Date of Graduation

7-2026

Document Type

Thesis

Degree Name

Master of Science in Computer Science (MS)

Degree Level

Graduate

Department

Computer Science & Computer Engineering

Advisor/Mentor

Gauch, John

Committee Member

Luu, Khoa

Second Committee Member

Gauch, Susan

Keywords

CAD Models, LLM, Domain Specific Contraints (DSC)

Abstract

This paper presents a method to generate feature-based parametric mechanical CAD models from text input. The method uses domain-specific constraints (DSCs) to guide a large language model (LLM) in the generation of scripts to build models from the CAD API. It also presents a framework for an iterative text-based system that produces parametric CAD models. The method was implemented by developing DSCs for FreeCAD and Open AI GPT-5.2 and incorporated into a web-based software application which generates models that can be visualized with an interactive viewer after each iteration. Tests were run comparing various models with and without this method. Results show that a general LLM (like GPT-5.2) alone struggles to build all but the simplest CAD models. However, using DSCs is an effective way to enable a general LLM to generate more complex, feature-based CAD models from text input. An iterative modeling approach is shown to further increase model generation reliability.

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