import streamlit as st
from sentence_transformers import CrossEncoder

model_name = "Anvilogic/CE-typosquat-detect" 
model = CrossEncoder(model_name)

st.title("Typosquatting Detection App")
st.write("Enter two domains to check if one is a typosquatted variant of the other.")

domain = st.text_input("Enter the legitimate domain name:")
sim_domain = st.text_input("Enter the potentially typosquatted domain name:")

if st.button("Check Typosquatting"):
    inputs = [(domain, sim_domain)]
    prediction = model.predict(inputs)[0]

    if prediction > 0.5:
        st.success(f"The model predicts that '{sim_domain}' is likely a typosquatted version of '{domain}'.")
    else:
        st.warning(f"The model predicts that '{sim_domain}' is NOT likely a typosquatted version of '{domain}'.")