Additionally, LLMs were shown to possess expert knowledge in many research domains where DSLs are used, including chemistry. Among others, LLMs were found useful for molecular design , property prediction , and chemistry-specific code synthesis. For instance, they can synthesise Python code that can be used to solve chemistry problems and perform robotic experiments , and, in a small case study, were shown to create Python code generating simple inputs for the quantum chemistry program Gaussian . Yet, direct DSL-synthesis with LLMs in chemistry has not been demonstrated so far.