MULTIPLE_PROMPT_FORCE = 'You are a helpful assistant, below is a query from a user and some relevant contexts. \ Answer the query given the information in those contexts.\ \n\nContexts: [context] \n\nQuery: [question] \n\nAnswer:' SELF_CITATION_PROMPT = """You are a helpful assistant, below is a query from a user, some relevant contexts, and an answer to the query. Please cite the top [k] most important contexts that lead to the answer using their indexes, and order these [k] contexts from most important to least important. e.g.,[10]>[32]>[6]>[8]>[25]. ">" means "more important than". Only output these indexes. \n\nContexts: [context] \n\nQuery: [question] \n\nAnswer: [answer].""" GUARDRAIL_PROMPT = """[context]""" MULTIPLE_PROMPT_PART1 = 'You are a helpful assistant, below is a query from a user and some relevant contexts. \ Answer the question given the information in those contexts. \ \n\nContexts: ' MULTIPLE_PROMPT_PART2 = ' \n\nQuery: [question] \n\nAnswer:' def wrap_prompt_attention(question,customized_template = None) -> str: if customized_template is None: prompt_part1 = MULTIPLE_PROMPT_PART1 prompt_part2 = MULTIPLE_PROMPT_PART2.replace('[question]', question) else: prompt_part1 = customized_template.split("[context]")[0] prompt_part2 = customized_template.split("[context]")[1] prompt_part1 = prompt_part1.replace('[question]', question) prompt_part2 = prompt_part2.replace('[question]', question) return prompt_part1, prompt_part2 def wrap_prompt(question, context, split_token = "",customized_template = None) -> str: assert type(context) == list context_str = split_token.join(context) if customized_template is None: input_prompt = MULTIPLE_PROMPT_FORCE.replace('[question]', question).replace('[context]', context_str) else: input_prompt = customized_template.replace('[question]', question).replace('[context]', context_str) return input_prompt def wrap_prompt_guardrail(question, context, split_token = "") -> str: assert type(context) == list context_str = split_token.join(context) input_prompt = GUARDRAIL_PROMPT.replace('[question]', question).replace('[context]', context_str) return input_prompt def wrap_prompt_self_citation(question, context,answer,k = 5) -> str: assert type(context) == list context_str = "\n".join(context) input_prompt = SELF_CITATION_PROMPT.replace('[question]', question).replace('[context]', context_str).replace('[answer]', answer).replace('[k]', str(k)) return input_prompt