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

# Azure AI Foundry

> Configure AzureAIFoundry, Agno's model class for Azure AI Foundry-hosted models.

The Azure AI Foundry model provides access to Azure-hosted AI Foundry models.

## 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, then `"2024-05-01-preview"`) |
| `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 |
| `client` | `Optional[ChatCompletionsClient]` | `None` | Pre-configured Azure AI client |
| `async_client` | `Optional[AsyncChatCompletionsClient]` | `None` | Pre-configured async Azure AI client |
| `model_type` | `ModelType` | `ModelType.MODEL` | Functional role of this model (e.g. `MODEL`, `OUTPUT_MODEL`, `PARSER_MODEL`). Set by the agent |
| `supports_native_structured_outputs` | `bool` | `False` | Whether the model supports structured outputs natively |
| `supports_json_schema_outputs` | `bool` | `False` | Whether the model uses JSON schema for structured outputs |
| `system_prompt` | `Optional[str]` | `None` | System prompt from the model added to the agent |
| `instructions` | `Optional[List[str]]` | `None` | Instructions from the model added to the agent |
| `tool_message_role` | `str` | `"tool"` | Role of tool messages |
| `assistant_message_role` | `str` | `"assistant"` | Role of assistant messages |
| `cache_response` | `bool` | `False` | Cache model responses to avoid redundant API calls during development |
| `cache_ttl` | `Optional[int]` | `None` | Time-to-live for cached responses, in seconds |
| `cache_dir` | `Optional[str]` | `None` | Directory for the response cache. Defaults to `~/.agno/cache/model_responses` |
| `retries` | `int` | `0` | Number of retries to attempt before raising a ModelProviderError |
| `delay_between_retries` | `int` | `1` | Delay between retries, in seconds |
| `exponential_backoff` | `bool` | `False` | If True, the delay between retries is doubled each time |
| `retry_with_guidance` | `bool` | `True` | Retry a failed model invocation once with a guidance message appended |
| `retry_with_guidance_limit` | `int` | `1` | Number of times to retry the model invocation with guidance |


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