app.py

import streamlit as st
import pandas as pd

from utils import predict_toxicity


st.set_page_config(
    page_title="ToxiGuard AI",
    page_icon="🛡️",
    layout="centered"
)

# LOAD CSS
with open("style.css") as f:
    st.markdown(
        f"<style>{f.read()}</style>",
        unsafe_allow_html=True
    )

# TITLE
st.title("🛡️ ToxiGuard AI")
st.subheader(
    "Advanced Multi-label Toxic Comment Detection using BERT"
)

st.markdown("---")

# TEXT INPUT
user_input = st.text_area(
    "Enter a comment",
    height=180,
    placeholder="Type comment here..."
)

# BUTTON
if st.button("Analyze Toxicity"):

    if user_input.strip() == "":

        st.warning(
            "Please enter a comment."
        )

    else:

        results = predict_toxicity(
            user_input
        )

        st.markdown("## Detection Results")

        toxicity_detected = False

        for label, score in results.items():

            st.progress(score)

            st.write(
                f"### {label}: {score:.4f}"
            )

            if score >= 0.5:
                toxicity_detected = True

        st.markdown("---")

        if toxicity_detected:

            st.error(
                " Toxic content detected."
            )

        else:

            st.success(
                " Comment appears safe."
            )