removed xgboost training

app.py

@@ -48,16 +48,16 @@ tokenizer_model_name = "nlptown/bert-base-multilingual-uncased-sentiment"
 mental_classifier_model_path = "mental_health_model.pkl"
 mental_classifier = MentalHealthClassifier(data_path, mental_classifier_model_path)
 
-if not os.path.exists(mental_classifier_model_path):
-    mental_classifier.initialize_tokenizer(tokenizer_model_name)
-    X, y = mental_classifier.preprocess_data()
-    y_test, y_pred = mental_classifier.train_model(X, y)
-    mental_classifier.save_model()
-else:
-    mental_classifier.load_model()
-    mental_classifier.initialize_tokenizer(tokenizer_model_name)  # Ensure tokenizer is initialized if loading model from pickle
-    X, y = mental_classifier.preprocess_data()  # Preprocess data again if needed
-    mental_classifier.model.fit(X, y)  # Fit the loaded model to the data
+# if not os.path.exists(mental_classifier_model_path):
+#     mental_classifier.initialize_tokenizer(tokenizer_model_name)
+#     X, y = mental_classifier.preprocess_data()
+#     y_test, y_pred = mental_classifier.train_model(X, y)
+#     mental_classifier.save_model()
+# else:
+#     mental_classifier.load_model()
+#     mental_classifier.initialize_tokenizer(tokenizer_model_name)  # Ensure tokenizer is initialized if loading model from pickle
+#     X, y = mental_classifier.preprocess_data()  # Preprocess data again if needed
+#     mental_classifier.model.fit(X, y)  # Fit the loaded model to the data
 
 # Function to display Q-table
 def display_q_table(q_values, states, actions):