app.py

import gradio as gr
from transformers import pipeline

# Load your summarization model
summarizer = pipeline("summarization", model="Curative/t5-summarizer-cnn")

# Define function for Gradio
def summarize_text(input_text):
    if not input_text.strip():
        return "Please enter some text to summarize."
    result = summarizer(input_text, max_length=150, min_length=40, do_sample=False)
    return result[0]['summary_text']

# Create Gradio interface
demo = gr.Interface(
    fn=summarize_text,
    inputs=gr.Textbox(lines=10, placeholder="Enter text to summarize..."),
    outputs="text",
    title="T5 Summarizer (CNN/DailyMail)",
    description="A fine-tuned T5 model for text summarization (based on cnn_dailymail v3.0.0)."
)

# Launch app
demo.launch()