Adapt [vector_async_index] add collection.flush_index()

src/pyseekdb/client/client_base.py

@@ -1504,6 +1504,24 @@ def _fork_database_enabled(self) -> bool:
         logger.debug(f"db_type: {db_type}, version: {version}")
         return db_type.lower() == "seekdb" and version >= version_120
 
+    def _refresh_enabled(self) -> bool:
+        db_type, version = self.detect_db_type_and_version()
+        version_130 = Version("1.3.0.0")
+        logger.debug(f"db_type: {db_type}, version: {version}")
+        return db_type.lower() == "seekdb" and version >= version_130
+
+    def refresh_index(self) -> None:
+        """
+        Flush async vector index build tasks when supported.
+
+        For unsupported database versions, this method is a no-op to keep
+        collection-level API calls backward compatible.
+        """
+        if not self._refresh_enabled():
+            return
+
+        self._execute("CALL dbms_index_manager.refresh();")
+
     def _get_collection_id(self, collection_name: str) -> str:
         collection_id_query_sql = f"SELECT COLLECTION_ID FROM `{CollectionNames.sdk_collections_table_name()}` WHERE COLLECTION_NAME = '{collection_name}'"
         collection_id_query_result = self._execute(collection_id_query_sql)

src/pyseekdb/client/collection.py

@@ -593,6 +593,19 @@ def hybrid_search(
             **kwargs,
         )
 
+    def refresh_index(self) -> None:
+        """
+        Flush async vector index build tasks.
+
+        This executes ``CALL dbms_index_manager.refresh();`` and returns only
+        after the database completes the refresh procedure.
+
+        Note:
+            This method is only available for seekdb version 1.3.0.0 or higher.
+            In 1.2.0.0 and earlier, this method is a no-op.
+        """
+        self._client.refresh_index()
+
     # ==================== Collection Info ====================
 
     def count(self) -> int:

tests/integration_tests/test_collection_query.py

@@ -110,6 +110,8 @@ def test_collection_query(self, db_client):
         # Insert test data
         self._insert_test_data(db_client, collection_name, dimension=actual_dimension)
 
+        collection.refresh_index()
+
         # Test 1: Basic vector similarity query
         print("\n✅ Testing basic query")
         # Generate query vector with correct dimension

tests/integration_tests/test_collection_v1_compatibility.py

@@ -325,6 +325,8 @@ def test_v1_collection_query(self, db_client):
             ],
         )
 
+        collection.refresh_index()
+
         # Query with vector similarity
         query_vector = [1.0, 2.0, 3.0]
         results = collection.query(

tests/integration_tests/test_offical_case.py

@@ -50,6 +50,8 @@ def _run_official_example(collection):
         ids=PRODUCT_IDS,
     )
 
+    collection.refresh_index()
+
     results = collection.query(
         query_texts=["powerful computer for professional work"],
         where={

tests/integration_tests/test_sparse_vector_index.py

@@ -474,6 +474,7 @@ def test_dense_query_still_works(self, db_client):
         name = _unique_name("query_dense_with_sparse")
         try:
             collection, _ids, _ = self._setup_with_data(db_client, name)
+            collection.refresh_index()
             results = collection.query(
                 query_embeddings=[1.0, 2.0, 3.0],
                 n_results=3,