# we just return the full output
                return AgentFinish({"output": full_output}, full_output)
        else:
            raise ValueError(
                "early_stopping_method should be one of `force` or `generate`, "
                f"got {early_stopping_method}"
            )
[docs]    def tool_run_logging_kwargs(self) -> Dict:
        return {
            "llm_prefix": self.llm_prefix,
            "observation_prefix": self.observation_prefix,
        }
[docs]class ExceptionTool(BaseTool):
    """Tool that just returns the query."""
    name = "_Exception"
    """Name of the tool."""
    description = "Exception tool"
    """Description of the tool."""
    def _run(
        self,
        query: str,
        run_manager: Optional[CallbackManagerForToolRun] = None,
    ) -> str:
        return query
    async def _arun(
        self,
        query: str,
        run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
    ) -> str:
        return query
[docs]class AgentExecutor(Chain):
    """Agent that is using tools."""
    agent: Union[BaseSingleActionAgent, BaseMultiActionAgent]
    """The agent to run for creating a plan and determining actions
    to take at each step of the execution loop."""
    tools: Sequence[BaseTool]
    """The valid tools the agent can call."""
    return_intermediate_steps: bool = False
    """Whether to return the agent's trajectory of intermediate steps
    at the end in addition to the final output."""
    max_iterations: Optional[int] = 15
    """The maximum number of steps to take before ending the execution
    loop.