making list_samples endpoint robust to stale predictions

pyproject.toml

@@ -7,7 +7,7 @@ packages = ["src/nyckel"]
 
 [project]
 name = "nyckel"
-version = "0.4.11"
+version = "0.4.12"
 authors = [{ name = "Oscar Beijbom", email = "[email protected]" }]
 description = "Python package for the Nyckel API"
 readme = "README.md"

src/nyckel/functions/tags/tabular_tags.py

@@ -308,12 +308,16 @@ def _sample_from_dict(
             annotation = None
 
         if "prediction" in sample_dict:
+            # TODO: Note that we filter out predictsion that are not in the label list.
+            # This is a temporary fix since these should not be there in the first place.
+
             prediction = [
                 ClassificationPrediction(
                     confidence=entry["confidence"],
                     label_name=label_name_by_id[strip_nyckel_prefix(entry["labelId"])],
                 )
                 for entry in sample_dict["prediction"]
+                if strip_nyckel_prefix(entry["labelId"]) in label_name_by_id
             ]
         else:
             prediction = None