inference.py

import joblib
import pandas as pd

model = joblib.load("best_random_forest_model.joblib")
scaler = joblib.load("std_scaler.bin")

def predict(data):

    df = pd.DataFrame(
        data,
        columns=[
            "LoanOriginalAmount",
            "CreditScoreRangeLower",
            "StatedMonthlyIncome",
            "Investors",
            "MonthlyLoanPayment",
        ],
    )

    scaled = scaler.transform(df.values)

    prediction = model.predict(scaled)

    return prediction.tolist()