import gradio as gr

from transformers import AutoTokenizer
from transformers import AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Oysiyl/elvish-translator-quenya-t5-small")
model = AutoModelForSeq2SeqLM.from_pretrained("Oysiyl/elvish-translator-quenya-t5-small")

prefix = "translate English to Elvish: "

def greet(name):
    inputs = tokenizer(prefix + text, return_tensors="pt").input_ids
    outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95)
    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return result

demo = gr.Interface(title="English to Elvish translation!", 
    description="<p style='text-align: center'>Provide English text and let's model try to guess the text in Elvish!</p>", 
    article = "<p style='text-align: center'>Text Translation English -> Elvish | Demo Model</p>",fn=greet, inputs="text", outputs="text")
demo.launch()