Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("ahmedabdo/arabic-summarizer-bart")
+model = AutoModelForSeq2SeqLM.from_pretrained("ahmedabdo/arabic-summarizer-bart")
+
+def summarize_text(text):
+    if not text.strip():
+        return "Please enter some text to summarize."
+    inputs = tokenizer(text, return_tensors="pt", max_length=1024, truncation=True)
+    summary_ids = model.generate(inputs["input_ids"], min_length=10, max_length=100, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+# Define the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# تلخيص النصوص باستخدام نموذج BART")
+    
+    with gr.Row():
+        input_text = gr.Textbox(label="أدخل النص", placeholder="ضع النص هنا", lines=10)
+    
+    summarize_button = gr.Button("أبدا التلخيص")
+    
+    output_text = gr.Textbox(label="تلخيص النص", interactive=False)
+    
+    summarize_button.click(summarize_text, inputs=input_text, outputs=output_text)
+
+# Launch the app
+demo.launch()