Simplyretrieve: A Private And Lightweight Retrieval-centric Generative AI Tool

Ng Youyang, Miyashita Daisuke, Hoshi Yasuto, Morioka Yasuhiro, Torii Osamu, Kodama Tomoya, Deguchi Jun. Arxiv 2023

[Paper] [Code]    
Fine Tuning Has Code Model Architecture Pretraining Methods RAG Tools Training Techniques

Large Language Model (LLM) based Generative AI systems have seen significant progress in recent years. Integrating a knowledge retrieval architecture allows for seamless integration of private data into publicly available Generative AI systems using pre-trained LLM without requiring additional model fine-tuning. Moreover, Retrieval-Centric Generation (RCG) approach, a promising future research direction that explicitly separates roles of LLMs and retrievers in context interpretation and knowledge memorization, potentially leads to more efficient implementation. SimplyRetrieve is an open-source tool with the goal of providing a localized, lightweight, and user-friendly interface to these sophisticated advancements to the machine learning community. SimplyRetrieve features a GUI and API based RCG platform, assisted by a Private Knowledge Base Constructor and a Retrieval Tuning Module. By leveraging these capabilities, users can explore the potential of RCG for improving generative AI performance while maintaining privacy standards. The tool is available at https://github.com/RCGAI/SimplyRetrieve with an MIT license.

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