Update app.py

app.py

@@ -771,15 +771,17 @@ def save_to_github(personalized_message, model_name, comment, corrected_message,
     response = requests.put(url, headers=headers, data=json.dumps(data))
 
 
-def personalize_and_save(gpt4o_message, gigachat_pro_message, gigachat_lite_message, gigachat_plus_message, meta_llama_405b_message, meta_llama_70b_message, meta_llama_8b_message, gemma_27b_message, gemma_9b_message, mistral_message, description, advantages, *selected_values):
-    personalization_results = list(personalize_messages_with_yield(
-        gpt4o_message, gigachat_pro_message, gigachat_lite_message, gigachat_plus_message, meta_llama_405b_message, meta_llama_70b_message, meta_llama_8b_message, gemma_27b_message, gemma_9b_message, mistral_message, *selected_values
-    ))
-
-    # Save to GitHub after the personalization
-    save_user_request_to_github(description, advantages, selected_values)
-
-    return personalization_results[-1]  # Return the last set of outputs from personalization
+def personalize_and_save(*args):
+    # Разделим на два этапа
+    # 1. Персонализация (с использованием yield для пошагового отображения)
+    personalization_results = list(personalize_messages_with_yield(*args[:-2]))
+
+    # 2. Сохранение (выполняется после завершения персонализации)
+    description, advantages = args[-2], args[-1]
+    selected_values = args[-(2 + len(selections)):-2]  # Извлекаем параметры персонализации
+    save_user_request_to_github(personalization_results[1], personalization_results[2], selected_values)
+    
+    return personalization_results
 
 
 # Создание интерфейса Gradio