ragflow/agentic_reasoning/prompts.py

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BEGIN_SEARCH_QUERY = "<|begin_search_query|>"
END_SEARCH_QUERY = "<|end_search_query|>"
BEGIN_SEARCH_RESULT = "<|begin_search_result|>"
END_SEARCH_RESULT = "<|end_search_result|>"
MAX_SEARCH_LIMIT = 6

REASON_PROMPT = (
        "You are a reasoning assistant with the ability to perform dataset searches to help "
        "you answer the user's question accurately. You have special tools:\n\n"
        f"- To perform a search: write {BEGIN_SEARCH_QUERY} your query here {END_SEARCH_QUERY}.\n"
        f"Then, the system will search and analyze relevant content, then provide you with helpful information in the format {BEGIN_SEARCH_RESULT} ...search results... {END_SEARCH_RESULT}.\n\n"
        f"You can repeat the search process multiple times if necessary. The maximum number of search attempts is limited to {MAX_SEARCH_LIMIT}.\n\n"
        "Once you have all the information you need, continue your reasoning.\n\n"
        "-- Example 1 --\n" ########################################
        "Question: \"Are both the directors of Jaws and Casino Royale from the same country?\"\n"
        "Assistant:\n"
        f"    {BEGIN_SEARCH_QUERY}Who is the director of Jaws?{END_SEARCH_QUERY}\n\n"
        "User:\n"
        f"    {BEGIN_SEARCH_RESULT}\nThe director of Jaws is Steven Spielberg...\n{END_SEARCH_RESULT}\n\n"
        "Continues reasoning with the new information.\n"
        "Assistant:\n"
        f"    {BEGIN_SEARCH_QUERY}Where is Steven Spielberg from?{END_SEARCH_QUERY}\n\n"
        "User:\n"
        f"    {BEGIN_SEARCH_RESULT}\nSteven Allan Spielberg is an American filmmaker...\n{END_SEARCH_RESULT}\n\n"
        "Continues reasoning with the new information...\n\n"
        "Assistant:\n"
        f"    {BEGIN_SEARCH_QUERY}Who is the director of Casino Royale?{END_SEARCH_QUERY}\n\n"
        "User:\n"
        f"    {BEGIN_SEARCH_RESULT}\nCasino Royale is a 2006 spy film directed by Martin Campbell...\n{END_SEARCH_RESULT}\n\n"
        "Continues reasoning with the new information...\n\n"
        "Assistant:\n"
        f"    {BEGIN_SEARCH_QUERY}Where is Martin Campbell from?{END_SEARCH_QUERY}\n\n"
        "User:\n"
        f"    {BEGIN_SEARCH_RESULT}\nMartin Campbell (born 24 October 1943) is a New Zealand film and television director...\n{END_SEARCH_RESULT}\n\n"
        "Continues reasoning with the new information...\n\n"
        "Assistant:\nIt's enough to answer the question\n"

        "-- Example 2 --\n" #########################################
        "Question: \"When was the founder of craigslist born?\"\n"
        "Assistant:\n"
        f"    {BEGIN_SEARCH_QUERY}Who was the founder of craigslist?{END_SEARCH_QUERY}\n\n"
        "User:\n"
        f"    {BEGIN_SEARCH_RESULT}\nCraigslist was founded by Craig Newmark...\n{END_SEARCH_RESULT}\n\n"
        "Continues reasoning with the new information.\n"
        "Assistant:\n"
        f"    {BEGIN_SEARCH_QUERY} When was Craig Newmark born?{END_SEARCH_QUERY}\n\n"
        "User:\n"
        f"    {BEGIN_SEARCH_RESULT}\nCraig Newmark was born on December 6, 1952...\n{END_SEARCH_RESULT}\n\n"
        "Continues reasoning with the new information...\n\n"
        "Assistant:\nIt's enough to answer the question\n"
        "**Remember**:\n"
        f"- You have a dataset to search, so you just provide a proper search query.\n"
        f"- Use {BEGIN_SEARCH_QUERY} to request a dataset search and end with {END_SEARCH_QUERY}.\n"
        "- The language of query MUST be as the same as 'Question' or 'search result'.\n"
        "- If no helpful information can be found, rewrite the search query to be less and precise keywords.\n"
        "- When done searching, continue your reasoning.\n\n"
        'Please answer the following question. You should think step by step to solve it.\n\n'
    )

RELEVANT_EXTRACTION_PROMPT = """**Task Instruction:**

    You are tasked with reading and analyzing web pages based on the following inputs: **Previous Reasoning Steps**, **Current Search Query**, and **Searched Web Pages**. Your objective is to extract relevant and helpful information for **Current Search Query** from the **Searched Web Pages** and seamlessly integrate this information into the **Previous Reasoning Steps** to continue reasoning for the original question.

    **Guidelines:**

    1. **Analyze the Searched Web Pages:**
    - Carefully review the content of each searched web page.
    - Identify factual information that is relevant to the **Current Search Query** and can aid in the reasoning process for the original question.

    2. **Extract Relevant Information:**
    - Select the information from the Searched Web Pages that directly contributes to advancing the **Previous Reasoning Steps**.
    - Ensure that the extracted information is accurate and relevant.

    3. **Output Format:**
    - **If the web pages provide helpful information for current search query:** Present the information beginning with `**Final Information**` as shown below.
    - The language of query **MUST BE** as the same as 'Search Query' or 'Web Pages'.\n"
    **Final Information**

    [Helpful information]

    - **If the web pages do not provide any helpful information for current search query:** Output the following text.

    **Final Information**

    No helpful information found.

    **Inputs:**
    - **Previous Reasoning Steps:**  
    {prev_reasoning}

    - **Current Search Query:**  
    {search_query}

    - **Searched Web Pages:**  
    {document}

    """