that after the tool is called, the AgentExecutor will stop looping.
    """
    verbose: bool = False
    """Whether to log the tool's progress."""
    callbacks: Callbacks = Field(default=None, exclude=True)
    """Callbacks to be called during tool execution."""
    callback_manager: Optional[BaseCallbackManager] = Field(default=None, exclude=True)
    """Deprecated. Please use callbacks instead."""
    tags: Optional[List[str]] = None
    """Optional list of tags associated with the tool. Defaults to None
    These tags will be associated with each call to this tool,
    and passed as arguments to the handlers defined in `callbacks`.
    You can use these to eg identify a specific instance of a tool with its use case.
    """
    metadata: Optional[Dict[str, Any]] = None
    """Optional metadata associated with the tool. Defaults to None
    This metadata will be associated with each call to this tool,
    and passed as arguments to the handlers defined in `callbacks`.
    You can use these to eg identify a specific instance of a tool with its use case.
    """
    handle_tool_error: Optional[
        Union[bool, str, Callable[[ToolException], str]]
    ] = False
    """Handle the content of the ToolException thrown."""
    class Config:
        """Configuration for this pydantic object."""
        extra = Extra.forbid
        arbitrary_types_allowed = True
    @property
    def is_single_input(self) -> bool:
        """Whether the tool only accepts a single input."""
        keys = {k for k in self.args if k != "kwargs"}
        return len(keys) == 1
    @property
    def args(self) -> dict:
        if self.args_schema is not None: