Create app.py

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+from transformers import pipeline
+
+summarizer_en = pipeline("summarization", model="facebook/bart-large-cnn")
+summarizer_ar = pipeline("translation", model="Helsinki-NLP/opus-mt-ar-en")
+translator_ar = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ar")
+
+def summarize_text(text, language):
+    if not text.strip():
+        return " الرجاء إدخال نص للتلخيص."
+    
+    if language == "العربية":
+
+        translated_text = summarizer_ar(text)[0]['translation_text']
+        summary = summarizer_en(translated_text, min_length=10, max_length=100, do_sample=False)
+
+        final_summary = translator_ar(summary[0]['summary_text'])[0]['translation_text']
+    else:
+        summary = summarizer_en(text, min_length=10, max_length=100, do_sample=False)
+        final_summary = summary[0]['summary_text']
+    
+    return final_summary
+
+# Gradio
+with gr.Blocks() as demo:
+    gr.Markdown("# Text Summarization App")
+    gr.Markdown("Enter a long text below, choose the language, and get a summarized version!")
+    
+    input_text = gr.Textbox(label="Input Text", placeholder="Enter your text here ^^ ...")
+    language = gr.Dropdown(choices=["العربية", "English"], value="English", label="Select Language")
+    summarize_btn = gr.Button("Summarize")
+    output_text = gr.Textbox(label="Summarized Text", interactive=False)
+    
+    summarize_btn.click(summarize_text, inputs=[input_text, language], outputs=output_text)
+
+if __name__ == "__main__":
+    demo.launch()