Deploy backend Flask app

bot_detector_api.py

@@ -115,15 +115,27 @@ def predict():
     try:
         row = request.get_json()
         X = prepare_features(row)
+        
+        # Get prediction probability and predicted class
         probs = model.predict_proba(X)[0]
-        pred_label = model.classes_[int(np.argmax(probs))]
+        pred_label = int(np.argmax(probs))  # 0 or 1
 
+        # Generate SHAP values
         shap_values = explainer.shap_values(X)
-        explanation = generate_shap_explanation(0, shap_values, X)
+
+        # Generate explanation for class 1
+        explanation, base_val, final_log_odds = generate_shap_explanation(
+            index=0,
+            shap_values=shap_values,
+            X=X,
+            class_index=1  # anomaly class
+        )
 
         return jsonify({
-            "Prediction": pred_label,
-            "SHAP Explanation": explanation.strip()
+            "Prediction": "Bot Attack" if pred_label == 1 else "Legitimate",
+            "SHAP Base Value": round(float(base_val), 4),
+            "SHAP Predicted Value": round(float(final_log_odds), 4),
+            "SHAP Explanation": explanation
         })
 
     except Exception as e: