chore: restore working behavior

Author: rishisurana-labelbox

libs/labelbox/src/labelbox/data/annotation_types/temporal.py

@@ -5,9 +5,11 @@
 frame-level precision. All temporal classifications support nested hierarchies.
 """
 
-from typing import List, Optional, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple, Union
 from pydantic import BaseModel, Field
 
+from ...annotated_types import Cuid
+
 
 class TemporalClassificationAnswer(BaseModel):
     """
@@ -21,6 +23,8 @@ class TemporalClassificationAnswer(BaseModel):
         frames (List[Tuple[int, int]]): List of (start_frame, end_frame) ranges in milliseconds
         classifications (Optional[List[Union[TemporalClassificationText, TemporalClassificationQuestion]]]):
             Nested classifications within this answer
+        feature_schema_id (Optional[Cuid]): Feature schema identifier
+        extra (Dict[str, Any]): Additional metadata
 
     Example:
         >>> # Radio answer with nested classifications
@@ -49,6 +53,8 @@ class TemporalClassificationAnswer(BaseModel):
     classifications: Optional[
         List[Union["TemporalClassificationText", "TemporalClassificationQuestion"]]
     ] = None
+    feature_schema_id: Optional[Cuid] = None
+    extra: Dict[str, Any] = Field(default_factory=dict)
 
 
 class TemporalClassificationText(BaseModel):
@@ -63,6 +69,8 @@ class TemporalClassificationText(BaseModel):
         value (List[Tuple[int, int, str]]): List of (start_frame, end_frame, text_value) tuples
         classifications (Optional[List[Union[TemporalClassificationText, TemporalClassificationQuestion]]]):
             Nested classifications
+        feature_schema_id (Optional[Cuid]): Feature schema identifier
+        extra (Dict[str, Any]): Additional metadata
 
     Example:
         >>> # Simple text with multiple temporal values
@@ -99,6 +107,8 @@ class TemporalClassificationText(BaseModel):
     classifications: Optional[
         List[Union["TemporalClassificationText", "TemporalClassificationQuestion"]]
     ] = None
+    feature_schema_id: Optional[Cuid] = None
+    extra: Dict[str, Any] = Field(default_factory=dict)
 
 
 class TemporalClassificationQuestion(BaseModel):
@@ -111,8 +121,8 @@ class TemporalClassificationQuestion(BaseModel):
     Args:
         name (str): Name of the question/classification
         value (List[TemporalClassificationAnswer]): List of answer options with frame ranges
-        classifications (Optional[List[Union[TemporalClassificationText, TemporalClassificationQuestion]]]):
-            Nested classifications (typically not used at question level)
+        feature_schema_id (Optional[Cuid]): Feature schema identifier
+        extra (Dict[str, Any]): Additional metadata
 
     Note:
         - Radio: Single answer in the value list
@@ -177,6 +187,8 @@ class TemporalClassificationQuestion(BaseModel):
     classifications: Optional[
         List[Union["TemporalClassificationText", "TemporalClassificationQuestion"]]
     ] = None
+    feature_schema_id: Optional[Cuid] = None
+    extra: Dict[str, Any] = Field(default_factory=dict)
 
 
 # Update forward references for recursive types

libs/labelbox/src/labelbox/data/serialization/ndjson/label.py

@@ -29,7 +29,7 @@
     TemporalClassificationText,
     TemporalClassificationQuestion,
 )
-from .temporal import create_temporal_ndjson_classifications
+from .temporal import create_temporal_ndjson_annotations
 from labelbox.types import DocumentRectangle, DocumentEntity
 from .classification import (
     NDChecklistSubclass,
@@ -75,7 +75,7 @@ def from_common(
             yield from cls._create_relationship_annotations(label)
             yield from cls._create_non_video_annotations(label)
             yield from cls._create_video_annotations(label)
-            yield from cls._create_temporal_classifications(label)
+            yield from cls._create_temporal_annotations(label)
 
     @staticmethod
     def _get_consecutive_frames(
@@ -167,7 +167,7 @@ def _create_video_annotations(
                 yield NDObject.from_common(segments, label.data)
 
     @classmethod
-    def _create_temporal_classifications(
+    def _create_temporal_annotations(
         cls, label: Label
     ) -> Generator[BaseModel, None, None]:
         """Create temporal annotations with nested classifications using new temporal classes."""
@@ -182,7 +182,7 @@ def _create_temporal_classifications(
             return
 
         # Use the new temporal serializer to create NDJSON annotations
-        ndjson_annotations = create_temporal_ndjson_classifications(
+        ndjson_annotations = create_temporal_ndjson_annotations(
             temporal_annotations, label.data.global_key
         )
 

libs/labelbox/src/labelbox/data/serialization/ndjson/temporal.py

@@ -26,7 +26,7 @@ class TemporalNDJSON(BaseModel):
     dataRow: Dict[str, str]
 
 
-def create_temporal_ndjson_classifications(
+def create_temporal_ndjson_annotations(
     annotations: List[
         Union[TemporalClassificationText, TemporalClassificationQuestion]
     ],
@@ -45,10 +45,11 @@ def create_temporal_ndjson_classifications(
     if not annotations:
         return []
 
-    # Group by classification name
+    # Group by classification name/schema_id
     groups = defaultdict(list)
     for ann in annotations:
-        groups[ann.name].append(ann)
+        key = ann.feature_schema_id or ann.name
+        groups[key].append(ann)
 
     results = []
     for group_key, group_anns in groups.items():
@@ -266,12 +267,13 @@ def _process_nested_classifications(
     """
     Process nested classifications recursively.
 
-    Groups by name and processes each group.
+    Groups by name/schema_id and processes each group.
     """
     # Group by name
     groups = defaultdict(list)
     for cls in classifications:
-        groups[cls.name].append(cls)
+        key = cls.feature_schema_id or cls.name
+        groups[key].append(cls)
 
     results = []
     for group_key, group_items in groups.items():

libs/labelbox/tests/data/serialization/ndjson/test_temporal.py

@@ -2,7 +2,7 @@
 
 import labelbox.types as lb_types
 from labelbox.data.serialization.ndjson.temporal import (
-    create_temporal_ndjson_classifications,
+    create_temporal_ndjson_annotations,
 )
 
 
@@ -18,7 +18,7 @@ def test_temporal_text_simple():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     assert result[0].name == "transcription"
@@ -49,7 +49,7 @@ def test_temporal_question_radio():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     assert result[0].name == "speaker"
@@ -78,7 +78,7 @@ def test_temporal_question_checklist():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     assert result[0].name == "audio_quality"
@@ -123,7 +123,7 @@ def test_temporal_text_nested():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     assert result[0].name == "transcription"
@@ -185,7 +185,7 @@ def test_temporal_question_nested():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     answer = result[0].answer[0]
@@ -227,7 +227,7 @@ def test_frame_validation_discard_invalid():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     # Find the nested notes classification
     answer = result[0].answer[0]
@@ -251,7 +251,7 @@ def test_frame_deduplication():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     # Should only have one entry
     assert len(result[0].answer) == 1
@@ -291,7 +291,7 @@ def test_mixed_text_and_question_nesting():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     answer = result[0].answer[0]
@@ -341,7 +341,7 @@ def test_inductive_structure_text_with_shared_nested_radio():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     assert result[0].name == "content_notes"
@@ -416,7 +416,7 @@ def test_inductive_structure_checklist_with_multiple_text_values():
         )
     ]
 
-    result = create_temporal_ndjson_classifications(annotations, "test-global-key")
+    result = create_temporal_ndjson_annotations(annotations, "test-global-key")
 
     assert len(result) == 1
     assert result[0].name == "checklist_class"