app.py

import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# تهيئة النموذج
model = AutoModelForSeq2SeqLM.from_pretrained("methodya/arabic-summarizer-philosophy")
tokenizer = AutoTokenizer.from_pretrained("methodya/arabic-summarizer-philosophy")

def summarize(text, max_length=150, num_beams=7, length_penalty=0.8):
    # تحويل القيم إلى النوع المناسب
    max_length = int(max_length)
    num_beams = int(num_beams)
    length_penalty = float(length_penalty)

    # تجهيز البيانات للنموذج
    inputs = tokenizer(text, return_tensors="pt", max_length=2048, truncation=True)
    
    outputs = model.generate(
        **inputs,
        max_length=max_length,
        num_beams=num_beams,
        length_penalty=length_penalty,
        early_stopping=True
    )
    
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

css = """
.gradio-container {background: #f9fafb !important}
.rtl-text {
    direction: rtl;
    text-align: right;
    font-family: Arial, sans-serif;
}
"""

interface = gr.Interface(
    fn=summarize,
    inputs=[
        gr.Textbox(lines=8, label="النص", elem_classes="rtl-text"),
        gr.Slider(50, 250, value=150, label="طول الملخص"),
        gr.Slider(1, 10, value=7, step=1, label="دقة التلخيص (num_beams)"),
        gr.Slider(0.1, 2.0, value=0.8, step=0.1, label="معامل الطول")
    ],
    outputs=gr.Textbox(label="الملخص", elem_classes="rtl-text"),
    title="ملخص النصوص الفلسفية",
    theme=gr.themes.Soft(),
    css=css
)

interface.launch()