This online interactive demo allows you to create arbitrary multi-agent pathfinding (MAPF) instance on square grid worlds, by placing obstacles, agents (robots), and corresponding goals, before running a trained PRIMAL model in real-time to see agents plan individual collision-free paths to their goal. The full PRIMAL paper is available at this link, while the full training and testing code is available on github. More information and resources about MAPF can be found at the main MAPF community website.