app.py

import gradio as gr
from transformers import pipeline

pipe = pipeline("text2text-generation", model="YoussefAnwar/mt5-summarize-ar-en")

gen_config = {
    'max_length': 128,
    'num_beams': 15,
    'length_penalty': 0.6,
    'no_repeat_ngram_size': 2
}

def summarize(text):
    summary = pipe(text, **gen_config)
    return summary[0]['generated_text']

interface = gr.Interface(
    fn=summarize,
    inputs=gr.Textbox(lines=10, placeholder="Enter text to summarize..."),
    outputs="text",
    title="Arabic-English Text Summarizer",
    description="Enter Arabic or English text, and the model will generate a summary."
)

interface.launch()