PlanGPT: Enhancing Urban Planning with Tailored Language Model and
  Efficient Retrieval
He Zhu Wenjia Zhang Nuoxian Huang Boyang Li Luyao Niu Zipei Fan Tianle Lun Yicheng Tao Junyou Su Zhaoya Gong Chenyu Fang Xing Liu
In the field of urban planning, general-purpose large language models often
struggle to meet the specific needs of planners. Tasks like generating urban
planning texts, retrieving related information, and evaluating planning
documents pose unique challenges. To enhance the efficiency of urban
professionals and overcome these obstacles, we introduce PlanGPT, the first
specialized Large Language Model tailored for urban and spatial planning.
Developed through collaborative efforts with institutions like the Chinese
Academy of Urban Planning, PlanGPT leverages a customized local database
retrieval framework, domain-specific fine-tuning of base models, and advanced
tooling capabilities. Empirical tests demonstrate that PlanGPT has achieved
advanced performance, delivering responses of superior quality precisely
tailored to the intricacies of urban planning.