def _get_embeddings_per_level(self, level: int = 0) -> List[float]:
        """
        Retrieve embeddings per level in the abstraction tree.

        Args:
            level (int, optional): Target level. Defaults to 0 which stands for leaf nodes.

        Returns:
            List[float]: List of embeddings

        """
        filters = MetadataFilters(filters=[MetadataFilter("level", level)])

        # kind of janky, but should work with any vector index
        source_nodes = self.index.as_retriever(
            similarity_top_k=10000, filters=filters
        ).retrieve("retrieve")

        return [x.node for x in source_nodes]

        Retrieve embeddings per level in the abstraction tree.

        Args:
            level (int, optional): Target level. Defaults to 0 which stands for leaf nodes.

        Returns:
            List[float]: List of embeddings

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