> ## 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.

# Meta

> Configure Llama, Agno's model class for Meta's Llama API.

The Meta model provides access to Meta's language models.

## Parameters

| Parameter | Type | Default | Description |
| - | - | - | - |
| `id` | `str` | `"Llama-4-Maverick-17B-128E-Instruct-FP8"` | The id of the Llama model to use |
| `name` | `str` | `"Llama"` | The name of the model |
| `provider` | `str` | `"Llama"` | The provider of the model |
| `max_completion_tokens` | `Optional[int]` | `None` | Maximum number of tokens to generate |
| `repetition_penalty` | `Optional[float]` | `None` | Penalty for repeating tokens (higher values reduce repetition) |
| `temperature` | `Optional[float]` | `None` | Controls randomness in the model's output |
| `top_p` | `Optional[float]` | `None` | Controls diversity via nucleus sampling |
| `top_k` | `Optional[int]` | `None` | Controls diversity via top-k sampling |
| `extra_headers` | `Optional[Any]` | `None` | Additional headers for the request |
| `extra_query` | `Optional[Any]` | `None` | Additional query parameters for the request |
| `extra_body` | `Optional[Any]` | `None` | Additional body fields for the request |
| `request_params` | `Optional[Dict[str, Any]]` | `None` | Additional parameters to include in the request |
| `api_key` | `Optional[str]` | `None` | The API key for the Llama API (defaults to LLAMA\_API\_KEY env var) |
| `base_url` | `Optional[Union[str, httpx.URL]]` | `None` | The base URL for the Llama API |
| `timeout` | `Optional[float]` | `None` | Request timeout in seconds |
| `max_retries` | `Optional[int]` | `None` | Maximum number of client retries for failed requests |
| `default_headers` | `Optional[Any]` | `None` | Default headers for client requests |
| `default_query` | `Optional[Any]` | `None` | Default query parameters for client requests |
| `http_client` | `Optional[Union[httpx.Client, httpx.AsyncClient]]` | `None` | Custom HTTP client for requests |
| `client_params` | `Optional[Dict[str, Any]]` | `None` | Additional parameters for client configuration |
| `client` | `Optional[LlamaAPIClient]` | `None` | Pre-configured Llama API client |
| `async_client` | `Optional[AsyncLlamaAPIClient]` | `None` | Pre-configured async Llama API 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` | `True` | 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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