class_docstr: Wrapper class for Chinese retrieval conversation system
class_docstr_tok: ["Wrapper","class","for","Chinese","retrieval","conversation","system"]
code: def run(
      self, user_input: str, memory: ConversationBufferWithSummary
  ) -> Tuple[str, ConversationBufferWithSummary]:
      if memory:
          # TODO add translation chain here
          self.memory.buffered_history.messages = (
              memory.buffered_history.messages
          )
          self.memory.summarized_history_temp.messages = (
              memory.summarized_history_temp.messages
          )
      return (
          self.retrieval_chain.run(
              query=user_input,
              stop=[self.memory.human_prefix + ": "],
              rejection_trigger_keywrods=["cannot answer the question"],
              rejection_answer="Sorry, this question cannot be answered based on the information provided.",
          ).split("\n")[0],
          self.memory,
      )
  
file_path: colossalai/applications/ColossalQA/colossalqa/retrieval_conversation_en.py
imports: from typing import Tuple
  from colossalqa.chain.retrieval_qa.base import RetrievalQA
  from colossalqa.local.llm import ColossalAPI, ColossalLLM
  from colossalqa.memory import ConversationBufferWithSummary
  from colossalqa.mylogging import get_logger
  from colossalqa.prompt.prompt import PROMPT_DISAMBIGUATE_EN, PROMPT_RETRIEVAL_QA_EN
  from colossalqa.retriever import CustomRetriever
  from langchain import LLMChain
label_desc: Use image node_id 4 for calling the EnglishRetrievalConversation obj's underlying member method code with example usage: obj.run(user_input, memory) and returns: self,  self