ChatGPT

an advanced natural language processing model based on the GPT-4 architecture

has shown remarkable potential across various fields. This study explores the application potential of ChatGPT in developing computational programs for three-dimensional slope stability analysis. This research integrates natural language processing with civil engineering calculations

proposing a novel ChatGPT-Python intelligent programming methodology for three-dimensional slope stability evaluation. The method enables automated implementation of Python-based computational programs for safety factor calculations using both the limit equilibrium method and the strength reduction method. The methodology comprises three main steps: problem definition (detailing the engineering scenario and guiding ChatGPT to generate a conceptual diagram)

algorithm design (elaborating the computational problem and prompting ChatGPT to provide effective solutions)

and code implementation (generating feasible programming solutions based on computational theory). At each stage

ChatGPT provides intelligent suggestions

which are supplemented by manual review to ensure the theoretical accuracy and engineering feasibility of the calculation results. As demonstrated through three-dimensional slope stability analysis

the Python algorithm generated based on ChatGPT achieves a maximum relative error of 4.99% when compared with commercial software results

confirming its high calculation accuracy. This study introduces an innovative approach to engineering computations

underscoring the significant application prospects of artificial intelligence in civil engineering.