Abstract The Starlink Tables Infrastructure Library Tool Set (STILTS) is a powerful suite for astronomical data analysis, particularly useful when dealing with large datasets. However, like other software suites in astronomy its comprehensive syntax creates a significant learning curve to new users. To address this, we present STILTS-NLI, a natural language interface that generates STILTS commands from user prompts, with agentic support for a user-friendly experience. We developed STILTS-NLI by fine-tuning a compact, open-source Large Language Model (LLM) on a synthetically generated dataset. This dataset was curated and validated to ensure both comprehensive coverage of key STILTS functionalities and the syntactic correctness of the resulting commands. Our results demonstrate that this specialised model generates valid commands that match and in some cases outperform larger proprietary models. By leveraging small, open-source models, STILTS-NLI provides an accessible, low-resource solution that lowers the barrier to entry for using STILTS.
Shaw et al. (Thu,) studied this question.