def METHOD_NAME(self, prompt: BasePromptTemplate, **prompt_args: Any) -> str:
    """Mock predict."""
    prompt_str = prompt.metadata["prompt_type"]
    if prompt_str == PromptType.SUMMARY:
        output = _mock_summary_predict(self.max_tokens, prompt_args)
    elif prompt_str == PromptType.TREE_INSERT:
        output = _mock_insert_predict()
    elif prompt_str == PromptType.TREE_SELECT:
        output = _mock_query_select()
    elif prompt_str == PromptType.TREE_SELECT_MULTIPLE:
        output = _mock_query_select_multiple(prompt_args["num_chunks"])
    elif prompt_str == PromptType.REFINE:
        output = _mock_refine(self.max_tokens, prompt, prompt_args)
    elif prompt_str == PromptType.QUESTION_ANSWER:
        output = _mock_answer(self.max_tokens, prompt_args)
    elif prompt_str == PromptType.KEYWORD_EXTRACT:
        output = _mock_keyword_extract(prompt_args)
    elif prompt_str == PromptType.QUERY_KEYWORD_EXTRACT:
        output = _mock_query_keyword_extract(prompt_args)
    elif prompt_str == PromptType.KNOWLEDGE_TRIPLET_EXTRACT:
        output = _mock_knowledge_graph_triplet_extract(
            prompt_args,
            int(prompt.kwargs.get("max_knowledge_triplets", 2)),
        )
    elif prompt_str == PromptType.CUSTOM:
        # we don't know specific prompt type, return generic response
        output = ""
    else:
        raise ValueError("Invalid prompt type.")
    return output