Update app.py

app.py

@@ -12,6 +12,7 @@ from together import Together
 import pymorphy2
 import re
 import string
+import io
 
 morph = pymorphy2.MorphAnalyzer()
 
@@ -109,6 +110,70 @@ def save_user_request_to_github(description, advantages, key_message, approach,
     else:
         print(f"Ошибка при сохранении данных на GitHub: {response.status_code} {response.text}")
 
+
+def save_message_to_table(data):
+    # data is a dictionary containing the message and personalization parameters
+    
+    repo = "fruitpicker01/Storage_dev"
+    file_path = "messages.csv"  # Use 'messages.xlsx' if you prefer Excel
+    
+    # Get the file from the repository
+    url = f"https://api.github.com/repos/{repo}/contents/{file_path}"
+    headers = {
+        "Authorization": f"token {token}",
+        "Content-Type": "application/json"
+    }
+    
+    response = requests.get(url, headers=headers)
+    
+    if response.status_code == 200:
+        # File exists, download and load it
+        content = response.json()
+        file_content = base64.b64decode(content['content'])
+        if file_path.endswith('.xlsx'):
+            df = pd.read_excel(io.BytesIO(file_content))
+        else:
+            df = pd.read_csv(io.StringIO(file_content.decode('utf-8')))
+        sha = content['sha']  # For updating the file later
+    elif response.status_code == 404:
+        # File does not exist, create an empty DataFrame
+        df = pd.DataFrame(columns=[
+            "Timestamp", "Персонализированное сообщение", "Откорректированное сообщение",
+            "Пол", "Поколение", "Психотип", "Стадия бизнеса", "Отрасль", "ОПФ"
+        ])
+        sha = None  # No sha since the file doesn't exist yet
+    else:
+        print(f"Error accessing the file: {response.status_code}")
+        return
+    
+    # Append the new data
+    df = df.append(data, ignore_index=True)
+    
+    # Convert the DataFrame back to a file
+    if file_path.endswith('.xlsx'):
+        with io.BytesIO() as output:
+            df.to_excel(output, index=False)
+            file_content_encoded = base64.b64encode(output.getvalue()).decode('utf-8')
+    else:
+        csv_string = df.to_csv(index=False)
+        file_content_encoded = base64.b64encode(csv_string.encode('utf-8')).decode('utf-8')
+    
+    # Prepare the data for the API request
+    data = {
+        "message": "Update messages file",
+        "content": file_content_encoded,
+        "sha": sha  # Include the sha if the file exists
+    }
+    
+    # Send the PUT request to update the file
+    response = requests.put(url, headers=headers, data=json.dumps(data))
+    
+    if response.status_code in [200, 201]:
+        print("Messages file updated successfully.")
+    else:
+        print(f"Error updating messages file: {response.status_code}")
+
+
 def load_previous_user_request_from_github():
     global current_request_index  # Используем глобальную переменную
 
@@ -160,6 +225,129 @@ def load_previous_user_request_from_github():
         return "", "", "", "", "", "", "", "", "", "", None, None, None, None, None, None
 
 
+def get_reference_message(gender, generation, psychotype, business_stage, industry, legal_form):
+    # Import io if not already done
+    import io
+    
+    # Define the repository and file path
+    repo = "fruitpicker01/Storage_dev"
+    file_path = "messages.csv"  # Or 'messages.xlsx' if you prefer Excel
+    
+    # Get the file from the repository
+    url = f"https://api.github.com/repos/{repo}/contents/{file_path}"
+    headers = {
+        "Authorization": f"token {token}",
+        "Content-Type": "application/json"
+    }
+    
+    response = requests.get(url, headers=headers)
+    
+    if response.status_code == 200:
+        # File exists, download and load it
+        content = response.json()
+        file_content = base64.b64decode(content['content'])
+        if file_path.endswith('.xlsx'):
+            df = pd.read_excel(io.BytesIO(file_content))
+        else:
+            df = pd.read_csv(io.StringIO(file_content.decode('utf-8')))
+    else:
+        # File does not exist or error
+        print(f"Error accessing the file: {response.status_code}")
+        return None
+    
+    # Filter the DataFrame based on the personalization parameters
+    filter_condition = (
+        (df["Пол"] == gender) &
+        (df["Поколение"] == generation) &
+        (df["Психотип"] == psychotype) &
+        (df["Стадия бизнеса"] == business_stage) &
+        (df["Отрасль"] == industry) &
+        (df["ОПФ"] == legal_form)
+    )
+    
+    filtered_df = df[filter_condition]
+    
+    if filtered_df.empty:
+        # No previous messages with these parameters
+        return None
+    
+    # Sort the filtered DataFrame by timestamp in descending order
+    filtered_df = filtered_df.sort_values(by="Timestamp", ascending=False)
+    
+    # Get the latest message
+    latest_row = filtered_df.iloc[0]
+    
+    # Get the "Откорректированное сообщение" if it exists, else "Персонализированное сообщение"
+    if pd.notnull(latest_row["Откорректированное сообщение"]) and latest_row["Откорректированное сообщение"].strip():
+        reference_message = latest_row["Откорректированное сообщение"]
+    else:
+        reference_message = latest_row["Персонализированное сообщение"]
+    
+    return reference_message
+
+def adapt_messages_to_best_example(
+    personalized_gigachat_pro,
+    personalized_gigachat_lite,
+    personalized_gigachat_plus,
+    personalized_gpt4o,
+    personalized_meta_llama_405b,
+    key_message,
+    approach,
+    *selected_values
+):
+    # Extract personalization parameters
+    gender = selected_values[0]
+    generation = selected_values[1]
+    psychotype = selected_values[2]
+    business_stage = selected_values[3]
+    industry = selected_values[4]
+    legal_form = selected_values[5]
+    
+    # Retrieve the reference message
+    reference_message = get_reference_message(gender, generation, psychotype, business_stage, industry, legal_form)
+    
+    if not reference_message:
+        # No reference message found
+        adapted_messages = ["Эталонное сообщение не найдено для выбранных параметров персонализации."] * 5
+        return adapted_messages
+    else:
+        # Construct the prompt template
+        prompt_template = (
+            f"Есть эталонное сообщение: \"{reference_message}\". "
+            "Эталонное сообщение используется исключительно для адаптации стиля текста, а не для изменения его смысла. "
+            "Пожалуйста, следуй этой инструкции и сохраняй основной смысл исходного текста, адаптируя его под стилистику эталонного сообщения: \"{personalized_message}\"."
+        )
+        
+        # Adapt each message
+        adapted_messages = []
+        # For GigaChat-Pro
+        prompt = prompt_template.format(personalized_message=personalized_gigachat_pro)
+        adapted_gigachat_pro = generate_message_gigachat_pro_with_retry(prompt)
+        adapted_messages.append(adapted_gigachat_pro)
+        
+        # For GigaChat-Lite
+        prompt = prompt_template.format(personalized_message=personalized_gigachat_lite)
+        adapted_gigachat_lite = generate_message_gigachat_lite_with_retry(prompt)
+        adapted_messages.append(adapted_gigachat_lite)
+        
+        # For GigaChat-Plus
+        prompt = prompt_template.format(personalized_message=personalized_gigachat_plus)
+        adapted_gigachat_plus = generate_message_gigachat_plus_with_retry(prompt)
+        adapted_messages.append(adapted_gigachat_plus)
+        
+        # For GPT-4o
+        prompt = prompt_template.format(personalized_message=personalized_gpt4o)
+        adapted_gpt4o = generate_message_gpt4o_with_retry(prompt)
+        adapted_messages.append(adapted_gpt4o)
+        
+        # For Meta-Llama-3.1-405B
+        prompt = prompt_template.format(personalized_message=personalized_meta_llama_405b)
+        adapted_meta_llama_405b = generate_message_meta_llama_3_1_405b_with_retry(prompt)
+        adapted_messages.append(adapted_meta_llama_405b)
+        
+        return adapted_messages
+
+
 # Функция для генерации стандартного промпта
 def generate_standard_prompt(description, advantages, key_message, approach, *selected_values):
 
@@ -564,20 +752,21 @@ def generate_error_check_prompt():
     return prompt
 
 
-def save_to_github(personalized_message, model_name, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach):
+def save_to_github(adapted_message, personalized_message, model_name, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach):
     # Собираем все данные в один словарь
     data_to_save = {
         "Модель": model_name,
+        "Адаптированное сообщение": adapted_message,
         "Персонализированное сообщение": personalized_message,
         "Комментарий": comment,
         "Откорректированное сообщение": corrected_message,
         "Описание предложения": description,
         "Преимущества": advantages,
-        "Ключевое сообщение": key_message,  # Save key message
-        "Подход": approach,  # Save approach
+        "Ключевое сообщение": key_message,
+        "Подход": approach,
         "Неперсонализированный промпт": non_personalized_prompt,
         "Неперсонализированное сообщение": non_personalized_message,
-        "Персонализированный промпт": personalization_prompt,  # Добавляем персонализированный промпт
+        "Персонализированный промпт": personalization_prompt,
         "Пол": gender,
         "Поколение": generation,
         "Психотип": psychotype,
@@ -604,6 +793,10 @@ def save_to_github(personalized_message, model_name, comment, corrected_message,
 
     # Отправка POST-запроса на GitHub API для создания файла в репозитории
     response = requests.put(url, headers=headers, data=json.dumps(data))
+    if response.status_code == 201:
+        print("Данные успешно сохранены на GitHub")
+    else:
+        print(f"Ошибка при сохранении данных на GitHub: {response.status_code} {response.text}")
 
 
 def personalize_and_save( 
@@ -1685,16 +1878,6 @@ with gr.Blocks() as demo:
         )
 
     
-#    analyze_btn = gr.Button("Выполнить анализ персонализации (экспериментальная фича)")
-
-#    with gr.Row():
-#        analysis_gigachat_pro = gr.Textbox(label="Анализ персонализации сообщения 1", lines=4, interactive=False)
-#        analysis_gigachat_lite = gr.Textbox(label="Анализ персонализации сообщения 2", lines=4, interactive=False)
-#        analysis_gigachat_plus = gr.Textbox(label="Анализ персонализации сообщения 3", lines=4, interactive=False)
-#        analysis_gpt4o = gr.Textbox(label="Анализ персонализации сообщения 4", lines=4, interactive=False)
-#        analysis_meta_llama_405b = gr.Textbox(label="Анализ персонализации сообщения 5", lines=4, interactive=False)
-
-
     # Добавление функционала для кнопок
     submit_btn.click(
         clear_fields,
@@ -1787,7 +1970,26 @@ with gr.Blocks() as demo:
         ]
     )
 
-    
+    best_example_btn.click(
+        fn=adapt_messages_to_best_example,
+        inputs=[
+            personalized_output_text_gigachat_pro,
+            personalized_output_text_gigachat_lite,
+            personalized_output_text_gigachat_plus,
+            personalized_output_text_gpt4o,
+            personalized_output_text_meta_llama_405b,
+            key_message_input,
+            approach_input,
+        ] + selections,
+        outputs=[
+            adapted_output_text_gigachat_pro,
+            adapted_output_text_gigachat_lite,
+            adapted_output_text_gigachat_plus,
+            adapted_output_text_gpt4o,
+            adapted_output_text_meta_llama_405b,
+        ]
+    )
+
     # Обработка клика по кнопке восстановления
     load_btn.click(
         fn=lambda: load_previous_user_request_from_github(),
@@ -1950,9 +2152,14 @@ with gr.Blocks() as demo:
         inputs=[],
         outputs=[save_gigachat_pro_btn]
     ).then(
-        fn=lambda personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach:
-            save_to_github(personalized_message, "GigaChat-Pro", comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach),
+        fn=lambda adapted_message, personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt,
+            non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form,
+            key_message, approach:
+            save_to_github(adapted_message, personalized_message, "GigaChat-Pro", comment, corrected_message, description, advantages,
+                           non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype,
+                           business_stage, industry, legal_form, key_message, approach),
         inputs=[
+            adapted_output_text_gigachat_pro,
             personalized_output_text_gigachat_pro,
             comment_gigachat_pro,
             corrected_gigachat_pro,
@@ -1978,6 +2185,7 @@ with gr.Blocks() as demo:
         fn=reset_button_text,
         outputs=[save_gigachat_pro_btn]
     )
+
     
     # Повторяем аналогично для других кнопок:
     save_gigachat_lite_btn.click(
@@ -1985,9 +2193,14 @@ with gr.Blocks() as demo:
         inputs=[],
         outputs=[save_gigachat_lite_btn]
     ).then(
-        fn=lambda personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach:
-            save_to_github(personalized_message, "GigaChat-Lite", comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach),
+        fn=lambda adapted_message, personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt,
+            non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form,
+            key_message, approach:
+            save_to_github(adapted_message, personalized_message, "GigaChat-Lite", comment, corrected_message, description, advantages,
+                           non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype,
+                           business_stage, industry, legal_form, key_message, approach),
         inputs=[
+            adapted_output_text_gigachat_lite,
             personalized_output_text_gigachat_lite,
             comment_gigachat_lite,
             corrected_gigachat_lite,
@@ -2020,9 +2233,14 @@ with gr.Blocks() as demo:
         inputs=[],
         outputs=[save_gigachat_plus_btn]
     ).then(
-        fn=lambda personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach:
-            save_to_github(personalized_message, "GigaChat-Lite+", comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach),
+        fn=lambda adapted_message, personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt,
+            non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form,
+            key_message, approach:
+            save_to_github(adapted_message, personalized_message, "GigaChat-Lite+", comment, corrected_message, description, advantages,
+                           non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype,
+                           business_stage, industry, legal_form, key_message, approach),
         inputs=[
+            adapted_output_text_gigachat_plus,
             personalized_output_text_gigachat_plus,
             comment_gigachat_plus,
             corrected_gigachat_plus,
@@ -2049,14 +2267,20 @@ with gr.Blocks() as demo:
         outputs=[save_gigachat_plus_btn]
     )
 
+
     save_gpt4o_btn.click(
-        fn=prepare_button_text,  # Сначала меняем текст на "Сохраняется..."
+        fn=prepare_button_text,
         inputs=[],
         outputs=[save_gpt4o_btn]
     ).then(
-        fn=lambda personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach: 
-            save_to_github(personalized_message, "GPT-4o", comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach),
+        fn=lambda adapted_message, personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt,
+            non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form,
+            key_message, approach:
+            save_to_github(adapted_message, personalized_message, "GPT-4o", comment, corrected_message, description, advantages,
+                           non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype,
+                           business_stage, industry, legal_form, key_message, approach),
         inputs=[
+            adapted_output_text_gpt4o,
             personalized_output_text_gpt4o,
             comment_gpt4o,
             corrected_gpt4o,
@@ -2076,21 +2300,27 @@ with gr.Blocks() as demo:
         ],
         outputs=None
     ).then(
-        fn=update_button_text,  # Обновляем текст на "Сохранено!" после сохранения
+        fn=update_button_text,
         outputs=[save_gpt4o_btn]
     ).then(
-        fn=reset_button_text,  # Возвращаем текст на кнопке обратно через 3 секунды
+        fn=reset_button_text,
         outputs=[save_gpt4o_btn]
     )
+
     
     save_meta_llama_405b_btn.click(
         fn=prepare_button_text,
         inputs=[],
         outputs=[save_meta_llama_405b_btn]
     ).then(
-        fn=lambda personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach:
-            save_to_github(personalized_message, "Meta-Llama-3.1-405B", comment, corrected_message, description, advantages, non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form, key_message, approach),
+        fn=lambda adapted_message, personalized_message, comment, corrected_message, description, advantages, non_personalized_prompt,
+            non_personalized_message, personalization_prompt, gender, generation, psychotype, business_stage, industry, legal_form,
+            key_message, approach:
+            save_to_github(adapted_message, personalized_message, "Meta-Llama-3.1-405B", comment, corrected_message, description, advantages,
+                           non_personalized_prompt, non_personalized_message, personalization_prompt, gender, generation, psychotype,
+                           business_stage, industry, legal_form, key_message, approach),
         inputs=[
+            adapted_output_text_meta_llama_405b,
             personalized_output_text_meta_llama_405b,
             comment_meta_llama_405b,
             corrected_meta_llama_405b,
@@ -2117,25 +2347,5 @@ with gr.Blocks() as demo:
         outputs=[save_meta_llama_405b_btn]
     )
 
-    # Обработчик нажатия кнопки
-#    analyze_btn.click(
-#        fn=perform_analysis_with_yield,
-#        inputs=[
-#            output_text_gigachat_pro, 
-#            output_text_gigachat_lite, 
-#            output_text_gigachat_plus,
-#            output_text_gpt4o,
-#            output_text_meta_llama_405b,
-#            personalization_prompt
-#        ],
-#        outputs=[
-#            analysis_gigachat_pro,
-#            analysis_gigachat_lite,
-#            analysis_gigachat_plus,
-#            analysis_gpt4o,
-#            analysis_meta_llama_405b
-#        ]
-#    )
-
 
     demo.launch()