import gradio as gr
from transformers import pipeline

# Load a pre-trained conversational model from Hugging Face
chatbot_model = pipeline("text-generation", model="microsoft/DialoGPT-medium")

# Function to handle user input and return chatbot response
def chat_with_zomato(user_input):
    # Get the response from the chatbot model
    response = chatbot_model(user_input, max_length=100, num_return_sequences=1)[0]["generated_text"]
    return response[len(user_input):].strip()  # Remove the user input part from the response

# Gradio Interface for the chatbot
def launch_zomato_chatbot():
    # Define the Gradio interface
    chatbot_interface = gr.Interface(
        fn=chat_with_zomato,
        inputs=gr.Textbox(lines=2, placeholder="Ask Zomato..."),  # User input field
        outputs="text",  # Text output
        title="Zomato Chatbot",
        description="Ask Zomato anything about restaurants, food orders, or cuisine recommendations."
    )
    
    # Launch the interface
    chatbot_interface.launch()

# Call the function to launch the chatbot
if __name__ == "__main__":
    launch_zomato_chatbot()