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.

翻译：基于大语言模型的生成式AI系统近年来取得了显著进展。通过集成知识检索架构，无需额外模型微调即可将私有数据无缝整合到使用预训练LLM的公开生成式AI系统中。此外，以检索为核心的生成范式——将LLM与检索器在语境理解与知识记忆中的角色明确分离——作为未来极具前景的研究方向，有望实现更高效的部署。SimplyRetrieve是一个开源工具，旨在为机器学习社区提供本地化、轻量级且用户友好的接口以应用这些前沿技术。该工具搭载了基于图形界面和API的RCG平台，并配有私有知识库构建器与检索调优模块。借助这些功能，用户可在维护隐私标准的同时探索RCG对生成式AI性能提升的潜力。该工具以MIT许可证发布于https://github.com/RCGAI/SimplyRetrieve。