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import torch
import gradio as gr
from transformers import pipeline
# Load summarization pipeline
model_id = "sshleifer/distilbart-cnn-12-3"
pipe = pipeline("summarization", model=model_id)
# Define summarization function
def summarize_text_gradio(input_text):
if not input_text or len(input_text.strip()) < 140:
return "⚠️ Please enter at least 140 characters to generate a summary."
summary = pipe(input_text)[0]['summary_text']
return summary
# Use Gradio Blocks for better layout control
with gr.Blocks(theme="default") as demo:
gr.Markdown("# 📝 Text Summarization Web App AI")
gr.Markdown(
"""
This WebPage allows you to summarizes long articles or texts using a pretrained transformer model.
Enter your text below (minimum 140 characters) and click **Submit** to generate a summary in 3 sec
"""
)
with gr.Row():
input_box = gr.Textbox(label="Input Text", lines=15, placeholder="Paste your long text here...")
with gr.Row():
output_box = gr.Textbox(label="🧾 Summary", lines=10)
summarize_button = gr.Button("🔍 Summarize")
summarize_button.click(fn=summarize_text_gradio, inputs=input_box, outputs=output_box)
# Footer with links at the bottom
gr.Markdown("---")
gr.Markdown(
"""
#### 👤 Created by Neeraj Sharma
📬 [LinkedIn](https://www.linkedin.com/in/neeraj-sharma-6017b854/) | 🛠️ [GitHub](https://github.com/MissNeerajSharma)
""",
elem_id="footer",
)
demo.launch()
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