If by “different shape” you mean the length of the vector is different, then it is a typical use case and you can follow the similar example in the doc.
If you meant you have new previously unobserved categories (e.g., new individuals that are not in the training set), then in you model block instead of using train.content_id.cat.codes.size as the shape you should use the total number of individuals. Also in this case hyper prior would help (which you are already doing for mu the parameter for individuals).