At the intersection of science and technology, graphs are increasingly attracting the attention of researchers as important tools for expressing complex relationships. From chemical molecule design to social network analysis, graphs play an indispensable role in numerous fields. However, generating graphics efficiently and flexibly has always been a challenging problem. Recently, research teams from Tufts University, Northeastern University, and Cornell University have collaborated to launch a project called Graph Generative Pre-trained Tran.