從指令到提示：基於LLM的AIOS語義檔案系統

From Commands to Prompts: LLM-based Semantic File System for AIOS

September 23, 2024

作者: Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang

cs.AI

摘要

大型語言模型（LLMs）已展示在智能應用程式和系統的發展中具有顯著潛力，例如基於LLM的代理和代理操作系統（AIOS）。然而，當這些應用程式和系統與底層檔案系統互動時，檔案系統仍然保持傳統範式：依賴通過精確指令的手動導覽。這種範式對這些系統的可用性構成瓶頸，因為用戶需要導航複雜的資料夾層次結構並記住晦澀的檔案名稱。為了解決這個限制，我們提出了一個基於LLM的語義檔案系統（LSFS）用於基於提示的檔案管理。與傳統方法不同，LSFS整合了LLMs，使用戶或代理能夠通過自然語言提示與檔案互動，促進語義檔案管理。在宏觀層面，我們開發了一套全面的API集合，以實現語義檔案管理功能，例如語義檔案檢索、檔案更新監控和摘要，以及語義檔案回滾。在微觀層面，我們通過為檔案構建語義索引，設計並實現不同語義操作的系統調用（例如CRUD、分組、連接），並由向量資料庫提供支援。我們的實驗表明，LSFS在用戶便利性、支援功能的多樣性，以及檔案操作的準確性和效率方面，相對傳統檔案系統有顯著改進。此外，通過LLM的整合，我們的系統實現了更智能的檔案管理任務，例如內容摘要和版本比較，進一步增強了其功能。

English

Large language models (LLMs) have demonstrated significant potential in the development of intelligent applications and systems such as LLM-based agents and agent operating systems (AIOS). However, when these applications and systems interact with the underlying file system, the file system still remains the traditional paradigm: reliant on manual navigation through precise commands. This paradigm poses a bottleneck to the usability of these systems as users are required to navigate complex folder hierarchies and remember cryptic file names. To address this limitation, we propose an LLM-based semantic file system ( LSFS ) for prompt-driven file management. Unlike conventional approaches, LSFS incorporates LLMs to enable users or agents to interact with files through natural language prompts, facilitating semantic file management. At the macro-level, we develop a comprehensive API set to achieve semantic file management functionalities, such as semantic file retrieval, file update monitoring and summarization, and semantic file rollback). At the micro-level, we store files by constructing semantic indexes for them, design and implement syscalls of different semantic operations (e.g., CRUD, group by, join) powered by vector database. Our experiments show that LSFS offers significant improvements over traditional file systems in terms of user convenience, the diversity of supported functions, and the accuracy and efficiency of file operations. Additionally, with the integration of LLM, our system enables more intelligent file management tasks, such as content summarization and version comparison, further enhancing its capabilities.