kelindar/search: Go library for embedded vector search and semantic embeddings using llama.cpp

The kelindar/search library provides an easy and efficient solution for embedding and vector search in Go applications, designed primarily for small-scale projects. It supports GGUF BERT models, offers GPU acceleration, and includes features such as search index creation from embeddings. While excellent for datasets with fewer than 100,000 entries, it may face performance challenges with larger datasets due to its brute-force search approach. The library also simplifies integration and deployment by avoiding cgo and relying on purego to call shared C libraries directly from Go code.