Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import joblib
 import numpy as np
 
-# Load XGBoost model
+# Load trained model
 model = joblib.load("xgboost_model.pkl")
 
 # 🔧 Preprocessing Function
@@ -20,7 +20,10 @@ def preprocess(age, gender, bmi, smoking, alcohol, diabetes, hypertension, famil
 # 🧠 Prediction Function
 def predict_alzheimers(age, gender, bmi, smoking, alcohol, diabetes, hypertension, family_history, cognitive_score, apoe4):
     features = preprocess(age, gender, bmi, smoking, alcohol, diabetes, hypertension, family_history, cognitive_score, apoe4)
-    
+
+    # Debug: print features being sent to model
+    print("🛠️ Processed input sent to model:", features)
+
     # Predict probability of class 1 (positive)
     proba = model.predict_proba(features)[0][1]
     proba_percent = round(proba * 100, 2)