refine_llm_chain = load_chain_from_config(refine_llm_chain_config)
    elif "refine_llm_chain_path" in config:
        refine_llm_chain = load_chain(config.pop("refine_llm_chain_path"))
    else:
        raise ValueError(
            "One of `refine_llm_chain` or `refine_llm_chain_config` must be present."
        )
    if "document_prompt" in config:
        prompt_config = config.pop("document_prompt")
        document_prompt = load_prompt_from_config(prompt_config)
    elif "document_prompt_path" in config:
        document_prompt = load_prompt(config.pop("document_prompt_path"))
    return RefineDocumentsChain(
        initial_llm_chain=initial_llm_chain,
        refine_llm_chain=refine_llm_chain,
        document_prompt=document_prompt,
        **config,
    )
def _load_qa_with_sources_chain(config: dict, **kwargs: Any) -> QAWithSourcesChain:
    if "combine_documents_chain" in config:
        combine_documents_chain_config = config.pop("combine_documents_chain")
        combine_documents_chain = load_chain_from_config(combine_documents_chain_config)
    elif "combine_documents_chain_path" in config:
        combine_documents_chain = load_chain(config.pop("combine_documents_chain_path"))
    else:
        raise ValueError(
            "One of `combine_documents_chain` or "
            "`combine_documents_chain_path` must be present."
        )
    return QAWithSourcesChain(combine_documents_chain=combine_documents_chain, **config)
def _load_sql_database_chain(config: dict, **kwargs: Any) -> Any:
    from langchain_experimental.sql import SQLDatabaseChain
    if "database" in kwargs:
        database = kwargs.pop("database")
    else: