import gradio as gr

from transformers import PreTrainedTokenizerFast, BartForConditionalGeneration
# from transformers import로 시작하는 import 문을 보면
# 많은 경우 AutoTokenizer, AutoModel
# tokenizer = AutoTokenizer.from_pretrained("model 이름 어쩌고 저쩌고")
# PreTrainedTokenizerFast : https://huggingface.co./docs/transformers/main_classes/tokenizer
# BART는 encoder-decoder 모델의 예시

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

# 원문을 받아서 요약문을 반환
def summ(txt):
  input_ids = tokenizer.encode(input_text, return_tensors="pt")
  summary_text_ids = model.generate(
    input_ids=input_ids,
    bos_token_id=model.config.bos_token_id,
    eos_token_id=model.config.eos_token_id,
    length_penalty=2.0,
    max_length=142,
    min_length=56,
    num_beams=4)
  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(share=True)