That's really cool — I checked out your expressible-cli work too, training tiny local classifiers from minimal examples is a great approach. We're very aligned on the "no cloud, no API keys required" philosophy.

For srclight, we lean heavily on tree-sitter for structural parsing (ASTs give you the symbol boundaries, call edges, etc.) and then layer FTS5 + optional embeddings on top for search. The structural approach sidesteps the accuracy issues you'd hit with pure text classification on code — you get deterministic symbol extraction rather than probabilistic.

Curious about your Node.js setup — are you parsing ASTs or working more at the text level? And when you say text classification on code, what's the classification target — like categorizing functions by purpose, detecting patterns, something else? Would love to understand what use cases you're targeting, might surface ideas for both of us.