Enhance metrics handling and logging in bot

- Integrated metrics scheduler start and stop functionality in `run_helper.py` for better resource management.
- Improved logging for metrics server operations in `server_prometheus.py`, ensuring clearer error reporting and status updates.
- Updated metrics middleware to collect comprehensive metrics for all event types, enhancing monitoring capabilities.
- Added active user metrics tracking in `admin_handlers.py` to provide insights on user engagement.
- Refactored command and callback handling in `metrics_middleware.py` to improve clarity and error handling.

helper_bot/main.py

@@ -81,8 +81,20 @@ async def start_bot(bdf):
         # Запускаем метрики сервер
         await start_metrics_server(metrics_host, metrics_port)
         
+        # Запускаем планировщик метрик для периодического обновления
+        from .utils.metrics_scheduler import start_metrics_scheduler
+        await start_metrics_scheduler()
+        
+        logging.info(f"✅ Метрики сервер запущен на {metrics_host}:{metrics_port}")
+        logging.info("✅ Планировщик метрик запущен")
+        
         # Запускаем бота с retry логикой
         await start_bot_with_retry(bot, dp)
+
+        logging.info("✅ Бот запущен")
+    except Exception as e:
+        logging.error(f"❌ Ошибка запуска метрик сервера: {e}")
+        # Продолжаем работу бота даже если метрики не запустились
         
     except Exception as e:
         logging.error(f"Error in bot startup: {e}")
@@ -99,5 +111,5 @@ async def start_bot(bdf):
             await bot.session.close()
         except Exception as e:
             logging.error(f"Error closing bot session: {e}")
-    
+
     return bot