Building a RAG System from Scratch: A Complete Guide

This article wraps up a series on building a production-ready RAG system from scratch using Python, pgvector, and Gemini embeddings. It covers design decisions like using pgvector over dedicated vector DBs, HNSW indexing, and asymmetric task types for embeddings. The series also explores MCP servers, agentic patterns, and cloud deployment on Render and Supabase.