RAG for Beginners: Architecture + Simple API Tutorial 2026 | Simple Rag Application

RAG Architecture Explained + Simple RAG API Tutorial In this video, I break down the full Retrieval-Augmented Generation (RAG) architecture and show how to build a simple RAG API endpoint step by step. You will learn how documents are loaded, chunked, embedded, stored in a vector database, retrieved with similarity search, and passed to an LLM to generate grounded answers. This tutorial is designed for beginners and intermediate developers who want to understand how real RAG systems work behind the scenes and how to turn that understanding into a practical API project. The video covers both the offline indexing phase and the online retrieval + generation phase, so you can clearly see how the full pipeline fits together. What you’ll learn What RAG is and why it is used The core RAG architecture and flow Document loading and chunking Embeddings and vector databases Similarity search and retrieved context Prompt construction for RAG LLM response generation How to build a simple RAG API endpoint How to organize the project for learning and GitHub sharing Project files / Source code GitHub Repository: https://github.com/kosalanayanajithde... #RAG #LLM #AI #MachineLearning #GenerativeAI #Python #LangChain #VectorDatabase #MLOps #ComputerEngineering #StudentLearning