Create app.py

app.py

@@ -0,0 +1,50 @@
+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()