app.py

import gradio as gr
from transformers import pipeline

# Load a ready-made keyword extraction / summarization model
extractor = pipeline("summarization", model="pszemraj/keyword-extraction-distilbart-cnn-12-6")

def extract_keywords(text):
    if not text.strip():
        return "⚠️ Please enter some text."
    try:
        result = extractor(text, max_length=64, min_length=5, do_sample=False)
        keywords = result[0]['summary_text']
        return f"🧠 **Extracted Keywords:**\n\n{keywords}"
    except Exception as e:
        return f"❌ Error: {str(e)}"

demo = gr.Interface(
    fn=extract_keywords,
    inputs=gr.Textbox(label="📝 Enter text here", lines=6, placeholder="Paste medical or general text..."),
    outputs=gr.Markdown(label="📊 Keywords"),
    title="🔍 Keyword Extractor (Hugging Face Model)",
    description="A lightweight keyword extraction tool using a fine-tuned DistilBART model.",
    theme="soft"
)

if __name__ == "__main__":
    demo.launch()