input_variables sequence	output_parser null	template stringclasses 1 value	template_format stringclasses 1 value
[ "question", "existing_answer", "context_str" ]	null	The original question is as follows: {question}\nWe have provided an existing answer: {existing_answer}\nWe have the opportunity to refine the existing answer(only if needed) with some more context below.\n------------\n{context_str}\n------------\nGiven the new context, refine the original answer to better answer the question. If the context isn't useful, return the original answer.	f-string

input_variables

sequence

output_parser

null

template

stringclasses

1 value

template_format

stringclasses

1 value

[ "question", "existing_answer", "context_str" ]

null

The original question is as follows: {question}\nWe have provided an existing answer: {existing_answer}\nWe have the opportunity to refine the existing answer(only if needed) with some more context below.\n------------\n{context_str}\n------------\nGiven the new context, refine the original answer to better answer the question. If the context isn't useful, return the original answer.

f-string

Description of QA Refine

Prompts designed to be used to refine original answers during question answering chains using the refine method.

Inputs

This is a description of the inputs that the prompt expects.

question: Original question to be answered.
existing_answer: Existing answer from previous documents.
context_str: New piece of context to use to refine the existing answer.

Usage

Below is a code snippet for how to use the prompt.

from langchain.prompts import load_prompt
from langchain.chains.question_answering import load_qa_chain

llm = ...
prompt = load_prompt('lc://prompts/qa/refine/<file-name>')
chain = load_qa_chain(llm, chain_type="refine", refine_prompt=prompt)