AI SDK Azure Provider

import { azure, createAzure } from "@ai-sdk/azure";
import type { AzureOpenAIProvider, AzureOpenAIProviderSettings } from "@ai-sdk/azure";

const { azure, createAzure } = require("@ai-sdk/azure");

import { azure } from "@ai-sdk/azure";
import { generateText } from "ai";

// Using the default provider instance
const { text } = await generateText({
  model: azure("gpt-4o"), // your deployment name
  prompt: "Write a vegetarian lasagna recipe for 4 people.",
});

// Creating a custom provider with specific configuration
import { createAzure } from "@ai-sdk/azure";

const customAzure = createAzure({
  resourceName: "my-azure-resource",
  apiKey: "your-api-key",
  apiVersion: "2025-03-01-preview",
});

const model = customAzure("my-deployment");

function azure(deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;

interface AzureOpenAIProvider {
  (deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;
  languageModel(deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;
  chat(deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;
  completion(deploymentId: string, settings?: OpenAICompletionSettings): LanguageModelV1;
  responses(deploymentId: string): LanguageModelV1;
}

// Current method
textEmbeddingModel(deploymentId: string, settings?: OpenAIEmbeddingSettings): EmbeddingModelV1<string>;

// Deprecated methods (use textEmbeddingModel instead)
embedding(deploymentId: string, settings?: OpenAIEmbeddingSettings): EmbeddingModelV1<string>;
textEmbedding(deploymentId: string, settings?: OpenAIEmbeddingSettings): EmbeddingModelV1<string>;

// Current method
imageModel(deploymentId: string, settings?: OpenAIImageSettings): ImageModelV1;

// Deprecated method (use imageModel instead)
image(deploymentId: string, settings?: OpenAIImageSettings): ImageModelV1;

transcription(deploymentId: string): TranscriptionModelV1;

function createAzure(options?: AzureOpenAIProviderSettings): AzureOpenAIProvider;

interface AzureOpenAIProviderSettings {
  resourceName?: string;
  baseURL?: string;
  apiKey?: string;
  headers?: Record<string, string>;
  fetch?: FetchFunction;
  apiVersion?: string;
}

interface AzureOpenAIProvider extends ProviderV1 {
  (deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;
  languageModel(deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;
  chat(deploymentId: string, settings?: OpenAIChatSettings): LanguageModelV1;
  completion(deploymentId: string, settings?: OpenAICompletionSettings): LanguageModelV1;
  responses(deploymentId: string): LanguageModelV1;
  embedding(deploymentId: string, settings?: OpenAIEmbeddingSettings): EmbeddingModelV1<string>;
  textEmbedding(deploymentId: string, settings?: OpenAIEmbeddingSettings): EmbeddingModelV1<string>;
  textEmbeddingModel(deploymentId: string, settings?: OpenAIEmbeddingSettings): EmbeddingModelV1<string>;
  image(deploymentId: string, settings?: OpenAIImageSettings): ImageModelV1;
  imageModel(deploymentId: string, settings?: OpenAIImageSettings): ImageModelV1;
  transcription(deploymentId: string): TranscriptionModelV1;
}

interface AzureOpenAIProviderSettings {
  /** Name of the Azure OpenAI resource. Either this or `baseURL` can be used. */
  resourceName?: string;
  /** Use a different URL prefix for API calls, e.g. to use proxy servers. Either this or `resourceName` can be used. */
  baseURL?: string;
  /** API key for authenticating requests. */
  apiKey?: string;
  /** Custom headers to include in the requests. */
  headers?: Record<string, string>;
  /** Custom fetch implementation. You can use it as a middleware to intercept requests. */
  fetch?: FetchFunction;
  /** Custom API version to use. Defaults to `2025-03-01-preview`. */
  apiVersion?: string;
}

interface OpenAIChatSettings {
  /** Modify the likelihood of specified tokens appearing in the completion. */
  logitBias?: Record<number, number>;
  /** Return the log probabilities of the tokens. Setting to true returns log probabilities of generated tokens. Setting to a number returns top n tokens. */
  logprobs?: boolean | number;
  /** Whether to enable parallel function calling during tool use. Default to true. */
  parallelToolCalls?: boolean;
  /** Whether to use structured outputs. Defaults to false. */
  structuredOutputs?: boolean;
  /** Whether to use legacy function calling. Defaults to false. */
  useLegacyFunctionCalling?: boolean;
  /** A unique identifier representing your end-user. */
  user?: string;
  /** Automatically download images and pass the image as data to the model. Defaults to `false`. */
  downloadImages?: boolean;
  /** Simulates streaming by using a normal generate call and returning it as a stream. Defaults to `false`. */
  simulateStreaming?: boolean;
  /** Reasoning effort for reasoning models. Defaults to `medium`. */
  reasoningEffort?: 'low' | 'medium' | 'high';
}

interface OpenAICompletionSettings {
  /** Echo back the prompt in addition to the completion. */
  echo?: boolean;
  /** Modify the likelihood of specified tokens appearing in the completion. */
  logitBias?: Record<number, number>;
  /** Return the log probabilities of the tokens. */
  logprobs?: boolean | number;
  /** The suffix that comes after a completion of inserted text. */
  suffix?: string;
  /** A unique identifier representing your end-user. */
  user?: string;
}

interface OpenAIEmbeddingSettings {
  /** Override the maximum number of embeddings per call. */
  maxEmbeddingsPerCall?: number;
  /** Override the parallelism of embedding calls. */
  supportsParallelCalls?: boolean;
  /** The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models. */
  dimensions?: number;
  /** A unique identifier representing your end-user. */
  user?: string;
}

interface OpenAIImageSettings {
  /** Override the maximum number of images per call (default is dependent on the model). */
  maxImagesPerCall?: number;
}

// AI SDK Base Types
interface LanguageModelV1 {
  /** The language model provider. */
  readonly provider: string;
  /** The model name of the language model. */
  readonly modelName: string;
  /** Generate text and call tools for a prompt. */
  doGenerate(options: any): Promise<any>;
  /** Generate a stream of text and tool calls for a prompt. */
  doStream(options: any): Promise<any>;
}

interface EmbeddingModelV1<VALUE> {
  /** The embedding model provider. */
  readonly provider: string;
  /** The embedding model name. */
  readonly modelName: string;
  /** The maximum number of values that can be embedded in a single call. */
  readonly maxEmbeddingsPerCall?: number;
  /** Whether the model supports parallel embedding calls. */
  readonly supportsParallelCalls?: boolean;
  /** Generate embeddings for the given values. */
  doEmbed(options: any): Promise<any>;
}

interface ImageModelV1 {
  /** The image model provider. */
  readonly provider: string;
  /** The image model name. */
  readonly modelName: string;
  /** Generate images for the given prompt. */
  doGenerate(options: any): Promise<any>;
}

interface TranscriptionModelV1 {
  /** The transcription model provider. */
  readonly provider: string;
  /** The transcription model name. */
  readonly modelName: string;
  /** Transcribe audio for the given audio data. */
  doTranscribe(options: any): Promise<any>;
}

interface ProviderV1 {
  /** The provider identifier. */
  readonly providerId: string;
}

type FetchFunction = typeof globalThis.fetch;