OpenHGNN is a research-oriented framework that integrates state-of-the-art heterogeneous graph neural network models. It provides standardized implementations of GNN architectures, datasets, training pipelines, and evaluation tasks including recommendation, graph attacks/defenses, and anomaly detection. The toolkit supports graph prompt pipelines, distributed training, and TensorBoard visualization.