app.py

import gradio as gr
from transformers import pipeline

# Load Hugging Face's conversational model (DialoGPT in this case)
generator = pipeline("conversational", model="microsoft/DialoGPT-medium")

# Define a function that will interact with the model
def chatbot_response(user_input, chat_history):
    # Create response by sending the user input and previous history to the model
    response = generator(user_input, pad_token_id=50256)
    chat_history.append((user_input, response[0]['generated_text']))
    
    # Return the updated chat history for displaying the conversation
    return chat_history, chat_history

# Gradio interface setup
def create_gradio_interface():
    # Create a chat-based interface using Gradio
    interface = gr.Interface(
        fn=chatbot_response,
        inputs=[gr.Textbox(label="Ask about food customization...", placeholder="Type your message...", lines=1), 
                gr.State()],
        outputs=[gr.Chatbot(), gr.State()],
        title="Food Customization Assistant",
        description="Talk to the bot and customize your food preferences. Ask about recipes, categories, or ingredients.",
        theme="compact"  # Custom theme
    )
    
    return interface

if __name__ == "__main__":
    interface = create_gradio_interface()
    interface.launch()