Is it possible to rename intercept in glm.from_formula?

Hello, i was wondering if it is possible to rename intercept in glm.from_formula, or generaly if it is possible to use hiearchical modeling using glm_formula? Example of what I’d like to do is:

import pymc3 as pm 
import pandas as pd 

data = pd.read_csv("data.csv")
with pm.Model() as logistic_model:
    pm.glm.GLM.from_formula('action_1 ~ x_1 + x_2 + x_3 + x_4',
    pm.glm.GLM.from_formula('action_2 ~ x_1 + x_2 + x_3 + x_4 + action_1',

    trace = pm.sample(1000, tune=1000, init='adapt_diag')

The error i get trying something like that is:
“ValueError: Variable name Intercept already exists.”

Something like that would lead to easy implementation of Gaussian Bayesian Networks using pymc3.

I had a similar question, Just checking if you figured out how to use hierarchical modeling using glm_formula?

I have not tried, but IIRC, you should be able to use -1 to remove the intercept and then add a new factor (which would be the renamed intercept) referring to a vector of ones.