**kwargs: Any,
) -> MapReduceDocumentsChain:
    map_chain = LLMChain(llm=llm, prompt=question_prompt, verbose=verbose)
    _reduce_llm = reduce_llm or llm
    reduce_chain = LLMChain(llm=_reduce_llm, prompt=combine_prompt, verbose=verbose)
    combine_documents_chain = StuffDocumentsChain(
        llm_chain=reduce_chain,
        document_variable_name=combine_document_variable_name,
        document_prompt=document_prompt,
        verbose=verbose,
    )
    if collapse_prompt is None:
        collapse_chain = None
        if collapse_llm is not None:
            raise ValueError(
                "collapse_llm provided, but collapse_prompt was not: please "
                "provide one or stop providing collapse_llm."
            )
    else:
        _collapse_llm = collapse_llm or llm
        collapse_chain = StuffDocumentsChain(
            llm_chain=LLMChain(
                llm=_collapse_llm,
                prompt=collapse_prompt,
                verbose=verbose,
            ),
            document_variable_name=combine_document_variable_name,
            document_prompt=document_prompt,
        )
    reduce_documents_chain = ReduceDocumentsChain(
        combine_documents_chain=combine_documents_chain,
        collapse_documents_chain=collapse_chain,
        token_max=token_max,
        verbose=verbose,
    )
    return MapReduceDocumentsChain(
        llm_chain=map_chain,
        reduce_documents_chain=reduce_documents_chain,
        document_variable_name=map_reduce_document_variable_name,
        verbose=verbose,
        **kwargs,
    )
def _load_refine_chain(
    llm: BaseLanguageModel,
    question_prompt: BasePromptTemplate = refine_prompts.DEFAULT_TEXT_QA_PROMPT,