Update risk_model.py

risk_model.py

@@ -29,32 +29,4 @@ def load_model():
 
 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
-    timestamp = get_ist_time()
-    HISTORY.append({
-        "Temperature": temp,
-        "Duration": duration,
-        "Risk": pred,
-        "Confidence": round(score, 2),
-        "Timestamp": timestamp
-    })
-    return pred, round(score, 2), timestamp
-
-def retrain_model():
-    try:
-        data = pd.read_csv(DATA_PATH)
-        X = data[["temperature", "duration"]]
-        y = data["risk_level"]
-        clf = RandomForestClassifier().fit(X, y)
-        dump(clf, MODEL_PATH)
-        global model
-        model = clf
-        return "✅ Model retrained successfully"
-    except Exception as e:
-        return f"❌ Error: {str(e)}"
-
-def get_history_df():
-    return pd.DataFrame(HISTORY)
+def predict_risk_