Local semantic search engine in Rust, no external DB

- LocalMind is an open-source semantic search engine written in Rust that runs entirely on-device with no external database dependency — it uses local embeddings and in-memory vector search. - Semantic search goes beyond keyword matching by understanding the meaning behind queries; it's what powers tools like Google, ChatGPT search, and RAG (retrieval-augmented generation) apps. - "Embeddings" are numerical vector representations of text; similarity between texts is computed by measuring distance between vectors. Running this locally means no data leaves your machine — important for privacy-conscious users. - Rust is a systems programming language known for performance and safety; building search in Rust without external DBs (no Postgres, no Elasticsearch, no SQLite) means the entire project is a single self-contained binary. - This is relevant to the growing "local-first" and "offline AI" movement, where developers want powerful NLP (natural language processing) capabilities without cloud API calls, subscription costs, or data exposure.