I actually have a WIP library for this, the indexing server isn't where I want it just yet, but I have an entire agent toolkit that does this stuff, and the indexing server is quite advance, with self-tuning, raptor/lsp integration, solves for optimal result set using knapsack, etc.
Lens is basically a rust local first mmapped file base search store, it combines RAPTOR with LSP, semantic vectors and a dual dense/sparse encoding, and can learn a function over those to tune the weights of the relevance sources adaptively per query using your data. It also uses linear programming to select an "efficient" set of results that minimizes mutual information between result atoms -- regular rag/rerank pipelines just dump the top K, but those often have a significant amount of overlap so you bloat context for no benefit.
https://github.com/sibyllinesoft/grimoire