Presentation
Chameleon Concierge: Retrieval-Augmented Generation (RAG) To Enhance Open Testbed Documentation
DescriptionResearchers in high performance computing (HPC) and cloud environments encounter disparate sources of documentation and difficulties finding accurate information. This can cause inefficiency, increase the reliance on support teams, and change the focus of the researcher from the main experiment. To address these challenges, we developed an AI-powered search system leveraging large language models (LLMs) with retrieval-augmented generation (RAG) to unify various documentation sources and provide accurate, context-aware answers with cited references to relevant sources. We evaluated our RAG system with Chameleon Cloud testbed documentation as a case study, finding that our RAG system outperforms other generic LLMs in answering a variety of user questions and performs comparable to proprietary LLMs when properly tuned and optimized.
Event Type
Research and ACM SRC Posters
TimeThursday, 20 November 20258:00am - 5:00pm CST
LocationSecond Floor Atrium
Archive
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