app.py

import gradio as gr
from detoxify import Detoxify

all_categories = {'all_categories': [
                                    'toxicity',
                                    'obscene',
                                    'threat',
                                    'insult',
                                    'identity_attack',
                                    'sexual_explicit'
                                    ]
                  }


examples = [
    ['Yes indeed. She sort of reminds me of the elder lady that played the part in the movie "Titanic" who was telling her story!!! And I wouldn\'t have wanted to cover who I really am!! I would be proud!!!! WE should be proud of our race no matter what it is!!',
  50],
 ['The trans women reading this tweet right now is beautiful', 50],
 ["Question: These 4 broads who criticize America, what country did they flee to get here? And now they want to make OUR America like THEIR former HELL HOLE. I don't think so!!!!!!!!!!  Let them explain their GRATITUDE for letting them in OUR country.",
  50],
 ['Well being subtle you could not have been born because black people don\'t matter',
  50],
 ["For starters bend over the one in pink and kick that ass and pussy to get a taste until she's begging for a dick inside her.",
  50]
]


model = Detoxify('multilingual')


def toxicity(sentence, threshold):
    predicts = model.predict(sentence)
    return [ x for x in predicts if predicts[x] > threshold/100 ], all_categories

gr.Interface(fn=toxicity, 
             inputs=[
                 gr.Textbox(placeholder="Enter sentence here..."),
                 gr.Slider(0, 100)
             ], 
             outputs=[
                 'text',
                 gr.JSON(all_categories)
             ],
             examples=examples).launch()