More about the project
Large language models get better and better over time. With the progress in model accuracy, rises more and more practical usages, but at the same time, the complexity of implementing such systems prevents fast growth in AI. To combat this, we need a new framework that makes standard procedures we do with AI like generating files, decision making etc. much easier. Like with the prompt engineering methods rising, the number of statistical methods that work on low-level information also rises, but there's no platform that would implement those algorithms in some higher abstraction. We're still on the beginning of the process of understanding the new AI, the one that can generate meaningful responses. There are no beaten paths when it comes to solving many problems that have an root in connecting the classical programming with LLM. One of the keypoints of the project is to find more solutions to those problems, by creating a programming environment for exploring those issues.
Main concept
Application uses python scripts to implement tool usage and more sophisticated techniques of controlling the model. By solving more and more practical problems author believes that it will be possible to create an self-defined API for working with models.