Retrieval-Augmented Generation (RAG) Tutorial: Architecture, Implementation, and Production Guide
This Retrieval-Augmented Generation (RAG) tutorial is a step-by-step, production-focused guide to building real-world RAG systems. If you are searching for: How to build a RAG system RAG architecture explained RAG tutorial with examples How to implement RAG with vector databases RAG with reranking RAG with web search Production RAG best practices You are in the right place. This guide consolidates practical RAG implementation knowledge, architectural patterns, and optimization techniques used in production AI systems. What Is Retrieval-Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is a system design pattern that combines: Information retrieval Context augmentation Large language model generation In simple terms, a RAG pipeline retrieves relevant documents and injects them into the prompt before the model generates an answer. Unlike fine-tuning, RAG : Works with frequently updated data Supports private knowledge bases Reduces hallucination Avoids re...
