OpenTinker is a framework for agentic reinforcement learning, offering a range of training scenarios and environments. It features both data-dependent and data-free paradigms, with single-turn and multi-turn interaction modes for various use cases. The setup involves cloning the repository, installing dependencies, and configuring an authentication system for API access.