import gradio as gr

title = "BERT"
description = "Gradio Demo for BERT. 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/1810.04805' target='_blank'>BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding</a></p>"

examples = [
    ['Paris is the [MASK] of France.', 'bert-base-cased']
]

# Lade die Interfaces für die Modelle
io1 = gr.load("huggingface/bert-base-cased")
io2 = gr.load("huggingface/bert-base-uncased")

def inference(inputtext, model):
    if model == "bert-base-cased":
        outlabel = io1(inputtext)
    elif model == "bert-base-uncased":
        outlabel = io2(inputtext)
    else:
        outlabel = "Invalid model selected"
    # Sicherstellen, dass die Ausgabe eine formatierte Zeichenkette ist
    return str(outlabel)

# Aktualisierte Gradio-Syntax
gr.Interface(
    fn=inference,
    inputs=[
        gr.Textbox(label="Context", lines=10, placeholder="Enter text with [MASK] token"),
        gr.Dropdown(choices=["bert-base-cased", "bert-base-uncased"], value="bert-base-cased", label="model")
    ],
    outputs=gr.Label(label="Output"),
    examples=examples,
    article=article,
    title=title,
    description=description
).launch()