Update pydantic types to Annotated

Author: Val Brodsky

libs/labelbox/src/labelbox/data/annotation_types/metrics/scalar.py

@@ -1,11 +1,13 @@
 from typing import Dict, Optional, Union
+from typing_extensions import Annotated
 from enum import Enum
 
-from .base import ConfidenceValue, BaseMetric
+from pydantic import field_validator
+from pydantic.types import confloat
 
-from pydantic import confloat, field_validator, model_serializer
+from .base import ConfidenceValue, BaseMetric
 
-ScalarMetricValue = confloat(ge=0, le=100_000_000)
+ScalarMetricValue = Annotated[float, confloat(ge=0, le=100_000_000)]
 ScalarMetricConfidenceValue = Dict[ConfidenceValue, ScalarMetricValue]
 
 
@@ -27,11 +29,12 @@ class ScalarMetric(BaseMetric):
     For backwards compatibility, metric_name is optional.
     The metric_name will be set to a default name in the editor if it is not set.
     This is not recommended and support for empty metric_name fields will be removed.
-    aggregation will be ignored wihtout providing a metric name.
+    aggregation will be ignored without providing a metric name.
     """
     metric_name: Optional[str] = None
     value: Union[ScalarMetricValue, ScalarMetricConfidenceValue]
-    aggregation: ScalarMetricAggregation = ScalarMetricAggregation.ARITHMETIC_MEAN
+    aggregation: Optional[
+        ScalarMetricAggregation] = ScalarMetricAggregation.ARITHMETIC_MEAN
 
     @field_validator('metric_name')
     def validate_metric_name(cls, name: Union[str, None]):