app.py

import gradio as gr
from transformers import pipeline

# Load paraphrasing pipeline
paraphraser = pipeline("text2text-generation", model="Vamsi/T5_Paraphrase_Paws")

def paraphrase(text):
    result = paraphraser(text, max_length=100, num_return_sequences=1)
    return result[0]['generated_text']

# Gradio interface
demo = gr.Interface(
    fn=paraphrase,
    inputs=gr.Textbox(lines=4, placeholder="Enter text to paraphrase..."),
    outputs="text",
    title="Smooth Paraphraser",
    description="A simple app to smoothly paraphrase text using a pretrained T5 transformer model."
)

if __name__ == "__main__":
    demo.launch()