Update app.py

app.py

@@ -9,22 +9,25 @@ def make_prediction(al, type, dr, sn, percent, tmax):
                 clf  = pickle.load(f)
                 preds = clf.predict([[type, dr, sn, percent]])
             return f"""Shear strength after improvement: {round((preds.squeeze() * tmax),2)}
-            Improvement percentage is {round((preds.squeeze()-1)*100,2)}%"""
+Improvement percentage is {round((preds.squeeze()-1)*100,2)}%"""
         elif al == "Random Forest" :
             with open("random_forest.pkl", "rb") as f:
                 clf  = pickle.load(f)
                 preds = clf.predict([[type, dr, sn, percent]])
-            return f"Improvement percentage would be around {round((preds.squeeze()-1)*100, 2)}% and shear strength improvement predicted by Random Forest is {round((preds.squeeze() * tmax), 2)}"
+            return f"""Shear strength after improvement: {round((preds.squeeze() * tmax),2)}
+Improvement percentage is {round((preds.squeeze()-1)*100,2)}%"""
         elif al == "XGBoost" :
             with open("XGBoost.pkl", "rb") as f:
                 clf  = pickle.load(f)
                 preds = clf.predict([[type, dr, sn, percent]])
-            return f"Improvement percentage would be around {round((preds.squeeze()-1)*100, 2)}% and shear strength improvement predicted by XGBoost is {round((preds.squeeze() * tmax), 2)}"
+            return f"""Shear strength after improvement: {round((preds.squeeze() * tmax),2)}
+Improvement percentage is {round((preds.squeeze()-1)*100,2)}%"""
         elif al == "AdaBoost" :
             with open("AdaBoost.pkl", "rb") as f:
                 clf  = pickle.load(f)
                 preds = clf.predict([[type, dr, sn, percent]])
-            return f"Improvement percentage would be around {round((preds.squeeze()-1)*100, 2)}% and shear strength improvement predicted by AdaBoost is {round((round(preds.squeeze() * tmax), 2))}"
+            return f"""Shear strength after improvement: {round((preds.squeeze() * tmax),2)}
+Improvement percentage is {round((preds.squeeze()-1)*100,2)}%"""
 
 
 import gradio as gr