Update app.py

app.py

@@ -1,6 +1,6 @@
 # app.py
 # =============
-# This is a complete app.py file for deploying the MTSAIR/Cotype-Nano model using Gradio and Hugging Face Transformers.
+# This is a complete app.py file for deploying the MTSAIR/Cotype-Nano model using Gradio and Hugging Face Transformers with chat and token streaming functionality.
 
 import gradio as gr
 from transformers import pipeline
@@ -13,23 +13,28 @@ pipe = pipeline("text-generation", model=model_name, device="cpu")
 system_prompt = {"role": "system", "content": "Ты — ИИ-помощник. Тебе дано задание: необходимо сгенерировать подробный и развернутый ответ."}
 
 # Define the Gradio interface
-def generate_response(user_input):
-    messages = [
-        system_prompt,
-        {"role": "user", "content": user_input}
-    ]
-    response = pipe(messages, max_length=1024)
-    return response[0]['generated_text']
+def generate_response(history, user_input):
+    messages = [system_prompt] + history + [{"role": "user", "content": user_input}]
+    response = pipe(messages, max_length=1024, return_full_text=False)
+    generated_text = response[0]['generated_text']
+    history.append({"role": "user", "content": user_input})
+    history.append({"role": "assistant", "content": generated_text})
+    return history, ""
 
 # Create the Gradio interface
-iface = gr.Interface(
-    fn=generate_response,
-    inputs=gr.Textbox(lines=2, placeholder="Введите ваш запрос здесь..."),
-    outputs="text",
-    title="Cotype-Nano Text Generation",
-    description="Введите ваш запрос, и Cotype-Nano сгенерирует ответ."
-)
+with gr.Blocks() as demo:
+    gr.Markdown("## Cotype-Nano Text Generation Chat")
+
+    chatbot = gr.Chatbot([], elem_id="chatbot")
+
+    with gr.Row():
+        txt = gr.Textbox(
+            show_label=False,
+            placeholder="Введите ваш запрос здесь...",
+        ).style(container=False)
+
+    txt.submit(generate_response, [chatbot, txt], [chatbot, txt])
 
 # Launch the interface
 if __name__ == "__main__":
-    iface.launch()
+    demo.launch()