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An Adaptable AI Assistant for Network Management

Published

Author(s)

Amar Abane, Abdella Battou, Mheni Merzouki

Abstract

This paper presents a network management AI assistant built with Large Language Models. It adapts at runtime to the network state and specific platform, leveraging techniques like prompt engineering, document retrieval, and Knowledge Graph integration. The AI assistant aims to simplify management tasks and is easily reproducible with available source code.
Conference Dates
May 6-10, 2024
Conference Location
Seoul, KR
Conference Title
IEEE/IFIP Network Operations and Management Symposium

Keywords

LLMs, text embeddings, RAG, network management, knowledge graph, Neo4j, graph database

Citation

Abane, A. , Battou, A. and Merzouki, M. (2024), An Adaptable AI Assistant for Network Management, IEEE/IFIP Network Operations and Management Symposium, Seoul, KR (Accessed May 26, 2024)

Issues

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Created April 12, 2024