gollum VS agency

I did a similar optimization via https://github.com/viterin/vek as the SIMD version. Some somewhat unscientific calculations showed a 10x improvement staying in float32: https://github.com/stillmatic/gollum/blob/07a9aa35d2517af8cf...

TBH my takeaway was that it was more useful to use smaller vectors as a representation

I like Go a lot for working with OpenAI etc, it's 'just' API calls and Go is great at that. I've opensourced some bits here: https://github.com/stillmatic/gollum -- in particular, function dispatch (given a prompt, return an arbitrary Go struct) is really nice, as is a very fast in-memory KNN index.

I've written a version of this in Golang: https://github.com/stillmatic/gollum/blob/main/dispatch.go

```go

I have gotten 10x speedups with SIMD on modern hardware. Goroutines make this actually fairly tricky, as you essentially have to process all the events and then sort the entire array, which is usually the bottleneck. The heap adds a small amount of complexity but is significantly more efficient, feels like good ROI.

https://github.com/stillmatic/gollum/blob/main/vectorstore.g...

I would, at the very least, wrap the errors being returned inside the process function https://github.com/neurocult/agency/blob/14b14e50a7570189388...

Or, I suppose the user must handle exception behavior in their custom `OperationHandler`

Recognizing the need for a Go-friendly tool that’s simple yet powerful, we developed Agency. This Go library, designed with a clean approach, matches Go's strengths in a static type system and high performance. It's our answer to bringing easy-to-use, efficient AI capabilities to Go developers.