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Azure OpenAI Provider

The Azure OpenAI provider enables you to use OpenAI models through Microsoft Azure with enterprise features, security, and compliance.

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Installation

npm install @ai-sdk/azure

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Setup

Get your credentials from the Azure Portal and set them as environment variables: 
AZURE_RESOURCE_NAME=your-resource-name
AZURE_API_KEY=your-api-key

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Usage

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Basic Text Generation

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

const { text } = await generateText({
  model: azure('your-gpt-4-deployment'),
  prompt: 'Explain enterprise AI solutions.',
});

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Streaming Responses

import { azure } from '@ai-sdk/azure';
import { streamText } from 'ai';

const result = streamText({
  model: azure('your-gpt-4-deployment'),
  prompt: 'Write about cloud security.',
});

for await (const chunk of result.textStream) {
  process.stdout.write(chunk);
}

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Structured Output

import { azure } from '@ai-sdk/azure';
import { generateObject } from 'ai';
import { z } from 'zod';

const { object } = await generateObject({
  model: azure('your-gpt-4-deployment'),
  schema: z.object({
    risks: z.array(z.string()),
    recommendations: z.array(z.string()),
  }),
  prompt: 'Analyze security risks.',
});

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Configuration

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Custom Provider Instance

import { createAzure } from '@ai-sdk/azure';

const azure = createAzure({
  resourceName: 'your-resource-name',
  apiKey: process.env.AZURE_API_KEY,
});

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Provider Options

  • resourceName: Your Azure resource name
  • apiKey: Azure OpenAI API key
  • apiVersion: API version (defaults to ‘v1’)
  • baseURL: Custom endpoint URL

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Available Models

You can deploy the following OpenAI models on Azure:

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Chat Models

  • GPT-4 Turbo
  • GPT-4
  • GPT-3.5 Turbo

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Embeddings

import { azure } from '@ai-sdk/azure';
import { embed } from 'ai';

const { embedding } = await embed({
  model: azure.embedding('your-embedding-deployment'),
  value: 'Enterprise document',
});
Available Models:
  • text-embedding-3-small
  • text-embedding-3-large
  • text-embedding-ada-002

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Image Generation

import { azure } from '@ai-sdk/azure';
import { generateImage } from 'ai';

const { image } = await generateImage({
  model: azure.image('your-dalle-deployment'),
  prompt: 'Professional office space',
  size: '1024x1024',
});
Available Models:
  • DALL-E 3
  • DALL-E 2

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Advanced Features

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Tool Calling

import { azure } from '@ai-sdk/azure';
import { generateText } from 'ai';
import { z } from 'zod';

const result = await generateText({
  model: azure('your-gpt-4-deployment'),
  tools: {
    database_query: {
      description: 'Query the database',
      parameters: z.object({
        query: z.string(),
      }),
      execute: async ({ query }) => {
        return { results: [] };
      },
    },
  },
  prompt: 'Find all users from last month.',
});

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Vision

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

const result = await generateText({
  model: azure('your-gpt-4-vision-deployment'),
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'Analyze this chart.' },
        { type: 'image', image: fs.readFileSync('./chart.png') },
      ],
    },
  ],
});

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PDF Support

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

const result = await generateText({
  model: azure('your-gpt-4-deployment'),
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'Review this contract.' },
        {
          type: 'file',
          data: fs.readFileSync('./contract.pdf'),
          mediaType: 'application/pdf',
        },
      ],
    },
  ],
});

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Deployment Notes

  • Create deployments in the Azure Portal before use
  • Each deployment has its own name and configuration
  • Deployment names are used as model identifiers
  • Supports virtual network integration
  • Provides managed identity authentication

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Resources