Dialog agents need to keep track of the various pieces of information to make decisions how to respond to a given user input. This is referred to as context, session, or state tracking. As the dialog complexity increases, this state-tracking logic becomes harder to write, debug, and maintain. This library takes the finite-state machine design approach to address this complexity. Developers using this library can model dialog agents with first-class concepts such as states, attributes, transition, and actions. Visualization and other tools are also provided to help understand and debug complex FSM conversations. Also check out our blog post.