After training our UVGPT on UV-light responsive molecules, a total of one thousand molecules were gen-erated by the model. Out of these, 443 possessed valid chemical structures processed with RDkit. Dylan M. Anstine and Olexandr Isayev have reviewed generative methods in Chemical Sciences and proposed evaluation metrics . The methods for calculating druglikeness and SAscore, as outlined in their publications , were employed in our research. QED estimated the drug-likeness of molecules using a machine learning model trained on a dataset of drug-like compounds. Higher QED values suggest increased likelihood of drug-likeness. Similarly, the Synthetic Accessibility Score calculation methods aimed to systematically assess the ease of synthesizing drug-like molecules, aiding in prioritizing compounds for molecular design.