import streamlit as st
from joblib import load

model = load("kmeans_model.pkl") 

st.title("Customer Segmentation")

# inputs
Sex = st.selectbox("gender of a customer",options= ["Male","Female"])
Sex=1 if Sex=="Male" else 0
Marital_status = st.selectbox("Marital Status",options= ["Single","Non-single"])
Marital_status=0 if Sex=="Single" else 1
Age = st.number_input("age of the customer",min_value=18,max_value=90)
Education = st.selectbox("Education Level of education of the customer",
                         options= ["other / unknown","high school","university","graduate school"])
Education_d={"other / unknown":0,"high school":1,"university":2,"graduate school":3}
Education = Education_d[Education]
Income = st.number_input("Self-reported annual income in US dollars of the customer",step=100,min_value=30000)
Occupation = st.selectbox("occupation of the customer",
                          options= ["unemployed / unskilled","skilled employee","highly qualified employee"])
Occupation_d={"unemployed / unskilled":0,"skilled employee":1,"highly qualified employee":2}
Occupation = Occupation_d[Occupation]
Settlement_size = st.selectbox("The size of the city that the customer lives in",
                          options= ["small city","mid-sized city","big city"])
Settlement_size_d={"small city":0,"mid-sized city":1,"big city":2}
Settlement_size = Settlement_size_d[Settlement_size]
values = [Sex,Marital_status,	Age,Education,Income,Occupation,Settlement_size]

if st.button("Predict"):
    label = model.predict([values])[0]
    st.success(f"Customer Belongs to Segment *{label}*")