Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Define the summarization function
+def summarize_text(input_text):
+    if not input_text.strip():
+        return "Please provide some text to summarize."
+    try:
+        summary = summarizer(input_text, max_length=130, min_length=30, do_sample=False)
+        return summary[0]["summary_text"]
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=summarize_text,
+    inputs=gr.Textbox(lines=5, label="Input Text"),
+    outputs=gr.Textbox(label="Summarized Text"),
+    title="Text Summarizer",
+    description="Summarize long articles or paragraphs using the `facebook/bart-large-cnn` model."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()