In this thread https://communities.sas.com/t5/SAS-Statistical-Procedures/Proc-mixed/m-p/489027#M25407 I noted that you cannot include "random rep;" with type=un. You cannot include it with type=cs either, or with most of the other commonly used types. You can optionally include it with type=ar(1), to generate "AR(1) + RE". Refer to the paper by Littell et al. that I linked in the other thread, as well as https://www.sas.com/store/books/categories/usage-and-reference/sas-for-mixed-models-second-edition/prodBK_59882_en.html
I am not entirely sure what you mean by "the literals to appear as in the lsmeans like glm". I'm guessing you mean letter assignments, which you can get using the LINES option on the LSMEANS statement.
Tukey-adjusted pairwise comparisons among main effects means are fine. But I do not recommend using Tukey-adjusted comparisons among interaction means; they are too conservative because they control for all pairwise comparisons (of which there are 630, for 4 x 9 = 36 means) whereas you are typically interested in only a subset of comparisons (198, if I've computed correctly). Consider SLICE and SLICEDIFF.
In general, I believe pairwise comparisons are a poor approach to interpreting an interaction (especially when factors have many levels, for example 4 x 9), so I generally test what I consider to be contextually useful hypotheses with CONTRAST or ESTIMATE statements.
If you post your GLIMMIX code, the Community might be able to make suggestions.
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