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Refine prompt of agentic search. (#5312)
### What problem does this PR solve? #5173 ### Type of change - [x] New Feature (non-breaking change which adds functionality)
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Kevin Hu
GitHub
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eb72d598b1
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b3d579e2c1
@ -874,18 +874,43 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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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"
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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"
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"Once you have all the information you need, continue your reasoning.\n\n"
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"-- Example --\n"
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"Question: \"Find the minimum number of vertices in a Steiner tree that includes all specified vertices in a given tree.\"\n"
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"-- Example 1 --\n" ########################################
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"Question: \"Are both the directors of Jaws and Casino Royale from the same country?\"\n"
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"Assistant:\n"
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" - I need to understand what a Steiner tree is.\n\n"
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f" {BEGIN_SEARCH_QUERY}What's Steiner tree{END_SEARCH_QUERY}\n\n"
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f" {BEGIN_SEARCH_RESULT}\n(System returns processed information from relevant web pages)\n{END_SEARCH_RESULT}\n\n"
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"User:\nContinues reasoning with the new information.\n\n"
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f" {BEGIN_SEARCH_QUERY}Who is the director of Jaws?{END_SEARCH_QUERY}\n\n"
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"User:\n"
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f" {BEGIN_SEARCH_RESULT}\nThe director of Jaws is Steven Spielberg...\n{END_SEARCH_RESULT}\n\n"
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"Continues reasoning with the new information.\n"
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"Assistant:\n"
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" - I need to understand what the difference between minimum number of vertices and edges in the Steiner tree is.\n\n"
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f" {BEGIN_SEARCH_QUERY}What's the difference between minimum number of vertices and edges in the Steiner tree{END_SEARCH_QUERY}\n\n"
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f" {BEGIN_SEARCH_RESULT}\n(System returns processed information from relevant web pages)\n{END_SEARCH_RESULT}\n\n"
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"User:\nContinues reasoning with the new information...\n\n"
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f" {BEGIN_SEARCH_QUERY}Where is Steven Spielberg from?{END_SEARCH_QUERY}\n\n"
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"User:\n"
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f" {BEGIN_SEARCH_RESULT}\nSteven Allan Spielberg is an American filmmaker...\n{END_SEARCH_RESULT}\n\n"
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"Continues reasoning with the new information...\n\n"
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"Assistant:\n"
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f" {BEGIN_SEARCH_QUERY}Who is the director of Casino Royale?{END_SEARCH_QUERY}\n\n"
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"User:\n"
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f" {BEGIN_SEARCH_RESULT}\nCasino Royale is a 2006 spy film directed by Martin Campbell...\n{END_SEARCH_RESULT}\n\n"
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"Continues reasoning with the new information...\n\n"
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"Assistant:\n"
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f" {BEGIN_SEARCH_QUERY}Where is Martin Campbell from?{END_SEARCH_QUERY}\n\n"
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"User:\n"
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f" {BEGIN_SEARCH_RESULT}\nMartin Campbell (born 24 October 1943) is a New Zealand film and television director...\n{END_SEARCH_RESULT}\n\n"
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"Continues reasoning with the new information...\n\n"
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"Assistant:\nIt's enough to answer the question\n"
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"-- Example 2 --\n" #########################################
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"Question: \"When was the founder of craigslist born?\"\n"
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"Assistant:\n"
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f" {BEGIN_SEARCH_QUERY}Who was the founder of craigslist?{END_SEARCH_QUERY}\n\n"
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"User:\n"
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f" {BEGIN_SEARCH_RESULT}\nCraigslist was founded by Craig Newmark...\n{END_SEARCH_RESULT}\n\n"
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"Continues reasoning with the new information.\n"
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"Assistant:\n"
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f" {BEGIN_SEARCH_QUERY} When was Craig Newmark born?{END_SEARCH_QUERY}\n\n"
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"User:\n"
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f" {BEGIN_SEARCH_RESULT}\nCraig Newmark was born on December 6, 1952...\n{END_SEARCH_RESULT}\n\n"
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"Continues reasoning with the new information...\n\n"
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"Assistant:\nIt's enough to answer the question\n"
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"**Remember**:\n"
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f"- You have a dataset to search, so you just provide a proper search query.\n"
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f"- Use {BEGIN_SEARCH_QUERY} to request a dataset search and end with {END_SEARCH_QUERY}.\n"
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@ -934,7 +959,7 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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"""
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executed_search_queries = []
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msg_hisotry = [{"role": "user", "content": f'Question:\n{question}\n\n'}]
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msg_hisotry = [{"role": "user", "content": f'Question:\"{question}\"\n'}]
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all_reasoning_steps = []
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think = "<think>"
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for ii in range(MAX_SEARCH_LIMIT + 1):
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@ -948,6 +973,8 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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query_think = ""
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if msg_hisotry[-1]["role"] != "user":
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msg_hisotry.append({"role": "user", "content": "Continues reasoning with the new information.\n"})
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else:
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msg_hisotry[-1]["content"] += "\n\nContinues reasoning with the new information.\n"
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for ans in chat_mdl.chat_streamly(reason_prompt, msg_hisotry, {"temperature": 0.7}):
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ans = re.sub(r"<think>.*</think>", "", ans, flags=re.DOTALL)
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if not ans:
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@ -957,7 +984,6 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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think += rm_query_tags(query_think)
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all_reasoning_steps.append(query_think)
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msg_hisotry.append({"role": "assistant", "content": query_think})
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queries = extract_between(query_think, BEGIN_SEARCH_QUERY, END_SEARCH_QUERY)
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if not queries:
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if ii > 0:
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@ -966,6 +992,7 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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for search_query in queries:
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logging.info(f"[THINK]Query: {ii}. {search_query}")
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msg_hisotry.append({"role": "assistant", "content": search_query})
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think += f"\n\n> {ii+1}. {search_query}\n\n"
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yield {"answer": think + "</think>", "reference": {}, "audio_binary": None}
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@ -975,7 +1002,7 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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summary_think = f"\n{BEGIN_SEARCH_RESULT}\nYou have searched this query. Please refer to previous results.\n{END_SEARCH_RESULT}\n"
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yield {"answer": think + summary_think + "</think>", "reference": {}, "audio_binary": None}
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all_reasoning_steps.append(summary_think)
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msg_hisotry.append({"role": "assistant", "content": summary_think})
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msg_hisotry.append({"role": "user", "content": summary_think})
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think += summary_think
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continue
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@ -1034,7 +1061,7 @@ def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LL
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all_reasoning_steps.append(summary_think)
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msg_hisotry.append(
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{"role": "assistant", "content": f"\n\n{BEGIN_SEARCH_RESULT}{summary_think}{END_SEARCH_RESULT}\n\n"})
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{"role": "user", "content": f"\n\n{BEGIN_SEARCH_RESULT}{summary_think}{END_SEARCH_RESULT}\n\n"})
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think += rm_result_tags(summary_think)
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logging.info(f"[THINK]Summary: {ii}. {summary_think}")
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