Update app.py

app.py

@@ -1,14 +1,13 @@
 import gradio as gr
 from transformers import pipeline
 from langdetect import detect
-import os
 
-# Use a free Hugging Face model (you can change this to a better one later)
+# Load models
 generator = pipeline("text-generation", model="gpt2")
 bg_to_en = pipeline("translation", model="Helsinki-NLP/opus-mt-bg-en")
 en_to_bg = pipeline("translation", model="Helsinki-NLP/opus-mt-en-bg")
 
-NUM_THREADS = 2  # Adjust as needed
+NUM_THREADS = 2
 
 def generate_response(user_input, top_p, temperature, chat_counter, chatbot, history, request: gr.Request):
     lang = detect(user_input)
@@ -39,6 +38,26 @@ def generate_response(user_input, top_p, temperature, chat_counter, chatbot, his
 def reset_textbox():
     return gr.update(value='', interactive=False), gr.update(interactive=False)
 
-demo.queue(max_size=10).launch()
+with gr.Blocks(theme=gr.themes.Default()) as demo:
+    gr.Markdown("""
+    # 🛍️ MasterBrand AI Assistant  
+    Ask me anything about your e-commerce store – in English or Bulgarian.
+    """)
+    
+    chatbot = gr.Chatbot()
+    inputs = gr.Textbox(placeholder="What product should I sell?", label="Your question")
+    state = gr.State([])
+    chat_counter = gr.Number(value=0, visible=False)
+    top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-p (creativity)")
+    temperature = gr.Slider(minimum=0.1, maximum=2.0, value=1.0, step=0.1, label="Temperature")
+
+    with gr.Row():
+        submit_btn = gr.Button("🚀 Ask")
+        status_box = gr.Textbox(label="Status", interactive=False)
+
+    inputs.submit(reset_textbox, [], [inputs, submit_btn], queue=False)
+    inputs.submit(generate_response, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, status_box, inputs, submit_btn])
+    submit_btn.click(reset_textbox, [], [inputs, submit_btn], queue=False)
+    submit_btn.click(generate_response, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, status_box, inputs, submit_btn])
 
-    
+demo.queue(max_size=10).launch()