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75 lines
2.5 KiB
Python
75 lines
2.5 KiB
Python
from langchain_core.prompts.prompt import PromptTemplate
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from datetime import datetime, timezone
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DATE_TODAY = "Today's date is " + datetime.now(timezone.utc).astimezone().isoformat() + '\n'
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# Create a prompt template for sub-query decomposition
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SUBQUERY_DECOMPOSITION_TEMPLATE = DATE_TODAY + """You are an AI assistant tasked with breaking down complex queries into simpler sub-queries for a vector store.
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Given the original query, decompose it into 2-4 simpler sub-queries for vector search that helps in expanding context.
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Original query: {original_query}
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IMPORTANT INSTRUCTION: Make sure to only return sub-queries and no explanation.
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EXAMPLE:
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User Query: What are the impacts of climate change on the environment?
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AI Answer:
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What are the impacts of climate change on biodiversity?
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How does climate change affect the oceans?
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What are the effects of climate change on agriculture?
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What are the impacts of climate change on human health?
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"""
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# SUBQUERY_DECOMPOSITION_TEMPLATE_TWO = DATE_TODAY + """You are an AI language model assistant. Your task is to generate five
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# different versions of the given user question to retrieve relevant documents from a vector
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# database. By generating multiple perspectives on the user question, your goal is to help
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# the user overcome some of the limitations of the distance-based similarity search.
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# Provide these alternative questions separated by newlines.
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# Original question: {original_query}"""
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SUBQUERY_DECOMPOSITION_PROMT = PromptTemplate(
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input_variables=["original_query"],
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template=SUBQUERY_DECOMPOSITION_TEMPLATE
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)
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CONTEXT_ANSWER_TEMPLATE = DATE_TODAY + """You are a phd in english litrature. You are given the task to give detailed research report and explanation to the user query based on the given context.
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IMPORTANT INSTRUCTION: Only return answer if you can find it in given context otherwise just say you don't know.
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Context: {context}
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User Query: {query}
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Detailed Report:"""
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ANSWER_WITH_CITATIONS = DATE_TODAY + """You're a helpful AI assistant. Given a user question and some Webpage article snippets, \
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answer the user question and provide citations. If none of the articles answer the question, just say you don't know.
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Remember, you must return both an answer and citations. Citation information is given in Document Metadata.
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Here are the Webpage article snippets:
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{context}
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User Query: {query}
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Your Answer:"""
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CONTEXT_ANSWER_PROMPT = PromptTemplate(
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input_variables=["context","query"],
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template=ANSWER_WITH_CITATIONS
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)
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