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import gradio as gr
from transformers import pipeline
import PyPDF2
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
def summarize_pdf(pdf_file):
if pdf_file is None:
return "❌ Please upload a PDF file first."
try:
reader = PyPDF2.PdfReader(pdf_file)
text = ""
for page in reader.pages:
text += page.extract_text() or ""
text = text[:2000] # limit to avoid too long input
summary = summarizer(text, max_length=150, min_length=30, do_sample=False)[0]['summary_text']
return summary
except Exception as e:
return f"❌ Error reading PDF: {str(e)}"
with gr.Blocks(css="""
body {background: #f0f4f8; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;}
#main_container { max-width: 720px; margin: auto; padding: 2rem; background: white;
box-shadow: 0 8px 24px rgba(149, 157, 165, 0.2); border-radius: 12px; }
.btn-primary {background: #3b82f6; color: white; font-weight: 600; padding: 0.8rem 1.6rem;
border-radius: 8px; border: none; transition: background 0.3s;}
.btn-primary:hover {background: #2563eb;}
.scroll-box {max-height: 220px; overflow-y: auto; padding: 1rem; border: 1px solid #ddd; border-radius: 8px; background: #fafafa;}
""") as demo:
with gr.Column(elem_id="main_container"):
gr.Markdown(
"""
<h1 style="text-align:center; color:#1e40af;">📄 PDF Summarizer</h1>
<p style="text-align:center; color:#475569;">
Upload your PDF and get a crisp summary generated by Hugging Face's BART model.
</p>
"""
)
pdf_input = gr.File(label="Upload PDF file", file_types=[".pdf"], interactive=True)
summary_output = gr.Textbox(label="Summary", interactive=False, elem_classes="scroll-box", lines=8)
summarize_btn = gr.Button("Generate Summary", elem_classes="btn-primary")
summarize_btn.click(fn=summarize_pdf, inputs=pdf_input, outputs=summary_output)
gr.Markdown(
"""
<footer style="text-align:center; margin-top:2rem; font-size:0.9rem; color:#94a3b8;">
Made with ❤️ by YourName | Powered by Hugging Face & Gradio
</footer>
"""
)
if __name__ == "__main__":
demo.launch()
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