We'll build a minimal but honest RAG pipeline: structural chunking, batched embeddings, a pgvector-backed index, hybrid search fused with Reciprocal Rank Fusion, and a prompt template that forces citations. Every piece here maps directly onto what a production system does — production just adds retries, batching, and monitoring around the same skeleton.
Layer 3 · Code
Retrieval Augmented Generation
Build the whole loop: chunk with overlap, embed, store in pgvector, hybrid search with RRF, and assemble a cited prompt.
12 min read110 XP