Abstract: Currently, most RAGs are cloud-based and include Bedrock. However, there is a trend to return from the cloud to on-premises due to security concerns. In addition, it is common for APIs to call Lambda or EC2 for data access, but it is not easy to select the optimal framework depending on the data attributes. For this reason, the author devised a system for selecting the optimal framework using an AI agent. Furthermore, the author decided to use Dify, which is based on a DSL, as the user interface for the on-premises version of RAG, and ollama as a large-scale language model that can be installed on-premises as well. The author also considered the specifications of the hardware required to build this RAG and confirmed the feasibility of implementation.

Kohei Arai, “Design of On-Premises Version of RAG with AI Agent for Framework Selection Together with Dify and DSL as Well as Ollama for LLM” International Journal of Advanced Computer Science and Applications(IJACSA), 15(12), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151212

@article{Arai2024,
title = {Design of On-Premises Version of RAG with AI Agent for Framework Selection Together with Dify and DSL as Well as Ollama for LLM},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151212},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151212},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {12},
author = {Kohei Arai}
}