Research [1][2] shows that 70-85% of developer code search value comes from keyword-based queries. Developers usually search with exact terms they already know (function names, API calls, error messages) and less so with natural language concepts. Github's codesearch famously runs without vector search. I wasn't aware of any BM25-only codesearch tools, so I created shebe.
See releases at https://gitlab.com/rhobimd-oss/shebe/-/releases/v0.5.6-rc3 and give it a try.
I'm continually validating and asking, is this really useful? see https://github.com/rhobimd-oss/shebe/blob/main/docs/testing/...
[1] https://research.google/pubs/how-developers-search-for-code-...
[2] https://sourcegraph.com/blog/keeping-it-boring-and-relevant-...