Inference of complex demographic histories typically requires parameterized models specified manually by the researcher. With an increased variety of methods and tools, each with its own interface, model specification becomes tedious and error-prone. Moreover, optimization algorithms used to find optimal parameters sometimes turn out to be inefficient. The open source software GADMA addresses these problems, providing automatic demographic inference. It proposes a common interface for several simulation engines and provides global optimization of parameters based on a genetic algorithm. Here, we introduce new features of GADMA2, the second version of the GADMA software. It has renovated core code base, new simulation engines, an updated optimization algorithm, and flexible specification of demographic history parameters. We provide a full overview of GADMA2 enhancements and demonstrate example of their usage.