# model.py
import joblib

class LinearRegressionModel:
    def __init__(self):
        # Load the model
        self.model = joblib.load("linear_regression_model.joblib")

    def get_coefficients(self, columns):
        # Return coefficients as a dictionary with column names as keys
        coefficients = dict(zip(columns, self.model.coef_.tolist()))
        intercept = self.model.intercept_
        return {"coefficients": coefficients, "intercept": intercept}

# Instantiate the model for inference
model = LinearRegressionModel()

# Sample usage function to demonstrate
def predict(inputs):
    # Assume 'columns' is a key in the inputs dict with a list of column names
    columns = inputs.get("columns", [])
    return model.get_coefficients(columns)