class VectorStoreIndex(BaseIndex[IndexDict]):
    """
    Vector Store Index.

    Args:
        use_async (bool): Whether to use asynchronous calls. Defaults to False.
        show_progress (bool): Whether to show tqdm progress bars. Defaults to False.
        store_nodes_override (bool): set to True to always store Node objects in index
            store and document store even if vector store keeps text. Defaults to False
    """

    index_struct_cls = IndexDict

    def __init__(
        self,
        nodes: Optional[Sequence[BaseNode]] = None,
        # vector store index params
        use_async: bool = False,
        store_nodes_override: bool = False,
        embed_model: Optional[EmbedType] = None,
        insert_batch_size: int = 2048,
        # parent class params
        objects: Optional[Sequence[IndexNode]] = None,
        index_struct: Optional[IndexDict] = None,
        storage_context: Optional[StorageContext] = None,
        callback_manager: Optional[CallbackManager] = None,
        transformations: Optional[List[TransformComponent]] = None,
        show_progress: bool = False,
        **kwargs: Any,
    ) -> None:
        """Initialize params."""
        self._use_async = use_async
        self._store_nodes_override = store_nodes_override
        self._embed_model = (
            resolve_embed_model(embed_model, callback_manager=callback_manager)
            if embed_model
            else Settings.embed_model
        )

        self._insert_batch_size = insert_batch_size
        super().__init__(
            nodes=nodes,
            index_struct=index_struct,
            storage_context=storage_context,
            show_progress=show_progress,
            objects=objects,
            callback_manager=callback_manager,
            transformations=transformations,
            **kwargs,
        )