diff --git a/telegram_bot/bot.py b/telegram_bot/bot.py
index 4d98991..c1c7cc5 100644
--- a/telegram_bot/bot.py
+++ b/telegram_bot/bot.py
@@ -1,97 +1,96 @@
-import os
-import torch
-import logging
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-from telegram import Update
-from telegram.ext import Application, MessageHandler, filters, CommandHandler, CallbackContext
-from dotenv import load_dotenv
-import mysql.connector
-
-
-# Загрузка переменных окружения из .env
-load_dotenv()
-TOKEN = os.getenv("TOKEN")
-
-# Путь к модели
-MODEL_PATH = "./hate_speech_model/final_model"
-
-db_config = {
-    "host": "mysql",
-    "user": "root",
-    "password": "0674998280tanya",
-    "database": "telegram_bot"
-}
-
-def save_violator(username, message):
-    """Сохраняет нарушителя в базу данных"""
-    try:
-        conn = mysql.connector.connect(**db_config)
-        cursor = conn.cursor()
-        query = "INSERT INTO violators (username, message) VALUES (%s, %s)"
-        cursor.execute(query, (username, message))
-        conn.commit()
-        cursor.close()
-        conn.close()
-    except mysql.connector.Error as err:
-        logging.error(f"Ошибка MySQL: {err}")
-
-
-# Настройка логирования
-logging.basicConfig(
-    format="%(asctime)s - %(levelname)s - %(message)s",
-    level=logging.INFO,
-    handlers=[
-        logging.FileHandler("log.txt"),
-        logging.StreamHandler()
-    ]
-)
-
-# Загрузка модели и токенизатора
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
-model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH).to(device)
-
-def classify_text(text):
-    """Функция для классификации текста"""
-    model.eval()
-    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding="max_length", max_length=128).to(device)
-
-    with torch.no_grad():
-        outputs = model(**inputs)
-
-    logits = outputs.logits
-    pred = torch.argmax(logits, dim=-1).item()
-
-    return "🛑 Nenávistná reč" if pred == 1 else "✅ OK"
-
-async def check_message(update: Update, context: CallbackContext):
-    """Проверяет сообщения в чате и реагирует на токсичные сообщения"""
-    message_text = update.message.text
-    result = classify_text(message_text)
-
-    if result == "🛑 Nenávistná reč":
-        username = update.message.from_user.username or "unknown"
-        await update.message.reply_text("⚠️ Upozornenie! Dodržiavajte kultúru komunikácie.")
-        await update.message.delete()  # Автоматическое удаление токсичных сообщений
-        
-        # Логирование токсичного сообщения
-        logging.warning(f"Toxická správa od {update.message.from_user.username}: {message_text}")
-        save_violator(username, message_text)
-
-async def start(update: Update, context: CallbackContext):
-    """Отправляет приветственное сообщение при запуске бота"""
-    await update.message.reply_text("Ahoj! Sledujem kultúru komunikácie v chate!")
-
-def main():
-    """Запуск бота"""
-    app = Application.builder().token(TOKEN).build()
-
-    # Добавление обработчиков команд и сообщений
-    app.add_handler(CommandHandler("start", start))
-    app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, check_message))
-
-    # Запуск бота
-    app.run_polling()
-
-if __name__ == "__main__":
-    main()
+import os
+import torch
+import logging
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from telegram import Update
+from telegram.ext import Application, MessageHandler, filters, CommandHandler, CallbackContext
+from dotenv import load_dotenv
+import mysql.connector
+
+# Load environment variables from .env file
+load_dotenv()
+TOKEN = os.getenv("TOKEN")
+
+# Path to the model
+MODEL_PATH = "./hate_speech_model/final_model"
+
+# Database configuration
+db_config = {
+    "host": "mysql",
+    "user": "root",
+    "password": "0674998280tanya",
+    "database": "telegram_bot"
+}
+
+def save_violator(username, message):
+    """Saves the violator's message to the database"""
+    try:
+        conn = mysql.connector.connect(**db_config)
+        cursor = conn.cursor()
+        query = "INSERT INTO violators (username, message) VALUES (%s, %s)"
+        cursor.execute(query, (username, message))
+        conn.commit()
+        cursor.close()
+        conn.close()
+    except mysql.connector.Error as err:
+        logging.error(f"MySQL error: {err}")
+
+# Logging setup
+logging.basicConfig(
+    format="%(asctime)s - %(levelname)s - %(message)s",
+    level=logging.INFO,
+    handlers=[
+        logging.FileHandler("log.txt"),
+        logging.StreamHandler()
+    ]
+)
+
+# Load tokenizer and model
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH).to(device)
+
+def classify_text(text):
+    """Classifies the input text"""
+    model.eval()
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding="max_length", max_length=128).to(device)
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    logits = outputs.logits
+    pred = torch.argmax(logits, dim=-1).item()
+
+    return "🛑 Hate speech detected" if pred == 1 else "✅ OK"
+
+async def check_message(update: Update, context: CallbackContext):
+    """Checks chat messages and reacts to toxic content"""
+    message_text = update.message.text
+    result = classify_text(message_text)
+
+    if result == "🛑 Hate speech detected":
+        username = update.message.from_user.username or "unknown"
+        await update.message.reply_text("⚠️ Warning! Please maintain respectful communication.")
+        await update.message.delete()  # Automatically deletes toxic message
+        
+        # Log the toxic message
+        logging.warning(f"Toxic message from {username}: {message_text}")
+        save_violator(username, message_text)
+
+async def start(update: Update, context: CallbackContext):
+    """Sends welcome message on /start"""
+    await update.message.reply_text("Hi! I'm monitoring the chat for hate speech!")
+
+def main():
+    """Starts the bot"""
+    app = Application.builder().token(TOKEN).build()
+
+    # Register command and message handlers
+    app.add_handler(CommandHandler("start", start))
+    app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, check_message))
+
+    # Start polling
+    app.run_polling()
+
+if __name__ == "__main__":
+    main()