app.py

import gradio as gr
from transformers import pipeline

# Load summarization pipeline
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

# Define function to summarize input text
def summarize_notes(text):
    if len(text.strip()) == 0:
        return "Please paste your academic notes."
    summary = summarizer(text, max_length=150, min_length=40, do_sample=False)
    return summary[0]['summary_text']

# Gradio interface
demo = gr.Interface(
    fn=summarize_notes,
    inputs=gr.Textbox(lines=15, placeholder="Paste your academic notes here...", label="Academic Notes"),
    outputs=gr.Textbox(label="Summarized Notes"),
    title="📚 Academic Note Summarizer",
    description="Paste your long academic notes and get a short summary using a Hugging Face Transformer model."
)

# Launch the app
demo.launch()