Enhancing the development of Cherenkov Telescope Array control software with Large Language Models

Abstract: We develop AI agents based on instruction-finetuned LLMs to assist in the engineering and operation of the Cherenkov Telescope Array Observatory (CTAO) Control and Data Acquisition Software (ACADA). These agents align with project-specific documentation and codebases, understand contextual information, interact with external APIs, and communicate with users in natural language. We present our progress in integrating these features into CTAO pipelines for operations and offline data analysis.