CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers?

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Xehetasun bibliografikoak
Argitaratua izan da:	arXiv.org (Dec 18, 2024), p. n/a
Egile nagusia:	Mallis, Dimitrios
Beste egile batzuk:	Karadeniz, Ahmet Serdar, Cavada, Sebastian, Rukhovich, Danila, Foteinopoulou, Niki, Cherenkova, Kseniya, Anis Kacem, Aouada, Djamila
Argitaratua:	Cornell University Library, arXiv.org
Gaiak:	Solvers Python Modules Computer aided design > CAD Large language models
Sarrera elektronikoa:	Citation/Abstract Full text outside of ProQuest
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Deskribapena
Laburpena:	We propose CAD-Assistant, a general-purpose CAD agent for AI-assisted design. Our approach is based on a powerful Vision and Large Language Model (VLLM) as a planner and a tool-augmentation paradigm using CAD-specific modules. CAD-Assistant addresses multimodal user queries by generating actions that are iteratively executed on a Python interpreter equipped with the FreeCAD software, accessed via its Python API. Our framework is able to assess the impact of generated CAD commands on geometry and adapts subsequent actions based on the evolving state of the CAD design. We consider a wide range of CAD-specific tools including Python libraries, modules of the FreeCAD Python API, helpful routines, rendering functions and other specialized modules. We evaluate our method on multiple CAD benchmarks and qualitatively demonstrate the potential of tool-augmented VLLMs as generic CAD task solvers across diverse CAD workflows.
ISSN:	2331-8422
Baliabidea:	Engineering Database