Recognize more LobeHub-backed model brands so marketplace filters stop collapsing into other
Metapi was leaving many models under the uncategorized bucket even though the current LobeHub icon set already contains matching provider or vendor brands. This change moves brand detection into one shared registry, expands the rules with the user-reported gaps that have real upstream icon coverage, and makes server-side brand blocking reuse the same classification result as the web UI. Constraint: Existing workspace has unrelated in-progress edits, so this commit stages only the brand-classification slice Constraint: Brand matching must stay consistent between marketplace display and server-side blocked-brand filtering Rejected: Add more ad hoc rules separately in web and server files | would keep the drift bug alive Rejected: Blindly import every LobeHub slug as a model brand | would pollute filters with tool and app brands Confidence: high Scope-risk: moderate Reversibility: clean Directive: Keep new brand additions in src/server/shared/modelBrand.ts and let web/server consume that single source of truth Tested: npm test -- src/web/components/BrandIcon.test.ts src/server/services/brandMatcher.test.ts src/web/pages/Models.marketplace-text.test.tsx src/web/components/BrandIcon.architecture.test.ts src/web/components/BrandIcon.render.test.tsx Tested: npm run typecheck Tested: npm run repo:drift-check Not-tested: Live browser verification against the user's current marketplace dataset after deployment
This commit is contained in:
@@ -0,0 +1,41 @@
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import { describe, expect, it } from 'vitest';
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import { getAllBrandNames, getBlockedBrandRules, isModelBlockedByBrand } from './brandMatcher.js';
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describe('brandMatcher', () => {
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it('exposes newly supported provider and platform brands', () => {
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const brands = getAllBrandNames();
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expect(brands).toContain('OpenRouter');
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expect(brands).toContain('Groq');
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expect(brands).toContain('DeepInfra');
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expect(brands).toContain('Fireworks');
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expect(brands).toContain('Together AI');
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expect(brands).toContain('AI21 Labs');
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expect(brands).toContain('百川智能');
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expect(brands).toContain('Amazon Nova');
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expect(brands).toContain('百炼');
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expect(brands).toContain('Arcee');
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expect(brands).toContain('Xiaomi MiMo');
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expect(brands).toContain('LongCat');
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});
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it('deduplicates blocked brands and ignores unknown entries', () => {
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expect(getBlockedBrandRules(['OpenRouter', 'OpenRouter', 'Unknown Brand'])).toEqual(['OpenRouter']);
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});
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it('uses the shared frontend detection result for global brand blocking', () => {
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const providerRules = getBlockedBrandRules(['OpenRouter', 'Groq', '百炼', 'LongCat']);
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expect(isModelBlockedByBrand('openrouter/openrouter-auto', providerRules)).toBe(true);
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expect(isModelBlockedByBrand('groq/compound-beta', providerRules)).toBe(true);
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expect(isModelBlockedByBrand('dashscope/wanx2.1-t2i-turbo', providerRules)).toBe(true);
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expect(isModelBlockedByBrand('LongCat-Flash-Lite', providerRules)).toBe(true);
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const vendorRules = getBlockedBrandRules(['Anthropic', 'Meta', 'Google', 'OpenAI', 'Arcee', 'Xiaomi MiMo']);
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expect(isModelBlockedByBrand('openrouter/anthropic/claude-3-7-sonnet', vendorRules)).toBe(true);
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expect(isModelBlockedByBrand('deepinfra/meta-llama/llama-3.3-70b-instruct', vendorRules)).toBe(true);
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expect(isModelBlockedByBrand('vertexai/google/gemini-2.5-pro', vendorRules)).toBe(true);
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expect(isModelBlockedByBrand('azureai/gpt-4o', vendorRules)).toBe(true);
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expect(isModelBlockedByBrand('arcee-ai/trinity-mini', vendorRules)).toBe(true);
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expect(isModelBlockedByBrand('xiaomi/mimo-v2-pro', vendorRules)).toBe(true);
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});
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});
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@@ -1,273 +1,28 @@
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/**
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* Server-side brand matching for global brand filtering.
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*
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* Context-building logic is ported from the frontend BrandIcon.tsx
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* (collectBrandCandidates + buildMatchContext) to ensure identical
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* matching behavior between route display and rebuild filtering.
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*/
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import { getAllBrandNames as getSharedBrandNames, getBrand } from '../shared/modelBrand.js';
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type MatchMode = 'includes' | 'startsWith' | 'segment' | 'boundary';
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type KeywordRule = { keyword: string; mode: MatchMode };
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export type BlockedBrandRule = string;
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const BRAND_RULES: Record<string, KeywordRule[]> = {
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'OpenAI': [
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{ keyword: 'gpt', mode: 'startsWith' },
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{ keyword: 'chatgpt', mode: 'startsWith' },
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{ keyword: 'dall-e', mode: 'startsWith' },
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{ keyword: 'whisper', mode: 'startsWith' },
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{ keyword: 'text-embedding', mode: 'startsWith' },
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{ keyword: 'text-moderation', mode: 'startsWith' },
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{ keyword: 'davinci', mode: 'startsWith' },
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{ keyword: 'babbage', mode: 'startsWith' },
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{ keyword: 'codex-mini', mode: 'startsWith' },
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{ keyword: 'o1', mode: 'startsWith' },
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{ keyword: 'o3', mode: 'startsWith' },
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{ keyword: 'o4', mode: 'startsWith' },
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{ keyword: 'tts', mode: 'startsWith' },
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],
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'Anthropic': [
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{ keyword: 'claude', mode: 'includes' },
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],
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'Google': [
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{ keyword: 'gemini', mode: 'includes' },
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{ keyword: 'gemma', mode: 'includes' },
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{ keyword: 'google/', mode: 'includes' },
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{ keyword: 'palm', mode: 'includes' },
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{ keyword: 'paligemma', mode: 'includes' },
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{ keyword: 'shieldgemma', mode: 'includes' },
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{ keyword: 'recurrentgemma', mode: 'includes' },
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{ keyword: 'deplot', mode: 'includes' },
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{ keyword: 'codegemma', mode: 'includes' },
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{ keyword: 'imagen', mode: 'includes' },
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{ keyword: 'learnlm', mode: 'includes' },
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{ keyword: 'aqa', mode: 'includes' },
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{ keyword: 'veo', mode: 'startsWith' },
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],
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'DeepSeek': [
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{ keyword: 'deepseek', mode: 'includes' },
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{ keyword: 'ds-chat', mode: 'segment' },
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],
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'通义千问': [
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{ keyword: 'qwen', mode: 'includes' },
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{ keyword: 'qwq', mode: 'includes' },
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{ keyword: 'tongyi', mode: 'includes' },
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],
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'智谱 AI': [
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{ keyword: 'glm', mode: 'includes' },
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{ keyword: 'chatglm', mode: 'includes' },
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{ keyword: 'codegeex', mode: 'includes' },
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{ keyword: 'cogview', mode: 'includes' },
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{ keyword: 'cogvideo', mode: 'includes' },
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],
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'Meta': [
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{ keyword: 'llama', mode: 'includes' },
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{ keyword: 'code-llama', mode: 'includes' },
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{ keyword: 'codellama', mode: 'includes' },
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],
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'Mistral': [
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{ keyword: 'mistral', mode: 'includes' },
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{ keyword: 'mixtral', mode: 'includes' },
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{ keyword: 'codestral', mode: 'includes' },
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{ keyword: 'pixtral', mode: 'includes' },
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{ keyword: 'ministral', mode: 'includes' },
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{ keyword: 'voxtral', mode: 'includes' },
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{ keyword: 'magistral', mode: 'includes' },
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],
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'Moonshot': [
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{ keyword: 'moonshot', mode: 'includes' },
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{ keyword: 'kimi', mode: 'includes' },
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],
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'零一万物': [
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{ keyword: 'yi-', mode: 'startsWith' },
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{ keyword: 'yi', mode: 'boundary' },
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],
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'文心一言': [
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{ keyword: 'ernie', mode: 'includes' },
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{ keyword: 'eb-', mode: 'includes' },
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],
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'讯飞星火': [
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{ keyword: 'spark', mode: 'includes' },
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{ keyword: 'generalv', mode: 'includes' },
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],
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'腾讯混元': [
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{ keyword: 'hunyuan', mode: 'includes' },
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{ keyword: 'tencent-hunyuan', mode: 'includes' },
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],
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'豆包': [
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{ keyword: 'doubao', mode: 'includes' },
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],
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'MiniMax': [
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{ keyword: 'minimax', mode: 'includes' },
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{ keyword: 'abab', mode: 'includes' },
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{ keyword: 'mini2.1', mode: 'segment' },
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],
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'Cohere': [
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{ keyword: 'command', mode: 'includes' },
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{ keyword: 'c4ai-', mode: 'includes' },
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{ keyword: 'embed-', mode: 'startsWith' },
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],
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'Microsoft': [
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{ keyword: 'microsoft/', mode: 'includes' },
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{ keyword: 'phi-', mode: 'includes' },
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{ keyword: 'kosmos', mode: 'includes' },
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{ keyword: 'phi4', mode: 'segment' },
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],
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'xAI': [
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{ keyword: 'grok', mode: 'includes' },
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],
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'阶跃星辰': [
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{ keyword: 'stepfun', mode: 'includes' },
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{ keyword: 'step-', mode: 'startsWith' },
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{ keyword: 'step3', mode: 'startsWith' },
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],
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'Stability': [
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{ keyword: 'flux', mode: 'includes' },
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{ keyword: 'stablediffusion', mode: 'includes' },
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{ keyword: 'stable-diffusion', mode: 'includes' },
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{ keyword: 'sdxl', mode: 'includes' },
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{ keyword: 'sd3', mode: 'startsWith' },
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],
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'NVIDIA': [
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{ keyword: 'nvidia/', mode: 'includes' },
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{ keyword: 'nvclip', mode: 'includes' },
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{ keyword: 'nemotron', mode: 'includes' },
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{ keyword: 'nemoretriever', mode: 'includes' },
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{ keyword: 'neva', mode: 'includes' },
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{ keyword: 'riva-translate', mode: 'includes' },
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{ keyword: 'cosmos', mode: 'includes' },
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{ keyword: 'nv-', mode: 'startsWith' },
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],
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'IBM': [
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{ keyword: 'ibm/', mode: 'includes' },
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{ keyword: 'granite', mode: 'includes' },
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],
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'BAAI': [
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{ keyword: 'baai/', mode: 'includes' },
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{ keyword: 'bge-', mode: 'includes' },
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],
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'ByteDance': [
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{ keyword: 'bytedance', mode: 'includes' },
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{ keyword: 'seed-oss', mode: 'includes' },
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{ keyword: 'kolors', mode: 'includes' },
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{ keyword: 'kwai', mode: 'includes' },
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{ keyword: 'kwaipilot', mode: 'includes' },
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{ keyword: 'wan-', mode: 'startsWith' },
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{ keyword: 'kat-', mode: 'startsWith' },
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],
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'InternLM': [
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{ keyword: 'internlm', mode: 'includes' },
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],
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'Midjourney': [
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{ keyword: 'midjourney', mode: 'includes' },
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{ keyword: 'mj_', mode: 'startsWith' },
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],
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'DeepL': [
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{ keyword: 'deepl/', mode: 'includes' },
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{ keyword: 'deepl-', mode: 'startsWith' },
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],
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'Jina AI': [
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{ keyword: 'jina', mode: 'includes' },
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],
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};
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// ── Context building (ported from frontend BrandIcon.tsx) ──
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function stripCommonWrappers(value: string): string {
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return value
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.replace(/^(?:\[[^\]]+\]|【[^】]+】)\s*/g, '')
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.replace(/^re:\s*/g, '')
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.replace(/^\^+/, '')
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.replace(/\$+$/, '')
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.trim();
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}
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/**
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* Recursively split model name on `/`, `:`, `,` to build all candidate strings.
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* Mirrors the frontend collectBrandCandidates exactly.
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*/
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function collectCandidates(modelName: string): string[] {
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const queue: string[] = [];
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const seen = new Set<string>();
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const push = (value: string) => {
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const normalized = value.trim().toLowerCase();
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if (!normalized || seen.has(normalized)) return;
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seen.add(normalized);
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queue.push(normalized);
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};
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push(modelName);
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for (let i = 0; i < queue.length; i++) {
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const candidate = queue[i]!;
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const cleaned = stripCommonWrappers(candidate);
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push(cleaned);
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if (cleaned.includes('/')) for (const part of cleaned.split('/')) push(part);
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if (cleaned.includes(':')) for (const part of cleaned.split(':')) push(part);
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if (cleaned.includes(',')) for (const part of cleaned.split(',')) push(part);
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}
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return queue;
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}
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type MatchContext = {
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raw: string; // first candidate (normalized full name)
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candidates: string[]; // all candidates from recursive splitting
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segments: string[]; // candidates split on /,:,\s (NOT on - or _)
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};
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function buildMatchContext(modelName: string): MatchContext {
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const candidates = collectCandidates(modelName);
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const raw = candidates[0] || modelName.trim().toLowerCase();
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// Segments split on /,:,whitespace only — NOT on - or _ (matches frontend)
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const segments = Array.from(new Set(
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candidates
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.flatMap((c) => c.split(/[/:,\s]+/g))
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.map((s) => s.trim())
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.filter(Boolean),
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));
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return { raw, candidates, segments };
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}
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// ── Matching functions (mirror frontend includesAny / startsWithAny / hasExactSegment / matchesBoundary) ──
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function matchesRule(ctx: MatchContext, rule: KeywordRule): boolean {
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switch (rule.mode) {
|
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case 'includes':
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return ctx.raw.includes(rule.keyword)
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|| ctx.candidates.some((c) => c.includes(rule.keyword));
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case 'startsWith':
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return ctx.raw.startsWith(rule.keyword)
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|| ctx.segments.some((s) => s.startsWith(rule.keyword))
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|| ctx.candidates.some((c) => c.startsWith(rule.keyword));
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case 'segment':
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return ctx.segments.includes(rule.keyword);
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case 'boundary': {
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const pattern = new RegExp(`(^|[/:_\\-\\s])${rule.keyword}(?=$|[/:_\\-\\s])`);
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return pattern.test(ctx.raw) || ctx.candidates.some((c) => pattern.test(c));
|
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}
|
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default:
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return false;
|
||||
}
|
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}
|
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|
||||
// ── Public API ──
|
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const KNOWN_BRANDS = new Set(getSharedBrandNames());
|
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const KNOWN_BRAND_LIST = Array.from(KNOWN_BRANDS);
|
||||
|
||||
export function getAllBrandNames(): string[] {
|
||||
return Object.keys(BRAND_RULES);
|
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return KNOWN_BRAND_LIST;
|
||||
}
|
||||
|
||||
export function getBlockedBrandRules(blockedBrands: string[]): KeywordRule[] {
|
||||
const rules: KeywordRule[] = [];
|
||||
export function getBlockedBrandRules(blockedBrands: string[]): BlockedBrandRule[] {
|
||||
const seen = new Set<string>();
|
||||
const rules: string[] = [];
|
||||
for (const brand of blockedBrands) {
|
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const brandRules = BRAND_RULES[brand];
|
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if (brandRules) rules.push(...brandRules);
|
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const normalized = String(brand || '').trim();
|
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if (!normalized || seen.has(normalized) || !KNOWN_BRANDS.has(normalized)) continue;
|
||||
seen.add(normalized);
|
||||
rules.push(normalized);
|
||||
}
|
||||
return rules;
|
||||
}
|
||||
|
||||
export function isModelBlockedByBrand(modelName: string, rules: KeywordRule[]): boolean {
|
||||
export function isModelBlockedByBrand(modelName: string, rules: BlockedBrandRule[]): boolean {
|
||||
if (!modelName || rules.length === 0) return false;
|
||||
const ctx = buildMatchContext(modelName);
|
||||
if (!ctx.raw) return false;
|
||||
return rules.some((rule) => matchesRule(ctx, rule));
|
||||
const brand = getBrand(modelName);
|
||||
return !!brand && rules.includes(brand.name);
|
||||
}
|
||||
|
||||
@@ -0,0 +1,806 @@
|
||||
export interface BrandMatchContext {
|
||||
raw: string;
|
||||
cleaned: string;
|
||||
segments: string[];
|
||||
candidates: string[];
|
||||
}
|
||||
|
||||
export interface BrandInfo {
|
||||
name: string;
|
||||
icon: string;
|
||||
color: string;
|
||||
}
|
||||
|
||||
export type BrandMatchMode = 'includes' | 'startsWith' | 'segment' | 'boundary';
|
||||
|
||||
type BrandRule = {
|
||||
keyword: string;
|
||||
mode: BrandMatchMode;
|
||||
};
|
||||
|
||||
type BrandDefinition = BrandInfo & {
|
||||
rules: BrandRule[];
|
||||
};
|
||||
|
||||
const BRAND_DEFINITIONS: BrandDefinition[] = [
|
||||
{
|
||||
name: 'OpenAI',
|
||||
icon: 'openai',
|
||||
color: 'linear-gradient(135deg, #10a37f, #1a7f5a)',
|
||||
rules: [
|
||||
{ keyword: 'gpt', mode: 'startsWith' },
|
||||
{ keyword: 'chatgpt', mode: 'startsWith' },
|
||||
{ keyword: 'dall-e', mode: 'startsWith' },
|
||||
{ keyword: 'whisper', mode: 'startsWith' },
|
||||
{ keyword: 'text-embedding', mode: 'startsWith' },
|
||||
{ keyword: 'text-moderation', mode: 'startsWith' },
|
||||
{ keyword: 'davinci', mode: 'startsWith' },
|
||||
{ keyword: 'babbage', mode: 'startsWith' },
|
||||
{ keyword: 'codex-mini', mode: 'startsWith' },
|
||||
{ keyword: 'o1', mode: 'startsWith' },
|
||||
{ keyword: 'o3', mode: 'startsWith' },
|
||||
{ keyword: 'o4', mode: 'startsWith' },
|
||||
{ keyword: 'tts', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Anthropic',
|
||||
icon: 'claude-color',
|
||||
color: 'linear-gradient(135deg, #d4a574, #c4956a)',
|
||||
rules: [
|
||||
{ keyword: 'claude', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Google',
|
||||
icon: 'gemini-color',
|
||||
color: 'linear-gradient(135deg, #4285f4, #34a853)',
|
||||
rules: [
|
||||
{ keyword: 'gemini', mode: 'includes' },
|
||||
{ keyword: 'gemma', mode: 'includes' },
|
||||
{ keyword: 'google/', mode: 'includes' },
|
||||
{ keyword: 'palm', mode: 'includes' },
|
||||
{ keyword: 'paligemma', mode: 'includes' },
|
||||
{ keyword: 'shieldgemma', mode: 'includes' },
|
||||
{ keyword: 'recurrentgemma', mode: 'includes' },
|
||||
{ keyword: 'deplot', mode: 'includes' },
|
||||
{ keyword: 'codegemma', mode: 'includes' },
|
||||
{ keyword: 'imagen', mode: 'includes' },
|
||||
{ keyword: 'learnlm', mode: 'includes' },
|
||||
{ keyword: 'aqa', mode: 'includes' },
|
||||
{ keyword: 'veo', mode: 'startsWith' },
|
||||
{ keyword: 'google/', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'DeepSeek',
|
||||
icon: 'deepseek-color',
|
||||
color: 'linear-gradient(135deg, #4d6bfe, #44a3ec)',
|
||||
rules: [
|
||||
{ keyword: 'deepseek', mode: 'includes' },
|
||||
{ keyword: 'ds-chat', mode: 'segment' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '通义千问',
|
||||
icon: 'qwen-color',
|
||||
color: 'linear-gradient(135deg, #615cf7, #9b8afb)',
|
||||
rules: [
|
||||
{ keyword: 'qwen', mode: 'includes' },
|
||||
{ keyword: 'qwq', mode: 'includes' },
|
||||
{ keyword: 'tongyi', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '智谱 AI',
|
||||
icon: 'zhipu-color',
|
||||
color: 'linear-gradient(135deg, #3b6cf5, #6366f1)',
|
||||
rules: [
|
||||
{ keyword: 'glm', mode: 'includes' },
|
||||
{ keyword: 'chatglm', mode: 'includes' },
|
||||
{ keyword: 'codegeex', mode: 'includes' },
|
||||
{ keyword: 'cogview', mode: 'includes' },
|
||||
{ keyword: 'cogvideo', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Meta',
|
||||
icon: 'meta-color',
|
||||
color: 'linear-gradient(135deg, #0668E1, #1877f2)',
|
||||
rules: [
|
||||
{ keyword: 'llama', mode: 'includes' },
|
||||
{ keyword: 'code-llama', mode: 'includes' },
|
||||
{ keyword: 'codellama', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Mistral',
|
||||
icon: 'mistral-color',
|
||||
color: 'linear-gradient(135deg, #f7d046, #f2a900)',
|
||||
rules: [
|
||||
{ keyword: 'mistral', mode: 'includes' },
|
||||
{ keyword: 'mixtral', mode: 'includes' },
|
||||
{ keyword: 'codestral', mode: 'includes' },
|
||||
{ keyword: 'pixtral', mode: 'includes' },
|
||||
{ keyword: 'ministral', mode: 'includes' },
|
||||
{ keyword: 'voxtral', mode: 'includes' },
|
||||
{ keyword: 'magistral', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Moonshot',
|
||||
icon: 'moonshot',
|
||||
color: 'linear-gradient(135deg, #000000, #333333)',
|
||||
rules: [
|
||||
{ keyword: 'moonshot', mode: 'includes' },
|
||||
{ keyword: 'kimi', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '零一万物',
|
||||
icon: 'yi-color',
|
||||
color: 'linear-gradient(135deg, #1d4ed8, #3b82f6)',
|
||||
rules: [
|
||||
{ keyword: 'yi-', mode: 'startsWith' },
|
||||
{ keyword: 'yi', mode: 'boundary' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '文心一言',
|
||||
icon: 'wenxin-color',
|
||||
color: 'linear-gradient(135deg, #2932e1, #4468f2)',
|
||||
rules: [
|
||||
{ keyword: 'ernie', mode: 'includes' },
|
||||
{ keyword: 'eb-', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '讯飞星火',
|
||||
icon: 'spark-color',
|
||||
color: 'linear-gradient(135deg, #0070f3, #00d4ff)',
|
||||
rules: [
|
||||
{ keyword: 'spark', mode: 'includes' },
|
||||
{ keyword: 'generalv', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '腾讯混元',
|
||||
icon: 'hunyuan-color',
|
||||
color: 'linear-gradient(135deg, #00b7ff, #0052d9)',
|
||||
rules: [
|
||||
{ keyword: 'hunyuan', mode: 'includes' },
|
||||
{ keyword: 'tencent-hunyuan', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '豆包',
|
||||
icon: 'doubao-color',
|
||||
color: 'linear-gradient(135deg, #3b5bdb, #7048e8)',
|
||||
rules: [
|
||||
{ keyword: 'doubao', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'MiniMax',
|
||||
icon: 'minimax-color',
|
||||
color: 'linear-gradient(135deg, #6366f1, #818cf8)',
|
||||
rules: [
|
||||
{ keyword: 'minimax', mode: 'includes' },
|
||||
{ keyword: 'abab', mode: 'includes' },
|
||||
{ keyword: 'mini2.1', mode: 'segment' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Cohere',
|
||||
icon: 'cohere-color',
|
||||
color: 'linear-gradient(135deg, #39594d, #5ba77f)',
|
||||
rules: [
|
||||
{ keyword: 'command', mode: 'includes' },
|
||||
{ keyword: 'c4ai-', mode: 'includes' },
|
||||
{ keyword: 'aya', mode: 'includes' },
|
||||
{ keyword: 'embed-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Microsoft',
|
||||
icon: 'microsoft-color',
|
||||
color: 'linear-gradient(135deg, #00bcf2, #0078d4)',
|
||||
rules: [
|
||||
{ keyword: 'microsoft/', mode: 'includes' },
|
||||
{ keyword: 'phi-', mode: 'includes' },
|
||||
{ keyword: 'kosmos', mode: 'includes' },
|
||||
{ keyword: 'phi4', mode: 'segment' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'xAI',
|
||||
icon: 'xai',
|
||||
color: 'linear-gradient(135deg, #111, #444)',
|
||||
rules: [
|
||||
{ keyword: 'grok', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '阶跃星辰',
|
||||
icon: 'stepfun-color',
|
||||
color: 'linear-gradient(135deg, #0066ff, #3399ff)',
|
||||
rules: [
|
||||
{ keyword: 'stepfun', mode: 'includes' },
|
||||
{ keyword: 'step-', mode: 'startsWith' },
|
||||
{ keyword: 'step3', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '百川智能',
|
||||
icon: 'baichuan-color',
|
||||
color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
|
||||
rules: [
|
||||
{ keyword: 'baichuan', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'AI21 Labs',
|
||||
icon: 'ai21-brand-color',
|
||||
color: 'linear-gradient(135deg, #7c3aed, #a855f7)',
|
||||
rules: [
|
||||
{ keyword: 'ai21', mode: 'includes' },
|
||||
{ keyword: 'jamba', mode: 'startsWith' },
|
||||
{ keyword: 'jamba', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'AI2',
|
||||
icon: 'ai2-color',
|
||||
color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
|
||||
rules: [
|
||||
{ keyword: 'allenai', mode: 'includes' },
|
||||
{ keyword: 'olmo', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Amazon Nova',
|
||||
icon: 'nova',
|
||||
color: 'linear-gradient(135deg, #f59e0b, #f97316)',
|
||||
rules: [
|
||||
{ keyword: 'amazon/nova', mode: 'startsWith' },
|
||||
{ keyword: 'amazon.nova', mode: 'includes' },
|
||||
{ keyword: 'us.amazon.nova', mode: 'includes' },
|
||||
{ keyword: 'nova-', mode: 'startsWith' },
|
||||
{ keyword: 'nova-lite', mode: 'startsWith' },
|
||||
{ keyword: 'nova-pro', mode: 'startsWith' },
|
||||
{ keyword: 'nova-micro', mode: 'startsWith' },
|
||||
{ keyword: 'nova-canvas', mode: 'startsWith' },
|
||||
{ keyword: 'nova-reel', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Stability',
|
||||
icon: 'stability-color',
|
||||
color: 'linear-gradient(135deg, #8b5cf6, #a855f7)',
|
||||
rules: [
|
||||
{ keyword: 'flux', mode: 'includes' },
|
||||
{ keyword: 'stablediffusion', mode: 'includes' },
|
||||
{ keyword: 'stable-diffusion', mode: 'includes' },
|
||||
{ keyword: 'sdxl', mode: 'includes' },
|
||||
{ keyword: 'sd3', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'NVIDIA',
|
||||
icon: 'nvidia-color',
|
||||
color: 'linear-gradient(135deg, #76b900, #4a8c0b)',
|
||||
rules: [
|
||||
{ keyword: 'nvidia/', mode: 'includes' },
|
||||
{ keyword: 'nvclip', mode: 'includes' },
|
||||
{ keyword: 'nemotron', mode: 'includes' },
|
||||
{ keyword: 'nemoretriever', mode: 'includes' },
|
||||
{ keyword: 'neva', mode: 'includes' },
|
||||
{ keyword: 'riva-translate', mode: 'includes' },
|
||||
{ keyword: 'cosmos', mode: 'includes' },
|
||||
{ keyword: 'nv-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'IBM',
|
||||
icon: 'ibm',
|
||||
color: 'linear-gradient(135deg, #0f62fe, #4589ff)',
|
||||
rules: [
|
||||
{ keyword: 'ibm/', mode: 'includes' },
|
||||
{ keyword: 'granite', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'BAAI',
|
||||
icon: 'baai',
|
||||
color: 'linear-gradient(135deg, #111827, #374151)',
|
||||
rules: [
|
||||
{ keyword: 'baai/', mode: 'includes' },
|
||||
{ keyword: 'bge-', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'ByteDance',
|
||||
icon: 'bytedance-color',
|
||||
color: 'linear-gradient(135deg, #325ab4, #0f66ff)',
|
||||
rules: [
|
||||
{ keyword: 'bytedance', mode: 'includes' },
|
||||
{ keyword: 'seed-oss', mode: 'includes' },
|
||||
{ keyword: 'kolors', mode: 'includes' },
|
||||
{ keyword: 'kwai', mode: 'includes' },
|
||||
{ keyword: 'kwaipilot', mode: 'includes' },
|
||||
{ keyword: 'wan-', mode: 'startsWith' },
|
||||
{ keyword: 'kat-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'InternLM',
|
||||
icon: 'internlm-color',
|
||||
color: 'linear-gradient(135deg, #1b3882, #4063c5)',
|
||||
rules: [
|
||||
{ keyword: 'internlm', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Midjourney',
|
||||
icon: 'midjourney',
|
||||
color: 'linear-gradient(135deg, #4c6ef5, #748ffc)',
|
||||
rules: [
|
||||
{ keyword: 'midjourney', mode: 'includes' },
|
||||
{ keyword: 'mj_', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'DeepL',
|
||||
icon: 'deepl-color',
|
||||
color: 'linear-gradient(135deg, #0f2b46, #21476f)',
|
||||
rules: [
|
||||
{ keyword: 'deepl-', mode: 'startsWith' },
|
||||
{ keyword: 'deepl/', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Jina AI',
|
||||
icon: 'jina',
|
||||
color: 'linear-gradient(135deg, #111827, #4b5563)',
|
||||
rules: [
|
||||
{ keyword: 'jina', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Relace',
|
||||
icon: 'relace',
|
||||
color: 'linear-gradient(135deg, #7c3aed, #6366f1)',
|
||||
rules: [
|
||||
{ keyword: 'relace', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Arcee',
|
||||
icon: 'arcee-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #60a5fa)',
|
||||
rules: [
|
||||
{ keyword: 'arcee-ai', mode: 'includes' },
|
||||
{ keyword: 'arcee', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'AionLabs',
|
||||
icon: 'aionlabs-color',
|
||||
color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
|
||||
rules: [
|
||||
{ keyword: 'aion-labs', mode: 'includes' },
|
||||
{ keyword: 'aionlabs', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'DeepCogito',
|
||||
icon: 'deepcogito-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #7c3aed)',
|
||||
rules: [
|
||||
{ keyword: 'deepcogito', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Essential AI',
|
||||
icon: 'essentialai-color',
|
||||
color: 'linear-gradient(135deg, #0f172a, #334155)',
|
||||
rules: [
|
||||
{ keyword: 'essentialai', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Inception',
|
||||
icon: 'inception',
|
||||
color: 'linear-gradient(135deg, #7c3aed, #ec4899)',
|
||||
rules: [
|
||||
{ keyword: 'inception', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Inflection',
|
||||
icon: 'inflection',
|
||||
color: 'linear-gradient(135deg, #1d4ed8, #2563eb)',
|
||||
rules: [
|
||||
{ keyword: 'inflection', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Liquid AI',
|
||||
icon: 'liquid',
|
||||
color: 'linear-gradient(135deg, #0f172a, #475569)',
|
||||
rules: [
|
||||
{ keyword: 'liquid', mode: 'includes' },
|
||||
{ keyword: 'lfm-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'LongCat',
|
||||
icon: 'longcat-color',
|
||||
color: 'linear-gradient(135deg, #f97316, #fb7185)',
|
||||
rules: [
|
||||
{ keyword: 'longcat', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Morph',
|
||||
icon: 'morph-color',
|
||||
color: 'linear-gradient(135deg, #4f46e5, #8b5cf6)',
|
||||
rules: [
|
||||
{ keyword: 'morph/', mode: 'includes' },
|
||||
{ keyword: 'morph-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Nous Research',
|
||||
icon: 'nousresearch',
|
||||
color: 'linear-gradient(135deg, #111827, #4b5563)',
|
||||
rules: [
|
||||
{ keyword: 'nousresearch', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Upstage',
|
||||
icon: 'upstage-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #14b8a6)',
|
||||
rules: [
|
||||
{ keyword: 'upstage', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Xiaomi MiMo',
|
||||
icon: 'xiaomimimo',
|
||||
color: 'linear-gradient(135deg, #f97316, #fb923c)',
|
||||
rules: [
|
||||
{ keyword: 'xiaomi/mimo', mode: 'includes' },
|
||||
{ keyword: 'xiaomimimo', mode: 'includes' },
|
||||
{ keyword: 'mimo-v', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Z.ai',
|
||||
icon: 'zai',
|
||||
color: 'linear-gradient(135deg, #0f172a, #2563eb)',
|
||||
rules: [
|
||||
{ keyword: '2zai', mode: 'startsWith' },
|
||||
{ keyword: 'z-ai', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'SenseNova',
|
||||
icon: 'sensenova-brand-color',
|
||||
color: 'linear-gradient(135deg, #f59e0b, #f97316)',
|
||||
rules: [
|
||||
{ keyword: 'sensenova', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Perplexity',
|
||||
icon: 'perplexity-color',
|
||||
color: 'linear-gradient(135deg, #0f766e, #14b8a6)',
|
||||
rules: [
|
||||
{ keyword: 'perplexity', mode: 'includes' },
|
||||
{ keyword: 'pplx-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'OpenRouter',
|
||||
icon: 'openrouter',
|
||||
color: 'linear-gradient(135deg, #7c3aed, #2563eb)',
|
||||
rules: [
|
||||
{ keyword: 'openrouter', mode: 'includes' },
|
||||
{ keyword: 'openrouter-', mode: 'startsWith' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Groq',
|
||||
icon: 'groq',
|
||||
color: 'linear-gradient(135deg, #111827, #374151)',
|
||||
rules: [
|
||||
{ keyword: 'groq', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Fireworks',
|
||||
icon: 'fireworks-color',
|
||||
color: 'linear-gradient(135deg, #fb7185, #f97316)',
|
||||
rules: [
|
||||
{ keyword: 'fireworks-ai', mode: 'includes' },
|
||||
{ keyword: 'fireworks', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'DeepInfra',
|
||||
icon: 'deepinfra-color',
|
||||
color: 'linear-gradient(135deg, #4f46e5, #7c3aed)',
|
||||
rules: [
|
||||
{ keyword: 'deepinfra', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Together AI',
|
||||
icon: 'together-brand-color',
|
||||
color: 'linear-gradient(135deg, #7c3aed, #ec4899)',
|
||||
rules: [
|
||||
{ keyword: 'together.ai', mode: 'includes' },
|
||||
{ keyword: 'together', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Replicate',
|
||||
icon: 'replicate-brand',
|
||||
color: 'linear-gradient(135deg, #111827, #6366f1)',
|
||||
rules: [
|
||||
{ keyword: 'replicate', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'SambaNova',
|
||||
icon: 'sambanova-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #06b6d4)',
|
||||
rules: [
|
||||
{ keyword: 'sambanova', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Cerebras',
|
||||
icon: 'cerebras-brand-color',
|
||||
color: 'linear-gradient(135deg, #0f766e, #65a30d)',
|
||||
rules: [
|
||||
{ keyword: 'cerebras', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Ollama',
|
||||
icon: 'ollama',
|
||||
color: 'linear-gradient(135deg, #1f2937, #4b5563)',
|
||||
rules: [
|
||||
{ keyword: 'ollama', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'ModelScope',
|
||||
icon: 'modelscope-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #60a5fa)',
|
||||
rules: [
|
||||
{ keyword: 'modelscope', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'SiliconCloud',
|
||||
icon: 'siliconcloud-color',
|
||||
color: 'linear-gradient(135deg, #0ea5e9, #22d3ee)',
|
||||
rules: [
|
||||
{ keyword: 'siliconcloud', mode: 'includes' },
|
||||
{ keyword: 'siliconflow', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Azure AI',
|
||||
icon: 'azureai-color',
|
||||
color: 'linear-gradient(135deg, #0284c7, #2563eb)',
|
||||
rules: [
|
||||
{ keyword: 'azureai', mode: 'includes' },
|
||||
{ keyword: 'azure-openai', mode: 'includes' },
|
||||
{ keyword: 'azure/openai', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'AWS Bedrock',
|
||||
icon: 'bedrock-color',
|
||||
color: 'linear-gradient(135deg, #f59e0b, #f97316)',
|
||||
rules: [
|
||||
{ keyword: 'bedrock', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Vertex AI',
|
||||
icon: 'vertexai-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #6366f1)',
|
||||
rules: [
|
||||
{ keyword: 'vertexai', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: 'Google Cloud',
|
||||
icon: 'googlecloud-brand-color',
|
||||
color: 'linear-gradient(135deg, #4285f4, #34a853)',
|
||||
rules: [
|
||||
{ keyword: 'googlecloud', mode: 'includes' },
|
||||
{ keyword: 'google-cloud', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '百度智能云',
|
||||
icon: 'baiducloud-color',
|
||||
color: 'linear-gradient(135deg, #2563eb, #38bdf8)',
|
||||
rules: [
|
||||
{ keyword: 'baiducloud', mode: 'includes' },
|
||||
{ keyword: 'qianfan', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '百炼',
|
||||
icon: 'bailian-color',
|
||||
color: 'linear-gradient(135deg, #7c3aed, #2563eb)',
|
||||
rules: [
|
||||
{ keyword: 'bailian', mode: 'includes' },
|
||||
{ keyword: 'dashscope', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '阿里云',
|
||||
icon: 'alibabacloud-color',
|
||||
color: 'linear-gradient(135deg, #f97316, #fb923c)',
|
||||
rules: [
|
||||
{ keyword: 'alibabacloud', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '火山引擎',
|
||||
icon: 'volcengine-color',
|
||||
color: 'linear-gradient(135deg, #325ab4, #0f66ff)',
|
||||
rules: [
|
||||
{ keyword: 'volcengine', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
{
|
||||
name: '七牛云',
|
||||
icon: 'qiniu-color',
|
||||
color: 'linear-gradient(135deg, #06b6d4, #0891b2)',
|
||||
rules: [
|
||||
{ keyword: 'qiniu', mode: 'includes' },
|
||||
],
|
||||
},
|
||||
];
|
||||
|
||||
function normalizeInput(value: string): string {
|
||||
return String(value || '').trim().toLowerCase();
|
||||
}
|
||||
|
||||
export function stripCommonWrappers(value: string): string {
|
||||
return value
|
||||
.replace(/^(?:\[[^\]]+\]|【[^】]+】)\s*/g, '')
|
||||
.replace(/^re:\s*/g, '')
|
||||
.replace(/^\^+/, '')
|
||||
.replace(/\$+$/, '')
|
||||
.trim();
|
||||
}
|
||||
|
||||
export function collectBrandCandidates(modelName: string): string[] {
|
||||
const queue: string[] = [];
|
||||
const seen = new Set<string>();
|
||||
const push = (value: string) => {
|
||||
const normalized = normalizeInput(value);
|
||||
if (!normalized || seen.has(normalized)) return;
|
||||
seen.add(normalized);
|
||||
queue.push(normalized);
|
||||
};
|
||||
|
||||
push(modelName);
|
||||
|
||||
for (let index = 0; index < queue.length; index += 1) {
|
||||
const candidate = queue[index]!;
|
||||
const cleaned = stripCommonWrappers(candidate);
|
||||
push(cleaned);
|
||||
|
||||
if (cleaned.includes('/')) {
|
||||
for (const part of cleaned.split('/')) push(part);
|
||||
}
|
||||
if (cleaned.includes(':')) {
|
||||
for (const part of cleaned.split(':')) push(part);
|
||||
}
|
||||
if (cleaned.includes(',')) {
|
||||
for (const part of cleaned.split(',')) push(part);
|
||||
}
|
||||
}
|
||||
|
||||
return queue;
|
||||
}
|
||||
|
||||
function buildMatchContext(modelName: string): BrandMatchContext {
|
||||
const candidates = collectBrandCandidates(modelName);
|
||||
const raw = candidates[0] || normalizeInput(modelName);
|
||||
const cleaned = stripCommonWrappers(raw);
|
||||
const segments = Array.from(new Set(
|
||||
candidates
|
||||
.flatMap((candidate) => candidate.split(/[/:,\s]+/g))
|
||||
.map((segment) => segment.trim())
|
||||
.filter(Boolean),
|
||||
));
|
||||
|
||||
return {
|
||||
raw,
|
||||
cleaned,
|
||||
segments,
|
||||
candidates,
|
||||
};
|
||||
}
|
||||
|
||||
function matchesRule(context: BrandMatchContext, rule: BrandRule): boolean {
|
||||
switch (rule.mode) {
|
||||
case 'includes':
|
||||
return context.raw.includes(rule.keyword)
|
||||
|| context.cleaned.includes(rule.keyword)
|
||||
|| context.candidates.some((candidate) => candidate.includes(rule.keyword));
|
||||
case 'startsWith':
|
||||
return context.raw.startsWith(rule.keyword)
|
||||
|| context.cleaned.startsWith(rule.keyword)
|
||||
|| context.segments.some((segment) => segment.startsWith(rule.keyword))
|
||||
|| context.candidates.some((candidate) => candidate.startsWith(rule.keyword));
|
||||
case 'segment':
|
||||
return context.segments.includes(rule.keyword);
|
||||
case 'boundary': {
|
||||
const pattern = new RegExp(`(^|[/:_\\-\\s])${escapeRegExp(rule.keyword)}(?=$|[/:_\\-\\s])`);
|
||||
return pattern.test(context.raw)
|
||||
|| pattern.test(context.cleaned)
|
||||
|| context.candidates.some((candidate) => pattern.test(candidate));
|
||||
}
|
||||
default:
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
function escapeRegExp(value: string): string {
|
||||
return value.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
|
||||
}
|
||||
|
||||
const BRAND_FALLBACK_BOUNDARY_RULES = BRAND_DEFINITIONS.map((brand) => ({
|
||||
brand,
|
||||
boundaryRegex: new RegExp(`(^|[^a-z0-9])${escapeRegExp(brand.name.toLowerCase())}(?=$|[^a-z0-9])`),
|
||||
}));
|
||||
|
||||
export function getAllBrands(): BrandInfo[] {
|
||||
return BRAND_DEFINITIONS.map(({ name, icon, color }) => ({ name, icon, color }));
|
||||
}
|
||||
|
||||
export function getAllBrandNames(): string[] {
|
||||
return BRAND_DEFINITIONS.map((brand) => brand.name);
|
||||
}
|
||||
|
||||
export function getBrand(modelName: string): BrandInfo | null {
|
||||
const context = buildMatchContext(modelName);
|
||||
|
||||
for (const definition of BRAND_DEFINITIONS) {
|
||||
if (definition.rules.some((rule) => matchesRule(context, rule))) {
|
||||
return {
|
||||
name: definition.name,
|
||||
icon: definition.icon,
|
||||
color: definition.color,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
for (const candidate of context.candidates) {
|
||||
for (const rule of BRAND_FALLBACK_BOUNDARY_RULES) {
|
||||
if (rule.boundaryRegex.test(candidate)) {
|
||||
return {
|
||||
name: rule.brand.name,
|
||||
icon: rule.brand.icon,
|
||||
color: rule.brand.color,
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
Reference in New Issue
Block a user