RAG with OpenAI Embeddings, pgvector and LangChain

Retrieval-Augmented Generation (RAG) is a practical pattern: store knowledge as embeddings, retrieve the most relevant chunks with semantic search, then generate an answer grounded in that context. This guide shows a simple end-to-end flow with OpenAI embeddings, PostgreSQL + pgvector, and LangChain chunking. Prerequisites OpenAI account Generated API key Enabled billing Node.js version 26 PostgreSQL with pgvector extension enabled npm packages: openai, langchain, pg, pgvector...