Facebook AI Research today introduced ReAgent, a reinforcement learning toolkit for building decision-making AI that can receive feedback. ReAgent can assign scores to user actions and treat user input such as clicking on recommended content as training data. ReAgent is a small C library available for download on GitHub designed to be embedded in any application. The toolkit comes with a set of decision-making AI models to get started, an offline module for model performance assessment, and a platform to deploy AI into production using the TorchScript library in PyTorch. Horizon, a reinforcement learning platform for deployment of large-scale models in production open-sourced by Facebook in November 2018, is now part of ReAgent.