Agent - Agno

Parameter	Type	Default	Description
`model`	`Optional[Model]`	`None`	Model to use for this Agent
`name`	`Optional[str]`	`None`	Agent name
`agent_id`	`Optional[str]`	`None`	Agent UUID (autogenerated if not set)
`agent_data`	`Optional[Dict[str, Any]]`	`None`	Metadata associated with this agent
`introduction`	`Optional[str]`	`None`	Agent introduction. This is added to the chat history when a run is started.
`user_id`	`Optional[str]`	`None`	ID of the user interacting with this agent
`user_data`	`Optional[Dict[str, Any]]`	`None`	Metadata associated with the user interacting with this agent
`session_id`	`Optional[str]`	`None`	Session UUID (autogenerated if not set)
`session_name`	`Optional[str]`	`None`	Session name
`session_state`	`Optional[Dict[str, Any]]`	`None`	Session state (stored in the database to persist across runs)
`context`	`Optional[Dict[str, Any]]`	`None`	Context available for tools and prompt functions
`add_context`	`bool`	`False`	If True, add the context to the user prompt
`resolve_context`	`bool`	`True`	If True, resolve the context (i.e. call any functions in the context) before running the agent
`memory`	`Optional[Memory]`	`None`	Agent Memory
`add_history_to_messages`	`bool`	`False`	Add chat history to the messages sent to the Model
`num_history_responses`	`int`	`3`	Number of historical responses to add to the messages
`knowledge`	`Optional[AgentKnowledge]`	`None`	Agent Knowledge
`add_references`	`bool`	`False`	Enable RAG by adding references from AgentKnowledge to the user prompt
`retriever`	`Optional[Callable[..., Optional[List[Dict]]]]`	`None`	Function to get references to add to the user_message
`references_format`	`Literal["json", "yaml"]`	`"json"`	Format of the references
`storage`	`Optional[AgentStorage]`	`None`	Agent Storage
`extra_data`	`Optional[Dict[str, Any]]`	`None`	Extra data stored with this agent
`tools`	`Optional[List[Union[Toolkit, Callable, Function]]]`	`None`	A list of tools provided to the Model
`show_tool_calls`	`bool`	`False`	Show tool calls in Agent response
`tool_call_limit`	`Optional[int]`	`None`	Maximum number of tool calls allowed
`tool_choice`	`Optional[Union[str, Dict[str, Any]]]`	`None`	Controls which (if any) tool is called by the model
`reasoning`	`bool`	`False`	Enable reasoning by working through the problem step by step
`reasoning_model`	`Optional[Model]`	`None`	Model to use for reasoning
`reasoning_agent`	`Optional[Agent]`	`None`	Agent to use for reasoning
`reasoning_min_steps`	`int`	`1`	Minimum number of reasoning steps
`reasoning_max_steps`	`int`	`10`	Maximum number of reasoning steps
`read_chat_history`	`bool`	`False`	Add a tool that allows the Model to read the chat history
`search_knowledge`	`bool`	`True`	Add a tool that allows the Model to search the knowledge base
`update_knowledge`	`bool`	`False`	Add a tool that allows the Model to update the knowledge base
`read_tool_call_history`	`bool`	`False`	Add a tool that allows the Model to get the tool call history
`system_message`	`Optional[Union[str, Callable, Message]]`	`None`	Provide the system message as a string or function
`system_message_role`	`str`	`"system"`	Role for the system message
`create_default_system_message`	`bool`	`True`	If True, create a default system message using agent settings
`description`	`Optional[str]`	`None`	A description of the Agent that is added to the start of the system message
`goal`	`Optional[str]`	`None`	The goal of this task
`instructions`	`Optional[Union[str, List[str], Callable]]`	`None`	List of instructions for the agent
`expected_output`	`Optional[str]`	`None`	Provide the expected output from the Agent
`additional_context`	`Optional[str]`	`None`	Additional context added to the end of the system message
`markdown`	`bool`	`False`	If markdown=true, add instructions to format the output using markdown
`add_name_to_instructions`	`bool`	`False`	If True, add the agent name to the instructions
`add_datetime_to_instructions`	`bool`	`False`	If True, add the current datetime to the instructions
`add_state_in_messages`	`bool`	`False`	If True, add the session state variables in messages
`add_messages`	`Optional[List[Union[Dict, Message]]]`	`None`	A list of extra messages added after the system message
`user_message`	`Optional[Union[List, Dict, str, Callable, Message]]`	`None`	Provide the user message
`user_message_role`	`str`	`"user"`	Role for the user message
`create_default_user_message`	`bool`	`True`	If True, create a default user message
`retries`	`int`	`0`	Number of retries to attempt
`delay_between_retries`	`int`	`1`	Delay between retries
`exponential_backoff`	`bool`	`False`	If True, the delay between retries is doubled each time
`response_model`	`Optional[Type[BaseModel]]`	`None`	Provide a response model to get the response as a Pydantic model
`parse_response`	`bool`	`True`	If True, the response is converted into the response_model
`use_json_mode`	`bool`	`False`	If `response_model` is set, sets the response "mode" of the model, i.e. if the model should explicitly respond with a JSON object instead of a Pydantic model
`save_response_to_file`	`Optional[str]`	`None`	Save the response to a file
`stream`	`Optional[bool]`	`None`	Stream the response from the Agent
`stream_intermediate_steps`	`bool`	`False`	Stream the intermediate steps from the Agent
`team`	`Optional[List[Agent]]`	`None`	The team of agents that this agent can transfer tasks to
`team_data`	`Optional[Dict[str, Any]]`	`None`	Data shared between team members
`role`	`Optional[str]`	`None`	If this Agent is part of a team, this is the role of the agent
`respond_directly`	`bool`	`False`	If True, member agent responds directly to user
`add_transfer_instructions`	`bool`	`True`	Add instructions for transferring tasks to team members
`team_response_separator`	`str`	`"\n"`	Separator between responses from the team
`debug_mode`	`bool`	`False`	Enable debug logs
`monitoring`	`bool`	`False`	Log Agent information to agno.com for monitoring
`telemetry`	`bool`	`True`	Log minimal telemetry for analytics

Reference