Update app.py

app.py

@@ -182,7 +182,7 @@ def predict_inverse(hardness_original_target, ys_original_target, metals_to_use,
     result = result[result>0.0].dropna(axis=1)
 
     # Normalize metals outputs
-    sum_metals = np.sum(result[c] for c in list(result. columns) if c.startswith("PROPERTY: Metal"))
+    sum_metals = np.sum(result[c] for c in list(result.columns) if c.startswith("PROPERTY: Metal"))
     for column in result.columns:
         if column.startswith("PROPERTY: Metal"):
             result[column]/= sum_metals