app.py

import gradio as gr
def score_comment(comment):
    vectorized_comment = vectorizer([comment])
    results = model.predict(vectorized_comment)

    text = ''
    for idx, col in enumerate(df.columns[2:]):
        text += '{}: {}\n'.format(col, results[0][idx]>0.5)

    return text

interface = gr.Interface(fn = score_comment, inputs=gr.Textbox(lines=2, placeholder='Comment to score'), outputs = 'text', title='Comment Toxicity', description='Check comment, how much is it toxic:')
interface.launch(share=True)