class_docstr: RAGHandler is a MindsDB integration with supported LLM APIs allows users to run question answering
  on their data by providing a question.
  
  The User is able to provide data that provides context for the questions, see create() method for more details.
class_docstr_tok: ["RAGHandler","is","a","MindsDB","integration","with","supported","LLM","APIs","allows","users","to","run","question","answering","on","their","data","by","providing","a","question",".","The","User","is","able","to","provide","data","that","provides","context","for","the","questions",",","see","create","(",")","method","for","more","details","."]
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.generative = True
  
file_path: mindsdb/mindsdb/integrations/handlers/rag_handler/rag_handler.py
imports: from typing import Dict, Optional
  import pandas
  from mindsdb.integrations.handlers.rag_handler.ingest import RAGIngestor
  from mindsdb.integrations.handlers.rag_handler.rag import RAGQuestionAnswerer
  from mindsdb.integrations.handlers.rag_handler.settings import DEFAULT_EMBEDDINGS_MODEL, RAGHandlerParameters, build_llm_params
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.utilities import log
label_desc: Use image node_id 1 to create a new RAGHandler object from inherited base classes: BaseMLEngine with example: obj = RAGHandler()