| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113 | 
							- #
 - #  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 - #
 - #  Licensed under the Apache License, Version 2.0 (the "License");
 - #  you may not use this file except in compliance with the License.
 - #  You may obtain a copy of the License at
 - #
 - #      http://www.apache.org/licenses/LICENSE-2.0
 - #
 - #  Unless required by applicable law or agreed to in writing, software
 - #  distributed under the License is distributed on an "AS IS" BASIS,
 - #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 - #  See the License for the specific language governing permissions and
 - #  limitations under the License.
 - #
 - import logging
 - from abc import ABC
 - from api.db import LLMType
 - from api.db.services.llm_service import LLMBundle
 - from agent.component import GenerateParam, Generate
 - 
 - 
 - class RewriteQuestionParam(GenerateParam):
 - 
 -     """
 -     Define the QuestionRewrite component parameters.
 -     """
 -     def __init__(self):
 -         super().__init__()
 -         self.temperature = 0.9
 -         self.prompt = ""
 -         self.loop = 1
 - 
 -     def check(self):
 -         super().check()
 - 
 -     def get_prompt(self, conv):
 -         self.prompt = """
 -         You are an expert at query expansion to generate a paraphrasing of a question.
 -         I can't retrieval relevant information from the knowledge base by using user's question directly.     
 -         You need to expand or paraphrase user's question by multiple ways such as using synonyms words/phrase, 
 -         writing the abbreviation in its entirety, adding some extra descriptions or explanations, 
 -         changing the way of expression, translating the original question into another language (English/Chinese), etc. 
 -         And return 5 versions of question and one is from translation.
 -         Just list the question. No other words are needed.
 -         """
 -         return f"""
 - Role: A helpful assistant
 - Task: Generate a full user question that would follow the conversation.
 - Requirements & Restrictions:
 -   - Text generated MUST be in the same language of the original user's question.
 -   - If the user's latest question is completely, don't do anything, just return the original question.
 -   - DON'T generate anything except a refined question.
 - 
 - ######################
 - -Examples-
 - ######################
 - # Example 1
 - ## Conversation
 - USER: What is the name of Donald Trump's father?
 - ASSISTANT:  Fred Trump.
 - USER: And his mother?
 - ###############
 - Output: What's the name of Donald Trump's mother?
 - ------------
 - # Example 2
 - ## Conversation
 - USER: What is the name of Donald Trump's father?
 - ASSISTANT:  Fred Trump.
 - USER: And his mother?
 - ASSISTANT:  Mary Trump.
 - User: What's her full name?
 - ###############
 - Output: What's the full name of Donald Trump's mother Mary Trump?
 - ######################
 - # Real Data
 - ## Conversation
 - {conv}
 - ###############
 -     """
 -         return self.prompt
 - 
 - 
 - class RewriteQuestion(Generate, ABC):
 -     component_name = "RewriteQuestion"
 - 
 -     def _run(self, history, **kwargs):
 -         if not hasattr(self, "_loop"):
 -             setattr(self, "_loop", 0)
 -         if self._loop >= self._param.loop:
 -             self._loop = 0
 -             raise Exception("Sorry! Nothing relevant found.")
 -         self._loop += 1
 - 
 -         hist = self._canvas.get_history(4)
 -         conv = []
 -         for m in hist:
 -             if m["role"] not in ["user", "assistant"]:
 -                 continue
 -             conv.append("{}: {}".format(m["role"].upper(), m["content"]))
 -         conv = "\n".join(conv)
 - 
 -         chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
 -         ans = chat_mdl.chat(self._param.get_prompt(conv), [{"role": "user", "content": "Output: "}],
 -                             self._param.gen_conf())
 -         self._canvas.history.pop()
 -         self._canvas.history.append(("user", ans))
 - 
 -         logging.debug(ans)
 -         return RewriteQuestion.be_output(ans)
 - 
 - 
 
 
  |