📄 中文摘要
构建了一个检索增强生成（RAG）系统，能够快速回答关于2026年伊朗-美国冲突对全球民航影响的自然语言问题，并提供准确的、基于来源的答案。该系统的架构设计、决策过程及所获得的经验教训被详细阐述。通过实时演示，用户可以直接体验该应用的功能，同时源代码也在GitHub上公开，供开发者学习和参考。
从零开始构建 RAG 系统：将航空干扰数据转化为 AI 驱动的问答应用
📄 English Summary
Building a RAG System from Scratch: Turning Aviation Disruption Data into an AI-Powered Q&A App
A Retrieval-Augmented Generation (RAG) system has been developed to answer natural language questions regarding the impact of the 2026 Iran-US conflict on global civil aviation, providing accurate, source-backed responses in seconds. The article details the architecture of the system, the decisions made during its development, and the lessons learned throughout the process. A live demo allows users to experience the application firsthand, while the source code is publicly available on GitHub for developers to study and reference.