Function generate_ticket

chains.py:183–238

(neo4j_graph, llm_chain, input_question)

def generate_ticket(neo4j_graph, llm_chain, input_question):
    # Get high ranked questions
    records = neo4j_graph.query(
        "MATCH (q:Question) RETURN q.title AS title, q.body AS body ORDER BY q.score DESC LIMIT 3"
    )
    questions = []
    for i, question in enumerate(records, start=1):
        questions.append((question["title"], question["body"]))
    # Ask LLM to generate new question in the same style
    questions_prompt = ""
    for i, question in enumerate(questions, start=1):
        questions_prompt += f"{i}. \n{question[0]}\n----\n\n"
        questions_prompt += f"{question[1][:150]}\n\n"
        questions_prompt += "----\n\n"

    gen_system_template = f"""
    You're an expert in formulating high quality questions. 
    Formulate a question in the same style and tone as the following example questions.
    {questions_prompt}
    ---

    Don't make anything up, only use information in the following question.
    Return a title for the question, and the question post itself.

    Return format template:
    ---
    Title: This is a new title
    Question: This is a new question
    ---
    """
    # we need jinja2 since the questions themselves contain curly braces
    system_prompt = SystemMessagePromptTemplate.from_template(
        gen_system_template, template_format="jinja2"
    )
    chat_prompt = ChatPromptTemplate.from_messages(
        [
            system_prompt,
            SystemMessagePromptTemplate.from_template(
                """
                Respond in the following template format or you will be unplugged.
                ---
                Title: New title
                Question: New question
                ---
                """
            ),
            HumanMessagePromptTemplate.from_template("{question}"),
        ]
    )
    llm_response = llm_chain(
        f"Here's the question to rewrite in the expected format: ```{input_question}```",
        [],
        chat_prompt,
    )
    new_title, new_question = extract_title_and_question(llm_response["answer"])
    return (new_title, new_question)