import gradio as gr
from transformers import pipeline

languages = [
    "Arabic", "Basque", "Breton", "Catalan", "Chinese_China", "Chinese_Hongkong", 
    "Chinese_Taiwan", "Chuvash", "Czech", "Dhivehi", "Dutch", "English", 
    "Esperanto", "Estonian", "French", "Frisian", "Georgian", "German", "Greek", 
    "Hakha_Chin", "Indonesian", "Interlingua", "Italian", "Japanese", "Kabyle", 
    "Kinyarwanda", "Kyrgyz", "Latvian", "Maltese", "Mongolian", "Persian", "Polish", 
    "Portuguese", "Romanian", "Romansh_Sursilvan", "Russian", "Sakha", "Slovenian", 
    "Spanish", "Swedish", "Tamil", "Tatar", "Turkish", "Ukranian", "Welsh"
]

pipe = pipeline("text-classification", model="Mike0307/multilingual-e5-language-detection")

def func(inp):
    result = ''
    out = pipe(inp)
    for lang in out:
        result += languages[int(lang['label'][6:])] + ' ' + str(lang['score']) + '\n'
    return result

demo = gr.Interface(fn=func, inputs="text", outputs="text")
demo.launch()