class_docstr: A class for using a RAG model for question answering
class_docstr_tok: ["A","class","for","using","a","RAG","model","for","question","answering"]
code: def _prepare_prompt(self, vector_store_response, question) -> str:
      context = [doc.page_content for doc in vector_store_response]
  
      combined_context = "\n\n".join(context)
  
      if self.args.summarize_context:
          return self.summarize_context(combined_context, question)
  
      return self.prompt_template.format(
          question=question, context=combined_context
      )
  
file_path: mindsdb/mindsdb/integrations/handlers/rag_handler/rag.py
imports: import json
  from collections import defaultdict
  from typing import List
  from mindsdb.integrations.handlers.rag_handler.settings import LLMLoader, PersistedVectorStoreLoader, PersistedVectorStoreLoaderConfig, RAGBaseParameters, RAGHandlerParameters, load_embeddings_model
  from mindsdb.utilities import log
label_desc: Use image node_id 3 for calling the RAGQuestionAnswerer obj's underlying member method code with example usage: obj._prepare_prompt(vector_store_response, question) and returns: self, self