app.py

import gradio as gr
from transformers import pipeline

# Load the summarization pipeline
pipe = pipeline("summarization", model="yashugupta786/bart_large_xsum_samsum_conv_summarizer")

# Summarization function
def summarize(text):
    summary = pipe(text)
    return summary[0]['summary_text']

# Gradio interface
with gr.Blocks() as demo:
    gr.Interface(
        fn=summarize,
        inputs=gr.Textbox(label="Input Text", placeholder="Enter text to summarize..."),
        outputs=gr.Textbox(label="Summary"),
        title="Text Summarization",
        description="Summarize the input text using BART model."
    ).launch(share=True)