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import gradio as gr
from transformers import pipeline

pipe = pipeline(
    "token-classification",
    model="DanielDDDS/hebrew-recipe-modification-ner",
    aggregation_strategy="simple"
)

def predict(text):
    if isinstance(text, list):
        text = text[0]
    preds = pipe(text)
    return {"results": preds}

demo = gr.Interface(
    fn=predict,
    inputs=gr.Textbox(label="Hebrew comment", placeholder="ืืคืฉืจ ืœื”ื—ืœื™ืฃ ื—ืžืื” ื‘ืฉืžืŸ ืงื•ืงื•ืก"),
    outputs="json",
    title="Hebrew Recipe Modification Extractor",
    description="Extract recipe modifications from Hebrew YouTube comments",
    api_name="predict"          # <--- this line forces the endpoint name
)

demo.queue(max_size=10).launch()