remove has_any_of for consistency

Author: lb-pno

libs/labelbox/src/labelbox/schema/workflow/project_filter.py

@@ -111,17 +111,6 @@ def is_not_one_of(self, values: List[str]) -> Dict[str, Any]:
         """
         return {self._field_name: values, "__operator": "is_not"}
 
-    def has_any_of(self, values: List[str]) -> Dict[str, Any]:
-        """Filter for items that have any of the specified values.
-
-        This is semantically equivalent to is_one_of but provides clearer intent
-        for certain filter types like categories or annotations.
-
-        Args:
-            values: List of IDs to match
-        """
-        return {self._field_name: values}
-
 
 class RangeField:
     """Field class for range-based filters like consensus_average."""
@@ -498,8 +487,8 @@ class ProjectWorkflowFilter(BaseModel):
         filters = ProjectWorkflowFilter([
             labeled_by.is_one_of(["user-123"]),
             dataset.is_one_of(["dataset-456"]),
-            issue_category.has_any_of(["cat1", "cat2"]),
-            annotation.has_any_of(["bbox", "segmentation"]),
+            issue_category.is_one_of(["cat1", "cat2"]),
+            annotation.is_one_of(["bbox", "segmentation"]),
             sample(20),
             labeled_at.between("2024-01-01", "2024-12-31"),
             metadata([condition.contains("tag", "test")]),

libs/labelbox/tests/integration/test_workflow.py

@@ -458,7 +458,7 @@ def test_production_logic_node_with_comprehensive_filters(
                 labeling_time.greater_than(1000),
                 review_time.less_than_or_equal(100),
                 dataset.is_one_of(["cm37vyets000z072314wxgt0l"]),
-                annotation.has_any_of(["cm37w0e0500lf0709ba7c42m9"]),
+                annotation.is_one_of(["cm37w0e0500lf0709ba7c42m9"]),
                 consensus_average(0.17, 0.61),
                 model_prediction(
                     [