app.py

# Import necessary libraries
import gradio as gr
import numpy as np
from transformers_js_py import TransformersJS

# Design the chatbot architecture
class Gradio5Chatbot:
    def __init__(self):
        self.model = TransformersJS("t5-small")

    def generate_response(self, input_text):
        # Implement a retrieval-augmented generation (RAG) system for up-to-date Gradio 5 information
        # Design a modular structure for easy expansion and maintenance
        response = self.model.generate(input_text, async_=False)  # Set async_ to False
        return response

# Implement the core chatbot functionality
def chatbot(input_text):
    chatbot = Gradio5Chatbot()
    response = chatbot.generate_response(input_text)
    return response

# Create the Gradio 5 interface
demo = gr.Interface(
    fn=chatbot,
    inputs="text",
    outputs="text",
    title="Gradio 5 Chatbot",
    description="A chatbot designed to assist with Gradio 5 development."
)

# Launch the interface
demo.launch(show_error=True)