Adding Logging Traces, Ratings and Unit Tests to your Chat Assistant In this series of articles, we’ll delve into the important parts of creating a multi-user chat assistant using AWS serverless and OpenAI. Our goal is to provide you with a clear roadmap for building and continuously improving your solution. Ultimately, this series aims to empower you to build a full-fledged AI assistant using open-source models, your data, and your compute resources.

If you want to make an apple pie from scratch, you must first create the universe. — Carl Sagan In this series of articles, we’ll delve into the important parts of creating a multi-user chat assistant using AWS serverless and OpenAI. Our goal is to provide you with a clear roadmap for building and continuously improving your solution. Ultimately, this series aims to empower you to build a full-fledged AI assistant using open-source models, your data, and your compute resources.

The secret of getting ahead is getting started. — Mark Twain Introduction I’ve spent this year diving into the LLM application development scene, and there is a lot going on! Using my newfound knowledge, I built a multi-user chat assistant at work that can help data scientists. Challenged to do it quickly and at a low cost, I will share some of what I learned in the process. This is the first article in a series where we’ll delve into the intricacies of creating a multi-user chat assistant using AWS serverless and OpenAI.