Aura – A Ruby-inspired declarative language for AI/ML pipelines and web apps (github.com)

Aura has been introduced as a novel declarative programming language tailored for developing AI/ML pipelines and integrating AI into web applications, inspired by the developer-friendly syntax of Ruby. Its design aims to eliminate boilerplate code practices, enhance prototyping joy, and simplify the coding experience. By transpiling to efficient Ruby code using Torch-rb and Sinatra, Aura allows users, from data scientists to web developers, to write concise, human-readable code that feels like pseudocode while maintaining high performance. Significantly, Aura addresses common frustrations in AI and web development by offering features like smart defaults, auto-inference, and friendly error handling. Its architecture supports streamlined workflows for tasks like dataset management, model training, and web serving—all consolidated within an accessible syntax. Currently in its early version (v0.1), Aura can manage basic ML operations and facilitates easy extensions into existing Ruby systems. With a roadmap that includes enhanced integration with frameworks like Hugging Face and future support for large language models, Aura is poised to make coding in AI both faster and more enjoyable, marking a transformative step in bridging programming sophistication with user experience.