Network topology construction in this paper refers to designing the structural layouts and configuration rules among network devices according to natural language requirements in network simulation. Relatedly, Infrastructure as Code (IaC) enables the configuration and management of network devices through machine-readable code. Although there exist IaC generation approaches powered by Large Language Models (LLMs), they only focus on generating isolated configurations without consideration for holistic topology structure, leading to failure to form a complete, functional topology. Additionally, due to the LLMs’ limited knowledge of industry-specific device images, existing approaches struggle to adapt to diverse industry scenarios.

In this paper, we introduce IntelliTopo, which, to the best of our knowledge, is the first IaC generation framework targeted at industrial network topology construction. Specifically, IntelliTopo enhances the capabilities of LLMs through two novel mechanisms: (1) Through \textit{semantic topology parsing}, we enhance the LLMs’ understanding of the holistic topology structure; (2) Through \textit{domain-aware image retrieval}, the outputs of IntelliTopo are more aligned with real-world industry scenarios. Deployed on our PaaS system, the IntelliTopo service has operated continuously for 3 months, handling 50+ network simulation tasks across 10+ industries. IntelliTopo reduces average network topology deployment time from days to hours while requiring less computational power for LLM reasoning. This work bridges the gap between high-level requirements and executable infrastructure, providing a scalable solution for network topology construction.