import gradio as gr

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("liamvbetts/bart-large-cnn-v4")
model = AutoModelForSeq2SeqLM.from_pretrained("liamvbetts/bart-large-cnn-v4")

def summarize(article):
    inputs = tokenizer(article, return_tensors="pt").input_ids
    outputs = model.generate(inputs, max_new_tokens=128, do_sample=False)
    summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return summary

# Create Gradio interface
input_text = gr.Textbox(lines=10, label="Input Text")
output_text = gr.Textbox(label="Summary")

gr.Interface(
    fn=summarize,
    inputs=input_text,
    outputs=output_text,
    title="News Summary App",
    description="Enter a news text and get its summary."
).launch()