> ## Documentation Index > Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Agent > Constructor parameters and methods for the Agent class. ## Parameters | Parameter | Type | Default | Description | | - | - | - | - | | `model` | `Optional[Union[Model, str]]` | `None` | Model to use for this Agent. 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` | Agent name | | `id` | `Optional[str]` | `None` | Agent ID (autogenerated UUID if not set) | | `user_id` | `Optional[str]` | `None` | Default user\_id to use for this agent | | `session_id` | `Optional[str]` | `None` | Default session\_id to use for this agent (autogenerated if not set) | | `session_state` | `Optional[Dict[str, Any]]` | `None` | Default 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 agent 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 Agent session in memory for faster access | | `search_past_sessions` | `Optional[bool]` | `False` | Add tools that let the agent 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 | | `dependencies` | `Optional[Dict[str, Any]]` | `None` | Dependencies available for tools and prompt functions | | `add_dependencies_to_context` | `bool` | `False` | If True, add the dependencies to the user prompt | | `db` | `Optional[Union[BaseDb, AsyncBaseDb]]` | `None` | Database to use for this agent | | `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 reserved for 3.0 | | `memory_manager` | `Optional[MemoryManager]` | `None` | Memory manager to use for this agent | | `enable_agentic_memory` | `bool` | `False` | Enable the agent to manage memories of the user | | `update_memory_on_run` | `bool` | `False` | If True, the agent creates/updates user memories at the end of runs | | `add_memories_to_context` | `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_to_context` | `Optional[bool]` | `None` | If True, the agent adds session summaries to the context | | `session_summary_manager` | `Optional[SessionSummaryManager]` | `None` | Session summary manager | | `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. `True` uses the defaults, a `ResultStore` customizes them, `None` allows team inheritance, and `False` disables inherited offloading. | | `add_history_to_context` | `bool` | `False` | Add the chat history of the current session to the messages sent to the Model | | `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. | | `knowledge` | `Optional[Union[KnowledgeProtocol, Callable[..., KnowledgeProtocol]]]` | `None` | Agent Knowledge | | `knowledge_filters` | `Optional[Union[Dict[str, Any], List[FilterExpr]]]` | `None` | Knowledge filters to apply to the knowledge base | | `enable_agentic_knowledge_filters` | `Optional[bool]` | `None` | Let the agent choose the knowledge filters | | `add_knowledge_to_context` | `bool` | `False` | Enable RAG by adding references from Knowledge to the user prompt | | `knowledge_retriever` | `Optional[Callable[..., Optional[List[Union[Dict, str]]]]]` | `None` | Function to get references to add to the user\_message | | `references_format` | `Literal["json", "yaml"]` | `"json"` | Format of the references | | `skills` | `Optional[Skills]` | `None` | Skills for this agent. Loads structured instructions, reference docs, and scripts, and gives the agent tools to access them | | `metadata` | `Optional[Dict[str, Any]]` | `None` | Metadata stored with this agent | | `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_call_limit` | `Optional[int]` | `None` | Maximum number of tool calls allowed for a single run | | `tool_choice` | `Optional[Union[str, Dict[str, Any]]]` | `None` | Controls which (if any) tool is called by the model | | `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` | Functions that will run between tool calls | | `pre_hooks` | `Optional[List[Union[Callable[..., Any], BaseGuardrail, BaseEval]]]` | `None` | Functions called right after agent-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 | | `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 | | `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 | | `add_search_knowledge_instructions` | `bool` | `True` | If True, add instructions for using the `search_knowledge` tool to the system message | | `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 | | `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 | | `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 Agent | | `build_context` | `bool` | `True` | Set to False to skip context building | | `description` | `Optional[str]` | `None` | A description of the Agent that is added to the start of the system message | | `instructions` | `Optional[Union[str, List[str], Callable]]` | `None` | List of instructions for the agent | | `use_instruction_tags` | `bool` | `False` | If True, wrap the instructions in `` tags in the system message | | `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_context` | `bool` | `False` | If True, add the agent name to the instructions | | `add_datetime_to_context` | `bool` | `False` | If True, add the current datetime to the instructions to give the agent a sense of time | | `add_location_to_context` | `bool` | `False` | If True, add the current location to the instructions to give the agent a sense of place | | `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 (e.g. "Etc/UTC") | | `resolve_in_context` | `bool` | `True` | If True, resolve session\_state, dependencies, and metadata in the user and system messages | | `learning` | `Optional[Union[bool, LearningMachine]]` | `None` | Enable learning for this agent. `True` creates a default LearningMachine with user profile and user memory stores; pass a `LearningMachine` for full control. Requires `db` | | `add_learnings_to_context` | `bool` | `True` | If True, add learnings to the system message when learning is enabled | | `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 | | `user_message_role` | `str` | `"user"` | Role for the user message | | `build_user_context` | `bool` | `True` | Set to False to skip building the user context | | `retries` | `int` | `0` | Number of retries to attempt when running the Agent | | `delay_between_retries` | `int` | `1` | Delay between retries (in seconds) | | `exponential_backoff` | `bool` | `False` | If True, the delay between retries is doubled each time | | `input_schema` | `Optional[Type[BaseModel]]` | `None` | Provide an input schema to validate the input | | `output_schema` | `Optional[Union[Type[BaseModel], Dict[str, Any]]]` | `None` | Provide a response model to get the response as 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 structure the response from the main model. 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 | | `parse_response` | `bool` | `True` | If True, the response from the Model is converted into the output\_schema | | `structured_outputs` | `Optional[bool]` | `None` | Use model enforced structured\_outputs if supported (e.g. OpenAIChat) | | `use_json_mode` | `bool` | `False` | If `output_schema` 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 | | `followups` | `bool` | `False` | If True, generate followup prompt suggestions after the main response and set them on `RunOutput.followups` | | `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 agent's model | | `stream` | `Optional[bool]` | `None` | Stream the response from the Agent | | `stream_events` | `Optional[bool]` | `None` | Stream the intermediate steps from the Agent | | `store_events` | `bool` | `False` | Persist the events on the run response | | `events_to_skip` | `Optional[List[RunEvent]]` | `None` | Specify which event types to skip when storing events on the RunOutput | | `role` | `Optional[str]` | `None` | If this Agent is part of a team, this is the role of the agent in the team | | `debug_mode` | `bool` | `False` | Enable debug logs | | `debug_level` | `Literal[1, 2]` | `1` | Debug level for logging | | `telemetry` | `bool` | `True` | Log minimal telemetry for analytics | | `cache_callables` | `bool` | `True` | Cache the results of callable `tools` and `knowledge` factories between runs | | `callable_tools_cache_key` | `Optional[Callable[..., Optional[str]]]` | `None` | Function that returns the cache key for the callable `tools` factory. Defaults to user\_id or session\_id from the run context | | `callable_knowledge_cache_key` | `Optional[Callable[..., Optional[str]]]` | `None` | Function that returns the cache key for the callable `knowledge` factory. Defaults to user\_id or session\_id from the run context | ## Functions ### `run` Run the agent. **Parameters:** * `input` (Union\[str, List, Dict, Message, BaseModel, List\[Message]]): The input to send to the agent * `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 * `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 * `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 ### `arun` Run the agent asynchronously. **Parameters:** * `input` (Union\[str, List, Dict, Message, BaseModel, List\[Message]]): The input to send to the agent * `stream` (Optional\[bool]): Whether to stream the response * `user_id` (Optional\[str]): User ID to use * `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 * `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 * `stream_events` (Optional\[bool]): Whether to stream intermediate steps * `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` (Optional\[bool]): Whether to yield the run output (only for streaming) * `background` (bool): Whether to run the agent in background mode. Requires `stream=False` and a configured database. **Returns:** * `Union[RunOutput, AsyncIterator[RunOutputEvent]]`: Either a RunOutput or an iterator of RunOutputEvents, depending on the `stream` parameter ### `continue_run` Continue a run. **Parameters:** * `run_response` (Optional\[RunOutput]): The run response to continue * `run_id` (Optional\[str]): The run ID to continue * `requirements` (Optional\[List\[RunRequirement]]): 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[RunOutput, Iterator[RunOutputEvent]]`: Either a RunOutput or an iterator of RunOutputEvents, depending on the `stream` parameter ### `acontinue_run` Continue a run asynchronously. **Parameters:** * `run_response` (Optional\[RunOutput]): The run response to continue * `run_id` (Optional\[str]): The run ID to continue * `requirements` (Optional\[List\[RunRequirement]]): 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): Whether to continue the run in background mode **Returns:** * `Union[RunOutput, AsyncIterator[Union[RunOutputEvent, RunOutput]]]`: Either a RunOutput or an iterator of RunOutputEvents, depending on the `stream` parameter ### `print_response` Run the agent and print the response. **Parameters:** * `input` (Union\[List, Dict, str, Message, BaseModel, List\[Message]]): The input to send to the agent * `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 * `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 * `stream` (Optional\[bool]): Whether to stream the response * `markdown` (Optional\[bool]): Whether to format output as markdown * `show_message` (bool): Whether to show the input message * `show_reasoning` (bool): Whether to show reasoning steps * `show_full_reasoning` (bool): Whether to show full reasoning information * `console` (Optional\[Any]): Console to use for output * `tags_to_include_in_markdown` (Optional\[Set\[str]]): Tags to include in markdown content * `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 ### `aprint_response` Run the agent and print the response asynchronously. **Parameters:** * `input` (Union\[List, Dict, str, Message, BaseModel, List\[Message]]): The input to send to the agent * `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 * `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 * `stream` (Optional\[bool]): Whether to stream the response * `markdown` (Optional\[bool]): Whether to format output as markdown * `show_message` (bool): Whether to show the message * `show_reasoning` (bool): Whether to show reasoning * `show_full_reasoning` (bool): Whether to show full reasoning * `console` (Optional\[Any]): Console to use for output * `tags_to_include_in_markdown` (Optional\[Set\[str]]): Tags to include in markdown content * `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 * `debug_mode` (Optional\[bool]): Whether to enable debug mode ### `cli_app` Run an interactive command-line interface to interact with the agent. **Parameters:** * `input` (Optional\[str]): The input to send to the agent * `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 ### `acli_app` Run an interactive command-line interface to interact with the agent asynchronously. **Parameters:** * `input` (Optional\[str]): The input to send to the agent * `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 ### cancel\_run Cancel a run by run ID. **Parameters:** * `run_id` (str): The run ID to cancel **Returns:** * `bool`: True if the run was successfully cancelled ### 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[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 **Returns:** * `Optional[RunOutput]`: The last run output ### get\_session Get the session for the given session ID. **Parameters:** * `session_id` (Optional\[str]): Session ID to use * `user_id` (Optional\[str]): User ID to use **Returns:** * `Optional[AgentSession]`: The agent session ### get\_session\_summary Get the session summary for the given session ID. **Parameters:** * `session_id` (Optional\[str]): Session ID to use **Returns:** * Session summary for the given session ### get\_user\_memories Get the user memories for the given user ID. **Parameters:** * `user_id` (Optional\[str]): User ID to use **Returns:** * `Optional[List[UserMemory]]`: The user memories ### aget\_user\_memories Get the user memories for the given user ID asynchronously. **Parameters:** * `user_id` (Optional\[str]): User ID to use **Returns:** * `Optional[List[UserMemory]]`: The user memories ### get\_session\_state Get the session state for the given session ID. **Parameters:** * `session_id` (Optional\[str]): Session ID to use **Returns:** * `Dict[str, Any]`: The session state ### update\_session\_state Update the session state for the given session ID. **Parameters:** * `session_id` (Optional\[str]): Session ID to use * `session_state_updates` (Dict\[str, Any]): The session state keys and values to update. Existing keys are overwritten; other keys are kept. **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 **Returns:** * `Optional[SessionMetrics]`: The session metrics ### 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 ### save\_session Save a session to the database. **Parameters:** * `session` (AgentSession): The session to save ### asave\_session Save a session to the database asynchronously. **Parameters:** * `session` (AgentSession): The session to save ### rename Rename the agent and update the session. **Parameters:** * `name` (str): The new name for the agent * `session_id` (Optional\[str]): Session ID to use ### get\_session\_name Get the session name for the given session ID. **Parameters:** * `session_id` (Optional\[str]): Session ID to use **Returns:** * `str`: The session name ### set\_session\_name Set the session name. **Parameters:** * `session_id` (Optional\[str]): Session ID to use * `autogenerate` (bool): Whether to autogenerate the name * `session_name` (Optional\[str]): The name to set **Returns:** * `AgentSession`: The updated session ### get\_session\_messages Get the messages for the given session ID. **Parameters:** * `session_id` (Optional\[str]): The session ID to get the messages for. If not provided, the latest used session ID is used. * `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. **Returns:** * `List[Message]`: The messages for the session ### get\_chat\_history Get the chat history for the given session ID. **Parameters:** * `session_id` (Optional\[str]): The session ID to get the chat history for. If not provided, the latest used session ID 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 ### add\_tool Add a tool to the agent. **Parameters:** * `tool` (Union\[Toolkit, Callable, Function, Dict]): The tool to add ### set\_tools Replace the tools of the agent. **Parameters:** * `tools` (Union\[List\[Union\[Toolkit, Callable, Function, Dict]], Callable\[..., List]]): The tools to set, or a callable factory that returns the list This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.