Team - Agno

Parameters

Parameter	Type	Default	Description
`members`	`List[Union[Agent, Team]]`	-	List of agents or teams that make up this team
`mode`	`Literal["route", "coordinate", "collaborate"]`	`"coordinate"`	Team operating mode
`model`	`Optional[Model]`	`None`	Model to use for the team
`name`	`Optional[str]`	`None`	Name of the team
`team_id`	`Optional[str]	`None`	Team UUID (autogenerated if not set)
`parent_team_id`	`Optional[str]`	`None`	If this team is part of a team itself, this is the role of the team
`workflow_id`	`Optional[str]`	`None`	The workflow this team belongs to
`role`	`Optional[str]`	`None`	Role of the team within its parent team
`user_id`	`Optional[str]`	`None`	ID of the user interacting with this team
`session_id`	`Optional[str]`	`None`	Session UUID (autogenerated if not set)
`team_session_id`	`Optional[str]`	`None`	In the case where the team is a member of a team itself
`session_name`	`Optional[str]`	`None`	Session name
`session_state`	`Optional[Dict[str, Any]]`	`None`	Session state (stored in the database to persist across runs)
`team_session_state`	`Optional[Dict[str, Any]]`	`None`	Team session state (shared between team leaders and team members)
`add_state_in_messages`	`bool`	`False`	If True, add the session state variables in the user and system messages
`description`	`Optional[str]`	`None`	A description of the team that is added to the start of the system message
`instructions`	`Optional[Union[str, List[str], Callable]]`	`None`	List of instructions for the team
`expected_output`	`Optional[str]`	`None`	Provide the expected output from the team
`additional_context`	`Optional[str]`	`None`	Additional context added to the end of the system message
`success_criteria`	`Optional[str]`	`None`	Define the success criteria for the team
`markdown`	`bool`	`False`	If markdown=true, add instructions to format the output using markdown
`add_datetime_to_instructions`	`bool`	`False`	If True, add the current datetime to the instructions to give the team a sense of time
`add_location_to_instructions`	`bool`	`False`	If True, add the current location to the instructions to give the team a sense of location
`add_member_tools_to_system_message`	`bool`	`True`	If True, add the tools available to team members to the system message
`knowledge`	`Optional[AgentKnowledge]`	`None`	Add a knowledge base to the team
`knowledge_filters`	`Optional[Dict[str, Any]]`	`None`	Filters to apply to knowledge base searches
`enable_agentic_knowledge_filters`	`Optional[bool]`	`False`	Let the agent choose the knowledge filters
`retriever`	`Optional[Callable[..., Optional[List[Dict]]]]`	`None`	Custom retrieval function to get references
`references_format`	`Literal["json", "yaml"]`	`"json"`	Format of the references
`context`	`Optional[Dict[str, Any]]`	`None`	User provided context
`add_context`	`bool`	`False`	If True, add the context to the user prompt
`enable_agentic_context`	`bool`	`False`	If True, enable the team agent to update the team context and automatically send the team context to the members
`share_member_interactions`	`bool`	`False`	If True, send all previous member interactions to members
`get_member_information_tool`	`bool`	`False`	If True, add a tool to get information about the team members
`search_knowledge`	`bool`	`True`	Add a tool to search the knowledge base (aka Agentic RAG)
`read_team_history`	`bool`	`False`	If True, read the team history
`tools`	`Optional[List[Union[Toolkit, Callable, Function, Dict]]]`	`None`	A list of tools provided to the Model
`show_tool_calls`	`bool`	`True`	Show tool calls in Team 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 team model
`tool_hooks`	`Optional[List[Callable]]`	`None`	A list of hooks to be called before and after the tool call
`response_model`	`Optional[Type[BaseModel]]`	`None`	Response model for the team response
`parser_model`	`Optional[Model]`	`None`	Model to use for parsing the response
`parser_model_prompt`	`Optional[str]`	`None`	Prompt to use for parsing the response
`use_json_mode`	`bool`	`False`	If `response_model` is set, sets the response mode of the model
`parse_response`	`bool`	`True`	If True, parse the response
`memory`	`Optional[Union[TeamMemory, Memory]]`	`None`	Memory for the team
`enable_agentic_memory`	`bool`	`False`	Enable the agent to manage memories of the user
`enable_user_memories`	`bool`	`False`	If True, the agent creates/updates user memories at the end of runs
`add_memory_references`	`Optional[bool]`	`None`	If True, the agent adds a reference to the user memories in the response
`enable_session_summaries`	`bool`	`False`	If True, the agent creates/updates session summaries at the end of runs
`add_session_summary_references`	`Optional[bool]`	`None`	If True, the agent adds a reference to the session summaries in the response
`add_history_to_messages`	`bool`	`False`	If True, add messages from the chat history to the messages list sent to the Model.
`num_history_runs`	`int`	`3`	Number of historical runs to include in the messages
`storage`	`Optional[Storage]`	`None`	Storage for the team
`extra_data`	`Optional[Dict[str, Any]]`	`None`	Extra data stored with this team
`reasoning`	`bool`	`False`	Enable reasoning for the team
`reasoning_model`	`Optional[Model]`	`None`	Model to use for reasoning
`reasoning_min_steps`	`int`	`1`	Minimum number of reasoning steps
`reasoning_max_steps`	`int`	`10`	Maximum number of reasoning steps
`stream`	`Optional[bool]`	`None`	Stream the response from the Team
`stream_intermediate_steps`	`bool`	`False`	Stream the intermediate steps from the Team
`stream_member_events`	`bool`	`True`	Stream the member events from the Team members
`store_events`	`bool`	`False`	Store the streaming events on the TeamRunResponse
`events_to_skip`	`Optional[List[Union[RunEvent, TeamRunEvent]]]`	`None`	Specify which event types to skip when storing events on the TeamRunResponse
`app_id`	`Optional[str]`	`None`	Optional app ID. Indicates this team is part of an app
`debug_mode`	`bool`	`False`	Enable debug logs
`show_members_responses`	`bool`	`False`	Enable member logs - Sets the debug_mode for team and members
`monitoring`	`bool`	`False`	Log team information to agno.com for monitoring
`telemetry`	`bool`	`True`	Log minimal telemetry for analytics

Functions

Function	Description
`print_response`	Run the team and print the response
`run`	Run the team
`aprint_response`	Run the team and print the response asynchronously
`arun`	Run the team asynchronously
`get_session_summary`	Get the session summary for the given session ID and user ID
`get_user_memories`	Get the user memories for the given user ID
`load_session`	Load an existing session from the database or create a new one
`rename_session`	Rename the current session
`delete_session`	Delete a session
`get_images`	Get all images from the team session
`get_videos`	Get all videos from the team session
`get_audio`	Get all audio from the team session
`add_tool`	Add a tool to the team
`set_tools`	Replace the tools of the team

Team Modes

The team can operate in three different modes:

"route" - Routes tasks to specific team members
"coordinate" - Coordinates between team members (default)
"collaborate" - Enables collaboration between team members

Knowledge Base Integration

The team supports integration with a knowledge base through the following features:

knowledge: Add a knowledge base to the team
knowledge_filters: Apply filters to knowledge base searches
enable_agentic_knowledge_filters: Let the agent choose the knowledge filters
retriever: Custom retrieval function for references
search_knowledge: Tool to search the knowledge base

Memory and History

The team supports various memory and history features:

memory: Team memory storage
enable_agentic_memory: Enable agent memory management
enable_user_memories: Create/update user memories at the end of runs
enable_session_summaries: Create/update session summaries at the end of runs
add_history_to_messages: Add messages from the chat history to the messages list sent to the Model.
num_history_runs: Number of historical runs to include

Tools and Functions

The team can be equipped with various tools and functions:

tools: List of tools provided to the model
tool_call_limit: Maximum number of tool calls
tool_choice: Control which tool is called
tool_hooks: Hooks for tool execution

Reasoning

The team supports reasoning capabilities:

reasoning: Enable reasoning
reasoning_model: Model for reasoning
reasoning_min_steps: Minimum reasoning steps
reasoning_max_steps: Maximum reasoning steps

​Parameters

​Functions

​Team Modes

​Knowledge Base Integration

​Memory and History

​Tools and Functions

​Reasoning