Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import torch
+
+# Load summarization models
+english_summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+arabic_summarizer = pipeline("summarization", model="google/mt5-small")
+
+def summarize_text(text, language):
+    if language == 'English':
+        summary = english_summarizer(text, max_length=130, min_length=30, do_sample=False)
+        return summary[0]['summary_text']
+    elif language == 'Arabic':
+        summary = arabic_summarizer(text, max_length=130, min_length=30, do_sample=False)
+        return summary[0]['summary_text']
+    else:
+        return "Unsupported Language"
+
+with gr.Blocks() as app:
+    gr.Markdown("<h1 style='text-align: center;'>Text Summarization App</h1>")
+    
+    with gr.Row():
+        with gr.Column():
+            english_input = gr.Textbox(label="Enter English Text", placeholder="Type or paste your English text here...", lines=10)
+            english_button = gr.Button("Summarize English")
+            english_output = gr.Textbox(label="English Summary", interactive=False)
+
+        with gr.Column():
+            arabic_input = gr.Textbox(label="ادخل نص عربي", placeholder="اكتب أو الصق نصك العربي هنا...", lines=10)
+            arabic_button = gr.Button("تلخيص عربي")
+            arabic_output = gr.Textbox(label="ملخص عربي", interactive=False)
+
+    english_button.click(summarize_text, inputs=[english_input, 'English'], outputs=english_output)
+    arabic_button.click(summarize_text, inputs=[arabic_input, 'Arabic'], outputs=arabic_output)
+
+# Launch the interface
+if __name__ == "__main__":
+    app.launch()