import gradio as gr
from gradio.mix import Parallel, Series

from transformers import pipeline

translater = pipeline("translation", model="VietAI/envit5-translation")


def translate(inp, direction):
    if direction == 'en->vi':
        text = "en: " + inp
    else:
        text = "vi: " + inp
        
    res = translater(
        text,
        max_length=512,
        early_stopping=True,
    )[0]['translation_text'][3:]
    return res

description = """
<p>
<center>
Multi-domain Translation Between English and Vietnamese
</center>
</p>
"""
article = "<p style='text-align: center'><a href='http://translate.vietai.org' target='_blank'>by VietAI Research</a> | <a href='https://github.com/vietai/mTet' target='_blank'>Github</a> | Contact: <a href='mailto:heraclex12@gmail.com' target='_blank'>Hieu Tran</a></p></center></p>"
examples = [
    ["Dear God, thank you for granting us the evergreen garden of this world", "en->vi"],
    ["Thuốc này đã bị cấm sử dụng trong ngành thú y tại Ấn Độ.", "vi->en"]
]
iface = gr.Interface(
    fn=translate,

    title="🌸MTet Translation🌸",
    description=description,
    article=article,
    examples=examples,
    inputs=[
        gr.inputs.Textbox(lines=5, placeholder="Enter text (maximum 5 lines)", label="Input"),
        gr.inputs.Radio(
            choices=[
                'en->vi',
                'vi->en'],
            default='en->vi',
            label='Direction'),
    ],
    outputs="text")

iface.launch(enable_queue=True)