import gradio as grad
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model_name = "Helsinki-NLP/opus-mt-en-grk"

model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
model_tkn = AutoTokenizer(model_name)

#opus_translation = pipeline("translation", model=model_name)

def translate(text):
    inputs = model_tkn(text, return_tensors="pt")
    trans_ouput = model.generate(**inputs) #"generate": This method includes the logic for autoregressive generation
    response = model_tkn.decode(trans_output[0], skip_special_tokens=True)
    #response = opus_translator(text)
    return response
txt = grad.Textbox(line=1, label="English", placeholder = "English text here")
txt_out = grad.Textbox(line=1, label= "Greek", placeholder = "Greek translation")
grad.Interface(translate, inputs=txt, output=txt_out, theme="dark").launch()