Update app.py

app.py

@@ -108,7 +108,9 @@ def predict_inverse(hardness_original_target, ys_original_target, request: gr.Re
 
     one_hot_columns = utils.return_feature_names()
     min_df_hardness, max_df_hardness = scaling_factors["PROPERTY: HV"]
-    min_df_hardness, max_df_hardness = scaling_factors["PROPERTY: YS (MPa)"]
+    min_df_hardness, max_df_hardness = float(min_df_hardness), float(max_df_hardness)
+    min_df_ys, max_df_ys = scaling_factors["PROPERTY: YS (MPa)"]
+    min_df_ys, max_df_ys = float(min_df_ys), float(max_df_ys)
 
     hardness_target = (hardness_original_target-min_df_hardness)/(max_df_hardness-min_df_hardness)
     ys_target = (ys_original_target-min_df_ys)/(max_df_ys-min_df_ys)