app.py

import gradio as gr
from transformers import pipeline

classifier = pipeline(task='text-classification', model='cwchang/text-classification-model-multilingual', device=-1)

def classify(text):
    return classifier(text)[0]["label"]

demo = gr.Interface(
    fn=classify,
    inputs=gr.Textbox(placeholder="Please enter the text..."),
    outputs="label",
    examples=[
        ["What's the weather like today?"],
        ["Set an alarm for 7 AM tomorrow"],
        ["Call Mom"],
        ["Send a text to Alex saying, 'I'll be there in 15 minutes'"],
        ["Play some relaxing music"],
        ["Remind me to buy milk when I'm at the grocery store"],
        ["How do I get to the nearest coffee shop?"],
        ["What's the latest news?"],
        ["Translate 'thank you' into Spanish"],
        ["Add a meeting to my calendar for next Monday at 3 PM"],
        ["查詢今天的空氣品質指數"],
        ["明早八點鐘設一個鬧鐘"],
        ["給老闆發一封電子郵件，確認下週會議的時間"],
        ["給李明打個電話，問他晚餐時間是否方便"],
        ["播放一首運動時的動感音樂"],
        ["我到圖書館時，提醒我還書"],
        ["告訴我到最近的郵局怎麼走"],
        ["播報一下今天的頭條新聞"],
        ["將“生日快樂”翻譯成法語"],
        ["在下週三上午10點的日程中加入牙醫預約"],]
    )

demo.launch()