Extended Abstract: Enhancing Accessibility to MODTRAN Documentation: A Chatbot Framework Using Retrieval-Augmented Generation (RAG)
This work presents the development of a chatbot using Retrieval-Augmented Generation (RAG) to streamline access to MODerate resolution atmospheric TRANsmission (MODTRAN)'s extensive documentation. By combining document retrieval with a Large Language Model (LLM), the chatbot delivers accurate, context-aware answers to user queries. Key resources, including the MODTRAN6 User Manual, Algorithm Theoretic Basis Document (ATBD), and the frequently asked questions section from the MODTRAN website, were processed into a searchable vector database. The evaluation showed that the chatbot effectively provides satisfactory and accurate responses, though occasional extraneous information highlights the need for refinement.
Authors
- Emily Dunkel (ORCID: https://orcid.org/0000-0002-9105-5458)
- Debzani Deb (ORCID: https://orcid.org/0000-0002-3430-1130)
- Zarin T. Shejuti
Institutions
- Jet Propulsion Laboratory (US)
- Winston-Salem State University (US)
Publication Details
- Published
- 2025-03-22
- DOI
- https://doi.org/10.1109/southeastcon56624.2025.10971575
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00