import joblib
import pandas as pd
import streamlit as st

SPENDING_DICT = {'Low': 1,
            'Average': 2,
            'High': 3,
            }

model = joblib.load('model.joblib')#
unique_values = joblib.load('unique_value.joblib')#
    
unique_gender =  unique_values["Gender"]
unique_married =  unique_values["Ever_Married"]
unique_graduated =  unique_values["Graduated"]
unique_profession =  unique_values["Profession"]
unique_spending = unique_values["Spending_Score"]

def main():
    st.title("Segmentation")

    with st.form("questionaire"):
        gender = st.selectbox("Gender",options=unique_gender)# user's input
        married = st.selectbox("Married",options=unique_married)# user's input
        age = st.slider("Age",min_value=10,max_value=60)# user's input
        graduated = st.selectbox("Graduated",options=unique_graduated)# user's input
        profession = st.selectbox("Profession",options=unique_profession)# user's input
        workEX = st.slider("Work Experience",min_value=0,max_value=15)# user's input
        spending = st.selectbox("Spending Score",options=unique_spending)# user's input
        family = st.slider("Family",min_value=0,max_value=10)# user's input


        clicked = st.form_submit_button("Predict segmentation")
        if clicked:
            result=model.predict(pd.DataFrame({"Age": [age],
                                               "Work_Experience": [workEX],
                                               "Spending_Score": [SPENDING_DICT[spending]],
                                               "Gender": [gender],
                                               "Graduated": [graduated],
                                               "Profession": [profession],
                                               "Ever_Married": [married],
                                               "Family_Size": [family]}))
            result = "A" if result[0] == 0 else "Not A"
            st.success("Your segmentation is "+result)

if __name__=="__main__":
    main()
##