RAG

Embeddings and vector search, explained

An embedding turns text into a vector of meaning. Training (word2vec, contrastive), cosine similarity, ANN (HNSW/IVF/PQ), vector databases, MTEB.

Agentic RAG and GraphRAG: reasoning and structure above retrieval

Beyond naive RAG: agentic loops (Self-RAG, CRAG, routing, multi-hop), hybrid + rerank, and GraphRAG (entities, Leiden, summaries). Costs and RAGAS.