Curious about what you use to productionalize this; it is so cool and inspiring to see hierarchical bayes applications like this.
What is the go to "production" stack for something like this nowadays? Is Stan dead? Do you do HMC or approximations with e.g. Pyro?
We built our own collapsed Gibbs sampler in C: PyMC/Stan are use HMC which scales only to a few hundred parameters and we are modeling millions.
Above C we built a python wrapper to help construct arbitrary Dirichlet and Pitman-Yor Processes graphs.
From there we have some python wrappers and store it all in a hierarchical DuckDB schema for fast query access.
The site itself is actually just a light wrapper around our API that simplifies this process.