import gradio as gr

title = "Tagalog RoBERTa"

description = "<p style='text-align: center'>Tagalog Gradio Demo for RoBERTa. To use it, simply add your text, or click one of the examples to load them.</p>"

article = "<p style='text-align: center'>Improving Large-scale Language Models and Resources for Filipino,Jan Christian Blaise Cruz and Charibeth Cheng,arXiv preprint arXiv:2111.06053,2021</p>"

examples = [
    ['Makulay ang <mask> na suot ni Roberta.','roberta-tagalog-base'],
    ['Nakakasilaw ang sikat ng <mask>.', 'roberta-tagalog-large'],
    ['Malakas ang buhos ng <mask>.', 'roberta-tagalog-large' ]
]


i1 = gr.Interface.load("huggingface/jcblaise/roberta-tagalog-base")

i2 = gr.Interface.load("huggingface/jcblaise/roberta-tagalog-large")


def inference(inputtext, model):
    if model == "roberta-tagalog-base":
        outlabel = i1(inputtext)
    if model == "roberta-tagalog-large":
        outlabel = i2(inputtext)
    return outlabel
     

gr.Interface(
    inference, 
    [gr.inputs.Textbox(label="Input text",lines=10),gr.inputs.Dropdown(choices=["roberta-tagalog-base","roberta-tagalog-large"], type="value", default="roberta-tagalog-base", label="model")], 
    [gr.outputs.Label(label="Output")],
    examples=examples,
    article=article,
    title=title,
    description=description).launch(enable_queue=False)