Minari is a dataset library for offline reinforcement learning research, similar to an offline version of Gymnasium or HuggingFace datasets. It provides a standardized dataset format for storing and sharing offline RL trajectories, along with a CLI and Python API for listing, downloading, and managing popular reference datasets like D4RL.