feat: Fix typo in Vertex Feature Store SDK.

PiperOrigin-RevId: 627854409

Author: vertex-sdk-bot

tests/unit/vertexai/test_feature_online_store.py

@@ -483,9 +483,9 @@ def test_create_embedding_fv(
         FeatureView.BigQuerySource(uri="hi", entity_id_columns=["entity_id"]),
         index_config=IndexConfig(
             embedding_column="embedding",
-            filter_column=["currency_code", "gender", "shipping_country_codes"],
+            dimensions=1536,
+            filter_columns=["currency_code", "gender", "shipping_country_codes"],
             crowding_column="crowding",
-            dimentions=1536,
             distance_measure_type=DistanceMeasureType.SQUARED_L2_DISTANCE,
             algorithm_config=TreeAhConfig(),
         ),

vertexai/resources/preview/feature_store/utils.py

@@ -130,11 +130,11 @@ class IndexConfig:
     """Configuration options for the Vertex FeatureView for embedding."""
 
     embedding_column: str
-    filter_column: List[str]
-    crowding_column: str
-    dimentions: Optional[int]
-    distance_measure_type: DistanceMeasureType
+    dimensions: int
     algorithm_config: AlgorithmConfig
+    filter_columns: Optional[List[str]] = None
+    crowding_column: Optional[str] = None
+    distance_measure_type: Optional[DistanceMeasureType] = None
 
     def as_dict(self) -> Dict[str, Any]:
         """Returns the configuration as a dictionary.
@@ -144,11 +144,15 @@ def as_dict(self) -> Dict[str, Any]:
         """
         config = {
             "embedding_column": self.embedding_column,
-            "filter_columns": self.filter_column,
-            "crowding_column": self.crowding_column,
-            "embedding_dimension": self.dimentions,
-            "distance_measure_type": self.distance_measure_type.value,
+            "embedding_dimension": self.dimensions,
         }
+        if self.distance_measure_type is not None:
+            config["distance_measure_type"] = self.distance_measure_type.value
+        if self.filter_columns is not None:
+            config["filter_columns"] = self.filter_columns
+        if self.crowding_column is not None:
+            config["crowding_column"] = self.crowding_column
+
         if isinstance(self.algorithm_config, TreeAhConfig):
             config["tree_ah_config"] = self.algorithm_config.as_dict()
         else: