AI辅助个人笔记系统的设计与实现

AI-Assisted Personal Note Management System: Design and Implementation

摘要: 随着数字化学习与办公的日益普及，个人笔记软件已成为用户整理知识、沉淀信息的重要工具。然而，当笔记数量急剧增长时，传统笔记软件偏重记录而缺乏智能辅助的短板日益凸显，用户难以快速从海量内容中提取关键信息。针对该问题，本文设计并实现了一款AI辅助的个人笔记管理系统，旨在通过轻量级自然语言处理技术的本地化部署，为用户提供更智能、更安全的笔记管理体验。系统不仅实现了层级文件夹、富文本编辑、版本控制、全文搜索、标签管理、附件上传与在线预览等基础功能，还借助KeyBERT与ONNX Runtime在本地运行，自动完成笔记关键词提取、摘要生成及智能标签推荐，所有AI处理均在用户本地完成，确保数据隐私无泄露。同时，系统支持带密码与权限的笔记分享、评论与@通知、分享数据统计等协作模块，兼顾个人效率与团队交流。后端采用Django与Django REST Framework，通过JWT实现用户认证，数据库选用PostgreSQL (开发阶段兼容SQLite)；前端基于Vue 3与TypeScript，并借助Electron打包为跨平台桌面应用，兼顾可扩展性与日常使用便捷性。整体而言，本系统在满足笔记管理基本需求的基础上，借助本地AI能力有效减轻了用户整理信息的负担，提升了信息检索与回顾的效率，为隐私优先的智能笔记工具设计提供了可行参考。

Abstract: With the increasing prevalence of digital learning and office work, personal note-taking software has become an important tool for users to organize knowledge and store information. However, as the number of notes grows rapidly, traditional note-taking software—which emphasizes recording functions but lacks intelligent assistance—has become increasingly inadequate, making it difficult for users to quickly extract key information from massive amounts of content. To address this issue, this paper designs and implements an AI-assisted personal note management system that leverages the local deployment of lightweight natural language processing technologies to provide users with a more intelligent and more secure note management experience. The system not only implements basic functions such as hierarchical folders, rich-text editing, version control, full-text search, tag management, file attachment upload and online preview, but also leverages KeyBERT and ONNX Runtime to run locally, automatically performing keyword extraction, summarization, and intelligent tag recommendation for notes. All AI processing is completed on the user’s local machine, ensuring that data privacy remains uncompromised. In addition, the system supports note sharing with password and permission control, comments with @mentions, and sharing statistics, addressing both personal productivity and team collaboration needs. The backend is built with Django and Django REST Framework, with JWT for user authentication, and PostgreSQL as the database (SQLite is supported during development). The frontend is developed with Vue 3 and TypeScript, and packaged as a cross-platform desktop application using Electron, balancing extensibility with ease of daily use. Overall, while meeting the basic requirements of note management, this system effectively reduces the burden of information organization for users through local AI capabilities, improves the efficiency of information retrieval and review, and provides a feasible reference for the design of privacy-first intelligent note-taking tools.