我正在构建一个应用程序，使用Opensearch作为vecotr商店与Llamaindex使用this示例。下面是我的代码：

endpoint = getenv("OPENSEARCH_ENDPOINT", "http://localhost:9200")
    idx = getenv("OPENSEARCH_INDEX", "gpt-index-demo")
    
    UnstructuredReader = download_loader("UnstructuredReader")

    loader = UnstructuredReader()
    documents = loader.load_data(file=Path(file_name))

    # OpensearchVectorClient stores text in this field by default
    text_field = "content"
    # OpensearchVectorClient stores embeddings in this field by default
    embedding_field = "embedding"
    # OpensearchVectorClient encapsulates logic for a
    # single opensearch index with vector search enabled
    client = OpensearchVectorClient(endpoint, idx, 1536, embedding_field=embedding_field, text_field=text_field)
    # initialize vector store
    vector_store = OpensearchVectorStore(client)
    # initialize an index using our sample data and the client we just created
    index = GPTVectorStoreIndex.from_documents(documents=documents)

我的困惑是，当我们创建OpensearchVectorClient时，我们没有传递任何documents，然后当我们初始化index时，我们没有传递vector_store，也没有合适的字段通过查看GPTVectorStoreIndex.from_documents()的定义来传递它。那么，文档如何进入Elasticsearch索引？