Update risk_model.py

risk_model.py

@@ -7,7 +7,6 @@ MODEL_PATH = "heating_model.pkl"
 DATA_PATH = "mantle_training.csv"
 HISTORY = []
 
-# Train the model and save
 def train_and_save_model():
     data = pd.read_csv(DATA_PATH)
     X = data[["temperature", "duration"]]
@@ -17,20 +16,23 @@ def train_and_save_model():
     dump(model, MODEL_PATH)
     return model
 
-# Load model safely
 def load_model():
     if not os.path.exists(MODEL_PATH):
         return train_and_save_model()
     return load(MODEL_PATH)
 
-# Load once at startup
 model = load_model()
 
 def predict_risk(temp, duration):
     global model
     pred = model.predict([[temp, duration]])[0]
     score = max(model.predict_proba([[temp, duration]])[0]) * 100
-    HISTORY.append({"Temperature": temp, "Duration": duration, "Risk": pred, "Confidence": round(score, 2)})
+    HISTORY.append({
+        "Temperature": temp,
+        "Duration": duration,
+        "Risk": pred,
+        "Confidence": round(score, 2)
+    })
     return pred, round(score, 2)
 
 def retrain_model():