app.py

import gradio as gr
import tensorflow as tf

model = tf.keras.models.load_model('toxic-detect.h5')

def evaluate_comment(Comment):
    processed_Comment = vectorizer([Comment])
    res = model.predict(processed_Comment)

    text = ''
    for i, col in enumerate(df.columns[2:]):
        text += '{}: {}\n'.format(col, 'Violate' if res[0][i] > 0.5 else 'None')
    
    return text
    
interface = gr.Interface(fn = evaluate_comment, inputs = gr.inputs.Textbox(lines = 4, placeholder='Comment to evaluate'), outputs = 'text')
                         
interface.launch()