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from dataclasses import dataclass
from typing import List
from rag.retriever.vector import Document
ANSWER_INSTRUCTION = (
"Do not attempt to answer the query without relevant context, and do not use "
"prior knowledge or training data!\n"
"If the context does not contain the answer or is empty, only reply that you "
"cannot answer the query given the context."
)
@dataclass
class Prompt:
query: str
documents: List[Document]
generator_model: str
def __context(self, documents: List[Document]) -> str:
results = [
f"Document: {i}\ntitle: {doc.title}\ntext: {doc.text}"
for i, doc in enumerate(documents)
]
return "\n".join(results)
def to_str(self) -> str:
if self.generator_model == "cohere":
return f"{self.query}\n\n{ANSWER_INSTRUCTION}"
else:
return (
"Context information is below.\n"
"---------------------\n"
f"{self.__context(self.documents)}\n\n"
"---------------------\n"
f"{ANSWER_INSTRUCTION}"
"Do not attempt to answer the query without relevant context and do not use"
" prior knowledge or training data!\n"
f"Query: {self.query.strip()}\n\n"
"Answer:"
)
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