RAG System Construction for Beginners

Build a retrieval-augmented generation system from scratch.

Understanding RAG

Retrieval-Augmented Generation combines information retrieval with text generation. It lets AI answer questions based on your specific documents, reducing hallucinations and improving accuracy.

Core Components

You'll need a document loader, text splitter, embedding model, vector database, and LLM. Each component has multiple options—we'll guide you through choosing the right ones.

Building and Optimizing

Start with a simple pipeline, then optimize chunking strategy, retrieval parameters, and prompt design. Evaluation is key—measure accuracy and iterate systematically.