@ai-sdk/luma/dist/index.mjs.map

The **Luma provider** for the [AI SDK](https://ai-sdk.dev/docs) contains support for Luma AI's state-of-the-art image generation models - Photon and Photon Flash.

{"version":3,"sources":["../src/luma-provider.ts","../src/luma-image-model.ts"],"sourcesContent":["import { ImageModelV2, NoSuchModelError, ProviderV2 } from '@ai-sdk/provider';\nimport {\n  FetchFunction,\n  loadApiKey,\n  withoutTrailingSlash,\n} from '@ai-sdk/provider-utils';\nimport { LumaImageModel } from './luma-image-model';\nimport { LumaImageModelId } from './luma-image-settings';\n\nexport interface LumaProviderSettings {\n  /**\nLuma API key. Default value is taken from the `LUMA_API_KEY` environment\nvariable.\n  */\n  apiKey?: string;\n  /**\nBase URL for the API calls.\n  */\n  baseURL?: string;\n  /**\nCustom headers to include in the requests.\n  */\n  headers?: Record<string, string>;\n  /**\nCustom fetch implementation. You can use it as a middleware to intercept requests,\nor to provide a custom fetch implementation for e.g. testing.\n  */\n  fetch?: FetchFunction;\n}\n\nexport interface LumaProvider extends ProviderV2 {\n  /**\nCreates a model for image generation.\n  */\n  image(modelId: LumaImageModelId): ImageModelV2;\n\n  /**\nCreates a model for image generation.\n   */\n  imageModel(modelId: LumaImageModelId): ImageModelV2;\n}\n\nconst defaultBaseURL = 'https://api.lumalabs.ai';\n\nexport function createLuma(options: LumaProviderSettings = {}): LumaProvider {\n  const baseURL = withoutTrailingSlash(options.baseURL ?? defaultBaseURL);\n  const getHeaders = () => ({\n    Authorization: `Bearer ${loadApiKey({\n      apiKey: options.apiKey,\n      environmentVariableName: 'LUMA_API_KEY',\n      description: 'Luma',\n    })}`,\n    ...options.headers,\n  });\n\n  const createImageModel = (modelId: LumaImageModelId) =>\n    new LumaImageModel(modelId, {\n      provider: 'luma.image',\n      baseURL: baseURL ?? defaultBaseURL,\n      headers: getHeaders,\n      fetch: options.fetch,\n    });\n\n  return {\n    image: createImageModel,\n    imageModel: createImageModel,\n    languageModel: () => {\n      throw new NoSuchModelError({\n        modelId: 'languageModel',\n        modelType: 'languageModel',\n      });\n    },\n    textEmbeddingModel: () => {\n      throw new NoSuchModelError({\n        modelId: 'textEmbeddingModel',\n        modelType: 'textEmbeddingModel',\n      });\n    },\n  };\n}\n\nexport const luma = createLuma();\n","import {\n  ImageModelV2,\n  ImageModelV2CallWarning,\n  InvalidResponseDataError,\n} from '@ai-sdk/provider';\nimport {\n  FetchFunction,\n  combineHeaders,\n  createBinaryResponseHandler,\n  createJsonResponseHandler,\n  createJsonErrorResponseHandler,\n  createStatusCodeErrorResponseHandler,\n  delay,\n  getFromApi,\n  postJsonToApi,\n} from '@ai-sdk/provider-utils';\nimport { LumaImageSettings } from './luma-image-settings';\nimport { z } from 'zod/v4';\n\nconst DEFAULT_POLL_INTERVAL_MILLIS = 500;\nconst DEFAULT_MAX_POLL_ATTEMPTS = 60000 / DEFAULT_POLL_INTERVAL_MILLIS;\n\ninterface LumaImageModelConfig {\n  provider: string;\n  baseURL: string;\n  headers: () => Record<string, string>;\n  fetch?: FetchFunction;\n  _internal?: {\n    currentDate?: () => Date;\n  };\n}\n\nexport class LumaImageModel implements ImageModelV2 {\n  readonly specificationVersion = 'v2';\n  readonly maxImagesPerCall = 1;\n  readonly pollIntervalMillis = DEFAULT_POLL_INTERVAL_MILLIS;\n  readonly maxPollAttempts = DEFAULT_MAX_POLL_ATTEMPTS;\n\n  get provider(): string {\n    return this.config.provider;\n  }\n\n  constructor(\n    readonly modelId: string,\n    private readonly config: LumaImageModelConfig,\n  ) {}\n\n  async doGenerate({\n    prompt,\n    n,\n    size,\n    aspectRatio,\n    seed,\n    providerOptions,\n    headers,\n    abortSignal,\n  }: Parameters<ImageModelV2['doGenerate']>[0]): Promise<\n    Awaited<ReturnType<ImageModelV2['doGenerate']>>\n  > {\n    const warnings: Array<ImageModelV2CallWarning> = [];\n\n    if (seed != null) {\n      warnings.push({\n        type: 'unsupported-setting',\n        setting: 'seed',\n        details: 'This model does not support the `seed` option.',\n      });\n    }\n\n    if (size != null) {\n      warnings.push({\n        type: 'unsupported-setting',\n        setting: 'size',\n        details:\n          'This model does not support the `size` option. Use `aspectRatio` instead.',\n      });\n    }\n\n    // remove non-request options from providerOptions\n    const { pollIntervalMillis, maxPollAttempts, ...providerRequestOptions } =\n      providerOptions.luma ?? {};\n\n    const currentDate = this.config._internal?.currentDate?.() ?? new Date();\n    const fullHeaders = combineHeaders(this.config.headers(), headers);\n    const { value: generationResponse, responseHeaders } = await postJsonToApi({\n      url: this.getLumaGenerationsUrl(),\n      headers: fullHeaders,\n      body: {\n        prompt,\n        ...(aspectRatio ? { aspect_ratio: aspectRatio } : {}),\n        model: this.modelId,\n        ...providerRequestOptions,\n      },\n      abortSignal,\n      fetch: this.config.fetch,\n      failedResponseHandler: this.createLumaErrorHandler(),\n      successfulResponseHandler: createJsonResponseHandler(\n        lumaGenerationResponseSchema,\n      ),\n    });\n\n    const imageUrl = await this.pollForImageUrl(\n      generationResponse.id,\n      fullHeaders,\n      abortSignal,\n      providerOptions.luma,\n    );\n\n    const downloadedImage = await this.downloadImage(imageUrl, abortSignal);\n\n    return {\n      images: [downloadedImage],\n      warnings,\n      response: {\n        modelId: this.modelId,\n        timestamp: currentDate,\n        headers: responseHeaders,\n      },\n    };\n  }\n\n  private async pollForImageUrl(\n    generationId: string,\n    headers: Record<string, string | undefined>,\n    abortSignal: AbortSignal | undefined,\n    imageSettings?: LumaImageSettings,\n  ): Promise<string> {\n    const url = this.getLumaGenerationsUrl(generationId);\n    const maxPollAttempts =\n      imageSettings?.maxPollAttempts ?? this.maxPollAttempts;\n    const pollIntervalMillis =\n      imageSettings?.pollIntervalMillis ?? this.pollIntervalMillis;\n\n    for (let i = 0; i < maxPollAttempts; i++) {\n      const { value: statusResponse } = await getFromApi({\n        url,\n        headers,\n        abortSignal,\n        fetch: this.config.fetch,\n        failedResponseHandler: this.createLumaErrorHandler(),\n        successfulResponseHandler: createJsonResponseHandler(\n          lumaGenerationResponseSchema,\n        ),\n      });\n\n      switch (statusResponse.state) {\n        case 'completed':\n          if (!statusResponse.assets?.image) {\n            throw new InvalidResponseDataError({\n              data: statusResponse,\n              message: `Image generation completed but no image was found.`,\n            });\n          }\n          return statusResponse.assets.image;\n        case 'failed':\n          throw new InvalidResponseDataError({\n            data: statusResponse,\n            message: `Image generation failed.`,\n          });\n      }\n      await delay(pollIntervalMillis);\n    }\n\n    throw new Error(\n      `Image generation timed out after ${this.maxPollAttempts} attempts.`,\n    );\n  }\n\n  private createLumaErrorHandler() {\n    return createJsonErrorResponseHandler({\n      errorSchema: lumaErrorSchema,\n      errorToMessage: (error: LumaErrorData) =>\n        error.detail[0].msg ?? 'Unknown error',\n    });\n  }\n\n  private getLumaGenerationsUrl(generationId?: string) {\n    return `${this.config.baseURL}/dream-machine/v1/generations/${\n      generationId ?? 'image'\n    }`;\n  }\n\n  private async downloadImage(\n    url: string,\n    abortSignal: AbortSignal | undefined,\n  ): Promise<Uint8Array> {\n    const { value: response } = await getFromApi({\n      url,\n      // No specific headers should be needed for this request as it's a\n      // generated image provided by Luma.\n      abortSignal,\n      failedResponseHandler: createStatusCodeErrorResponseHandler(),\n      successfulResponseHandler: createBinaryResponseHandler(),\n      fetch: this.config.fetch,\n    });\n    return response;\n  }\n}\n\n// limited 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 lumaGenerationResponseSchema = z.object({\n  id: z.string(),\n  state: z.enum(['queued', 'dreaming', 'completed', 'failed']),\n  failure_reason: z.string().nullish(),\n  assets: z\n    .object({\n      image: z.string(), // URL of the generated image\n    })\n    .nullish(),\n});\n\nconst lumaErrorSchema = z.object({\n  detail: z.array(\n    z.object({\n      type: z.string(),\n      loc: z.array(z.string()),\n      msg: z.string(),\n      input: z.string(),\n      ctx: z\n        .object({\n          expected: z.string(),\n        })\n        .nullish(),\n    }),\n  ),\n});\n\nexport type LumaErrorData = z.infer<typeof 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