Embeddings & Vector Stores with PGVector and Qdrant

https://www.youtube.com/watch?v=FDBnyJu_Ndg Vector Stores in the Production Stack Once documents are split into clean chunks, they must be converted into numerical vectors (embeddings) and indexed for similarity search. An embedding model maps semantic meaning into high-dimensional geometric space (for example, 1,536 dimensions for OpenAI text-embedding-3-sm...