Join me on the RAG (Retrieval Augmented Generation) road. In this talk we start from the basics, we will go through embeddings and vector databases. Then finally i'll show you a great use case for a RAG application that has a React front end and utilizes the capabilities of generative AI.

A lightning walkthrough taking an existing site and turning it into searchable content using OpenAI embeddings. We'll use react server components to create an extremely snappy UX while using server-side cosine similarity functions to determine the best search results.

The secret sauce behind LLMs are embedding vectors — just arrays of very small numbers. But with them, you can build absurdly useful things ranging from cross-language search features to polyglot chat bots. We'll talk about how they work and how you can use them to build magical things.