The state of the art for equilibrium calculations are Calphad-based programs such as FactSage, Thermo-Calc or Pandat. These are mostly used by scientists and engineers in their GUI-mode since the GUI supports in translating the real-world problems into thermochemical calculation input and the interpretation of the results. On the other hand, the GUIs of Calphad-based programs do not offer good support for the setup and analysis of hundreds of thousands to millions of equilibrium calculations, as would be interesting for Materials Informatics applications. The existing Python interfaces of the different programs (and also alternatives such as PyCalphad or OpenCalphad) are on the other hand difficult to master. In effect, there are only few persons who have sufficient knowledge of both thermochemical calculations and big data handling. 

In order to bridge the gap between GUI-based Calphad calculations and Python-based data handling, Equi2Py has recently been introduced in FactSage. This program allows to set up equilibrium calculations using the GUI of FactSage and then to export the same calculation as fully running Python script, including typical post-processing examples. Now, engineers and scientists only need to modify the script, rather than write the full code from scratch. It is advocated that the extension is a much easier problem, especially due to the advent of LLMs such as ChatGPT, increasing drastically the accessibility of Calphad-based equilibrium calculations in Materials Informatics applications. As examples for the latter, the design of hardfacing alloys for mining applications is introduced.