HuggingFace

The HuggingFace model provides access to models hosted on the HuggingFace Hub.

Parameters

Parameter	Type	Default	Description
id	str	"meta-llama/Meta-Llama-3-8B-Instruct"	The id of the Hugging Face model to use
name	str	"HuggingFace"	The name of the model
provider	str	"HuggingFace"	The provider of the model
store	Optional[bool]	None	Whether to store the output of the request
frequency_penalty	Optional[float]	None	Penalizes new tokens based on their frequency in the text so far
logit_bias	Optional[Any]	None	Modifies the likelihood of specified tokens appearing
logprobs	Optional[bool]	None	Return log probabilities of the output tokens
max_tokens	Optional[int]	None	Maximum number of tokens to generate
presence_penalty	Optional[float]	None	Penalizes new tokens based on whether they appear in the text so far
seed	Optional[int]	None	Random seed for deterministic sampling
stop	Optional[Union[str, List[str]]]	None	Sequences where the API stops generating further tokens
temperature	Optional[float]	None	Controls randomness in the model’s output
top_logprobs	Optional[int]	None	Number of most likely tokens to return log probabilities for
top_p	Optional[float]	None	Controls diversity via nucleus sampling
request_params	Optional[Dict[str, Any]]	None	Additional parameters to include in the request
api_key	Optional[str]	None	The API key for Hugging Face (defaults to HF_TOKEN env var)
base_url	Optional[Union[str, httpx.URL]]	None	The base URL for the inference endpoint
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
client_params	Optional[Dict[str, Any]]	None	Additional parameters for client configuration
client	Optional[InferenceClient]	None	Pre-configured HuggingFace inference client
async_client	Optional[AsyncInferenceClient]	None	Pre-configured async HuggingFace inference client
model_type	ModelType	ModelType.MODEL	Functional role of this model (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