LLM-based Conversational Assistant for Intent-driven Management

This paper focuses on how the concepts conceptualized by ETSI ZSM in the Intent Management project and TM Forum in the Autonomous Networks project have been adopted and enhanced by 6G-INTENSE. Specifically, we demonstrate how intent translation, decomposition, and propagation have been realized across the operational domains of the architecture, to control the management and orchestration of resources at the infrastructure level. We propose an LLM-based Conversational Assistant (Chatbot) for Intent-driven Management to ease the process of Service Ordering by Verticals. Our Chatbot intelligently translates natural language requests into business requests, which are subsequently processed to generate actions at the infrastructure level, as demonstrated in the results section