Update app.py

app.py

@@ -1,33 +1,32 @@
+import os
+os.system("pip install transformers torch accelerate gradio")  # Install dependencies
+
 import gradio as gr
 from transformers import pipeline
 
-# Load a Hugging Face model for chat (choose an appropriate model)
+# Load the Hugging Face model
 chatbot_pipeline = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct", max_new_tokens=100)
 
-# Chatbot function using HF's transformer model
+# Chatbot function
 def chat_response(history, user_input):
-    """Handles chatbot interactions using a Hugging Face model."""
     if not user_input.strip():
         return history + [{"role": "user", "content": user_input}, {"role": "assistant", "content": "Please enter a valid message."}], ""
 
-    # Generate AI response
     bot_reply = chatbot_pipeline(user_input)[0]["generated_text"]
 
-    # Append messages to history
     history.append({"role": "user", "content": user_input})
     history.append({"role": "assistant", "content": bot_reply})
 
     return history, ""
 
-# Initialize Gradio chatbot
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## 🤖 AI Bandar - Powered by Hugging Face")
 
-    chatbot = gr.Chatbot(type="messages")  # Correct type
+    chatbot = gr.Chatbot(type="messages")
     user_input = gr.Textbox(label="Your Message")
     submit_button = gr.Button("Send")
 
-    # Button click or Enter key submits the message
     submit_button.click(chat_response, inputs=[chatbot, user_input], outputs=[chatbot, user_input])
     user_input.submit(chat_response, inputs=[chatbot, user_input], outputs=[chatbot, user_input])