def from_connection_string(
        cls,
        connection_string: str,
        table_name: str,
        table_schema: Dict[str, str] = {"document": "text"},
        embedding_dimension: int = 1536,
        pre_delete_table: bool = False,
    ) -> "HologresVectorStore":
        """
        Create Hologres Vector Store from connection string.

        Args:
            connection_string: connection string of hologres database
            table_name: table name to persist data
            table_schema: table column schemam
            embedding_dimension: dimension size of embedding vector
            pre_delete_table: whether to erase data from table on creation

        """
        hologres_storage = HologresVector(
            connection_string,
            ndims=embedding_dimension,
            table_name=table_name,
            table_schema=table_schema,
            pre_delete_table=pre_delete_table,
        )
        return cls(hologres_storage=hologres_storage)

        Create Hologres Vector Store from connection string.

        Args:
            connection_string: connection string of hologres database
            table_name: table name to persist data
            table_schema: table column schemam
            embedding_dimension: dimension size of embedding vector
            pre_delete_table: whether to erase data from table on creation

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