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.Interface.load("huggingface/bert-base-cased")
io2 = gr.Interface.load("huggingface/bert-base-uncased")

def inference(inputtext, model):
    if "[MASK]" not in inputtext:
        return {"error": "The input text must contain the [MASK] token."}
    
    if model == "bert-base-cased":
        return io1(inputtext)
    elif model == "bert-base-uncased":
        return io2(inputtext)
    else:
        return {"error": "Invalid model selected"}

iface = 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.JSON(label="Output"),  # We use JSON to display errors or outputs
    examples=examples,
    article=article,
    title=title,
    description=description
)

iface.launch(share=True)