Build a RAG Pipeline with pgvector and Gemini in 5 Steps

This tutorial walks through creating a RAG system using pgvector for vector storage and Google's Gemini for answer generation. It covers environment setup, database configuration, embedding ingestion, semantic search, and the full pipeline. The guide uses Python 3.12, Docker, and the new google-genai package.