import joblib
import pandas as pd
import streamlit as st 


EDU_DICT = {'Preschool': 1,
            '1st-4th': 2,
            '5th-6th': 3,
            '7th-8th': 4,
            '9th': 5,
            '10th': 6,
            '11th': 7,
            '12th': 8,
            'HS-grad': 9, 
            'Some-college': 10,
            'Assoc-voc': 11,
            'Assoc-acdm': 12,
            'Bachelors': 13,
            'Masters': 14,
            'Prof-school': 15,
            'Doctorate': 16
            }

model = joblib.load('model (2).joblib')
unique_values = joblib.load('unique_values (2).joblib')
    
unique_class =  unique_values["workclass"]
unique_education =  unique_values["education"]
unique_marital_status =  unique_values["marital.status"]
unique_relationship =  unique_values["relationship"]
unique_occupation =  unique_values["occupation"]
unique_sex =  unique_values["sex"]
unique_race = unique_values["race"]
unique_country =  unique_values["native.country"]
print(list(unique_values.keys()))

def main():
    st.title("Adult Income")

    with st.form("questionnaire"):
        age = st.slider("Age", min_value=10, max_value=100)
        workclass = st.selectbox("Workclass", options=unique_class)
        fnlwgt = st.selectbox("fnlwgt", options=unique_fnlwgt)  # ต้องกำหนด unique_fnlwgt ก่อนใช้
        education = st.selectbox("Education", options=unique_education)
        educational_num = st.selectbox("Educational Num", options=unique_education_num)  # ต้องกำหนด unique_education_num ก่อนใช้
        marital_status = st.selectbox("Marital Status", options=unique_marital_status)
        occupation = st.selectbox("Occupation", options=unique_occupation)
        relationship = st.selectbox("Relationship", options=unique_relationship)
        race = st.selectbox("Race", options=unique_race)
        sex = st.selectbox("Sex", options=unique_sex)  # ต้องกำหนด unique_gender ก่อนใช้
        capital_gain = st.selectbox("Capital Gain", options=unique_capital_gain)  # ต้องกำหนด unique_capital_gain ก่อนใช้
        capital_loss = st.selectbox("Capital Loss", options=unique_capital_loss)  # ต้องกำหนด unique_capital_loss ก่อนใช้
        hours_per_week = st.slider("Hours per week", min_value=1, max_value=100)
        native_country = st.selectbox("Country", options=unique_country)

clicked = st.form_submit_button("predict income")
if clicked:
    education_encoded = EDU_DICT.get(education, 0)  # Default to 0 if education is not found
    result = model.predict(pd.DataFrame({"age": [age],
                                         "workclass": [workclass],
                                         "fnlwgt": [fnlwgt],
                                         "education": [education_encoded],
                                         "educational-num": [educational_num],
                                         "marital.status": [marital_status],
                                         "occupation": [occupation],
                                         "relationship": [relationship],
                                         "race": [race],
                                         "sex": [sex],
                                         "capital_gain": [capital_gain],
                                         "capital_loss": [capital_loss],
                                         "hours.per.week": [hours_per_week],
                                         "native.country": [native_country]}))
    result = '>50K' if result[0] == 1 else '<=50K'
    st.success('The predicted income is {}'.format(result))



if __name__ == '__main__':
     main()