import gradio as gr
from xlit_src import XlitEngine


def transliterate(input_text):
    engine = XlitEngine()
    result = engine.translit_sentence(input_text)
    return result


input_box = gr.inputs.Textbox(type="str", label="Input Text")
target = gr.outputs.Textbox()

iface = gr.Interface(
    transliterate,
    input_box,
    target,
    title="English to Hindi Transliteration",
    description='Model for Translating English to Hindi using a Character-level recurrent sequence-to-sequence trained with <a href="http://workshop.colips.org/news2018/dataset.html">NEWS2018 DATASET_04</a>',
    article='Author: <a href="https://huggingface.co/anuragshas">Anurag Singh</a> . Using training and inference script from <a href="https://github.com/AI4Bharat/IndianNLP-Transliteration.git">AI4Bharat/IndianNLP-Transliteration</a>.',
    examples=["Hi.", "Wait!", "Namaste"],
)

iface.launch(enable_queue=True)