Update app.py

app.py

@@ -253,11 +253,9 @@ def generate_message_with_retry(model_prompt):
         msg = clean_message(msg)
         length = len(msg)
         if 160 <= length <= 250:
-            # Добавляем информацию о количестве знаков
             msg += f"\n\n------\nКоличество знаков: {length}"
             return msg
         last_message = msg
-    # Если не удалось подобрать длину
     length = len(last_message)
     last_message += f"\n\n------\nКоличество знаков: {length}"
     return last_message
@@ -268,7 +266,8 @@ def update_prompts_on_params_change(description, product_name, benefits, key_mes
     prompt_1, prompt_2 = generate_display_prompts(description, product_name, benefits, key_message,
                                                   chosen_approach, gender, generation, psychotype,
                                                   business_stage, industry, opf)
-    return chosen_approach, prompt_1, prompt_2
+    # Очистка полей SMS и комментариев при изменении параметров
+    return chosen_approach, prompt_1, prompt_2, "", "", "", "", "", ""
 
 def save_user_request_to_github(selected_product, description, product_name, benefits, key_message, approach, personalization_params):
     global current_request_index
@@ -313,7 +312,7 @@ def load_previous_user_request_from_github():
         json_files = [file for file in files if file['name'].startswith("user_request_")]
         if not json_files:
             print("Нет сохраненных запросов.")
-            return "", "", "", "", "", None, None, None, None, None, None
+            return products[0], "", "", "", "", "", None, None, None, None, None, "", "", ""
         current_request_index -= 1
         if abs(current_request_index) > len(json_files):
             current_request_index = -len(json_files)
@@ -322,7 +321,7 @@ def load_previous_user_request_from_github():
         file_response = requests.get(file_url)
         if file_response.status_code == 200:
             data = json.loads(file_response.text)
-            selected_product = data.get('selected_product', "")
+            selected_product = data.get('selected_product', products[0])
             description = data.get('description', "")
             product_name = data.get('product_name', "")
             benefits = data.get('benefits', "")
@@ -331,13 +330,13 @@ def load_previous_user_request_from_github():
             personalization_params = data.get('personalization_params', [None]*6)
             if len(personalization_params) < 6:
                 personalization_params += [None]*(6-len(personalization_params))
-            return selected_product, description, product_name, benefits, key_message, approach, *personalization_params
+            return (selected_product, description, product_name, benefits, key_message, approach, *personalization_params)
         else:
             print(f"Ошибка при загрузке файла: {file_response.status_code}")
-            return "", "", "", "", "", "", None, None, None, None, None
+            return products[0], "", "", "", "", "", None, None, None, None, None, "", "", ""
     else:
         print(f"Ошибка при обращении к GitHub: {response.status_code}")
-        return "", "", "", "", "", "", None, None, None, None, None
+        return products[0], "", "", "", "", "", None, None, None, None, None, "", "", ""
 
 def generate_final_prompt_from_display(prompt_text, single_approach, is_prompt_1=True):
     prefix = approach_dict[single_approach]["prefix"]
@@ -348,9 +347,9 @@ def generate_final_prompt_from_display(prompt_text, single_approach, is_prompt_1
                          f"\n{suffix}.\nУбедись, что УМЕСТНО использовал КАЖДЫЙ необходимый термин.\nУбедись, что в SMS без изменений, синонимов и перестановок слов используется наименование продукта:\nУбедись, что в SMS есть следующая ключевая информация:", prompt_text, flags=re.DOTALL)
     return prompt_text
 
-def generate_personalized_sms(description, product_name, benefits, key_message,
-                              gender, generation, psychotype, business_stage, industry, opf,
-                              chosen_approach, prompt_1, prompt_2):
+def generate_personalized_sms_wrapper(selected_product, description, product_name, benefits, key_message,
+                                      gender, generation, psychotype, business_stage, industry, opf,
+                                      chosen_approach, prompt_1, prompt_2):
     if "Для формирования промпта выберите хотя бы один личный персональный параметр" in prompt_1 or chosen_approach == "Подход не найден для выбранных параметров.":
         gr.Warning("Задайте хотя бы о��ин личный персональный параметр для определения подхода, чтобы был сформирован промпт")
         return "", ""
@@ -365,7 +364,12 @@ def generate_personalized_sms(description, product_name, benefits, key_message,
     sms_1 = generate_message_with_retry(final_prompt_1)
     sms_2 = generate_message_with_retry(final_prompt_2)
     personalization_params = [gender, generation, psychotype, business_stage, industry, opf]
+    save_user_request_to_github(selected_product, description, product_name, benefits, key_message, chosen_approach, personalization_params)
+    return sms_1, sms_2
 
+def clear_sms_fields(chosen_approach, p1, p2):
+    # очистка sms_1, sms_2, comment_sms_1, comment_sms_2, corrected_sms_1, corrected_sms_2
+    return chosen_approach, p1, p2, "", "", "", "", "", ""
 
 with gr.Blocks(theme="default") as demo:
     gr.Markdown("**Процент созданных SMS по выбранному продукту**")
@@ -412,7 +416,7 @@ with gr.Blocks(theme="default") as demo:
                         gr.update(value=new_pname, interactive=(selected=="Свой продукт")),
                         gr.update(value=new_ben, interactive=(selected=="Свой продукт")),
                         gr.update(value=new_kmsg, interactive=(selected=="Свой продукт")),
-                        chosen_approach_val, p1, p2)
+                        chosen_approach_val, p1, p2, "", "", "", "", "", "")
 
         with gr.Column(scale=1):
             gr.Markdown("**Клиент**")
@@ -464,40 +468,29 @@ with gr.Blocks(theme="default") as demo:
                 gender_dropdown, generation_dropdown, psychotype_dropdown,
                 business_stage_dropdown, industry_dropdown, opf_dropdown],
         outputs=[description, product_name, benefits, key_message,
-                 chosen_approach, prompt_1, prompt_2]
+                 chosen_approach, prompt_1, prompt_2,
+                 sms_1, sms_2, comment_sms_1, comment_sms_2, corrected_sms_1, corrected_sms_2]
     )
 
+    def params_change_wrapper(description, product_name, benefits, key_message,
+                              gender, generation, psychotype, business_stage, industry, opf):
+        chosen_approach_val, p1, p2 = update_prompts_on_params_change(description, product_name, benefits, key_message,
+                                                                     gender, generation, psychotype,
+                                                                     business_stage, industry, opf)
+        return chosen_approach_val, p1, p2, "", "", "", "", "", ""
+
     client_params = [gender_dropdown, generation_dropdown, psychotype_dropdown,
                      business_stage_dropdown, industry_dropdown, opf_dropdown]
     for cp in client_params:
         cp.change(
-            fn=update_prompts_on_params_change,
+            fn=params_change_wrapper,
             inputs=[description, product_name, benefits, key_message,
                     gender_dropdown, generation_dropdown, psychotype_dropdown,
                     business_stage_dropdown, industry_dropdown, opf_dropdown],
-            outputs=[chosen_approach, prompt_1, prompt_2]
+            outputs=[chosen_approach, prompt_1, prompt_2,
+                     sms_1, sms_2, comment_sms_1, comment_sms_2, corrected_sms_1, corrected_sms_2]
         )
 
-    def generate_personalized_sms_wrapper(selected_product, description, product_name, benefits, key_message,
-                                          gender, generation, psychotype, business_stage, industry, opf,
-                                          chosen_approach, prompt_1, prompt_2):
-        if "Для формирования промпта выберите хотя бы один личный персональный параметр" in prompt_1 or chosen_approach == "Подход не найден для выбранных параметров.":
-            gr.Warning("Задайте хотя бы один личный персональный параметр для определения подхода, чтобы был сформирован промпт")
-            return "", ""
-        approach_list = [a.strip() for a in chosen_approach.split(',') if a.strip()]
-        if not approach_list:
-            gr.Warning("Задайте хотя бы один личный персональный параметр для определения подхода, чтобы был сформирован промпт")
-            return "", ""
-        chosen_single_approach_1 = random.choice(approach_list) if len(approach_list) > 1 else approach_list[0]
-        chosen_single_approach_2 = random.choice(approach_list) if len(approach_list) > 1 else approach_list[0]
-        final_prompt_1 = generate_final_prompt_from_display(prompt_1, chosen_single_approach_1, is_prompt_1=True)
-        final_prompt_2 = generate_final_prompt_from_display(prompt_2, chosen_single_approach_2, is_prompt_1=False)
-        sms_1 = generate_message_with_retry(final_prompt_1)
-        sms_2 = generate_message_with_retry(final_prompt_2)
-        personalization_params = [gender, generation, psychotype, business_stage, industry, opf]
-        save_user_request_to_github(selected_product, description, product_name, benefits, key_message, chosen_approach, personalization_params)
-        return sms_1, sms_2
-
     create_personal_sms_btn.click(
         fn=generate_personalized_sms_wrapper,
         inputs=[product_dropdown, description, product_name, benefits, key_message, 
@@ -510,7 +503,7 @@ with gr.Blocks(theme="default") as demo:
     def on_load_previous():
         loaded_data = load_previous_user_request_from_github()
         if not loaded_data or len(loaded_data) < 11:
-            return (products[0], "", "", "", "", None, None, None, None, None, None, "", "", "")
+            return (products[0], "", "", "", "", None, None, None, None, None, None, "", "", "", "", "", "")
         selected_product_val, description_val, product_name_val, benefits_val, key_message_val, approach_val = loaded_data[0], loaded_data[1], loaded_data[2], loaded_data[3], loaded_data[4], loaded_data[5]
         gender_val, generation_val, psychotype_val, business_stage_val, industry_val, opf_val = loaded_data[6:12]
         chosen_approach_val, p1, p2 = update_prompts_on_params_change(description_val, product_name_val, benefits_val, key_message_val,
@@ -518,7 +511,7 @@ with gr.Blocks(theme="default") as demo:
                                                                       business_stage_val, industry_val, opf_val)
         return (selected_product_val, description_val, product_name_val, benefits_val, key_message_val,
                 gender_val, generation_val, psychotype_val, business_stage_val, industry_val, opf_val,
-                chosen_approach_val, p1, p2)
+                chosen_approach_val, p1, p2, "", "", "")
 
     return_params_btn.click(
         fn=on_load_previous,
@@ -526,7 +519,8 @@ with gr.Blocks(theme="default") as demo:
         outputs=[product_dropdown, description, product_name, benefits, key_message,
                  gender_dropdown, generation_dropdown, psychotype_dropdown,
                  business_stage_dropdown, industry_dropdown, opf_dropdown,
-                 chosen_approach, prompt_1, prompt_2]
+                 chosen_approach, prompt_1, prompt_2,
+                 sms_1, sms_2, comment_sms_1, comment_sms_2, corrected_sms_1, corrected_sms_2]
     )
 
     demo.queue().launch()