> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/openai/openai-python/llms.txt
> Use this file to discover all available pages before exploring further.

# Azure OpenAI

> Use the OpenAI Python SDK with Azure OpenAI Service

The OpenAI Python SDK supports [Azure OpenAI Service](https://learn.microsoft.com/azure/ai-services/openai/overview) through the `AzureOpenAI` class.

<Note>
  The Azure API shape differs from the core OpenAI API shape, which means that the static types for responses and parameters won't always be correct.
</Note>

## Basic Usage

### With API Key

```python theme={null}
from openai import AzureOpenAI

# API key is read from AZURE_OPENAI_API_KEY environment variable
client = AzureOpenAI(
    api_version="2023-07-01-preview",
    azure_endpoint="https://example-endpoint.openai.azure.com",
)

completion = client.chat.completions.create(
    model="deployment-name",  # e.g. gpt-35-instant
    messages=[
        {
            "role": "user",
            "content": "How do I output all files in a directory using Python?",
        },
    ],
)
print(completion.to_json())
```

### With Azure Deployment

You can specify an `azure_deployment` to include it in the base URL:

```python theme={null}
from openai import AzureOpenAI

client = AzureOpenAI(
    api_version="2023-07-01-preview",
    azure_endpoint="https://example-resource.azure.openai.com/",
    azure_deployment="deployment-name",  # e.g. gpt-35-instant
)

completion = client.chat.completions.create(
    model="<ignored>",  # Model parameter is ignored when using azure_deployment
    messages=[
        {
            "role": "user",
            "content": "How do I output all files in a directory using Python?",
        },
    ],
)
print(completion.to_json())
```

<Warning>
  The `azure_deployment` parameter is not supported with Assistants APIs.
</Warning>

## Authentication Methods

Azure OpenAI supports multiple authentication methods:

### API Key

The simplest method uses an API key:

```python theme={null}
from openai import AzureOpenAI

client = AzureOpenAI(
    api_key="your-azure-api-key",  # or use AZURE_OPENAI_API_KEY env var
    api_version="2023-07-01-preview",
    azure_endpoint="https://example-endpoint.openai.azure.com",
)
```

### Azure Active Directory (Recommended)

For production deployments, use Azure AD authentication:

```python theme={null}
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from openai import AzureOpenAI

token_provider = get_bearer_token_provider(
    DefaultAzureCredential(),
    "https://cognitiveservices.azure.com/.default"
)

client = AzureOpenAI(
    api_version="2023-07-01-preview",
    azure_endpoint="https://example-endpoint.openai.azure.com",
    azure_ad_token_provider=token_provider,
)
```

### Azure AD Token (Static)

You can also pass a static Azure AD token:

```python theme={null}
from openai import AzureOpenAI

client = AzureOpenAI(
    api_version="2023-07-01-preview",
    azure_endpoint="https://example-endpoint.openai.azure.com",
    azure_ad_token="your-azure-ad-token",  # or use AZURE_OPENAI_AD_TOKEN env var
)
```

## Configuration

### Required Parameters

The following parameters are required:

* **`api_version`**: Azure API version (or `OPENAI_API_VERSION` environment variable)
* **`azure_endpoint`** OR **`base_url`**: Your Azure endpoint (or `AZURE_OPENAI_ENDPOINT` environment variable)

### Environment Variables

The SDK automatically reads these environment variables:

```bash theme={null}
export AZURE_OPENAI_API_KEY="your-azure-key"
export AZURE_OPENAI_ENDPOINT="https://example-endpoint.openai.azure.com"
export OPENAI_API_VERSION="2023-07-01-preview"
export AZURE_OPENAI_AD_TOKEN="your-ad-token"  # Optional
```

### Available Options

All options from the base `OpenAI` client are available, plus:

| Parameter                 | Description                                  |
| ------------------------- | -------------------------------------------- |
| `azure_endpoint`          | Your Azure endpoint URL                      |
| `azure_deployment`        | Model deployment name to include in base URL |
| `api_version`             | Azure API version                            |
| `azure_ad_token`          | Static Azure AD token                        |
| `azure_ad_token_provider` | Function that returns an Azure AD token      |

## Async Client

Use `AsyncAzureOpenAI` for async operations:

```python theme={null}
import asyncio
from openai import AsyncAzureOpenAI

async def main():
    client = AsyncAzureOpenAI(
        api_version="2023-07-01-preview",
        azure_endpoint="https://example-endpoint.openai.azure.com",
    )
    
    completion = await client.chat.completions.create(
        model="deployment-name",
        messages=[
            {
                "role": "user",
                "content": "Say this is a test",
            }
        ],
    )
    print(completion.to_json())

asyncio.run(main())
```

## API Version

Azure OpenAI uses versioned APIs. See the [Azure REST API versioning docs](https://learn.microsoft.com/azure/ai-services/openai/reference#rest-api-versioning) for available versions.

Currently recommended version: `2023-07-01-preview`

## Deployment Names

In Azure OpenAI, you deploy models with custom deployment names. Use your deployment name in the `model` parameter:

```python theme={null}
completion = client.chat.completions.create(
    model="my-gpt-4-deployment",  # Your Azure deployment name
    messages=[...],
)
```

## Learn More

* [Azure OpenAI Service Documentation](https://learn.microsoft.com/azure/ai-services/openai/overview)
* [Create an Azure OpenAI Resource](https://learn.microsoft.com/azure/cognitive-services/openai/how-to/create-resource)
* [Azure Active Directory Authentication](https://www.microsoft.com/security/business/identity-access/microsoft-entra-id)