Ollama

The Ollama model provides access to open source models, both locally-hosted and via Ollama Cloud.

Local Usage: Run models on your own hardware using the Ollama client. Perfect for development, privacy-sensitive workloads, and when you want full control over your infrastructure.

Cloud Usage: Access cloud-hosted models via Ollama Cloud with an API key for scalable, production-ready deployments. No local setup required - simply set your OLLAMA_API_KEY and start using powerful models instantly.

Key Features

• Dual Deployment Options: Choose between local hosting for privacy and control, or cloud hosting for scalability
• Seamless Switching: Easy transition between local and cloud deployments with minimal code changes
• Auto-configuration: When using an API key, the host automatically defaults to Ollama Cloud
• Wide Model Support: Access to extensive library of open-source models including GPT-OSS, Llama, Qwen, DeepSeek, and Phi models

Parameters

Parameter	Type	Default	Description
id	str	"llama3.1"	The name of the Ollama model to use
name	str	"Ollama"	The name of the model
provider	str	"Ollama"	The provider of the model
format	Optional[Any]	None	The format to return the response in (e.g., “json”)
options	Optional[Any]	None	Additional model options (temperature, top_p, etc.)
keep_alive	Optional[Union[float, str]]	None	How long to keep the model loaded (e.g., “5m”, 3600 seconds)
request_params	Optional[Dict[str, Any]]	None	Additional parameters to include in the request
host	Optional[str]	None ("http://localhost:11434"; "https://ollama.com" when api_key is set)	The host URL for the Ollama server
timeout	Optional[Any]	None	Request timeout in seconds
api_key	Optional[str]	getenv("OLLAMA_API_KEY")	API key for Ollama Cloud. When set, the host defaults to Ollama Cloud
client_params	Optional[Dict[str, Any]]	None	Additional parameters for client configuration
client	Optional[OllamaClient]	None	Pre-configured Ollama client
async_client	Optional[AsyncOllamaClient]	None	Pre-configured async Ollama 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	True	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