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import joblib
import pandas as pd
import streamlit as st
from huggingface_hub import hf_hub_download
REPO_ID = "chanyaphas/creditc"
access_token = st.secrets["HF_TOKEN"]
model = joblib.load(
hf_hub_download(repo_id=REPO_ID, filename='model.joblib', token=access_token, repo_type="space")
)
unique_values = joblib.load(
hf_hub_download(repo_id=REPO_ID, filename='unique_values.joblib', token=access_token, repo_type="space")
)
EDU_DICT = {'Lower secondary': 1,
'Secondary / secondary special': 2,
'Academic degree': 3,
'Incomplete higher': 4,
'Higher education' : 5
}
def main():
st.title("Credit Card Approval Prediction")
with st.form("questionaire"):
Gender = st.selectbox('Gender', unique_values['CODE_GENDER'])
Own_car = st.selectbox('Own_car', unique_values['FLAG_OWN_CAR'])
Property = st.selectbox('Property', unique_values['FLAG_OWN_REALTY'])
Income_type = st.selectbox('Income_type', unique_values['NAME_INCOME_TYPE'])
Marital_status = st.selectbox('Marital_status', unique_values['NAME_FAMILY_STATUS'])
Housing_type = st.selectbox('Housing_type', unique_values['NAME_HOUSING_TYPE'])
Education = st.selectbox('Education', unique_values['NAME_EDUCATION_TYPE'])
Income = st.slider('Income', min_value=27000, max_value=1575000)
Children = st.slider('Children', min_value=0, max_value=19)
Day_Employed = st.slider('Day_Employed', min_value=0, max_value=3)
Flag_Mobile = st.slider('Flag_Mobile', min_value=0, max_value=1)
Flag_work_phone = st.slider('Flag_work_phone', min_value=0, max_value=1)
Flag_Phone = st.slider('Flag_Phone', min_value=0, max_value=1)
Flag_Email = st.slider('Flag_Email', min_value=0, max_value=1)
Family_mem = st.slider('Family_mem', min_value=1, max_value=20)
clicked = st.form_submit_button("Result")
if clicked:
result = model.predict(pd.DataFrame({
"CODE_GENDER": [Gender],
"FLAG_OWN_CAR": [Own_car],
"FLAG_OWN_REALTY": [Property],
"CNT_CHILDREN": [Children],
"AMT_INCOME_TOTAL": [Income],
"NAME_INCOME_TYPE": [Income_type],
"NAME_EDUCATION_TYPE": [EDU_DICT[Education]],
"NAME_FAMILY_STATUS": [Marital_status],
"NAME_HOUSING_TYPE": [Housing_type],
"DAYS_EMPLOYED": [Day_Employed],
"FLAG_MOBIL": [Flag_Mobile],
"FLAG_WORK_PHONE": [Flag_work_phone],
"FLAG_PHONE": [Flag_Phone],
"FLAG_EMAIL": [Flag_Email],
"CNT_FAM_MEMBERS": [Family_mem]}))
result = 'Pass' if result[0] == 1 else 'Did not Pass'
st.success('Credit Card approval prediction results is {}'.format(result))
if __name__ == '__main__':
main()
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