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

The **[Azure provider](https://ai-sdk.dev/providers/ai-sdk-providers/azure)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the Azure OpenAI API.

{"version":3,"sources":["../src/azure-openai-provider.ts"],"sourcesContent":["import {\n  OpenAIChatLanguageModel,\n  OpenAIChatSettings,\n  OpenAICompletionLanguageModel,\n  OpenAICompletionSettings,\n  OpenAIEmbeddingModel,\n  OpenAIEmbeddingSettings,\n  OpenAIImageModel,\n  OpenAIImageSettings,\n  OpenAIResponsesLanguageModel,\n  OpenAITranscriptionModel,\n} from '@ai-sdk/openai/internal';\nimport {\n  EmbeddingModelV1,\n  LanguageModelV1,\n  ProviderV1,\n  ImageModelV1,\n  TranscriptionModelV1,\n} from '@ai-sdk/provider';\nimport { FetchFunction, loadApiKey, loadSetting } from '@ai-sdk/provider-utils';\n\nexport interface AzureOpenAIProvider extends ProviderV1 {\n  (deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;\n\n  /**\nCreates an Azure OpenAI chat model for text generation.\n   */\n  languageModel(\n    deploymentId: string,\n    settings?: OpenAIChatSettings,\n  ): LanguageModelV1;\n\n  /**\nCreates an Azure OpenAI chat model for text generation.\n   */\n  chat(deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;\n\n  /**\nCreates an Azure OpenAI responses API model for text generation.\n   */\n  responses(deploymentId: string): LanguageModelV1;\n\n  /**\nCreates an Azure OpenAI completion model for text generation.\n   */\n  completion(\n    deploymentId: string,\n    settings?: OpenAICompletionSettings,\n  ): LanguageModelV1;\n\n  /**\n@deprecated Use `textEmbeddingModel` instead.\n   */\n  embedding(\n    deploymentId: string,\n    settings?: OpenAIEmbeddingSettings,\n  ): EmbeddingModelV1<string>;\n\n  /**\n   * Creates an Azure OpenAI DALL-E model for image generation.\n   * @deprecated Use `imageModel` instead.\n   */\n  image(deploymentId: string, settings?: OpenAIImageSettings): ImageModelV1;\n\n  /**\n   * Creates an Azure OpenAI DALL-E model for image generation.\n   */\n  imageModel(\n    deploymentId: string,\n    settings?: OpenAIImageSettings,\n  ): ImageModelV1;\n\n  /**\n@deprecated Use `textEmbeddingModel` instead.\n   */\n  textEmbedding(\n    deploymentId: string,\n    settings?: OpenAIEmbeddingSettings,\n  ): EmbeddingModelV1<string>;\n\n  /**\nCreates an Azure OpenAI model for text embeddings.\n   */\n  textEmbeddingModel(\n    deploymentId: string,\n    settings?: OpenAIEmbeddingSettings,\n  ): EmbeddingModelV1<string>;\n\n  /**\n   * Creates an Azure OpenAI model for audio transcription.\n   */\n  transcription(deploymentId: string): TranscriptionModelV1;\n}\n\nexport interface AzureOpenAIProviderSettings {\n  /**\nName of the Azure OpenAI resource. Either this or `baseURL` can be used.\n\nThe resource name is used in the assembled URL: `https://{resourceName}.openai.azure.com/openai/deployments/{modelId}{path}`.\n     */\n  resourceName?: string;\n\n  /**\nUse a different URL prefix for API calls, e.g. to use proxy servers. Either this or `resourceName` can be used.\nWhen a baseURL is provided, the resourceName is ignored.\n\nWith a baseURL, the resolved URL is `{baseURL}/{modelId}{path}`.\n   */\n  baseURL?: string;\n\n  /**\nAPI key for authenticating requests.\n     */\n  apiKey?: string;\n\n  /**\nCustom headers to include in the requests.\n     */\n  headers?: Record<string, string>;\n\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  /**\nCustom api version to use. Defaults to `2024-10-01-preview`.\n    */\n  apiVersion?: string;\n}\n\n/**\nCreate an Azure OpenAI provider instance.\n */\nexport function createAzure(\n  options: AzureOpenAIProviderSettings = {},\n): AzureOpenAIProvider {\n  const getHeaders = () => ({\n    'api-key': loadApiKey({\n      apiKey: options.apiKey,\n      environmentVariableName: 'AZURE_API_KEY',\n      description: 'Azure OpenAI',\n    }),\n    ...options.headers,\n  });\n\n  const getResourceName = () =>\n    loadSetting({\n      settingValue: options.resourceName,\n      settingName: 'resourceName',\n      environmentVariableName: 'AZURE_RESOURCE_NAME',\n      description: 'Azure OpenAI resource name',\n    });\n\n  const apiVersion = options.apiVersion ?? '2025-03-01-preview';\n  const url = ({ path, modelId }: { path: string; modelId: string }) => {\n    if (path === '/responses') {\n      return options.baseURL\n        ? `${options.baseURL}${path}?api-version=${apiVersion}`\n        : `https://${getResourceName()}.openai.azure.com/openai/responses?api-version=${apiVersion}`;\n    }\n\n    // Default URL format for other endpoints\n    return options.baseURL\n      ? `${options.baseURL}/${modelId}${path}?api-version=${apiVersion}`\n      : `https://${getResourceName()}.openai.azure.com/openai/deployments/${modelId}${path}?api-version=${apiVersion}`;\n  };\n\n  const createChatModel = (\n    deploymentName: string,\n    settings: OpenAIChatSettings = {},\n  ) =>\n    new OpenAIChatLanguageModel(deploymentName, settings, {\n      provider: 'azure-openai.chat',\n      url,\n      headers: getHeaders,\n      compatibility: 'strict',\n      fetch: options.fetch,\n    });\n\n  const createCompletionModel = (\n    modelId: string,\n    settings: OpenAICompletionSettings = {},\n  ) =>\n    new OpenAICompletionLanguageModel(modelId, settings, {\n      provider: 'azure-openai.completion',\n      url,\n      compatibility: 'strict',\n      headers: getHeaders,\n      fetch: options.fetch,\n    });\n\n  const createEmbeddingModel = (\n    modelId: string,\n    settings: OpenAIEmbeddingSettings = {},\n  ) =>\n    new OpenAIEmbeddingModel(modelId, settings, {\n      provider: 'azure-openai.embeddings',\n      headers: getHeaders,\n      url,\n      fetch: options.fetch,\n    });\n\n  const createResponsesModel = (modelId: string) =>\n    new OpenAIResponsesLanguageModel(modelId, {\n      provider: 'azure-openai.responses',\n      url,\n      headers: getHeaders,\n      fetch: options.fetch,\n    });\n\n  const createImageModel = (\n    modelId: string,\n    settings: OpenAIImageSettings = {},\n  ) =>\n    new OpenAIImageModel(modelId, settings, {\n      provider: 'azure-openai.image',\n      url,\n      headers: getHeaders,\n      fetch: options.fetch,\n    });\n\n  const createTranscriptionModel = (modelId: string) =>\n    new OpenAITranscriptionModel(modelId, {\n      provider: 'azure-openai.transcription',\n      url,\n      headers: getHeaders,\n      fetch: options.fetch,\n    });\n\n  const provider = function (\n    deploymentId: string,\n    settings?: OpenAIChatSettings | OpenAICompletionSettings,\n  ) {\n    if (new.target) {\n      throw new Error(\n        'The Azure OpenAI model function cannot be called with the new keyword.',\n      );\n    }\n\n    return createChatModel(deploymentId, settings as OpenAIChatSettings);\n  };\n\n  provider.languageModel = createChatModel;\n  provider.chat = createChatModel;\n  provider.completion = createCompletionModel;\n  provider.embedding = createEmbeddingModel;\n  provider.image = createImageModel;\n  provider.imageModel = createImageModel;\n  provider.textEmbedding = createEmbeddingModel;\n  provider.textEmbeddingModel = createEmbeddingModel;\n  provider.responses = createResponsesModel;\n  provider.transcription = createTranscriptionModel;\n  return provider;\n}\n\n/**\nDefault Azure OpenAI provider instance.\n */\nexport const azure = 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