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()