feat: refresh creation config and visual assets

2026-05-20 14:02:36 +08:00
parent 83e92fc3c4
commit ef09a23c35
509 changed files with 19470 additions and 43 deletions
--- a/scripts/generate-taonier-abstract-mascot-image2-logo-concepts.mjs
+++ b/scripts/generate-taonier-abstract-mascot-image2-logo-concepts.mjs
@@ -0,0 +1,330 @@
+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-abstract-mascot-image2-concepts',
+);
+const defaultTimeoutMs = 420000;
+
+const concepts = [
+  {
+    id: 'taonier-image2-clay-spirit-glyph',
+    title: '泥灵符号',
+    prompt:
+      '为中文产品“陶泥儿”设计一个无文字 Logo 图标。方向：陶泥人、陶泥手办、抽象角色 / 吉祥物，但不要做人体形象，也不要做完整角色插画。主体像一块被轻轻捏出生命感的陶泥符号：单一圆润剪影，内部一个极简星核或负形孔洞，只有很少的点状生命感。必须是扁平矢量、主流 App icon、简单几何、亲和、醒目、可记忆、小尺寸清晰。配色：奶油白主形、暖陶土橙点缀、深墨背景、少量金色星核。禁止文字、字母、汉字、水印、真实人形、手脚、复杂五官、聊天气泡、播放三角、儿童黏土课、3D、厚阴影、贴纸感。',
+  },
+  {
+    id: 'taonier-image2-pinched-seed-mascot',
+    title: '捏胚小偶',
+    prompt:
+      '为“陶泥儿”设计无文字品牌主标。把“陶泥小人 / 手办 / 吉祥物”的精神压缩成一个非人形的几何泥胚：像一颗被捏过的种子或软陶坯，带一点抽象生命感，但没有手、脚、头发、衣服。中心有一颗极简四角闪光星，表达 AI 把脑洞捏成作品。风格：flat vector mascot mark, modern, friendly, geometric, logo-ready, not illustration。颜色控制在 3 到 4 色：深墨、奶白、陶土橙、暖黄。禁止文字、字母、汉字、真实陶艺工具、儿童玩具、emoji 表情、聊天气泡、播放按钮、复杂装饰、立体渲染。',
+  },
+  {
+    id: 'taonier-image2-soft-totem-creature',
+    title: '软陶图灵',
+    prompt:
+      '为“陶泥儿”设计无文字 Logo。主体是一个抽象陶泥角色图腾，不是人，也不是动物，而是一枚软陶手办被极简化后的品牌符号：上窄下稳、边缘像手捏过，中央有一个圆形作品核和一个小泥点。要有吉祥物的亲和力，但更像成熟平台主标。风格：bold flat vector, iconic silhouette, playful premium, highly memorable, simple enough for favicon。配色：深色背景、奶油白大形、陶土橙作品核、薄荷青或金色小点。禁止中文英文、复杂脸、两只眼睛加嘴的头像感、人体、手、脚、聊天气泡、播放三角、3D 质感。',
+  },
+  {
+    id: 'taonier-image2-clay-pocket-token',
+    title: '口袋泥符',
+    prompt:
+      '为“陶泥儿”设计一个能做 App icon 的无文字主 Logo。方向是“抽象口袋陶泥手办”：它像一个可以被收藏的小软陶 token，但不能是具体人物。主图形由一个圆角几何泥块、一处被捏出的缺口、一枚小星核组成，轮廓要一眼能记住。气质年轻、Q、可爱但不幼稚，适合 AI UGC 轻休闲小游戏平台。扁平矢量感，少色，高对比。禁止文字、字母、水印、真实人脸、手脚、表情包、聊天气泡、播放按钮、过多小元素、3D、照片感。',
+  },
+  {
+    id: 'taonier-image2-work-core-puppet',
+    title: '作品泥偶',
+    prompt:
+      '为“陶泥儿”设计无文字 Logo 图标。把陶泥手办的收藏感、AI 创作的作品核、UGC 玩梗传播的轻松感融合成一个抽象泥偶符号。不要画成人体，只用几何软块和负形孔洞表现“像有生命的陶泥作品”。主体简单、厚实、圆润，中心一枚四角星或小圆核，最多两个辅助泥点。风格：minimal vector mascot logo, clean, premium cute, mainstream consumer app icon。颜色：奶白、陶土橙、深墨、暖黄，可少量青绿。禁止文字、英文、汉字、复杂背景、复杂五官、真实手办、玩具包装、儿童黏土、3D 厚重阴影。',
+  },
+  {
+    id: 'taonier-image2-mold-blob-companion',
+    title: '模团伙伴',
+    prompt:
+      '为“陶泥儿”做一个无文字 Logo 主标。方向：非人形抽象吉祥物，像一团被模具轻轻压出的陶泥伙伴。整体是一个简单几何软形，带一个偏心孔洞和一个小闪光星，让人感觉它能承载用户脑洞、生成小游戏作品。要求主流、亲和、可爱、扁平、矢量、识别强，不能像插画或头像。配色：深墨底、奶油白主体、陶土橙和暖黄点缀，最多 4 色。禁止文字、字母、汉字、水印、手脚、五官表情、聊天气泡、播放三角、复杂碎片、3D、真实陶泥照片。',
+  },
+];
+
+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',
+    quality: String(args.get('--quality') || 'low'),
+    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 limit = Number.parseInt(String(args.get('--limit') || '0'), 10);
+const selected = concepts
+  .filter((concept) => !onlyIds.length || onlyIds.includes(concept.id))
+  .slice(0, limit > 0 ? limit : concepts.length);
+
+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',
+            quality: String(args.get('--quality') || 'low'),
+            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,
+  ),
+);