app.py

import gradio as gr
import logging
import sys
from transformers import pipeline

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

# Load the model
logger.info("Loading bart-large-cnn model...")
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
logger.info("Model loaded successfully!")

def summarize_text(text, max_length=150, min_length=30):
    if not text or len(text.strip()) < 50:
        return text
        
    logger.info(f"Summarizing text of length {len(text)}")
    result = summarizer(
        text, 
        max_length=max_length, 
        min_length=min_length,
        truncation=True
    )
    summary = result[0]["summary_text"]
    return summary

# Create Gradio interface
demo = gr.Interface(
    fn=summarize_text,
    inputs=[
        gr.Textbox(lines=10, label="Text to Summarize"),
        gr.Slider(50, 500, value=150, label="Max Length"),
        gr.Slider(10, 200, value=30, label="Min Length")
    ],
    outputs=gr.Textbox(label="Summary"),
    title="StudAI ",
    description="Powered by facebook/bart-large-cnn model"
)

demo.launch(share=True, server_name="Leo", server_port=8000)