import gradio as gr

title = "FlauBERT"

description = "Gradio Demo for FlauBERT. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."

article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1912.05372' target='_blank'>FlauBERT: Unsupervised Language Model Pre-training for French</a></p>"

examples = [
    ["Paris est la <special1> de la France.","flaubert_small_cased"]
]


io1 = gr.Interface.load("huggingface/flaubert/flaubert_small_cased")

io2 = gr.Interface.load("huggingface/flaubert/flaubert_base_cased")

def inference(inputtext, model):
    if model == "flaubert_small_cased":
        outlabel = io1(inputtext)
    else:
        outlabel = io2(inputtext)
    return outlabel
     

gr.Interface(
    inference, 
    [gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["flaubert_small_cased","flaubert_base_cased"], type="value", default="flaubert_small_cased", label="model")], 
    [gr.outputs.Label(label="Output")],
    examples=examples,
    article=article,
    title=title,
    description=description).launch(enable_queue=True)