Add support for likert scale

libs/labelbox/src/labelbox/schema/tool_building/classification.py

@@ -76,14 +76,15 @@ class UIMode(Enum):
         None  # How this classification should be answered (e.g. hotkeys / autocomplete, etc)
     )
     attributes: Optional[FeatureSchemaAttributes] = None
+    is_likert_scale: bool = False
 
     def __post_init__(self):
         if self.name is None:
             msg = (
-                "When creating the Classification feature, please use “name” "
+                'When creating the Classification feature, please use "name" '
                 "for the classification schema name, which will be used when "
                 "creating annotation payload for Model-Assisted Labeling "
-                "Import and Label Import. “instructions” is no longer "
+                'Import and Label Import. "instructions" is no longer '
                 "supported to specify classification schema name."
             )
             if self.instructions is not None:
@@ -119,6 +120,7 @@ def from_dict(cls, dictionary: Dict[str, Any]) -> "Classification":
             ]
             if dictionary.get("attributes")
             else None,
+            is_likert_scale=dictionary.get("isLikertScale", False),
         )
 
     def asdict(self, is_subclass: bool = False) -> Dict[str, Any]:
@@ -138,6 +140,9 @@ def asdict(self, is_subclass: bool = False) -> Dict[str, Any]:
             if self.attributes is not None
             else None,
         }
+        if self.class_type == self.Type.RADIO and self.is_likert_scale:
+            # is_likert_scale is only applicable to RADIO classifications
+            classification["isLikertScale"] = self.is_likert_scale
         if (
             self.class_type == self.Type.RADIO
             or self.class_type == self.Type.CHECKLIST
@@ -159,6 +164,9 @@ def add_option(self, option: "Option") -> None:
                 f"Duplicate option '{option.value}' "
                 f"for classification '{self.name}'."
             )
+        # Auto-assign position if not set
+        if option.position is None:
+            option.position = len(self.options)
         self.options.append(option)
 
 
@@ -178,6 +186,7 @@ class Option:
         schema_id: (str)
         feature_schema_id: (str)
         options: (list)
+        position: (int) - Position of the option, auto-assigned starting from 0
     """
 
     value: Union[str, int]
@@ -187,6 +196,7 @@ class Option:
     options: Union[
         List["Classification"], List["PromptResponseClassification"]
     ] = field(default_factory=list)
+    position: Optional[int] = None
 
     def __post_init__(self):
         if self.label is None:
@@ -203,16 +213,20 @@ def from_dict(cls, dictionary: Dict[str, Any]) -> "Option":
                 Classification.from_dict(o)
                 for o in dictionary.get("options", [])
             ],
+            position=dictionary.get("position", None),
         )
 
     def asdict(self) -> Dict[str, Any]:
-        return {
+        result = {
             "schemaNodeId": self.schema_id,
             "featureSchemaId": self.feature_schema_id,
             "label": self.label,
             "value": self.value,
             "options": [o.asdict(is_subclass=True) for o in self.options],
         }
+        if self.position is not None:
+            result["position"] = self.position
+        return result
 
     def add_option(
         self, option: Union["Classification", "PromptResponseClassification"]
@@ -268,10 +282,10 @@ class PromptResponseClassification:
     def __post_init__(self):
         if self.name is None:
             msg = (
-                "When creating the Classification feature, please use “name” "
+                'When creating the Classification feature, please use "name" '
                 "for the classification schema name, which will be used when "
                 "creating annotation payload for Model-Assisted Labeling "
-                "Import and Label Import. “instructions” is no longer "
+                'Import and Label Import. "instructions" is no longer '
                 "supported to specify classification schema name."
             )
             if self.instructions is not None:

libs/labelbox/tests/unit/test_unit_ontology.py

@@ -294,3 +294,33 @@ def test_classification_using_instructions_instead_of_name_shows_warning():
 def test_classification_without_name_raises_error():
     with pytest.raises(ValueError):
         Classification(class_type=Classification.Type.TEXT)
+
+
+@pytest.mark.parametrize(
+    "class_type, is_likert_scale, should_include",
+    [
+        (Classification.Type.RADIO, True, True),
+        (Classification.Type.RADIO, False, False),
+        (Classification.Type.CHECKLIST, True, False),
+        (Classification.Type.TEXT, True, False),
+    ],
+)
+def test_is_likert_scale_serialization(
+    class_type, is_likert_scale, should_include
+):
+    c = Classification(
+        class_type=class_type, name="test", is_likert_scale=is_likert_scale
+    )
+    if class_type in Classification._REQUIRES_OPTIONS:
+        c.add_option(Option(value="option1"))
+    result = c.asdict()
+    assert ("isLikertScale" in result) == should_include
+
+
+def test_option_position_auto_assignment():
+    c = Classification(class_type=Classification.Type.RADIO, name="test")
+    o1, o2 = Option(value="first"), Option(value="second")
+    c.add_option(o1)
+    c.add_option(o2)
+    assert o1.position == 0 and o2.position == 1
+    assert c.asdict()["options"][0]["position"] == 0