********************** Examples ********************** ================================== Use an LLM to Control Software ================================== The LLM generates configuration files, script commands, and codes in Python/Julia, C++/C, and domain-specific languages to control the operational flow. * In a finite element solver, the main workflow is fixed, but many options are selected at each step. * Unlike the fixed solver core, pre/post-processing workflows are dynamic and highly customizable. =========================== ================================= ======================================================== ========================================= Type Flow Control Readability Examples =========================== ================================= ======================================================== ========================================= Configuration Files Fixed (all steps) Easy Palace (.msh and `.json `_) Script Commands Fixed (selectable steps) Simple `Gmsh `_, `LAMMPS/Kalmelo `_, Ansys APDL Python/Julia Dynamic (new flow) Moderate coding capability Gmsh (`.jl `_ and .py) C++/C Dynamic (new flow) Advanced coding capability Gmsh, OCCT, VTK Domain-Specific Languages Dynamic (new flow) Closed to human language `FEniCS (UFL) `_, KittyCAD/Zoo (KCL) =========================== ================================= ======================================================== ========================================= For LLM-driven software flow control, generating Python or Julia scripts is the recommended approach. Input the following content into DeepSeek: :: Write a Julia script using Gmsh to create three spheres: one large sphere centered at (0, 0, 0) with radius 1, and two small spheres centered at (0.2, 0, 0) and (-0.2, 0, 0) respectively, each with radius 0.1. Then, subtract the two small spheres from the large sphere and generate the mesh. The generated Julia script is available at this `link `_.