langchain/experimental/plan_and_execute/planners/base.py/LLMPlanner/aplan
class LLMPlanner:    async def aplan(
        self, inputs: dict, callbacks: Callbacks = None, **kwargs: Any
    ) -> Plan:
        """Given input, decided what to do."""
        llm_response = await self.llm_chain.arun(
            **inputs, stop=self.stop, callbacks=callbacks
        )
        return self.output_parser.parse(llm_response)