langchain.agents.agent.RunnableMultiActionAgent¶

class langchain.agents.agent.RunnableMultiActionAgent[source]¶

Bases: BaseMultiActionAgent

Agent powered by runnables.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param input_keys_arg: List[str] = []¶
param return_keys_arg: List[str] = []¶
param runnable: Runnable[dict, Union[List[AgentAction], AgentFinish]] [Required]¶

Runnable to call to get agent actions.

param stream_runnable: bool = True¶

Whether to stream from the runnable or not.

If True then underlying LLM is invoked in a streaming fashion to make it possible

to get access to the individual LLM tokens when using stream_log with the Agent Executor. If False then LLM is invoked in a non-streaming fashion and individual LLM tokens will not be available in stream_log.

async aplan(intermediate_steps: List[Tuple[AgentAction, str]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) Union[List[AgentAction], AgentFinish][source]¶

Based on past history and current inputs, decide what to do.

Parameters
  • intermediate_steps (List[Tuple[AgentAction, str]]) – Steps the LLM has taken to date, along with observations

  • callbacks (Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]) – Callbacks to run.

  • **kwargs (Any) – User inputs.

Returns

Action specifying what tool to use.

Return type

Union[List[AgentAction], AgentFinish]

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model¶

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Parameters
  • _fields_set (Optional[SetStr]) –

  • values (Any) –

Return type

Model

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model¶

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters
  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include

  • update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep (bool) – set to True to make a deep copy of the model

  • self (Model) –

Returns

new model instance

Return type

Model

dict(**kwargs: Any) Dict¶

Return dictionary representation of agent.

Parameters

kwargs (Any) –

Return type

Dict

classmethod from_orm(obj: Any) Model¶
Parameters

obj (Any) –

Return type

Model

get_allowed_tools() Optional[List[str]]¶
Return type

Optional[List[str]]

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode¶

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

Parameters
  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

  • encoder (Optional[Callable[[Any], Any]]) –

  • models_as_dict (bool) –

  • dumps_kwargs (Any) –

Return type

unicode

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model¶
Parameters
  • path (Union[str, Path]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

classmethod parse_obj(obj: Any) Model¶
Parameters

obj (Any) –

Return type

Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model¶
Parameters
  • b (Union[str, bytes]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

plan(intermediate_steps: List[Tuple[AgentAction, str]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) Union[List[AgentAction], AgentFinish][source]¶

Based on past history and current inputs, decide what to do.

Parameters
  • intermediate_steps (List[Tuple[AgentAction, str]]) – Steps the LLM has taken to date, along with the observations.

  • callbacks (Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]) – Callbacks to run.

  • **kwargs (Any) – User inputs.

Returns

Action specifying what tool to use.

Return type

Union[List[AgentAction], AgentFinish]

return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) AgentFinish¶

Return response when agent has been stopped due to max iterations.

Parameters
  • early_stopping_method (str) –

  • intermediate_steps (List[Tuple[AgentAction, str]]) –

  • kwargs (Any) –

Return type

AgentFinish

save(file_path: Union[Path, str]) None¶

Save the agent.

Parameters

file_path (Union[Path, str]) – Path to file to save the agent to.

Return type

None

Example: .. code-block:: python

# If working with agent executor agent.agent.save(file_path=”path/agent.yaml”)

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny¶
Parameters
  • by_alias (bool) –

  • ref_template (unicode) –

Return type

DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode¶
Parameters
  • by_alias (bool) –

  • ref_template (unicode) –

  • dumps_kwargs (Any) –

Return type

unicode

tool_run_logging_kwargs() Dict¶
Return type

Dict

classmethod update_forward_refs(**localns: Any) None¶

Try to update ForwardRefs on fields based on this Model, globalns and localns.

Parameters

localns (Any) –

Return type

None

classmethod validate(value: Any) Model¶
Parameters

value (Any) –

Return type

Model

property input_keys: List[str]¶

Return the input keys.

Returns

List of input keys.

property return_values: List[str]¶

Return values of the agent.