Create app.py

app.py

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+import gradio as gr
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+import torch
+
+# تحميل الموديل من الهاغينغ فيس
+model_name = "USERNAME/t5-title-generator-ar"  # بدّلك USERNAME باسم حسابك
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = model.to(device)
+
+def generate_title(abstract):
+    inputs = tokenizer(
+        "summarize: " + abstract,
+        return_tensors="pt",
+        max_length=256,
+        truncation=True
+    ).to(device)
+    
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=32,
+        num_beams=5,
+        num_return_sequences=3,
+        early_stopping=True,
+        no_repeat_ngram_size=2
+    )
+    titles = [tokenizer.decode(out, skip_special_tokens=True) for out in outputs]
+    return "\n".join([f"{i+1}. {title}" for i, title in enumerate(titles)])
+
+iface = gr.Interface(
+    fn=generate_title,
+    inputs=gr.Textbox(label="الملخص"),
+    outputs=gr.Textbox(label="العناوين المولّدة"),
+    title="مولد عناوين للأبحاث 🧠📄",
+    description="أدخل ملخص بحث وسنولد لك 3 عناوين محتملة باستخدام T5"
+)
+
+iface.launch(share=True, show_error=True)