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prompts
This commit is contained in:
Yuhong Sun
Evan Lohn
parent
c984c6c7f2
commit
59c65a4192
@ -38,9 +38,7 @@ from onyx.agents.agent_search.shared_graph_utils.utils import (
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get_langgraph_node_log_string,
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)
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from onyx.agents.agent_search.shared_graph_utils.utils import relevance_from_docs
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from onyx.agents.agent_search.shared_graph_utils.utils import (
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remove_document_citations,
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)
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from onyx.agents.agent_search.shared_graph_utils.utils import remove_document_citations
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from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
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from onyx.chat.models import AgentAnswerPiece
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from onyx.chat.models import ExtendedToolResponse
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@ -190,13 +188,15 @@ def generate_initial_answer(
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doc_context = format_docs(relevant_docs)
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doc_context = trim_prompt_piece(
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model.config,
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doc_context,
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base_prompt
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+ sub_question_answer_str
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+ prompt_enrichment_components.persona_prompts.contextualized_prompt
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+ prompt_enrichment_components.history
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+ prompt_enrichment_components.date_str,
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config=model.config,
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prompt_piece=doc_context,
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reserved_str=(
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base_prompt
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+ sub_question_answer_str
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+ prompt_enrichment_components.persona_prompts.contextualized_prompt
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+ prompt_enrichment_components.history
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+ prompt_enrichment_components.date_str
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),
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)
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msg = [
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@ -2,8 +2,8 @@
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SEPARATOR_LINE = "-------"
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UNKNOWN_ANSWER = "I do not have enough information to answer this question."
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NO_RECOVERED_DOCS = "No relevant information recovered"
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SUB_CHECK_YES = "yes"
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SUB_CHECK_NO = "no"
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YES = "yes"
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NO = "no"
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# Framing/Support/Template Prompts
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@ -51,13 +51,8 @@ Answer:
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""".strip()
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SUB_QUESTION_ANSWER_TEMPLATE_REFINED = """\n
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Sub-Question: Q{sub_question_num}\n Type: {sub_question_type}\n Sub-Question:\n
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- \n{sub_question}\n --\nAnswer:\n -\n {sub_answer}\n\n
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"""
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# Step/Utility Prompts
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# Note this one should always be used with the ENTITY_TERM_EXTRACTION_PROMPT_JSON_EXAMPLE
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ENTITY_TERM_EXTRACTION_PROMPT = f"""
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Based on the original question and some context retrieved from a dataset, please generate a list of
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entities (e.g. companies, organizations, industries, products, locations, etc.), terms and concepts
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@ -74,7 +69,7 @@ And here is the context retrieved:
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{SEPARATOR_LINE}
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Please format your answer as a json object in the following format:
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""".strip()
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""".lstrip()
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ENTITY_TERM_EXTRACTION_PROMPT_JSON_EXAMPLE = """
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{
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@ -274,7 +269,7 @@ SUB_ANSWER_CHECK_PROMPT = (
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f"{SEPARATOR_LINE}\n"
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"{base_answer}\n"
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f"{SEPARATOR_LINE}\n\n"
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f'Does the suggested answer address the question? Please answer with "{SUB_CHECK_YES}" or "{SUB_CHECK_NO}".'
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f'Does the suggested answer address the question? Please answer with "{YES}" or "{NO}".'
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).strip()
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@ -322,50 +317,35 @@ INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS = (
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).strip()
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# used if sub_question_answer_str is empty
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# Used if sub_question_answer_str is empty
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INITIAL_ANSWER_PROMPT_WO_SUB_QUESTIONS = (
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"""\n
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{answered_sub_questions}
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{persona_specification}
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"{answered_sub_questions}{persona_specification}\n\n"
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"Use the information provided below - and only the provided information - to answer the provided question. "
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"The information provided below consists of a number of documents that were deemed relevant for the question.\n"
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"{history}\n\n"
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"IMPORTANT RULES:\n"
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" - If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer. "
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"You may give some additional facts you learned, but do not try to invent an answer.\n"
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f' - If the information is irrelevant, just say "{UNKNOWN_ANSWER}".\n'
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" - If the information is relevant but not fully conclusive, specify that the information is not conclusive and say why.\n\n"
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"Again, you should be sure that the answer is supported by the information provided!\n\n"
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"It is critical that you provide proper inline citations to documents in the format [[D1]](), [[D2]](), [[D3]](), etc! "
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"It is important that the citation is close to the information it supports. If you have multiple citations, "
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"please cite for example as [[D1]]()[[D3]](), or [[D2]]()[[D4]](), etc. Citations are very important for the user!\n\n"
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"Here is the relevant context information:\n"
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f"{SEPARATOR_LINE}\n"
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"{relevant_docs}\n"
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f"{SEPARATOR_LINE}\n\n"
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"And here is the question I want you to answer based on the context above:\n"
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f"{SEPARATOR_LINE}\n"
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"{question}\n"
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f"{SEPARATOR_LINE}\n\n"
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"Please keep your answer brief and concise, and focus on facts and data.\n\n"
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"Answer:"
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).strip()
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Use the information provided below - and only the provided information - to answer the provided question.
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The information provided below consists of a number of documents that were deemed relevant for the question.
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{history}
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IMPORTANT RULES:
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- If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.
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You may give some additional facts you learned, but do not try to invent an answer.
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- If the information is irrelevant, just say """
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+ f'"{UNKNOWN_ANSWER}"'
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+ """.
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- If the information is relevant but not fully conclusive, specify that the information is not conclusive and say why.
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Again, you should be sure that the answer is supported by the information provided!
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It is critical that you provide proper inline citations to documents in the format [[D1]](), [[D2]](), [[D3]](), etc!
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It is important that the citation is close to the information it supports. If you have multiple
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citations, please cite for example as [[D1]]()[[D3]](), or [[D2]]()[[D4]](), etc. Citations are very important for the
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user!
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Try to keep your answer concise.
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Here are is the relevant context information:
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\n-------\n
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{relevant_docs}
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\n-------\n
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And here is the question I want you to answer based on the context above
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\n-------\n
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{question}
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\n-------\n
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Please keep your answer brief and concise, and focus on facts and data.
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Answer:"""
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)
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# REFINEMENT PHASE
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REFINEMENT_QUESTION_DECOMPOSITION_PROMPT = """ \n
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An initial user question needs to be answered. An initial answer has been provided but it wasn't quite
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good enough. Also, some sub-questions had been answered and this information has been used to provide
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@ -357,7 +357,9 @@ async def is_connected(request: Request) -> Callable[[], bool]:
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is_connected = not future.result(timeout=0.05)
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return is_connected
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except asyncio.TimeoutError:
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logger.error("Asyncio timed out")
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logger.warning(
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"Asyncio timed out (potentially missed request to stop streaming)"
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)
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return True
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except Exception as e:
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error_msg = str(e)
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