class_docstr: Integration with the LlamaIndex data framework for LLM applications.
class_docstr_tok: ["Integration","with","the","LlamaIndex","data","framework","for","LLM","applications","."]
code: def _setup_index(self, documents):
      args = self.model_storage.json_get("args")
      indexer: VectorStore = getattr(
          llama_index, args["using"]["index_class"]
      )
      index = indexer.from_documents(
          documents, service_context=self._get_service_context()
      )
  
      return index
  
imports: import os
  from typing import Optional, Dict
  import openai
  import pandas
  import llama_index
  from langchain.llms import OpenAI
  from llama_index.readers.schema.base import Document
  from llama_index.readers import SimpleWebPageReader
  from llama_index.prompts import PromptTemplate
  from llama_index import ServiceContext, StorageContext, load_index_from_storage
  from llama_index import LLMPredictor, OpenAIEmbedding
  from llama_index.indices.vector_store.base import VectorStore
  from llama_hub.github_repo import GithubClient, GithubRepositoryReader
  from llama_hub.youtube_transcript import YoutubeTranscriptReader, is_youtube_video
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.utilities.config import Config
  from mindsdb.utilities.security import is_private_url
  from mindsdb.integrations.handlers.llama_index_handler import config
  from mindsdb.integrations.handlers.llama_index_handler.github_loader_helper import _get_github_token, _get_filter_file_extensions, _get_filter_directories
  from mindsdb.integrations.utilities.handler_utils import get_api_key
label_desc: Use image node_id 7 for calling the LlamaIndexHandler obj's underlying member method code with example usage: obj._setup_index(documents) and returns: index