{"repo": "atom112/aio", "files": {"src/core/utils/models.ts": {"e77a3a145e375788b9e2f3e2ddd5606713ff185e": {"t": 1786067560.6301908, "n": 12026, "h": "a096d7cb4205538d", "c": "/**\n * 模型目录加载与查询工具\n * @description 包装 @aio/models-data 包，提供 catalog 加载、模型查询、能力补全\n * @data-source D:/base/aio-models-data (每周日 04:00 UTC 自动同步)\n */\n\nimport { invoke } from '@tauri-apps/api/core';\nimport type { ModelMeta, ProviderMeta, Catalog } from '@aio/models-data';\nimport {\n  formatDateTime as formatLocaleDateTime,\n  formatRelativeTime as formatLocaleRelativeTime,\n  t,\n} from '../i18n';\n\nexport type { ModelMeta, ProviderMeta, Catalog } from '@aio/models-data';\n\n/** 从 provider API 拉取并持久化的模型条目（仿 LobeHub 列表行） */\nexport interface FetchedModel {\n  id: string;\n  ownedBy: string;\n  /** 厂商返回的展示名（Google `displayName` / Anthropic `display_name`），OpenAI/Ollama 无 */\n  displayName?: string;\n  /** 发布日期 YYYY-MM-DD，OpenAI `created` 转 / Anthropic `created_at` 原样 */\n  releasedAt?: string;\n}\n\nexport interface ProviderConfig {\n  id: string;\n  enabled: boolean;\n  displayName: string;\n  apiUrl: string;\n  apiKey: string;\n  enabledModels: string[];\n  isCustom: boolean;\n  customModelIds: string[];\n  /** per-provider HTTP/HTTPS 代理 (例如 `http://127.0.0.1:7890`)，用于解决国内访问 OpenAI/Google 的网络问题 */\n  proxyUrl?: string;\n  /** 从 API 持久化拉取的模型列表，用于仿 LobeHub 风格的双段 toggle 列表 */\n  fetchedModels?: FetchedModel[];\n  /** 本地引擎专属：模型文件路径映射 { modelId -> localPath } */\n  localModelPaths?: Record<string, string>;\n}\n\nexport interface ProviderConfigFile {\n  version: number;\n  updatedAt: string;\n  providers: Record<string, ProviderConfig>;\n}\n\n// ==================== 本地推理引擎供应商定义 ====================\n\n/** 内置本地推理引擎供应商定义 */\nexport interface LocalEngineProvider {\n  id: string; // provider identifier, e.g. 'local-llamacpp'\n  name: string; // display name, e.g. 'llama.cpp'\n  defaultApiUrl: string; // pre-filled URL, e.g. 'http://127.0.0.1:8080/v1'\n  engineType: string; // 'llama_cpp' | 'vllm' | 'ollama'\n  fileExtensions: string[]; // ['gguf'] for file picker, [] for no file picker\n  allowModelFileSelection: boolean;\n  engineInstallUrl?: string; // docs URL for manual install (not AIO auto-install)\n  /** 是否支持从 API 拉取模型列表（Ollama 的 /api/tags；llama.cpp/vLLM 启动时固定模型，无需拉取） */\n  supportsFetchModels?: boolean;\n}\n\nexport const LOCAL_ENGINE_PROVIDERS: LocalEngineProvider[] = [\n  {\n    id: 'local-llamacpp',\n    name: 'llama.cpp',\n    defaultApiUrl: 'http://127.0.0.1:8080/v1',\n    engineType: 'llama_cpp',\n    fileExtensions: ['gguf'],\n    allowModelFileSelection: true,\n    engineInstallUrl: 'https://github.com/ggml-org/llama.cpp',\n    supportsFetchModels: false,\n  },\n  {\n    id: 'local-vllm',\n    name: 'vLLM',\n    defaultApiUrl: 'http://127.0.0.1:8000/v1',\n    engineType: 'vllm',\n    fileExtensions: [],\n    allowModelFileSelection: false,\n    engineInstallUrl: 'https://docs.vllm.ai',\n    supportsFetchModels: false,\n  },\n  {\n    id: 'ollama',\n    name: 'Ollama',\n    defaultApiUrl: 'http://localhost:11434',\n    engineType: 'ollama',\n    fileExtensions: ['gguf'],\n    allowModelFileSelection: true,\n    engineInstallUrl: 'https://ollama.ai',\n    supportsFetchModels: true,\n  },\n];\n\n/** 判断 provider id 是否是本地引擎 provider */\nexport const isLocalEngineProvider = (id: string): boolean =>\n  LOCAL_ENGINE_PROVIDERS.some((p) => p.id === id);\n\n/** 根据 provider id 取 LocalEngineProvider 定义 */\nexport const getLocalEngineProvider = (id: string): LocalEngineProvider | undefined =>\n  LOCAL_ENGINE_PROVIDERS.find((p) => p.id === id);\n\nexport interface TestConnectionResult {\n  success: boolean;\n  modelCount: number;\n  sampleModelIds: string[];\n  error: string | null;\n  elapsedMs: number;\n}\n\nexport interface FetchLiveModelsResult {\n  success: boolean;\n  models: Array<{ id: string; owned_by: string; display_name?: string; released_at?: string }>;\n  error: string | null;\n  elapsedMs: number;\n}\n\nexport type CatalogSourceTag = 'appdata' | 'bundled' | 'dev_fallback' | 'empty';\n\nexport interface CatalogResponse {\n  source: CatalogSourceTag;\n  json: string;\n  path: string | null;\n  version: string | null;\n  generatedAt: string | null;\n}\n\nexport interface UpdateResult {\n  success: boolean;\n  modelCount: number;\n  providerCount: number;\n  version: string;\n  cachedPath: string;\n  error: string | null;\n  bytes: number;\n  elapsedMs: number;\n}\n\nlet cachedCatalog: Catalog | null = null;\nlet cachedSource: CatalogSourceTag = 'empty';\nlet cachedPath: string | null = null;\nlet cachedVersion: string | null = null;\nlet cachedGeneratedAt: string | null = null;\nlet loadPromise: Promise<Catalog> | null = null;\n\nconst EMPTY_CATALOG: Catalog = {\n  version: '0.0.0',\n  generatedAt: '1970-01-01T00:00:00.000Z',\n  source: '',\n  providerCount: 0,\n  modelCount: 0,\n  providers: [],\n  models: [],\n};\n\nfunction applyResponse(resp: CatalogResponse): Catalog {\n  const cat = JSON.parse(resp.json) as Catalog;\n  cachedCatalog = cat;\n  cachedSource = resp.source;\n  cachedPath = resp.path;\n  cachedVersion = resp.version;\n  cachedGeneratedAt = resp.generatedAt;\n  return cat;\n}\n\nasync function loadCatalogFromBackend(): Promise<Catalog> {\n  try {\n    const resp = await invoke<CatalogResponse>('load_models_catalog_full');\n    return applyResponse(resp);\n  } catch (e) {\n    console.warn('[models] 从后端加载 catalog 失败:', e);\n    return EMPTY_CATALOG;\n  }\n}\n\nexport async function loadModelsCatalog(): Promise<Catalog> {\n  if (cachedCatalog) return cachedCatalog;\n  if (loadPromise) return loadPromise;\n  loadPromise = loadCatalogFromBackend().then((c) => {\n    loadPromise = null;\n    return c;\n  });\n  return loadPromise;\n}\n\nexport function getCachedCatalog(): Catalog | null {\n  return cachedCatalog;\n}\n\nexport function getCatalogMeta(): {\n  source: CatalogSourceTag;\n  path: string | null;\n  version: string | null;\n  generatedAt: string | null;\n} {\n  return {\n    source: cachedSource,\n    path: cachedPath,\n    version: cachedVersion,\n    generatedAt: cachedGeneratedAt,\n  };\n}\n\nexport async function refreshModelsCatalog(): Promise<Catalog> {\n  loadPromise = null;\n  return loadModelsCatalog();\n}\n\nexport async function updateModelsCatalog(url?: string): Promise<UpdateResult> {\n  const result = await invoke<UpdateResult>('update_models_catalog', { url: url ?? null });\n  if (result.success) {\n    await refreshModelsCatalog();\n  }\n  return result;\n}\n\nexport async function getCatalogUrl(): Promise<string> {\n  return await invoke<string>('get_catalog_url');\n}\n\nexport function findModel(catalog: Catalog, provider: string, id: string): ModelMeta | null {\n  const prov = (provider || '').toLowerCase();\n  const target = (id || '').toLowerCase();\n\n  const direct = catalog.models.find(\n    (m: ModelMeta) => m.provider.toLowerCase() === prov && m.id.toLowerCase() === target,\n  );\n  if (direct) return direct;\n\n  return (\n    catalog.models.find(\n      (m: ModelMeta) =>\n        m.provider.toLowerCase() === prov &&\n        m.aliases.some((a: string) => a.toLowerCase() === target),\n    ) ?? null\n  );\n}\n\nexport function listProvidersForApiUrl(catalog: Catalog, apiUrl: string): ProviderMeta[] {\n  if (!apiUrl) return catalog.providers.slice(0, 50);\n  const u = apiUrl.toLowerCase();\n  const knownHosts: Record<string, string> = {\n    'api.openai.com': 'openai',\n    'api.anthropic.com': 'anthropic',\n    'generativelanguage.googleapis.com': 'google',\n    'api.deepseek.com': 'deepseek',\n    'api.groq.com': 'groq',\n    'api.mistral.ai': 'mistral',\n    'api.x.ai': 'xai',\n    'openrouter.ai': 'openrouter',\n    'api.cohere.ai': 'cohere',\n  };\n  for (const [host, prov] of Object.entries(knownHosts)) {\n    if (u.includes(host)) {\n      return catalog.providers.filter((p: ProviderMeta) => p.id === prov);\n    }\n  }\n  return catalog.providers.filter((p: ProviderMeta) => !p.isAggregator).slice(0, 50);\n}\n\nexport function listCatalogModels(catalog: Catalog, providerId?: string): ModelMeta[] {\n  if (!providerId || providerId === 'all') return catalog.models;\n  return catalog.models.filter((m: ModelMeta) => m.provider === providerId);\n}\n\n/** 格式化上下文窗口（1234567 → \"1.2M\"） */\nexport function formatContextWindow(tokens: number): string {\n  if (tokens >= 1_000_000)\n    return `${(tokens / 1_000_000).toFixed(tokens % 1_000_000 === 0 ? 0 : 1)}M`;\n  if (tokens >= 1_000) return `${(tokens / 1_000).toFixed(0)}K`;\n  return String(tokens);\n}\n\n/** 格式化单条价格（per 1M tokens） */\nexport function formatPricing(input: number, output: number): string {\n  if (input === 0 && output === 0) return t('common.free');\n  return `$${input}/${output}/1M`;\n}\n\n/** 把 ISO 时间格式化为「X 天前」之类的相对描述 */\nexport function formatRelativeTime(iso: string | null): string {\n  if (!iso) return t('common.neverUpdated');\n  try {\n    const d = new Date(iso);\n    const now = Date.now();\n    const diff = now - d.getTime();\n    const minutes = Math.floor(diff / 60_000);\n    if (minutes < 1) return formatLocaleRelativeTime(0, 'minute');\n    if (minutes < 60) return formatLocaleRelativeTime(-minutes, 'minute');\n    const hours = Math.floor(minutes / 60);\n    if (hours < 24) return formatLocaleRelativeTime(-hours, 'hour');\n    const days = Math.floor(hours / 24);\n    if (days < 30) return formatLocaleRelativeTime(-days, 'day');\n    const months = Math.floor(days / 30);\n    if (months < 12) return formatLocaleRelativeTime(-months, 'month');\n    return formatLocaleRelativeTime(-Math.floor(months / 12), 'year');\n  } catch {\n    return iso;\n  }\n}\n\n/** 格式化 releaseDate（\"2025-01-15\" → \"2025-01\"）只取年月 */\nexport function formatReleaseDate(iso: string | null | undefined): string {\n  if (!iso) return '';\n  return formatLocaleDateTime(`${iso.slice(0, 10)}T00:00:00`, { year: 'numeric', month: 'short' });\n}\n\n// ==================== v2 工具函数 ====================\n\n/**\n * 合并 catalog 模型元数据 + 用户启用状态, 拆分为三段\n * - enabled: 已启用的 (按 enabledIds 原顺序)\n * - available: catalog 中有但未启用的 (按 releaseDate desc, 同日期按 id 字母序)\n * - orphans: enabledModels 中有但 catalog 没有的 (遗留 custom / 老 config)\n */\nexport function listProviderModels(\n  catalog: Catalog,\n  providerId: string,\n  enabledIds: readonly string[],\n): {\n  enabled: ModelMeta[];\n  available: ModelMeta[];\n  orphans: string[];\n} {\n  const catalogModels = catalog.models.filter((m: ModelMeta) => m.provider === providerId);\n  const enabledSet = new Set(enabledIds);\n  const enabledOrder = new Map(enabledIds.map((id, i) => [id, i]));\n\n  const enabled: ModelMeta[] = [];\n  const available: ModelMeta[] = [];\n  const seen = new Set<string>();\n\n  for (const m of catalogModels) {\n    if (enabledSet.has(m.id)) {\n      enabled.push(m);\n      seen.add(m.id);\n    }\n  }\n  // 按 enabledIds 顺序排序 enabled\n  enabled.sort((a, b) => (enabledOrder.get(a.id) ?? 0) - (enabledOrder.get(b.id) ?? 0));\n\n  for (const m of catalogModels) {\n    if (!seen.has(m.id)) {\n      available.push(m);\n    }\n  }\n  // 按 releaseDate desc, 同日期按 id 字母序\n  available.sort((a, b) => {\n    const ra = a.releaseDate ?? '';\n    const rb = b.releaseDate ?? '';\n    if (ra !== rb) return rb.localeCompare(ra); // desc\n    return a.id.localeCompare(b.id);\n  });\n\n  // orphans: enabledIds 中有但 catalog 没有的\n  const catalogIds = new Set(catalogModels.map((m: ModelMeta) => m.id));\n  const orphans = enabledIds.filter((id) => !catalogIds.has(id));\n\n  return { enabled, available, orphans };\n}\n\n/**\n * 通过 host 反查 provider id (统一入口, 替代三处重复实现)\n * 优先匹配 catalog 中 ProviderMeta 的 api 字段, 兜底用 9 个常见 host 映射\n */\nconst KNOWN_HOSTS: ReadonlyArray<readonly [string, string]> = [\n  ['api.openai.com', 'openai'],\n  ['api.anthropic.com', 'anthropic'],\n  ['generativelanguage.googleapis.com', 'google'],\n  ['api.deepseek.com', 'deepseek'],\n  ['api.groq.com', 'groq'],\n  ['api.mistral.ai', 'mistral'],\n  ['api.x.ai', 'xai'],\n  ['api.cohere.ai', 'cohere'],\n  ['openrouter.ai', 'openrouter'],\n];\n\nexport function detectProviderByUrl(url: string): string | null {\n  if (!url) return null;\n  const u = url.toLowerCase();\n  for (const [host, pid] of KNOWN_HOSTS) {\n    if (u.includes(host)) return pid;\n  }\n  return null;\n}\n\n/** 列表页搜索: 仅匹配 provider id / name, 不含模型名 */\nexport function searchProviders(catalog: Catalog, query: string): ProviderMeta[] {\n  if (!query.trim()) return catalog.providers;\n  const q = query.toLowerCase();\n  return catalog.providers.filter(\n    (p: ProviderMeta) => p.id.includes(q) || p.name.toLowerCase().includes(q),\n  );\n}\n"}}}}