import gradio as gr
from transformers import pipeline

# Load the summarization model (it will download automatically)
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

# Define a function that takes text and returns a summary
def summarize_text(text):
    if len(text.strip()) == 0:
        return "Please enter some text to summarize."
    # Summarize!
    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
    return summary[0]['summary_text']

# Create the Gradio interface
demo = gr.Interface(
    fn=summarize_text,
    inputs=gr.Textbox(
        placeholder="Enter text here to summarize...",
        lines=8,
        label="Input Text"
    ),
    outputs=gr.Textbox(label="Summary"),
    title="📝 AI Text Summarizer",
    description="Paste any article, email, or text and get a concise summary instantly!",
    theme="soft"
)

# Launch the app
demo.launch()