Pgvector Semantic Search

This is the reference implementation for pgvector semantic search. It defaults to HNSW indexes with halfvec storage for cosine distance, which gives you 50% smaller indexes and solid recall without much tuning. The guide is opinionated in the right ways: it tells you to skip IVFFlat unless you have write-heavy workloads, gives you actual ef_search numbers tied to recall tradeoffs, and includes rough capacity estimates so you know when 16GB RAM hits its limit around 2-3M vectors at 1536 dimensions. If you're building RAG or any embeddings-based search on Postgres, this cuts through the parameter space and gets you to production faster.