A simple project demonstrating Retrieval Augmented Generation (RAG) using SQLite, sqlite-vec, and OpenAI. It embeds text files, stores them in a SQLite database, and retrieves relevant documents using vector search. The project features lightweight single-file SQLite databases, vector search capabilities, and OpenAI integration for embeddings and chat responses.
The article explores the concept of Retrieval-Augmented Generation (RAG) using SQLite, specifically with the sqlite-vec extension and the OpenAI API. It outlines a simplified approach to RAG, moving away from complex frameworks and cloud vector databases, using SQLite's virtual tables for vector search and semantic understanding.
