def update_vector_search_index(
        self,
        dimensions: int,
        path: str,
        similarity: str,
        filters: Optional[List[str]] = None,
        *,
        wait_until_complete: Optional[float] = None,
        **kwargs: Any,
    ) -> None:
        """
        Update the vector search index for this store.

        Replace the existing index definition with the provided definition.

        Args:
            dimensions (int): Number of dimensions in embedding
            path (str): field with vector embedding
            similarity (str): The similarity score used for the index.
            filters (List[str]): Fields/paths to index to allow filtering in $vectorSearch
            wait_until_complete (Optional[float]): If provided, number of seconds to wait
                until search index is ready.
            kwargs: Keyword arguments supplying any additional options to SearchIndexModel.

        """
        return update_vector_search_index(
            self.collection,
            self._vector_index_name,
            dimensions,
            path,
            similarity,
            filters,
            wait_until_complete=wait_until_complete,
            **kwargs,
        )

        Update the vector search index for this store.

        Replace the existing index definition with the provided definition.

        Args:
            dimensions (int): Number of dimensions in embedding
            path (str): field with vector embedding
            similarity (str): The similarity score used for the index.
            filters (List[str]): Fields/paths to index to allow filtering in $vectorSearch
            wait_until_complete (Optional[float]): If provided, number of seconds to wait
                until search index is ready.
            kwargs: Keyword arguments supplying any additional options to SearchIndexModel.

        
llama-index-integrations/vector_stores/llama-index-vector-stores-mongodb/llama_index/vector_stores/mongodb/base.py