mixedbread-ai-provider/dist/index.mjs.map

Mixedbread AI Provider for running Mixedbread AI models with Vercel AI SDK

{"version":3,"sources":["../src/mixedbread-provider.ts","../src/mixedbread-embedding-model.ts","../src/mixedbread-error.ts","../src/mixedbread-embedding-options.ts"],"sourcesContent":["import type {\n  EmbeddingModelV2,\n  ImageModelV2,\n  LanguageModelV2,\n  ProviderV2,\n} from '@ai-sdk/provider';\nimport {\n  type FetchFunction,\n  loadApiKey,\n  withoutTrailingSlash,\n} from '@ai-sdk/provider-utils';\nimport { MixedbreadEmbeddingModel } from './mixedbread-embedding-model';\nimport type { MixedbreadEmbeddingModelId } from './mixedbread-embedding-options';\n\nexport interface MixedbreadProvider extends ProviderV2 {\n  (modelId: MixedbreadEmbeddingModelId): EmbeddingModelV2<string>;\n\n  textEmbeddingModel: (\n    modelId: MixedbreadEmbeddingModelId,\n  ) => EmbeddingModelV2<string>;\n}\n\nexport interface MixedbreadProviderSettings {\n  /**\n  Use a different URL prefix for API calls, e.g. to use proxy servers.\n  The default prefix is `https://api.mixedbread.com/v1`.\n     */\n  baseURL?: string;\n\n  /**\n  API key that is being send using the `Authorization` header.\n  It defaults to the `MIXEDBREAD_API_KEY` environment variable.\n     */\n  apiKey?: string;\n\n  /**\n  Custom headers to include in the requests.\n       */\n  headers?: Record<string, string>;\n\n  /**\n  Custom fetch implementation. You can use it as a middleware to intercept requests,\n  or to provide a custom fetch implementation for e.g. testing.\n      */\n  fetch?: FetchFunction;\n}\n\n/**\n  Create a Mixedbread AI provider instance.\n   */\nexport function createMixedbread(\n  options: MixedbreadProviderSettings = {},\n): MixedbreadProvider {\n  const baseURL =\n    withoutTrailingSlash(options.baseURL) ?? 'https://api.mixedbread.com/v1';\n\n  const getHeaders = () => ({\n    Authorization: `Bearer ${loadApiKey({\n      apiKey: options.apiKey,\n      environmentVariableName: 'MIXEDBREAD_API_KEY',\n      description: 'Mixedbread',\n    })}`,\n    ...options.headers,\n  });\n\n  const createEmbeddingModel = (modelId: MixedbreadEmbeddingModelId) =>\n    new MixedbreadEmbeddingModel(modelId, {\n      provider: 'mixedbread.embedding',\n      baseURL,\n      headers: getHeaders,\n      fetch: options.fetch,\n    });\n\n  const provider = function (modelId: MixedbreadEmbeddingModelId) {\n    if (new.target) {\n      throw new Error(\n        'The Mixedbread model function cannot be called with the new keyword.',\n      );\n    }\n\n    return createEmbeddingModel(modelId);\n  };\n\n  provider.textEmbeddingModel = createEmbeddingModel;\n\n  provider.chat = provider.languageModel = (): LanguageModelV2 => {\n    throw new Error('languageModel method is not implemented.');\n  };\n  provider.imageModel = (): ImageModelV2 => {\n    throw new Error('imageModel method is not implemented.');\n  };\n\n  return provider as MixedbreadProvider;\n}\n\n/**\n  Default Mixedbread provider instance.\n   */\nexport const mixedbread = createMixedbread();\n","import {\n  type EmbeddingModelV2,\n  TooManyEmbeddingValuesForCallError,\n} from '@ai-sdk/provider';\nimport {\n  combineHeaders,\n  createJsonResponseHandler,\n  type FetchFunction,\n  parseProviderOptions,\n  postJsonToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\nimport { mixedbreadFailedResponseHandler } from '@/mixedbread-error';\nimport {\n  mixedbreadEmbeddingOptions,\n  type MixedbreadEmbeddingModelId,\n} from './mixedbread-embedding-options';\n\ntype MixedbreadEmbeddingConfig = {\n  provider: string;\n  baseURL: string;\n  headers: () => Record<string, string | undefined>;\n  fetch?: FetchFunction;\n};\n\nexport class MixedbreadEmbeddingModel implements EmbeddingModelV2<string> {\n  readonly specificationVersion = 'v2';\n  readonly modelId: MixedbreadEmbeddingModelId;\n\n  private readonly config: MixedbreadEmbeddingConfig;\n\n  get provider(): string {\n    return this.config.provider;\n  }\n\n  get maxEmbeddingsPerCall(): number {\n    return 256;\n  }\n\n  get supportsParallelCalls(): boolean {\n    return true;\n  }\n\n  constructor(\n    modelId: MixedbreadEmbeddingModelId,\n    config: MixedbreadEmbeddingConfig,\n  ) {\n    this.modelId = modelId;\n    this.config = config;\n  }\n\n  async doEmbed({\n    abortSignal,\n    values,\n    headers,\n    providerOptions,\n  }: Parameters<EmbeddingModelV2<string>['doEmbed']>[0]): Promise<\n    Awaited<ReturnType<EmbeddingModelV2<string>['doEmbed']>>\n  > {\n    const embeddingOptions = await parseProviderOptions({\n      provider: 'mixedbread',\n      providerOptions,\n      schema: mixedbreadEmbeddingOptions,\n    });\n\n    if (values.length > this.maxEmbeddingsPerCall) {\n      throw new TooManyEmbeddingValuesForCallError({\n        maxEmbeddingsPerCall: this.maxEmbeddingsPerCall,\n        modelId: this.modelId,\n        provider: this.provider,\n        values,\n      });\n    }\n\n    const {\n      responseHeaders,\n      value: response,\n      rawValue,\n    } = await postJsonToApi({\n      abortSignal,\n      body: {\n        input: values,\n        model: this.modelId,\n        prompt: embeddingOptions?.prompt,\n        normalize: embeddingOptions?.normalized,\n        dimensions: embeddingOptions?.dimensions,\n        encoding_format: embeddingOptions?.encodingFormat,\n      },\n      failedResponseHandler: mixedbreadFailedResponseHandler,\n      fetch: this.config.fetch,\n      headers: combineHeaders(this.config.headers(), headers),\n      successfulResponseHandler: createJsonResponseHandler(\n        mixedbreadTextEmbeddingResponseSchema,\n      ),\n      url: `${this.config.baseURL}/embeddings`,\n    });\n\n    return {\n      embeddings: response.data.map((item) => item.embedding),\n      usage: response.usage\n        ? { tokens: response.usage.total_tokens }\n        : undefined,\n      response: { headers: responseHeaders, body: rawValue },\n    };\n  }\n}\n\n// minimal version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst mixedbreadTextEmbeddingResponseSchema = z.object({\n  data: z.array(z.object({ embedding: z.array(z.number()) })),\n  usage: z.object({ total_tokens: z.number() }).nullish(),\n});\n","import { createJsonErrorResponseHandler } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\nconst mixedbreadErrorDataSchema = z.object({\n  error: z.object({\n    code: z.string().nullable(),\n    message: z.string(),\n    param: z.any().nullable(),\n    type: z.string(),\n  }),\n});\n\nexport type MixedbreadErrorData = z.infer<typeof mixedbreadErrorDataSchema>;\n\nexport const mixedbreadFailedResponseHandler = createJsonErrorResponseHandler({\n  errorSchema: mixedbreadErrorDataSchema,\n  errorToMessage: (data) => data.error.message,\n});\n","import { z } from 'zod/v4';\n\nexport type MixedbreadEmbeddingModelId =\n  | 'mixedbread-ai/deepset-mxbai-embed-de-large-v1'\n  | 'mixedbread-ai/mxbai-embed-large-v1'\n  | 'mixedbread-ai/mxbai-embed-2d-large-v1'\n  // | 'mxbai-colbert-large-v1'\n  | (string & NonNullable<unknown>);\n\nexport const mixedbreadEmbeddingOptions = z.object({\n  /**\n   * An optional prompt to provide context to the model. Refer to the model's documentation for more information.\n   * A string between 1 and 256 characters.\n   */\n  prompt: z.string().optional(),\n\n  /**\n   * Option to normalize the embeddings.\n   */\n  normalized: z.boolean().optional(),\n\n  /**\n   * The desired number of dimensions in the output vectors. Defaults to the model's maximum.\n   * A number between 1 and the model's maximum output dimensions.\n   * Only applicable for Matryoshka-based models.\n   */\n  dimensions: z.number().optional(),\n\n  /**\n   * The desired format for the embeddings. 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