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-minimal-concepts', ); const defaultTimeoutMs = 420000; const concepts = [ { id: 'taonier-minimal-clay-core', title: '泥芯主标', prompt: '为中文产品“陶泥儿”设计一个无文字 Logo。方向是抽象陶泥角色 / 吉祥物,但不要人形,不要脸,不要手脚。主体是一枚极简陶泥胚,只有一个主轮廓、一个偏心孔或作品核、一个小星点,像会呼吸的陶泥主标。必须扁平、几何、简洁、亲和、主流 App icon 风格。配色:奶油白、陶土橙、深墨底、少量金色。禁止文字、字母、汉字、水印、复杂五官、聊天气泡、播放三角、儿童玩具、3D、厚阴影、背景场景。', }, { id: 'taonier-minimal-clay-token', title: '泥标小偶', prompt: '为“陶泥儿”设计无文字品牌 Logo。主体不是人物,而是一枚像被捏出来的软陶 token:圆润、稳定、边缘有手捏感,内部只有一个极简星核或孔洞,不要眼睛鼻子嘴巴。风格:flat vector mascot mark, simple, memorable, logo-ready, cute but mature. 配色限制在 3 色到 4 色:奶白、陶土橙、深墨、暖黄。禁止文字、字母、汉字、表情包、聊天气泡、播放按钮、真实陶艺工具、复杂碎片、3D、照片感。', }, { id: 'taonier-minimal-seed-glyph', title: '泥种图符', prompt: '为中文产品“陶泥儿”设计一个无文字 Logo 图标。主题是“抽象陶泥角色”,但造型不使用人体。图形像一颗被轻轻捏过的种子,或者一枚从模具里长出的泥符,轮廓简单,记忆点集中在一个偏心洞和一颗小星核。要求简洁、几何、扁平、可注册、适合 App icon。配色:奶油白主体、暖陶土点缀、深墨背景、少量金黄。禁止文字、字母、汉字、水印、五官、手脚、动物、聊天气泡、播放三角、厚阴影、3D、背景道具。', }, { id: 'taonier-minimal-mold-bud', title: '模胚小芽', prompt: '为“陶泥儿”设计无文字 Logo。主体像一枚从模具里鼓起来的陶泥小芽,只有一个主形、一个缺口、一个闪光点,不要人形,不要头像,不要复杂装饰。整体要像能代表 AI 创作、UGC 造物、轻休闲平台的品牌主标。风格:minimal flat mascot logo, clean, playful, premium, scalable. 配色:深墨、奶白、陶土橙、薄荷青或暖黄。禁止文字、字母、汉字、真实脸、聊天气泡、播放键、儿童卡通、3D、金属质感、摄影背景。', }, ]; 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, ), );