app.py

import gradio as gr
from transformers import PreTrainedTokenizerFast, BartForConditionalGeneration

model_name = "ainize/kobart-news"
tokenizer = PreTrainedTokenizerFast.from_pretrained(model_name)
model = BartForConditionalGeneration.from_pretrained(model_name)

def summ(txt):
    input_ids = tokenizer.encode(txt, return_tensors="pt")
    summary_text_ids = model.generate(
        input_ids=input_ids,
        bos_token_id=model.config.bos_token_id, # BOS는 Beginning of Sentence
        eos_token_id=model.config.eos_token_id, # EOS는 End of Sentence
        length_penalty=2.0, # 요약을 얼마나 짧게 할지
        max_length=142, 
        min_length=56,
        num_beams=4, # beam search
    )
    return tokenizer.decode(summary_text_ids[0], skip_special_tokens=True)

interface = gr.Interface(summ, 
                        [gr.Textbox(label="original text")],
                        [gr.Textbox(label="summary")])

interface.launch()