Design and Practice of Integrating Large Models with Low-Code Platforms

Authors

  • Pan Luo
  • Jiaojiao Wan

Keywords:

Large Model; Low-Code Platform; Intelligent Development; Code Generation; Natural Language Processing (NLP)

Abstract

With the rapid advancement of artificial intelligence technology, Large Language Models (LLMs) have gradually become a significant driving force in the intelligentization of software development. Meanwhile, low-code platforms have gained widespread adoption in enterprise information system construction due to their rapid development capabilities and ease of use. However, existing low-code platforms still exhibit limitations in terms of flexibility and intelligence. To address these issues, this paper proposes an intelligent development tool that integrates large language models with low-code platforms. Leveraging the natural language understanding and code generation capabilities of large language models, this approach significantly enhances the intelligence of low-code platforms. The paper elaborates on the design principles, key technical implementations, and practical application effects of the proposed intelligent development tool. Furthermore, the effectiveness of this method is validated through practical case studies.

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Published

2025-09-13

How to Cite

Luo, P., & Wan, J. (2025). Design and Practice of Integrating Large Models with Low-Code Platforms. Journal of Intelligent Machinery and Equipment, 1(1). Retrieved from https://masonpublish.org/index.php/Journal-of-Intelligent-Machinery/article/view/379

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