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app.py

@@ -72,9 +72,8 @@ if st.button("Predict Engine Condition", type="primary"):
             'lub oil temp', 'Coolant temp', 'load_index', 'thermal_stress'
         ])
 
-        # Perform prediction
+        # Perform prediction (Binary Result Only)
         prediction = model.predict(input_data)[0]
-        prediction_proba = model.predict_proba(input_data)[0]
 
         st.divider()
         st.subheader("Results")
@@ -84,18 +83,6 @@ if st.button("Predict Engine Condition", type="primary"):
              st.success("**Status: Engine is in Good Condition**")
         else:
              st.error("**Status: Maintenance Required (Potential Fault)**")
-
-        # --- FIX START: Handling st.progress error ---
-        # 1. Extract the probability for the "Healthy" class (Class 0)
-        health_score = float(prediction_proba[0])
-        
-        # 2. Clip the value to ensure it is strictly between 0.0 and 1.0
-        # This prevents crashes if the model returns 1.0000001 or -0.0000001
-        safe_progress_value = max(0.0, min(1.0, health_score))
-
-        st.write(f"**Confidence Score:** {max(prediction_proba)*100:.2f}%")
-        st.progress(safe_progress_value)
-        # --- FIX END ---
         
     else:
         st.error("Model could not be loaded. Check your Hugging Face Repo ID.")