How to decide number of neighbors and resolution for Louvain clustering
A general rule of thumb is that in order to improve the variance $n$ times you need $n^2$ neighbours. This is only applicable if you consider the $n^2$ nearest neighbours of a cell to be biologically identical (i.e. "similar enough"); if your data includes 10 types of cells with 10 cells each, then using the 20 nearest neighbours for smoothing will obscure the data.

As far as I know, there is no single best answer to this question. I would suggest trying different numbers and sticking to what agrees more with the biology of the dataset.