code: def set_embed_model(self, **kwargs):
      self.embed_model = HuggingFaceEmbeddings(
          model_name=kwargs["embed_model_name_or_path"],
          model_kwargs=kwargs["embed_model_device"],
          encode_kwargs={"normalize_embeddings": False},
      )
  
imports: import os
  from typing import Dict, Tuple
  from colossalqa.chain.retrieval_qa.base import RetrievalQA
  from colossalqa.data_loader.document_loader import DocumentLoader
  from colossalqa.memory import ConversationBufferWithSummary
  from colossalqa.mylogging import get_logger
  from colossalqa.prompt.prompt import PROMPT_DISAMBIGUATE_ZH, PROMPT_RETRIEVAL_QA_ZH, SUMMARY_PROMPT_ZH, ZH_RETRIEVAL_QA_REJECTION_ANSWER, ZH_RETRIEVAL_QA_TRIGGER_KEYWORDS
  from colossalqa.retriever import CustomRetriever
  from langchain import LLMChain
  from langchain.embeddings import HuggingFaceEmbeddings
label_desc: Use image node_id 2 for calling the RAG_ChatBot obj's underlying member method code with example usage: obj.set_embed_model() without return types