### What problem does this PR solve? This commit refactors the core prompts to decouple the high-level reasoning from the low-level information extraction. By making REASON_PROMPT a dedicated strategist that only generates search queries and re-tasking RELEVANT_EXTRACTION_PROMPT to be a specialized tool for single-fact extraction, we eliminate redundant information summarization. This clear separation of concerns makes the overall reasoning process significantly faster and more precise, as each component now has a single, well-defined responsibility. ### Type of change - [x] Performance Improvement

2 months ago · 7724acbadb
--- a/agentic_reasoning/prompts.py
+++ b/agentic_reasoning/prompts.py
@@ -20,94 +20,128 @@ 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}

    """
 REASON_PROMPT = f"""You are an advanced reasoning agent. Your goal is to answer the user's question by breaking it down into a series of verifiable steps.

 You have access to a powerful search tool to find information.

 **Your Task:**
 1.  Analyze the user's question.
 2.  If you need information, issue a search query to find a specific fact.
 3.  Review the search results.
 4.  Repeat the search process until you have all the facts needed to answer the question.
 5.  Once you have gathered sufficient information, synthesize the facts and provide the final answer directly.

 **Tool Usage:**
 - To search, you MUST write your query between the special tokens: {BEGIN_SEARCH_QUERY}your query{END_SEARCH_QUERY}.
 - The system will provide results between {BEGIN_SEARCH_RESULT}search results{END_SEARCH_RESULT}.
 - You have a maximum of {MAX_SEARCH_LIMIT} search attempts.

 ---
 **Example 1: Multi-hop Question**

 **Question:** "Are both the directors of Jaws and Casino Royale from the same country?"

 **Your Thought Process & Actions:**
 First, I need to identify the director of Jaws.
 {BEGIN_SEARCH_QUERY}who is the director of Jaws?{END_SEARCH_QUERY}
 [System returns search results]
 {BEGIN_SEARCH_RESULT}
 Jaws is a 1975 American thriller film directed by Steven Spielberg.
 {END_SEARCH_RESULT}
 Okay, the director of Jaws is Steven Spielberg. Now I need to find out his nationality.
 {BEGIN_SEARCH_QUERY}where is Steven Spielberg from?{END_SEARCH_QUERY}
 [System returns search results]
 {BEGIN_SEARCH_RESULT}
 Steven Allan Spielberg is an American filmmaker. Born in Cincinnati, Ohio...
 {END_SEARCH_RESULT}
 So, Steven Spielberg is from the USA. Next, I need to find the director of Casino Royale.
 {BEGIN_SEARCH_QUERY}who is the director of Casino Royale 2006?{END_SEARCH_QUERY}
 [System returns search results]
 {BEGIN_SEARCH_RESULT}
 Casino Royale is a 2006 spy film directed by Martin Campbell.
 {END_SEARCH_RESULT}
 The director of Casino Royale is Martin Campbell. Now I need his nationality.
 {BEGIN_SEARCH_QUERY}where is Martin Campbell from?{END_SEARCH_QUERY}
 [System returns search results]
 {BEGIN_SEARCH_RESULT}
 Martin Campbell (born 24 October 1943) is a New Zealand film and television director.
 {END_SEARCH_RESULT}
 I have all the information. Steven Spielberg is from the USA, and Martin Campbell is from New Zealand. They are not from the same country.

 Final Answer: No, the directors of Jaws and Casino Royale are not from the same country. Steven Spielberg is from the USA, and Martin Campbell is from New Zealand.

 ---
 **Example 2: Simple Fact Retrieval**

 **Question:** "When was the founder of craigslist born?"

 **Your Thought Process & Actions:**
 First, I need to know who founded craigslist.
 {BEGIN_SEARCH_QUERY}who founded craigslist?{END_SEARCH_QUERY}
 [System returns search results]
 {BEGIN_SEARCH_RESULT}
 Craigslist was founded in 1995 by Craig Newmark.
 {END_SEARCH_RESULT}
 The founder is Craig Newmark. Now I need his birth date.
 {BEGIN_SEARCH_QUERY}when was Craig Newmark born?{END_SEARCH_QUERY}
 [System returns search results]
 {BEGIN_SEARCH_RESULT}
 Craig Newmark was born on December 6, 1952.
 {END_SEARCH_RESULT}
 I have found the answer.

 Final Answer: The founder of craigslist, Craig Newmark, was born on December 6, 1952.

 ---
 **Important Rules:**
 - **One Fact at a Time:** Decompose the problem and issue one search query at a time to find a single, specific piece of information.
 - **Be Precise:** Formulate clear and precise search queries. If a search fails, rephrase it.
 - **Synthesize at the End:** Do not provide the final answer until you have completed all necessary searches.
 - **Language Consistency:** Your search queries should be in the same language as the user's question.

 Now, begin your work. Please answer the following question by thinking step-by-step.
 """

 RELEVANT_EXTRACTION_PROMPT = """You are a highly efficient information extraction module. Your sole purpose is to extract the single most relevant piece of information from the provided `Searched Web Pages` that directly answers the `Current Search Query`.

 **Your Task:**
 1.  Read the `Current Search Query` to understand what specific information is needed.
 2.  Scan the `Searched Web Pages` to find the answer to that query.
 3.  Extract only the essential, factual information that answers the query. Be concise.

 **Context (For Your Information Only):**
 The `Previous Reasoning Steps` are provided to give you context on the overall goal, but your primary focus MUST be on answering the `Current Search Query`. Do not use information from the previous steps in your output.

 **Output Format:**
 Your response must follow one of two formats precisely.

 1.  **If a direct and relevant answer is found:**
    - Start your response immediately with `Final Information`.
    - Provide only the extracted fact(s). Do not add any extra conversational text.

    *Example:*
    `Current Search Query`: Where is Martin Campbell from?
    `Searched Web Pages`: [Long article snippet about Martin Campbell's career, which includes the sentence "Martin Campbell (born 24 October 1943) is a New Zealand film and television director..."]
    
    *Your Output:*
    Final Information
    Martin Campbell is a New Zealand film and television director.

 2.  **If no relevant answer that directly addresses the query is found in the web pages:**
    - Start your response immediately with `Final Information`.
    - Write the exact phrase: `No helpful information found.`

 ---
 **BEGIN TASK**

 **Inputs:**

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

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

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