Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks, and arithmetic circuits. It focuses on structure learning, especially for tractable models in which exact inference is efficient. Each algorithm is implemented as a command-line program suitable for interactive use or scripting, with consistent options and file formats throughout the toolkit.