What is cosine similarity and how is it used in vector search?

Cosine similarity measures the angle between two vectors, ranging from negative one to positive one, where one means identical direction. It ignores vector magnitude, focusing only on direction, which is useful when comparing embeddings of different lengths or normalization. It is the most common similarity metric in semantic search and RAG systems.