import gradio as gr

title = "ProphetNet"

description = "Gradio Demo for ProphetNet. 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/2001.04063' target='_blank'>ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training</a></p>"

examples = [
    ["Paris is the capital of France","prophetnet-large-uncased"]
]

io1 = gr.Interface.load("huggingface/microsoft/prophetnet-large-uncased")

io2 = gr.Interface.load("huggingface/microsoft/prophetnet-large-uncased-squad-qg")

io3 = gr.Interface.load("huggingface/microsoft/prophetnet-large-uncased-cnndm")



def inference(text, model):
    if model == "prophetnet-large-uncased":
        outtext = io1(text)
    elif model == "prophetnet-large-uncased-squad-qg":
        outtext = io2(text)
    else:
        outtext = io3(text)
    return outtext   
    
gr.Interface(
    inference, 
    [gr.inputs.Textbox(label="Input", lines=10),gr.inputs.Dropdown(choices=["prophetnet-large-uncased","prophetnet-large-uncased-squad-qg","prophetnet-large-uncased-cnndm"], type="value", default="prophetnet-large-uncased", label="model")
], 
    gr.outputs.Textbox(label="Output"),
    examples=examples,
    article=article,
    title=title,
    description=description).launch(enable_queue=True, cache_examples=True)