def __init__(
        self,
        grouped_nodes: t.List[TextNode],
        small_toks: t.List[TextNode],
        vector_store: BasePydanticVectorStore,
        similarity_top_k: int = DEFAULT_TOP_K,
    ) -> None:
        """
        Constructor.

        Args:
            grouped_nodes (t.List[TextNode]): Long retrieval units, nodes with docs grouped together based on relationships
            small_toks (t.List[TextNode]): Smaller tokens
            embed_model (BaseEmbedding, optional): Embed model. Defaults to None.
            similarity_top_k (int, optional): Similarity top k. Defaults to 8.

        """
        self._grouped_nodes = grouped_nodes
        self._grouped_nodes_dict = {node.id_: node for node in grouped_nodes}
        self._small_toks = small_toks
        self._small_toks_dict = {node.id_: node for node in self._small_toks}

        self._similarity_top_k = similarity_top_k
        self._vec_store = vector_store
        self._embed_model = Settings.embed_model

        Constructor.

        Args:
            grouped_nodes (t.List[TextNode]): Long retrieval units, nodes with docs grouped together based on relationships
            small_toks (t.List[TextNode]): Smaller tokens
            embed_model (BaseEmbedding, optional): Embed model. Defaults to None.
            similarity_top_k (int, optional): Similarity top k. Defaults to 8.

        
llama-index-packs/llama-index-packs-longrag/llama_index/packs/longrag/base.py