Update app.py

app.py

@@ -256,7 +256,11 @@ if task == "Classification":
     target_feature_names = text_clf['clf'].classes_
     #target_feature_names = pd.unique(df[labels_column_name])
     target_feature_names_list = list(target_feature_names)
-    t_pred = te.explain_prediction(target_names = target_feature_names_list, top = top_features, top_targets = top_targets)
+    try:
+        t_pred = te.explain_prediction(target_names = target_feature_names_list, top = top_features, top_targets = top_targets)
+    except TypeError:
+        st.error("Unable to get target label names - most likely due to a numeric label feature type")
+        t_pred = te.explain_prediction(top = top_features, top_targets = top_targets)
 else:
     t_pred = te.explain_prediction(top = top_features, top_targets = top_targets)
 html = format_as_html(t_pred)