import gradio as gr
from transformers import pipeline

clf = pipeline("text-classification", model="your-username/bert-base-uncased-yelp")

def predict(text):
    pred = clf(text)[0]
    return f"Label: {pred['label']} (score={pred['score']:.2f})"

demo = gr.Interface(
    fn=predict,
    inputs=gr.Textbox(lines=4, placeholder="Paste a customer review here..."),
    outputs="text",
    title="Sentiment Analysis Demo",
    description="Fine‑tuned BERT‑base model on Yelp Polarity dataset"
)

if __name__ == "__main__":
    demo.launch()