import gradio as gr
from transformers import pipeline

# Load the new summarization model
summarizer = pipeline("summarization", model="falconsai/text_summarization")

def summarize_text(text):
    max_len = min(0.3 * len(text.split()), 200)  # 30% of input length or 200 max
    min_len = min(0.1 * len(text.split()), 50)   # 10% of input length or 50 min
    
    summary = summarizer(text, max_length=int(max_len), min_length=int(min_len), do_sample=False)
    return summary[0]['summary_text']

# Create Gradio Interface
iface = gr.Interface(
    fn=summarize_text,
    inputs=gr.Textbox(lines=5, placeholder="Enter text to summarize"),
    outputs="text",
    title="AI Summarizer",
    description="Enter a long paragraph, and the AI will summarize it for you.",
)

# Launch the app
if __name__ == "__main__":
    iface.launch()