import gradio as gr


from transformers import (
    AutoModelForSeq2SeqLM,
    AutoTokenizer,
    AutoConfig,
    pipeline,
)

model_name = "sagard21/python-code-explainer"

tokenizer = AutoTokenizer.from_pretrained(model_name, padding=True)

model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

config = AutoConfig.from_pretrained(model_name)

model.eval()

pipe = pipeline("summarization", model=model_name, config=config, tokenizer=tokenizer)

def generate_text(text_prompt):
  response = pipe(text_prompt)
  return response[0]['summary_text']

textbox = gr.Textbox()

demo = gr.Interface(generate_text, textbox, textbox)

if __name__ == "__main__":
    demo.launch(share = True)