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app.py

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+from transformers import pipeline
+import gradio as gr
+
+# Initialize summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Function to summarize input
+def summarize_text(text):
+    if not text.strip():
+        return "⚠️ Please enter some text."
+    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
+    return summary
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=summarize_text,
+    inputs=gr.Textbox(lines=15, placeholder="Paste article, essay, or book paragraph here..."),
+    outputs="text",
+    title="📘 AI Text Summarizer",
+    description="Summarizes text using Hugging Face's facebook/bart-large-cnn model."
+)
+
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

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+transformers==4.40.1
+torch
+gradio==5.34.1