code: from llama_index.core import Settings, Document, VectorStoreIndex
  from llama_index.core.node_parser import SentenceWindowNodeParser
  doc = Document(
      text="Sentence 1. Sentence 2. Sentence 3."
  )
  text_splitter = SentenceWindowNodeParser.from_defaults(
      window_size=2  ,
      window_metadata_key="ContextWindow",
      original_text_metadata_key="node_text"
  )
  Settings.text_splitter = text_splitter
  
  index = VectorStoreIndex.from_documents([doc])
  retriever = index.as_retriever(similarity_top_k=1)
  response = retriever.retrieve("Display the second sentence")
  print(response[0].node.metadata['node_text'])
  
  
apis: llama_index.core.node_parser.SentenceWindowNodeParser.from_defaults llama_index.core.VectorStoreIndex.from_documents llama_index.core.Document
extract_api: [((138, 190), 'llama_index.core.Document', 'Document', ([], {'text': '"""Sentence 1. Sentence 2. Sentence 3."""'}), "(text='Sentence 1. Sentence 2. Sentence 3.')\n", (146, 190), False, 'from llama_index.core import Settings, Document, VectorStoreIndex\n'), ((213, 348), 'llama_index.core.node_parser.SentenceWindowNodeParser.from_defaults', 'SentenceWindowNodeParser.from_defaults', ([], {'window_size': '(2)', 'window_metadata_key': '"""ContextWindow"""', 'original_text_metadata_key': '"""node_text"""'}), "(window_size=2, window_metadata_key=\n    'ContextWindow', original_text_metadata_key='node_text')\n", (251, 348), False, 'from llama_index.core.node_parser import SentenceWindowNodeParser\n'), ((408, 446), 'llama_index.core.VectorStoreIndex.from_documents', 'VectorStoreIndex.from_documents', (['[doc]'], {}), '([doc])\n', (439, 446), False, 'from llama_index.core import Settings, Document, VectorStoreIndex\n')]