
    prompt:
      '无文字扁平矢量 Logo，产品名“陶泥儿”。上下两团圆润软泥彼此靠近，中间形成一个自然的星形负空间，像灵感在缝隙中被捏出来。图形必须抽象、现代、活泼，不出现手、眼睛、嘴巴、聊天气泡、播放符号或花朵。适合 App icon，小尺寸一眼识别。配色：玫红 / 珊瑚红主上形，青绿色下形，奶白负形，最多 3 色。',
  },
  {
    id: 'taonier-squish-v2-comet',
    title: '合拍星流',
    prompt:
      '无文字扁平矢量 Logo，产品名“陶泥儿”。两个抽象软泥形上下错位合拍，中央小星点带出一条短短的流线，表达 AI 把脑洞捏成会传播的作品。风格轻快、年轻、抽象、生动，但不要像表情包或特效贴纸。禁止手、眼睛、聊天气泡、笑脸、花朵、播放键、褐色、3D、文字。配色：珊瑚红、青绿、奶白，最多 3 色，元素要少。',
  },
  {
    id: 'taonier-squish-v2-token',
    title: '成型软标',
    prompt:
      '无文字扁平矢量 Logo，产品名“陶泥儿”。把“软泥合拍”做得更像长期品牌主标：上下两块抽象软泥围成一个完整圆润符号，中间只有一颗小星或圆点，表达创作成型。不要手、眼睛、嘴巴、聊天气泡、播放键、花朵、褐色陶土、复杂碎片。主流、亲和、醒目、可记忆，App icon 风格。配色：珊瑚红、青绿、奶白，最多 3 色。',
  },
];

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

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 buildUrl(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 extractImageUrls(payload) {
  const urls = [];
  collectStringsByKey(payload, 'url', urls);
  collectStringsByKey(payload, 'image', urls);
  collectStringsByKey(payload, 'image_url', urls);
  return [...new Set(urls)].filter((url) => /^https?:\/\//u.test(url));
}

function extractBase64Images(payload) {
  const values = [];
  collectStringsByKey(payload, 'b64_json', values);
  return values;
}

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';
}

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 Buffer.from(await response.arrayBuffer());
  } catch (error) {
    if (error?.name === 'AbortError') {
      throw new Error(`Generated image download timed out after ${timeoutMs}ms`);
    }
    throw error;
  } finally {
    clearTimeout(timer);
  }
}

async function generateConcept(env, concept) {
  const requestBody = {
    model: 'gpt-image-2-all',
    prompt: concept.prompt,
    n: 1,
    size: '1024x1024',
  };
  const payload = await fetchJson(
    buildUrl(env.baseUrl),
    {
      method: 'POST',
      headers: {
        Authorization: `Bearer ${env.apiKey}`,
        Accept: 'application/json',
        'Content-Type': 'application/json',
      },
      body: JSON.stringify(requestBody),
    },
    env.timeoutMs,
  );

  const urls = extractImageUrls(payload);
  const b64Images = extractBase64Images(payload);
  let bytes;
  if (urls[0]) {
    bytes = await downloadUrl(urls[0], env.timeoutMs);
  } else if (b64Images[0]) {
    bytes = Buffer.from(b64Images[0], 'base64');
  } else {
    throw new Error(`VectorEngine returned no image for ${concept.id}`);
  }

  mkdirSync(outputDir, { recursive: true });
  const extension = inferExtensionFromBytes(bytes);
  const outputPath = path.join(outputDir, `${concept.id}.${extension}`);
  writeFileSync(outputPath, bytes);
  return outputPath;
}

const dryRun = args.has('--dry-run') || !args.has('--live');
const onlyIds = String(args.get('--only') || '')
  .split(',')
  .map((value) => value.trim())
  .filter(Boolean);
const selected = concepts.filter(
  (concept) => !onlyIds.length || onlyIds.includes(concept.id),
);

if (dryRun) {
  console.log(
    JSON.stringify(
      {
        mode: 'dry-run',
        outputDir,
        count: selected.length,
        requests: selected.map((concept) => ({
          id: concept.id,
          title: concept.title,
          body: {
            model: 'gpt-image-2-all',
            prompt: concept.prompt,
            n: 1,
            size: '1024x1024',
          },
        })),
      },
      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 generated = [];
for (const concept of selected) {
  console.log(`Generating ${concept.id}...`);
  generated.push(await generateConcept(env, concept));
}

console.log(
  JSON.stringify(
    {
      ok: true,
      count: generated.length,
      files: generated,
      verifiedFiles: readdirSync(outputDir).sort(),
    },
    null,
    2,
  ),
);