Abstract
Large Language Models (LLMs) can be used in a variety of environments to enhance user experience/understanding of information related to different scenarios. However, in the context of software-defined fabric management and/or design tasks, an LLM may provide responses to fabric management/design queries that may be of limited use to a network operator. Proposed herein are techniques for augmenting dynamic runtime information (e.g., topology, configuration, events, etc.) of a software-defined fabric to an LLM using a vector database to enable the LLM to provide recommendations to a user/administrator of the fabric that are based on the context as opposed to providing general, generic answers that are typically provided by LLMs.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
C Jain, Prakash and K Hooda, Sanjay, "CREATION/EXTENSION OF SOFTWARE-DEFINED FABRIC USING NETWORKING LLMS WITH AUGMENTED LEARNING", Technical Disclosure Commons, (June 27, 2024)
https://www.tdcommons.org/dpubs_series/7144