param custom_output_type: Optional[Any] = None¶
Override the output type of the underlying runnable with a custom type.
The type can be a pydantic model, or a type annotation (e.g., List[str]).
param kwargs: Mapping[str, Any] [Optional]¶
kwargs to pass to the underlying runnable when running.
For example, when the runnable binding is invoked the underlying
runnable will be invoked with the same input but with these additional
kwargs.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async ainvoke(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Output¶
Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code even if
the runnable did not implement a native async version of invoke.
Subclasses should override this method if they can run asynchronously.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.