In subsection 2.1, we describe the currently available generator algorithms, the different training modes, and data preprocessing steps and amend the recently introduced graph encoding of molecules from Ref. 8. In subsection 2.2, we present the three steps to score compounds for the RL, the computation and scaling of scores per objective and the multi-objective optimisation, and detail some predefined options. Furthermore, to facilitate usage, this work is supplemented with a rich Python application programming interface (API), a command line interface (CLI) and a graphical user interface (GUI) that are described in section 3. Finally, pre-trained models are made publicly available to ease the de novo design of molecules.