def _create_collection(self, dimension: int) -> None:
        """
        Create collection.

        Args:
            dimension (int): The dimension of the embeddings.

        """
        fields: List[dict] = [
            {"name": "id", "dataType": "STRING", "primaryKey": True},
            {"name": DEFAULT_DOC_ID_KEY, "dataType": "STRING"},
            {"name": DEFAULT_TEXT_KEY, "dataType": "STRING"},
            {
                "name": DEFAULT_EMBEDDING_KEY,
                "dataType": "VECTOR_FLOAT",
                "dimensions": dimension,
            },
            {"name": "metadata", "dataType": "JSON"},
        ]
        status_code, response = self._client.create_table(
            table_name=self._collection_name, table_fields=fields
        )
        if status_code != 200:
            self._handle_error(msg=response["message"])
        self._collection_created = True
        logger.debug(f"Successfully created collection: {self._collection_name}")

        Create collection.

        Args:
            dimension (int): The dimension of the embeddings.

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