ConfigTransLE: Large Language Models Enhanced Network Configuration Translation

Abstract

Network device replacement, relocation, and vendor migration often require existing configurations to be translated to devices from different manufacturers while preserving network policies and operational behaviors. However, manual configuration translation is labor-intensive and requires substantial expertise, especially for large-scale configurations. To address this problem, we propose ConfigTransLE, a large-language-model-enhanced network configuration translation framework. ConfigTransLE consists of four main components: parameter corresponding, command translation, command arrangement, and LLM-adviser. Specifically, for commands with parameters, we combine heuristic translation with an LLM-based command filling module to construct executable target commands under command-format and manual constraints. For commands without parameters, we use semantic retrieval and LLM-based selection to determine the target command and its keywords. To satisfy vendor-specific view requirements, the translated commands are further arranged according to the target command hierarchy. In addition, an LLM-adviser is introduced to identify remaining semantic or logical issues and perform one additional repair attempt on the translation result. We evaluate ConfigTransLE on three translation tasks, Huawei-to-Nokia, Juniper-to-Huawei, and Cisco-to-Huawei, covering multiple protocols and configuration granularities. Experimental results show that ConfigTransLE achieves high command-level translation accuracy across different tasks. We further compare different LLM backends and analyze their trade-offs between translation accuracy and inference cost. In addition, simulator-based deployment validation on the Juniper-to-Huawei task provides additional evidence regarding the practical deployability of translated configurations and highlights the gap between text-level correctness and actual deployment constraints. These results show that ConfigTransLE is an effective and practical framework for cross-vendor network configuration translation.