def save_to_yaml()

in hugegraph-llm/src/hugegraph_llm/config/models/base_prompt_config.py [0:0]

• 17 lines of code
• 10 McCabe index (conditional complexity)

    def save_to_yaml(self):
        indented_schema = "\n".join([f"  {line}" for line in self.graph_schema.splitlines()])
        indented_text2gql_schema = "\n".join([f"  {line}" for line in self.text2gql_graph_schema.splitlines()])
        indented_gremlin_prompt = "\n".join([f"  {line}" for line in self.gremlin_generate_prompt.splitlines()])
        indented_example_prompt = "\n".join([f"    {line}" for line in self.extract_graph_prompt.splitlines()])
        indented_question = "\n".join([f"    {line}" for line in self.default_question.splitlines()])
        indented_custom_related_information = (
            "\n".join([f"    {line}" for line in self.custom_rerank_info.splitlines()])
        )
        indented_default_answer_template = "\n".join([f"    {line}" for line in self.answer_prompt.splitlines()])
        indented_keywords_extract_template = (
            "\n".join([f"    {line}" for line in self.keywords_extract_prompt.splitlines()])
        )
        indented_doc_input_text = "\n".join([f"  {line}" for line in self.doc_input_text.splitlines()])

        # This can be extended to add storage fields according to the data needs to be stored
        yaml_content = f"""graph_schema: |
{indented_schema}

text2gql_graph_schema: |
{indented_text2gql_schema}

extract_graph_prompt: |
{indented_example_prompt}

default_question: |
{indented_question}

custom_rerank_info: |
{indented_custom_related_information}

answer_prompt: |
{indented_default_answer_template}

keywords_extract_prompt: |
{indented_keywords_extract_template}

gremlin_generate_prompt: |
{indented_gremlin_prompt}

doc_input_text: |
{indented_doc_input_text}

"""
        with open(yaml_file_path, "w", encoding="utf-8") as file:
            file.write(yaml_content)