Team | Agno

Parameters

Parameter	Type	Default	Description
`members`	`Union[List[Union[Agent, Team]], Callable[..., List]]`	-	List of agents or teams that make up this team, or a callable factory that returns the list
`id`	`Optional[str]`	`None`	Team ID (generated from name when supplied, otherwise generated automatically)
`model`	`Optional[Union[Model, str]]`	`None`	Model to use for the team. Can be a Model object or a model string (`provider:model_id`)
`fallback_models`	`Optional[List[Union[Model, str]]]`	`None`	Models tried in order when the primary model fails. Ignored if `fallback_config` is set
`fallback_config`	`Optional[FallbackConfig]`	`None`	Fallback configuration for model failures, with support for error-specific routing. Takes precedence over `fallback_models`
`name`	`Optional[str]`	`None`	Name of the team
`role`	`Optional[str]`	`None`	Role of the team within its parent team
`mode`	`Optional[TeamMode]`	`None`	Team coordination mode (`coordinate`, `route`, `broadcast`, `tasks`). When set, overrides delegation flags to match the mode
`respond_directly`	`bool`	`False`	If True, the team leader won't process responses from the members and instead will return them directly. If `delegate_to_all_members=True` is also set, this is silently disabled with a warning
`determine_input_for_members`	`bool`	`True`	Set to False if you want to send the run input directly to the member agents
`delegate_to_all_members`	`bool`	`False`	If True, the team leader will delegate tasks to all members automatically, without any decision from the team leader. Takes precedence over `respond_directly=True`
`max_iterations`	`int`	`10`	Maximum number of task-loop iterations when `mode=TeamMode.tasks`
`user_id`	`Optional[str]`	`None`	Default user ID for this team
`session_id`	`Optional[str]`	`None`	Default session ID for this team (autogenerated if not set)
`session_state`	`Optional[Dict[str, Any]]`	`None`	Session state (stored in the database to persist across runs)
`add_session_state_to_context`	`bool`	`False`	Set to True to add the session_state to the context
`enable_agentic_state`	`bool`	`False`	Set to True to give the team tools to update the session_state dynamically
`overwrite_db_session_state`	`bool`	`False`	Set to True to overwrite the session state in the database with the session state provided in the run
`cache_session`	`bool`	`False`	If True, cache the current Team session in memory for faster access
`resolve_in_context`	`bool`	`True`	If True, resolve the session_state, dependencies, and metadata 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
`use_instruction_tags`	`bool`	`False`	If True, wrap instructions in `<instructions>` tags
`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
`markdown`	`bool`	`False`	If markdown=true, add instructions to format the output using markdown
`add_datetime_to_context`	`bool`	`False`	If True, add the current datetime to the instructions to give the team a sense of time
`add_location_to_context`	`bool`	`False`	If True, add the current location to the instructions to give the team a sense of location
`datetime_format`	`Optional[str]`	`None`	Custom format string for the datetime added to context (e.g. `"%Y-%m-%d %H:%M:%S"`). If None, the default datetime string representation is used
`timezone_identifier`	`Optional[str]`	`None`	Allows for custom timezone for datetime instructions following the TZ Database format
`add_name_to_context`	`bool`	`False`	If True, add the team name to the instructions
`add_member_tools_to_context`	`bool`	`False`	If True, add the tools available to team members to the context
`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
`introduction`	`Optional[str]`	`None`	Introduction message for the Team
`additional_input`	`Optional[List[Union[str, Dict, BaseModel, Message]]]`	`None`	A list of extra messages added after the system message and before the user message
`db`	`Optional[Union[BaseDb, AsyncBaseDb]]`	`None`	Database to use for this team
`checkpoint`	`Optional[Literal["runs", "tool-batch", "tools"]]`	`None`	When to persist run state to the database. `"runs"` writes only at terminal states; `"tool-batch"` also writes after each model turn. `None` falls back to the AgentOS-level setting, else `"runs"`. `"tools"` is currently unsupported and raises `NotImplementedError`
`memory_manager`	`Optional[MemoryManager]`	`None`	Memory manager to use for this team
`dependencies`	`Optional[Dict[str, Any]]`	`None`	User provided dependencies
`add_dependencies_to_context`	`bool`	`False`	If True, add the dependencies to the user prompt
`knowledge`	`Optional[Union[KnowledgeProtocol, Callable[..., KnowledgeProtocol]]]`	`None`	Add a knowledge base to the team
`knowledge_filters`	`Optional[Union[Dict[str, Any], List[FilterExpr]]]`	`None`	Filters to apply to knowledge base searches
`enable_agentic_knowledge_filters`	`Optional[bool]`	`False`	Let the team choose the knowledge filters
`update_knowledge`	`bool`	`False`	Add a tool that allows the Team to update Knowledge
`add_knowledge_to_context`	`bool`	`False`	If True, add references to the user prompt
`knowledge_retriever`	`Optional[Callable[..., Optional[List[Union[Dict, str]]]]]`	`None`	Retrieval function to get references
`references_format`	`Literal["json", "yaml"]`	`"json"`	Format of the references
`skills`	`Optional[Skills]`	`None`	Skills for this team. Loads structured instructions, reference docs, and scripts, and gives the team tools to access them
`share_member_interactions`	`bool`	`False`	If True, send all member interactions (request/response) during the current run to members that have been delegated a task to
`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)
`add_search_knowledge_instructions`	`bool`	`True`	If True, add search_knowledge instructions to the system prompt
`send_media_to_model`	`bool`	`True`	If False, media (images, videos, audio, files) is only available to tools and not sent to the LLM
`store_media`	`bool`	`True`	If True, store media in the database
`media_storage`	`Optional[Union[MediaStorage, AsyncMediaStorage]]`	`None`	Offload media to external storage and keep only a reference in the database
`store_tool_messages`	`bool`	`True`	If True, store tool results in the database
`store_history_messages`	`bool`	`False`	If True, store history messages in the database
`tools`	`Optional[Union[List[Union[Toolkit, Callable, Function, Dict]], Callable[..., List]]]`	`None`	A list of tools provided to the Model, or a callable factory that returns the list
`tool_choice`	`Optional[Union[str, Dict[str, Any]]]`	`None`	Controls which (if any) tool is called by the team model
`tool_call_limit`	`Optional[int]`	`None`	Maximum number of tool calls allowed
`max_tool_calls_from_history`	`Optional[int]`	`None`	Maximum number of tool calls from history to keep in context. If None, all tool calls from history are included. If set to N, only the last N tool calls from history are added to the context for memory management
`tool_hooks`	`Optional[List[Callable]]`	`None`	A list of hooks to be called before and after the tool call
`pre_hooks`	`Optional[List[Union[Callable[..., Any], BaseGuardrail, BaseEval]]]`	`None`	Functions called right after team session is loaded, before processing starts
`post_hooks`	`Optional[List[Union[Callable[..., Any], BaseGuardrail, BaseEval]]]`	`None`	Functions called after output is generated but before the response is returned
`input_schema`	`Optional[Type[BaseModel]]`	`None`	Input schema for validating input
`output_schema`	`Optional[Union[Type[BaseModel], Dict[str, Any]]]`	`None`	Output schema for the team response. Can be a Pydantic model or a JSON schema
`parser_model`	`Optional[Union[Model, str]]`	`None`	Provide a secondary model to parse the response from the primary model. Can be a Model object or a model string (`provider:model_id`)
`parser_model_prompt`	`Optional[str]`	`None`	Provide a prompt for the parser model
`output_model`	`Optional[Union[Model, str]]`	`None`	Provide an output model to parse the response from the team. Can be a Model object or a model string (`provider:model_id`)
`output_model_prompt`	`Optional[str]`	`None`	Provide a prompt for the output model
`use_json_mode`	`bool`	`False`	If `output_schema` is set, sets the response mode of the model
`parse_response`	`bool`	`True`	If True, parse the response
`enable_agentic_memory`	`bool`	`False`	Enable the team to manage memories of the user
`update_memory_on_run`	`bool`	`False`	If True, the team creates/updates user memories at the end of runs
`add_memories_to_context`	`Optional[bool]`	`None`	If True, add stored user memories to the system context
`enable_session_summaries`	`bool`	`False`	If True, the team creates/updates session summaries at the end of runs
`session_summary_manager`	`Optional[SessionSummaryManager]`	`None`	Session summary manager
`add_session_summary_to_context`	`Optional[bool]`	`None`	If True, the team adds session summaries to the context
`learning`	`Optional[Union[bool, LearningMachine]]`	`None`	LearningMachine for unified learning capabilities
`add_learnings_to_context`	`bool`	`True`	Add learnings context to system prompt
`compress_tool_results`	`bool`	`False`	If True, compress tool call results to save context space
`compression_manager`	`Optional[CompressionManager]`	`None`	Custom compression manager for compressing tool call results
`offload_tool_results`	`Optional[Union[bool, ResultStore]]`	`None`	Offload long tool results and member answers. `True` uses the defaults, a `ResultStore` customizes them, `None` allows parent-team inheritance, and `False` disables inherited offloading.
`add_history_to_context`	`bool`	`False`	Add messages from the chat history to the messages list sent to the Model. This only applies to the team leader, not the members.
`num_history_runs`	`Optional[int]`	`None`	Number of historical runs to include in the messages.
`num_history_messages`	`Optional[int]`	`None`	Number of historical messages to include messages list sent to the Model.
`add_team_history_to_members`	`bool`	`False`	If True, send the team-level history to the members, not the agent-level history
`num_team_history_runs`	`int`	`3`	Number of historical runs to include in the messages sent to the members
`search_past_sessions`	`Optional[bool]`	`False`	Add tools that let the team search past sessions and read their full conversations
`num_past_sessions_to_search`	`Optional[int]`	`None`	Maximum number of past sessions returned by the `search_past_sessions` tool. Defaults to 20 when unset
`num_past_session_runs_in_search`	`Optional[int]`	`None`	Number of runs included in each session preview returned by the `search_past_sessions` tool. Defaults to 3 when unset
`read_chat_history`	`bool`	`False`	If True, adds a tool to allow the team to read the chat history
`metadata`	`Optional[Dict[str, Any]]`	`None`	Metadata stored with this team
`reasoning_model`	`Optional[Union[Model, str]]`	`None`	Model to use for reasoning. Can be a Model object or a model string (`provider:model_id`)
`reasoning_agent`	`Optional[Agent]`	`None`	Agent to use for reasoning
`followups`	`bool`	`False`	If True, generate followup prompt suggestions after the main response and set them on the run output
`num_followups`	`int`	`3`	Number of followup prompts to generate
`followup_model`	`Optional[Union[Model, str]]`	`None`	Model used to generate followups. Defaults to the team's model
`stream`	`Optional[bool]`	`None`	Stream the response from the Team
`stream_events`	`Optional[bool]`	`None`	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 events from the Team
`events_to_skip`	`Optional[List[Union[RunEvent, TeamRunEvent]]]`	`None`	List of events to skip from the Team
`store_member_responses`	`bool`	`False`	Store member agent runs inside the team's RunOutput
`debug_mode`	`bool`	`False`	Enable debug logs
`debug_level`	`Literal[1, 2]`	`1`	Debug level: 1 = basic, 2 = detailed
`show_members_responses`	`bool`	`False`	Enable member logs - Sets the debug_mode for team and members
`retries`	`int`	`0`	Number of retries to attempt when running the Team
`delay_between_retries`	`int`	`1`	Delay between retries (in seconds)
`exponential_backoff`	`bool`	`False`	Exponential backoff: if True, the delay between retries is doubled each time
`telemetry`	`bool`	`True`	Log minimal telemetry for analytics
`cache_callables`	`bool`	`True`	Cache callable factory results by key. Key resolution uses custom key, then `user_id`, then `session_id`
`callable_tools_cache_key`	`Optional[Callable[..., Optional[str]]]`	`None`	Custom cache key function for tools callable factory. Overrides default key resolution
`callable_knowledge_cache_key`	`Optional[Callable[..., Optional[str]]]`	`None`	Custom cache key function for knowledge callable factory. Overrides default key resolution
`callable_members_cache_key`	`Optional[Callable[..., Optional[str]]]`	`None`	Custom cache key function for members callable factory. Overrides default key resolution

Functions

`run`

Run the team.

Parameters:

input (Union[str, List, Dict, Message, BaseModel, List[Message]]): The input to send to the team
stream (Optional[bool]): Whether to stream the response
stream_events (Optional[bool]): Whether to stream intermediate steps
session_id (Optional[str]): Session ID to use
session_state (Optional[Dict[str, Any]]): Session state to use. By default, merged with the session state in the db.
run_context (Optional[RunContext]): Run context to use
run_id (Optional[str]): Run ID to use
user_id (Optional[str]): User ID to use
audio (Optional[Sequence[Audio]]): Audio files to include
images (Optional[Sequence[Image]]): Image files to include
videos (Optional[Sequence[Video]]): Video files to include
files (Optional[Sequence[File]]): Files to include
knowledge_filters (Optional[Union[Dict[str, Any], List[FilterExpr]]]): Knowledge filters to apply
add_history_to_context (Optional[bool]): Whether to add history to context
add_dependencies_to_context (Optional[bool]): Whether to add dependencies to context
add_session_state_to_context (Optional[bool]): Whether to add session state to context
dependencies (Optional[Dict[str, Any]]): Dependencies to use for this run
metadata (Optional[Dict[str, Any]]): Metadata to use for this run
output_schema (Optional[Union[Type[BaseModel], Dict[str, Any]]]): Output schema to use for this run. Can be a Pydantic model or a JSON schema.
debug_mode (Optional[bool]): Whether to enable debug mode
yield_run_output (bool): Whether to yield the run output (only for streaming)

Returns:

A TeamRunOutput in non-streaming mode. Streaming yields event objects (including member-agent events) and, when yield_run_output=True, a final TeamRunOutput.

`arun`

Run the team asynchronously.

Parameters:

input (Union[str, List, Dict, Message, BaseModel, List[Message]]): The input to send to the team
stream (Optional[bool]): Whether to stream the response
stream_events (Optional[bool]): Whether to stream intermediate steps
session_id (Optional[str]): Session ID to use
session_state (Optional[Dict[str, Any]]): Session state to use. By default, merged with the session state in the db.
run_id (Optional[str]): Run ID to use
run_context (Optional[RunContext]): Run context to use
user_id (Optional[str]): User ID to use
audio (Optional[Sequence[Audio]]): Audio files to include
images (Optional[Sequence[Image]]): Image files to include
videos (Optional[Sequence[Video]]): Video files to include
files (Optional[Sequence[File]]): Files to include
knowledge_filters (Optional[Union[Dict[str, Any], List[FilterExpr]]]): Knowledge filters to apply
add_history_to_context (Optional[bool]): Whether to add history to context
add_dependencies_to_context (Optional[bool]): Whether to add dependencies to context
add_session_state_to_context (Optional[bool]): Whether to add session state to context
dependencies (Optional[Dict[str, Any]]): Dependencies to use for this run
metadata (Optional[Dict[str, Any]]): Metadata to use for this run
output_schema (Optional[Union[Type[BaseModel], Dict[str, Any]]]): Output schema to use for this run. Can be a Pydantic model or a JSON schema.
debug_mode (Optional[bool]): Whether to enable debug mode
yield_run_output (bool): Whether to yield the run output (only for streaming)
background (bool): Whether to run the team in background mode. Requires a configured database. Both streaming and non-streaming modes are supported.

Returns by mode:

Mode	Result
Foreground, non-streaming	Await a `TeamRunOutput`
Foreground, streaming	Async iterator of events including member-agent events; `yield_run_output=True` also yields the final `TeamRunOutput`
Background, non-streaming	Await a pending `TeamRunOutput` for polling
Background, streaming	Async iterator of SSE-formatted strings

Direct SDK background execution is an in-process task. Durable acceptance requires the AgentOS queue path.

`continue_run`

Continue a run.

Parameters:

run_response (Optional[TeamRunOutput]): The run response to continue
run_id (Optional[str]): The run ID to continue
requirements (Optional[List[Any]]): Updated run requirements to resolve, e.g. tool approvals
input (Optional[str]): Additional input to send when continuing the run
continue_from (Union[int, Literal["end", "last_user"]]): Where to resume the run from. Defaults to "end"
fork (bool): If True, continue into a new forked run instead of updating the original
regenerate (bool): If True, regenerate the run instead of continuing it
replace_original (Optional[bool]): Whether the new run replaces the original run in the session
additional_instructions (Optional[str]): Extra instructions added for the continued run
stream (Optional[bool]): Whether to stream the response
stream_events (Optional[bool]): Whether to stream intermediate steps
user_id (Optional[str]): User ID to use
session_id (Optional[str]): Session ID to use
run_context (Optional[RunContext]): Run context to use
knowledge_filters (Optional[Union[Dict[str, Any], List[FilterExpr]]]): Knowledge filters to apply
dependencies (Optional[Dict[str, Any]]): Dependencies to use for this run
metadata (Optional[Dict[str, Any]]): Metadata to use for this run
debug_mode (Optional[bool]): Whether to enable debug mode
yield_run_output (bool): Whether to yield the run output (only for streaming)

Returns:

Union[TeamRunOutput, Iterator[Union[TeamRunOutputEvent, RunOutputEvent, TeamRunOutput]]]: Either a TeamRunOutput or an iterator of events, depending on the stream parameter

`acontinue_run`

Continue a run asynchronously.

Parameters:

run_response (Optional[TeamRunOutput]): The run response to continue
run_id (Optional[str]): The run ID to continue
requirements (Optional[List[Any]]): Updated run requirements to resolve, e.g. tool approvals
input (Optional[str]): Additional input to send when continuing the run
continue_from (Union[int, Literal["end", "last_user"]]): Where to resume the run from. Defaults to "end"
fork (bool): If True, continue into a new forked run instead of updating the original
regenerate (bool): If True, regenerate the run instead of continuing it
replace_original (Optional[bool]): Whether the new run replaces the original run in the session
additional_instructions (Optional[str]): Extra instructions added for the continued run
stream (Optional[bool]): Whether to stream the response
stream_events (Optional[bool]): Whether to stream intermediate steps
user_id (Optional[str]): User ID to use
session_id (Optional[str]): Session ID to use
run_context (Optional[RunContext]): Run context to use
knowledge_filters (Optional[Union[Dict[str, Any], List[FilterExpr]]]): Knowledge filters to apply
dependencies (Optional[Dict[str, Any]]): Dependencies to use for this run
metadata (Optional[Dict[str, Any]]): Metadata to use for this run
debug_mode (Optional[bool]): Whether to enable debug mode
yield_run_output (bool): Whether to yield the run output (only for streaming)
background (bool): Use the background SSE path when stream=True; requires a database. Non-streaming continuation still runs inline

Returns:

Non-streaming execution returns a TeamRunOutput after awaiting. Foreground streaming yields event objects and an optional final TeamRunOutput when yield_run_output=True. Background streaming yields SSE-formatted strings.

For durable HTTP continuation, use AgentOS HITL continuations; the direct SDK method does not enqueue a durable job.

`print_response`

Run the team and print the response.

Parameters:

input (Union[List, Dict, str, Message, BaseModel, List[Message]]): The input to send to the team
stream (Optional[bool]): Whether to stream the response
session_id (Optional[str]): Session ID to use
session_state (Optional[Dict[str, Any]]): Session state to use. By default, merged with the session state in the db.
user_id (Optional[str]): User ID to use
run_id (Optional[str]): Run ID to use
show_message (bool): Whether to show the message (default: True)
show_reasoning (bool): Whether to show reasoning (default: True)
show_full_reasoning (bool): Whether to show full reasoning (default: False)
console (Optional[Any]): Console to use for output
tags_to_include_in_markdown (Optional[Set[str]]): Tags to include in markdown content
audio (Optional[Sequence[Audio]]): Audio files to include
images (Optional[Sequence[Image]]): Image files to include
videos (Optional[Sequence[Video]]): Video files to include
files (Optional[Sequence[File]]): Files to include
markdown (Optional[bool]): Whether to format output as markdown
knowledge_filters (Optional[Union[Dict[str, Any], List[FilterExpr]]]): Knowledge filters to apply
add_history_to_context (Optional[bool]): Whether to add history to context
dependencies (Optional[Dict[str, Any]]): Dependencies to use for this run
add_dependencies_to_context (Optional[bool]): Whether to add dependencies to context
add_session_state_to_context (Optional[bool]): Whether to add session state to context
metadata (Optional[Dict[str, Any]]): Metadata to use for this run
debug_mode (Optional[bool]): Whether to enable debug mode
show_member_responses (Optional[bool]): Whether to show member responses

`aprint_response`

Run the team and print the response asynchronously.

Parameters:

input (Union[List, Dict, str, Message, BaseModel, List[Message]]): The input to send to the team
stream (Optional[bool]): Whether to stream the response
session_id (Optional[str]): Session ID to use
session_state (Optional[Dict[str, Any]]): Session state to use. By default, merged with the session state in the db.
user_id (Optional[str]): User ID to use
run_id (Optional[str]): Run ID to use
show_message (bool): Whether to show the message (default: True)
show_reasoning (bool): Whether to show reasoning (default: True)
show_full_reasoning (bool): Whether to show full reasoning (default: False)
console (Optional[Any]): Console to use for output
tags_to_include_in_markdown (Optional[Set[str]]): Tags to include in markdown content
audio (Optional[Sequence[Audio]]): Audio files to include
images (Optional[Sequence[Image]]): Image files to include
videos (Optional[Sequence[Video]]): Video files to include
files (Optional[Sequence[File]]): Files to include
markdown (Optional[bool]): Whether to format output as markdown
knowledge_filters (Optional[Union[Dict[str, Any], List[FilterExpr]]]): Knowledge filters to apply
add_history_to_context (Optional[bool]): Whether to add history to context
dependencies (Optional[Dict[str, Any]]): Dependencies to use for this run
add_dependencies_to_context (Optional[bool]): Whether to add dependencies to context
add_session_state_to_context (Optional[bool]): Whether to add session state to context
metadata (Optional[Dict[str, Any]]): Metadata to use for this run
debug_mode (Optional[bool]): Whether to enable debug mode
show_member_responses (Optional[bool]): Whether to show member responses

`cli_app`

Run an interactive command-line interface to interact with the team.

Parameters:

input (Optional[str]): The input to send to the team
user (str): Name for the user (default: "User")
emoji (str): Emoji for the user (default: ":sunglasses:")
stream (bool): Whether to stream the response (default: False)
markdown (bool): Whether to format output as markdown (default: False)
exit_on (Optional[List[str]]): List of commands to exit the CLI
**kwargs: Additional keyword arguments

`acli_app`

Run an interactive command-line interface to interact with the team asynchronously.

Parameters:

input (Optional[str]): The input to send to the team
session_id (Optional[str]): Session ID to use
user_id (Optional[str]): User ID to use
user (str): Name for the user (default: "User")
emoji (str): Emoji for the user (default: ":sunglasses:")
stream (bool): Whether to stream the response (default: False)
markdown (bool): Whether to format output as markdown (default: False)
exit_on (Optional[List[str]]): List of commands to exit the CLI
**kwargs: Additional keyword arguments

`get_session_summary`

Get the session summary for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)

Returns:

Optional[SessionSummary]: The session summary

`get_user_memories`

Get the user memories for the given user ID.

Parameters:

user_id (Optional[str]): User ID to use (if not provided, the current user is used)

Returns:

Optional[List[UserMemory]]: The user memories

`add_tool`

Add a tool to the team.

Parameters:

tool (Union[Toolkit, Callable, Function, Dict]): The tool to add

`set_tools`

Replace the tools of the team.

Parameters:

tools (Union[List[Union[Toolkit, Callable, Function, Dict]], Callable[..., List]]): The tools to set, or a callable factory that returns the list

`cancel_run`

Cancel a run by run ID.

Parameters:

run_id (str): The run ID to cancel

Returns:

bool: True when a registered run was marked for cancellation by the default manager. Cancellation is cooperative; this is not a terminal-state acknowledgement. The default manager also records intent for an unknown run while returning False

`get_run_output`

Get the run output for the given run ID.

Parameters:

run_id (str): The run ID
session_id (Optional[str]): Session ID to use
user_id (Optional[str]): User ID to use

Returns:

Optional[Union[TeamRunOutput, RunOutput]]: The run output

`get_last_run_output`

Get the last run output for the session.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)

Returns:

Optional[TeamRunOutput]: The last run output

`get_session`

Get the session for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)
user_id (Optional[str]): User ID to use

Returns:

Optional[TeamSession]: The team session

`save_session`

Save a session to the database.

Parameters:

session (TeamSession): The session to save

`asave_session`

Save a session to the database asynchronously.

Parameters:

session (TeamSession): The session to save

`delete_session`

Delete a session.

Parameters:

session_id (str): Session ID to delete
user_id (Optional[str]): User ID to use
delete_media (bool): If True, also delete the session's offloaded media from media_storage. Defaults to False

`get_session_name`

Get the session name for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)

Returns:

str: The session name

`set_session_name`

Set the session name.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)
autogenerate (bool): Whether to autogenerate the name
session_name (Optional[str]): The name to set

Returns:

TeamSession: The updated session

`get_session_state`

Get the session state for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)

Returns:

Dict[str, Any]: The session state

`update_session_state`

Update the session state for the given session ID.

Parameters:

session_state_updates (Dict[str, Any]): The session state keys and values to update. Provided keys are merged into the existing session state, overwriting existing values
session_id (Optional[str]): Session ID to use (if not provided, the current session is used)

Returns:

Dict[str, Any]: The updated session state

`get_session_metrics`

Get the session metrics for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)

Returns:

Optional[SessionMetrics]: The session metrics

`get_chat_history`

Get the chat history for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)
last_n_runs (Optional[int]): The number of runs to return messages from, counting from the latest. Defaults to all runs

Returns:

List[Message]: The chat history

`get_session_messages`

Get the messages for the given session ID.

Parameters:

session_id (Optional[str]): Session ID to use (if not provided, the current session is used)
member_ids (Optional[List[str]]): The ids of the members to get the messages from
last_n_runs (Optional[int]): The number of runs to return messages from, counting from the latest. Defaults to all runs
limit (Optional[int]): The number of messages to return, counting from the latest. Defaults to all messages
skip_roles (Optional[List[str]]): Skip messages with these roles
skip_statuses (Optional[List[RunStatus]]): Skip messages with these statuses
skip_history_messages (bool): Skip messages that were tagged as history in previous runs. Defaults to True
skip_member_messages (bool): Skip messages created by members of the team. Defaults to True

Returns:

List[Message]: The messages for the session

`as_tool`

as_tool(name=None, description=None, title=None, annotations=None) returns a ComponentTool marker with optional MCP metadata overrides. It declares how to publish the component; creating the marker does not execute it. See MCP tools.

`fork_session` and `afork_session`

Fork the conversation into a new session with independent copied runs. Both accept keyword-only source_session_id=None and user_id=None and return the new session ID. Use the async variant with an async database.

`clear_callable_cache` and `aclear_callable_cache`

Clear cached callable results. kind=None clears all supported kinds; choose "tools" or "knowledge", or "members" for a Team to clear one kind. Set close=True to close cached resources as they are removed; the default is False.

Component persistence

Method	Parameters	Result
`to_dict()`	None	Serialized component dictionary
`from_dict()`	`data`, `db=None`, `registry=None`, `links=None`, `strict=False`	Reconstructed `Team`
`save()`	Keyword-only `db=None`, `stage="published"`, `label=None`, `notes=None`	Saved version number, or `None`
`load()`	`id`; keyword-only required `db`, plus `registry=None`, `label=None`, `version=None`, `strict=False`, `published_only=False`	`Team` or `None`
`delete()`	Keyword-only `db=None`, `hard_delete=False`, `require_no_dependents=True`	Boolean deletion result

Strict reconstruction raises for unresolved required component references instead of silently degrading those references. published_only=True uses the published-version pointer when neither an explicit version nor a label is supplied. require_no_dependents=True prevents deleting a component pinned by another component.

Async counterparts are available for session reads and updates, such as aget_session, aget_session_state, aupdate_session_state, and aget_run_output. Use them with asynchronous databases. acancel_run is the asynchronous cancellation request method.

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