Update app.py

app.py

@@ -8,7 +8,7 @@ logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 # Загружаем модель
-model_name = "distilgpt2"
+model_name = "gpt2"  # Смена на базовую модель GPT-2
 try:
     logger.info(f"Попытка загрузки модели {model_name}...")
     generator = pipeline(
@@ -25,18 +25,11 @@ except Exception as e:
     logger.error(f"Ошибка загрузки модели: {e}")
     exit(1)
 
-def respond(message, history, max_tokens=256, temperature=0.7, top_p=0.9):
-    # История как список кортежей [(user_msg, bot_msg), ...]
-    history = history or []
-    input_text = ""
-    for user_msg, bot_msg in history:
-        input_text += f"User: {user_msg}\nAssistant: {bot_msg}\n"
-    input_text += f"User: {message}"
-
+def respond(message, max_tokens=256, temperature=0.7, top_p=0.9):
     try:
         logger.info(f"Генерация ответа для: {message}")
         outputs = generator(
-            input_text,
+            message,
             max_length=max_tokens,
             temperature=temperature,
             top_p=top_p,
@@ -44,72 +37,25 @@ def respond(message, history, max_tokens=256, temperature=0.7, top_p=0.9):
             no_repeat_ngram_size=2,
             num_return_sequences=1
         )
-        response = outputs[0]["generated_text"][len(input_text):].strip()
+        response = outputs[0]["generated_text"].strip()
         logger.info(f"Ответ сгенерирован: {response}")
     except Exception as e:
         logger.error(f"Ошибка генерации ответа: {e}")
-        return f"Ошибка генерации: {e}", history
-
-    formatted_response = format_response(response)
-    history.append((message, formatted_response))
-    return history
-
-def format_response(response):
-    diagnosis = extract_diagnosis(response)
-    operation = extract_operation(response)
-    treatment = extract_treatment(response)
-    return f"Предварительный диагноз: {diagnosis}\nОперация: {operation}\nЛечение: {treatment}"
-
-def extract_diagnosis(response):
-    sentences = response.split(".")
-    return sentences[0].strip() if sentences else response.strip()
-
-def extract_operation(response):
-    return "Не требуется"
-
-def extract_treatment(response):
-    sentences = response.split(".")
-    return sentences[-1].strip() if len(sentences) > 1 else "Не указано"
-
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## Медицинский чат-бот на базе DistilGPT-2")
-    chatbot = gr.Chatbot(label="Чат", height=400, type='messages')
-    with gr.Row():
-        msg = gr.Textbox(
-            label="Ваше сообщение",
-            placeholder="Опишите симптомы (например, 'Болит горло')...",
-            lines=2,
-            show_label=True
-        )
-        submit_btn = gr.Button("Отправить", variant="primary")
-    with gr.Row():
-        max_tokens = gr.Slider(minimum=50, maximum=512, value=256, step=10, label="Макс. токенов")
-        temperature = gr.Slider(minimum=0.1, maximum=1.5, value=0.7, label="Температура")
-        top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, label="Top-p")
-    clear_btn = gr.Button("Очистить чат", variant="secondary")
-
-    def submit_message(message, chat_history, max_tokens, temperature, top_p):
-        if not message.strip():
-            return chat_history, "Пожалуйста, введите сообщение."
-        updated_history = respond(message, chat_history, max_tokens, temperature, top_p)
-        return updated_history, ""
-
-    submit_btn.click(
-        fn=submit_message,
-        inputs=[msg, chatbot, max_tokens, temperature, top_p],
-        outputs=[chatbot, msg],
-        queue=True
-    )
-    msg.submit(
-        fn=submit_message,
-        inputs=[msg, chatbot, max_tokens, temperature, top_p],
-        outputs=[chatbot, msg],
-        queue=True
-    )
-    clear_btn.click(
-        fn=lambda: ([], ""),
-        outputs=[chatbot, msg]
-    )
+        return f"Ошибка генерации: {e}"
+    return response
+
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
+        gr.Textbox(label="Ваше сообщение", placeholder="Опишите симптомы (например, 'Болит горло')..."),
+        gr.Slider(minimum=50, maximum=512, value=256, step=10, label="Макс. токенов"),
+        gr.Slider(minimum=0.1, maximum=1.5, value=0.7, label="Температура"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.9, label="Top-p")
+    ],
+    outputs="text",
+    title="Медицинский чат-бот на базе GPT-2",
+    theme=gr.themes.Soft()
+)
 
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)