app.py

import gradio as gr
from transformers import pipeline

clf = pipeline("text-classification", model="afridi15/customer-support-intents")

def predict(text):
    result = clf(text)[0]  # {'label': 'LABEL_3', 'score': 0.85}

    return {
        "label": result["label"],
        "score": float(result["score"])
    }

with gr.Blocks() as demo:
    gr.Markdown("# Intent Classifier API")
    
    input_box = gr.Textbox(label="Message")
    output_box = gr.JSON(label="Prediction")

    input_box.submit(predict, inputs=input_box, outputs=output_box)

demo.queue(False)   # 🚀 Disable queue mode → NO event_id, instant JSON
demo.launch()