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app.py

@@ -30,7 +30,7 @@ model = load_model()
 # ==========================================
 st.title("🚢 Engine Condition Predictor")
 st.markdown("""
-This application uses a trained **XGBoost** model to predict engine health 
+This application uses a trained **XGBoost** model to predict engine health
 based on sensor patterns.
 """)
 
@@ -59,16 +59,16 @@ if st.button("Predict Engine Condition", type="primary"):
 
         # Create DataFrame with EXACT column names and order
         input_data = pd.DataFrame([[
-            engine_rpm, 
-            lub_oil_pressure, 
-            fuel_pressure, 
-            coolant_pressure, 
-            lub_oil_temp, 
-            coolant_temp, 
-            load_index, 
+            engine_rpm,
+            lub_oil_pressure,
+            fuel_pressure,
+            coolant_pressure,
+            lub_oil_temp,
+            coolant_temp,
+            load_index,
             thermal_stress
         ]], columns=[
-            'Engine rpm', 'Lub oil pressure', 'Fuel pressure', 'Coolant pressure', 
+            'Engine rpm', 'Lub oil pressure', 'Fuel pressure', 'Coolant pressure',
             'lub oil temp', 'Coolant temp', 'load_index', 'thermal_stress'
         ])
 
@@ -83,7 +83,7 @@ if st.button("Predict Engine Condition", type="primary"):
              st.success("**Status: Engine is in Good Condition**")
         else:
              st.error("**Status: Maintenance Required (Potential Fault)**")
-        
+
     else:
         st.error("Model could not be loaded. Check your Hugging Face Repo ID.")