app.py

import gradio as gr

from transformers import pipeline

detection = pipeline('comment detection')

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

demo = gr.Interface(
    fn=score_comment, 
    inputs=gr.inputs.Textbox(lines=2, placeholder='Comment to score'),
    outputs='text',
    title='Hate Comment Detector',
    description='Enter comment to verify',
    theme='compact',
    layout='vertical',
    width=600,
    height=400,
    allow_flagging=True,
    bgcolor='#f2f2f2',  
)

demo.launch(share=False)