Method ainvoke

libs/core/langchain_core/runnables/base.py:2514–2550

(
        self,
        input: Input,
        config: Optional[RunnableConfig] = None,
        **kwargs: Optional[Any],
    )

            return cast(Output, input)

    async def ainvoke(
        self,
        input: Input,
        config: Optional[RunnableConfig] = None,
        **kwargs: Optional[Any],
    ) -> Output:
        from langchain_core.beta.runnables.context import aconfig_with_context

        # setup callbacks and context
        config = aconfig_with_context(ensure_config(config), self.steps)
        callback_manager = get_async_callback_manager_for_config(config)
        # start the root run
        run_manager = await callback_manager.on_chain_start(
            dumpd(self),
            input,
            name=config.get("run_name") or self.get_name(),
            run_id=config.pop("run_id", None),
        )

        # invoke all steps in sequence
        try:
            for i, step in enumerate(self.steps):
                # mark each step as a child run
                config = patch_config(
                    config, callbacks=run_manager.get_child(f"seq:step:{i+1}")
                )
                if i == 0:
                    input = await step.ainvoke(input, config, **kwargs)
                else:
                    input = await step.ainvoke(input, config)
        # finish the root run
        except BaseException as e:
            await run_manager.on_chain_error(e)
            raise
        else:
            await run_manager.on_chain_end(input)
            return cast(Output, input)

    def batch(
        self,