> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-update-deprecated-models.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Azure AI Foundry

> Use Azure AI Foundry hosted models with Agno agents.

Use various open source models hosted on Azure's infrastructure. Learn more [here](https://learn.microsoft.com/azure/ai-services/models).

Azure AI Foundry provides access to models like `Phi`, `Llama`, `Mistral`, `Cohere` and more.

## Authentication

Navigate to Azure AI Foundry on the [Azure Portal](https://portal.azure.com/) and create a service. Then set your environment variables:

<CodeGroup>
  ```bash Mac theme={null}
  export AZURE_API_KEY=***
  export AZURE_ENDPOINT=***  # Of the form https://<your-host-name>.<your-azure-region>.models.ai.azure.com/models
  # Optional:
  # export AZURE_API_VERSION=***
  ```

  ```bash Windows theme={null}
  setx AZURE_API_KEY ***  # Of the form https://<your-host-name>.<your-azure-region>.models.ai.azure.com/models
  setx AZURE_ENDPOINT ***
  # Optional:
  # setx AZURE_API_VERSION ***
  ```
</CodeGroup>

## Example

Use `AzureAIFoundry` with your `Agent`:

<CodeGroup>
  ```python agent.py theme={null}
  from agno.agent import Agent
  from agno.models.azure import AzureAIFoundry

  agent = Agent(
      model=AzureAIFoundry(id="Phi-4"),
      markdown=True
  )

  # Print the response on the terminal
  agent.print_response("Share a 2 sentence horror story.")
  ```
</CodeGroup>

## Advanced Examples

View more examples [here](/models/providers/cloud/azure-ai-foundry/usage/basic-stream).

## Parameters

| Parameter           | Type                              | Default            | Description                                                                        |
| ------------------- | --------------------------------- | ------------------ | ---------------------------------------------------------------------------------- |
| `id`                | `str`                             | `"gpt-4o"`         | The id of the model to use                                                         |
| `name`              | `str`                             | `"AzureAIFoundry"` | The name of the model                                                              |
| `provider`          | `str`                             | `"Azure"`          | The provider of the model                                                          |
| `temperature`       | `Optional[float]`                 | `None`             | Controls randomness in the model's output (0.0 to 2.0)                             |
| `max_tokens`        | `Optional[int]`                   | `None`             | Maximum number of tokens to generate in the response                               |
| `frequency_penalty` | `Optional[float]`                 | `None`             | Penalizes new tokens based on their frequency in the text so far (-2.0 to 2.0)     |
| `presence_penalty`  | `Optional[float]`                 | `None`             | Penalizes new tokens based on whether they appear in the text so far (-2.0 to 2.0) |
| `top_p`             | `Optional[float]`                 | `None`             | Controls diversity via nucleus sampling (0.0 to 1.0)                               |
| `stop`              | `Optional[Union[str, List[str]]]` | `None`             | Up to 4 sequences where the API will stop generating further tokens                |
| `seed`              | `Optional[int]`                   | `None`             | Random seed for deterministic sampling                                             |
| `model_extras`      | `Optional[Dict[str, Any]]`        | `None`             | Additional model-specific parameters                                               |
| `strict_output`     | `bool`                            | `True`             | Controls schema adherence for structured outputs                                   |
| `request_params`    | `Optional[Dict[str, Any]]`        | `None`             | Additional parameters to include in the request                                    |
| `api_key`           | `Optional[str]`                   | `None`             | The API key for Azure AI Foundry (defaults to AZURE\_API\_KEY env var)             |
| `api_version`       | `Optional[str]`                   | `None`             | The API version to use (defaults to AZURE\_API\_VERSION env var)                   |
| `azure_endpoint`    | `Optional[str]`                   | `None`             | The Azure endpoint URL (defaults to AZURE\_ENDPOINT env var)                       |
| `timeout`           | `Optional[float]`                 | `None`             | Request timeout in seconds                                                         |
| `max_retries`       | `Optional[int]`                   | `None`             | Maximum number of retries for failed requests                                      |
| `http_client`       | `Optional[httpx.Client]`          | `None`             | HTTP client instance for making requests                                           |
| `client_params`     | `Optional[Dict[str, Any]]`        | `None`             | Additional parameters for client configuration                                     |

`AzureAIFoundry` is a subclass of the [Model](/reference/models/model) class and has access to the same params.

## Supported Models

Azure AI Foundry provides access to a wide variety of models including:

* **Microsoft Models**: `Phi-4`, `Phi-3.5-mini-instruct`, `Phi-3.5-vision-instruct`
* **Meta Models**: `Meta-Llama-3.1-405B-Instruct`, `Meta-Llama-3.1-70B-Instruct`, `Meta-Llama-3.1-8B-Instruct`
* **Mistral Models**: `Mistral-large`, `Mistral-small`, `Mistral-Nemo`
* **Cohere Models**: `Cohere-command-r-plus`, `Cohere-command-r`

For the complete list of available models, visit the [Azure AI Foundry documentation](https://learn.microsoft.com/azure/ai-services/models).