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Yuhong

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Yuhong Sun
2025-02-02 16:14:18 -08:00
committed by Evan Lohn
parent a067b32467
commit 506a9f1b94
6 changed files with 149 additions and 125 deletions
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175
backend/onyx/prompts/agent_search.py
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@ -2,7 +2,6 @@
SEPARATOR_LINE = "-------"
UNKNOWN_ANSWER = "I do not have enough information to answer this question."
NO_RECOVERED_DOCS = "No relevant information recovered"
DATE_PROMPT = "Today is {date}.\n\n"
SUB_CHECK_YES = "yes"
SUB_CHECK_NO = "no"
@ -16,9 +15,7 @@ For more context, here is the history of the conversation so far that preceded t
""".strip()
ASSISTANT_SYSTEM_PROMPT_DEFAULT = (
"""You are an assistant for question-answering tasks."""
)
ASSISTANT_SYSTEM_PROMPT_DEFAULT = "You are an assistant for question-answering tasks."
ASSISTANT_SYSTEM_PROMPT_PERSONA = f"""
You are an assistant for question-answering tasks. Here is more information about you:
@ -28,21 +25,25 @@ You are an assistant for question-answering tasks. Here is more information abou
""".strip()
SUB_QUESTION_ANSWER_TEMPLATE = """\n
Sub-Question: Q{sub_question_num}\n Sub-Question:\n - \n{sub_question}\n --\nAnswer:\n -\n {sub_answer}\n\n
"""
SUB_QUESTION_ANSWER_TEMPLATE = f"""
Sub-Question: Q{{sub_question_num}}
Question:
{{sub_question}}
{SEPARATOR_LINE}
Answer:
{{sub_answer}}
""".strip()
SUB_QUESTION_ANSWER_TEMPLATE_REFINED = f"""
Sub-Question: Q{{sub_question_num}}\n
Type:
{SEPARATOR_LINE}
{{sub_question_type}}
{SEPARATOR_LINE}
Sub-Question: Q{{sub_question_num}}
Type: {{sub_question_type}}
Sub-Question:
{SEPARATOR_LINE}
{{sub_question}}
{SEPARATOR_LINE}
Answer:
{SEPARATOR_LINE}
{{sub_answer}}
@ -73,30 +74,33 @@ And here is the context retrieved:
{SEPARATOR_LINE}
Please format your answer as a json object in the following format:
{{
"retrieved_entities_relationships": {{
""".strip()
ENTITY_TERM_EXTRACTION_PROMPT_JSON_EXAMPLE = """
{
"retrieved_entities_relationships": {
"entities": [
{{
{
"entity_name": "<assign a name for the entity>",
"entity_type": "<specify a short type name for the entity, such as 'company', 'location',...>"
}}
}
],
"relationships": [
{{
{
"relationship_name": "<assign a name for the relationship>",
"relationship_type": "<specify a short type name for the relationship, such as 'sales_to', 'is_location_of',...>",
"relationship_entities": ["<related entity name 1>", "<related entity name 2>", "..."]
}}
}
],
"terms": [
{{
{
"term_name": "<assign a name for the term>",
"term_type": "<specify a short type name for the term, such as 'revenue', 'market_share',...>",
"term_similar_to": ["<list terms that are similar to this term>"]
}}
}
]
}}
}}
}
}
""".strip()
@ -259,79 +263,63 @@ SUB_QUESTION_RAG_PROMPT = (
SUB_ANSWER_CHECK_PROMPT = (
"""\n
Your task is to see whether a given answer addresses a given question.
Please do not use any internal knowledge you may have - just focus on whether the answer
as given seems to largely address the question as given, or at least addresses part of the question.
Here is the question:
\n-------\n
{question}
\n-------\n
Here is the suggested answer:
\n-------\n
{base_answer}
\n-------\n
Does the suggested answer address the question? Please answer with """
+ f'"{SUB_CHECK_YES}" or "{SUB_CHECK_NO}".'
)
"Determine whether the given answer addresses the given question. "
"Please do not use any internal knowledge you may have - just focus on whether the answer "
"as given seems to largely address the question as given, or at least addresses part of the question.\n\n"
"Here is the question:\n"
f"{SEPARATOR_LINE}\n"
"{question}\n"
f"{SEPARATOR_LINE}\n\n"
"Here is the suggested answer:\n"
f"{SEPARATOR_LINE}\n"
"{base_answer}\n"
f"{SEPARATOR_LINE}\n\n"
f'Does the suggested answer address the question? Please answer with "{SUB_CHECK_YES}" or "{SUB_CHECK_NO}".'
).strip()
# Initial Answer Generation
INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS = (
""" \n
{persona_specification}
{date_prompt}
Use the information provided below - and only the provided information - to answer the provided main question.
The information provided below consists of:
1) a number of answered sub-questions - these are very important to help you organize your thoughts and your answer
2) a number of documents that deemed relevant for the question.
{history}
It is critical that you provide prover inline citations to documents in the format [[D1]](), [[D2]](), [[D3]](), etc.!
It is important that the citation is close to the information it supports. If you have multiple citations that support
a fact, please cite for example as [[D1]]()[[D3]](), or [[D2]]()[[D4]](), etc.
Feel free to also cite sub-questions in addition to documents, but make sure that you have documents cited with the sub-question
citation. If you want to cite both a document and a sub-question, please use [[D1]]()[[Q3]](), or [[D2]]()[[D7]]()[[Q4]](), etc.
Again, please NEVER cite sub-questions without a document citation!
Proper citations are very important for the user!
IMPORTANT RULES:
- If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.
You may give some additional facts you learned, but do not try to invent an answer.
- If the information is empty or irrelevant, just say """
+ f'"{UNKNOWN_ANSWER}"'
+ """.
- If the information is relevant but not fully conclusive, specify that the information is not conclusive and say why.
Again, you should be sure that the answer is supported by the information provided!
Try to keep your answer concise. But also highlight uncertainties you may have should there be substantial ones,
or assumptions you made.
Here is the contextual information:
---------------
*Answered Sub-questions (these should really matter!):
\n-------\n
{answered_sub_questions}
\n-------\n
And here are relevant document information that support the sub-question answers, or that are relevant for the actual question:\n
\n-------\n
{relevant_docs}
\n-------\n
And here is the question I want you to answer based on the information above:
\n-------\n
{question}
\n-------\n\n
Please keep your answer brief and concise, and focus on facts and data.
Answer:"""
)
"{persona_specification}\n\n"
"Use the information provided below - and only the provided information - to answer the provided main question.\n\n"
"The information provided below consists of:\n"
" 1) a number of answered sub-questions - these are very important to help you organize your thoughts and your answer\n"
" 2) a number of documents that deemed relevant for the question.\n\n"
"{history}\n\n"
"It is critical that you provide prover inline citations to documents in the format [[D1]](), [[D2]](), [[D3]](), etc.!\n"
"It is important that the citation is close to the information it supports. If you have multiple citations that support\n"
"a fact, please cite for example as [[D1]]()[[D3]](), or [[D2]]()[[D4]](), etc.\n"
"Feel free to also cite sub-questions in addition to documents, but make sure that you have documents cited with the "
"sub-question citation. If you want to cite both a document and a sub-question, please use [[D1]]()[[Q3]](), or "
"[[D2]]()[[D7]]()[[Q4]](), etc.\n"
"Again, please NEVER cite sub-questions without a document citation! "
"Proper citations are very important for the user!\n\n"
"IMPORTANT RULES:\n"
" - If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.\n"
" You may give some additional facts you learned, but do not try to invent an answer.\n"
f' - If the information is empty or irrelevant, just say "{UNKNOWN_ANSWER}".\n'
" - If the information is relevant but not fully conclusive, specify that the information is not conclusive and say why.\n\n"
"Again, you should be sure that the answer is supported by the information provided!\n\n"
"Try to keep your answer concise. But also highlight uncertainties you may have should there be substantial ones,\n"
"or assumptions you made.\n\n"
"Here is the contextual information:\n"
"---------------\n\n"
"*Answered Sub-questions (these should really matter!):\n"
f"{SEPARATOR_LINE}\n"
"{answered_sub_questions}\n"
f"{SEPARATOR_LINE}\n\n"
"And here are relevant document information that support the sub-question answers, "
"or that are relevant for the actual question:\n"
f"{SEPARATOR_LINE}\n"
"{relevant_docs}\n"
f"{SEPARATOR_LINE}\n\n"
"And here is the question I want you to answer based on the information above:\n"
f"{SEPARATOR_LINE}\n"
"{question}\n"
f"{SEPARATOR_LINE}\n\n"
"Please keep your answer brief and concise, and focus on facts and data.\n\n"
"Answer:"
).strip()
# used if sub_question_answer_str is empty
@ -339,7 +327,6 @@ INITIAL_ANSWER_PROMPT_WO_SUB_QUESTIONS = (
"""\n
{answered_sub_questions}
{persona_specification}
{date_prompt}
Use the information provided below - and only the provided information - to answer the provided question.
The information provided below consists of a number of documents that were deemed relevant for the question.
@ -465,7 +452,7 @@ Generate the list of questions separated by one new line like this:
REFINED_ANSWER_PROMPT_W_SUB_QUESTIONS = (
"""\n
{persona_specification}
{date_prompt}
Your task is to improve on a given answer to a question, as the initial answer was found to be lacking in some way.
Use the information provided below - and only the provided information - to write your new and improved answer.
@ -542,7 +529,7 @@ REFINED_ANSWER_PROMPT_WO_SUB_QUESTIONS = (
"""\n
{answered_sub_questions}\n
{persona_specification}
{date_prompt}
Use the information provided below - and only the
provided information - to answer the provided question.