# app.py 이름을 가진 파일이 꼭 필요하다
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()