app.py

from transformers import pipeline
import gradio as gr


corrector = pipeline(
              'text2text-generation',
              'pszemraj/flan-t5-large-grammar-synthesis',
              )

def correct(text):
    sentences = text.split(".")
    output = ""
    for sentence in sentences:
        sentence += "."
        output += corrector(sentence)[0]['generated_text']
    return output

iface = gr.Interface(
    fn= correct,
    inputs= "text",
    outputs= "text",
    title="Aeravat  Grammar Correction",
)

# Launch the Gradio interface
iface.launch(share=True)