class_docstr: Base model parameters for RAG Handler
class_docstr_tok: ["Base","model","parameters","for","RAG","Handler"]
code: def prompt_format_must_be_valid(cls, v):
      if "{context}" not in v or "{question}" not in v:
          raise InvalidPromptTemplate(
              "prompt_template must contain {context} and {question}"
              f"\n For example, {DEFAULT_QA_PROMPT_TEMPLATE}"
          )
      return v
  
imports: import json
  from dataclasses import dataclass
  from functools import lru_cache, partial
  from typing import Any, Dict, List, Union
  import html2text
  import openai
  import pandas
  import requests
  import writer
  from langchain import Writer
  from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
  from langchain.docstore.document import Document
  from langchain.document_loaders import DataFrameLoader
  from langchain.embeddings.base import Embeddings
  from langchain.embeddings.huggingface import HuggingFaceEmbeddings
  from langchain.vectorstores import FAISS, Chroma, VectorStore
  from pydantic import BaseModel, Extra, Field, validator
  from mindsdb.integrations.handlers.chromadb_handler.chromadb_handler import get_chromadb
  from mindsdb.integrations.handlers.rag_handler.exceptions import InvalidOpenAIModel, InvalidPromptTemplate, InvalidWriterModel, UnsupportedLLM, UnsupportedVectorStore
label_desc: Use image node_id 1 for calling the RAGBaseParameters obj's underlying member method code with example usage: obj.prompt_format_must_be_valid(cls, v) and returns: v