🔗 Ash AI: A comprehensive LLM toolbox for Ash framework

Let’s talk about the LLM-ephant in the room. There probably isn’t a single software engineer in the world remaining who has not been asked to implement some kind of LLM related feature for their application. Most likely that feature is something like a chat bot, either for front line customer support, or as a tool for users to interact with your application logic using natural language.

The AI scene is rapidly changing, but there is one thing that will always be true: AI agents must have their choices routed through a well formed and secure application layer. We do not build agentic tooling for our users by providing an LLM with full access to our database and including in the prompt “do not share other user’s data or you’ll go to jail”. At least, you don’t if you want to keep your job and/or stay out of jail yourself.

Introducing the Ash AI package

Ash aims to bring the best of the Elixir ecosystem to bear (and build it ourselves when necessary), to help developers solve real, every day problems. We take a ground up, methodical approach, and over time have begun layering high level concepts on top of a rich core framework. For example AshAuthentication, AshDoubleEntry and AshMoney are all packages that do far more for you, by way of integrating with and understanding the core framework, than a simple Elixir library ever could.

So what does that look like when it comes to AI? The Ash AI package builds on Ash Framework’s core strengths to rapidly implement LLM features for their application.

The earliest and strongest design principle of Ash Framework is the concept of modelling your application and its logic as data. When your application is modelled with data, tooling can be added that leverages your data at an astonishing rate of speed and fidelity. This also avoids the sprawl and spaghetti that often arises without this design pattern. We apply these same principles to help you integrate AI agents directly into your application powerfully, simply and safely. We integrate directly with and leverage LangChain, and plan to provide ongoing support for multiple lower level LLM tools in the future.