AI 中文总结
研究针对GUI原型制作耗时问题，提出AI Prototyper插件，通过分解和检索增强生成管道，结合特定技术栈与大语言模型，经人工参与编辑步骤，能多语言输入，在时间和质量维度上表现良好。
AI 中文摘要
图形用户界面（GUI）原型制作仍然是一项耗时的活动，需要设计专业知识和大量的人工努力。由于GUI原型是非代码工件，在整个开发周期中会随着需求的变化而演变，因此自动化生成与软件维护和演进直接相关。我们展示了AI原型制作器，这是一个开源的Figma插件，它通过分解和检索增强生成（RAG）管道实现GUI原型制作的自动化。给定所需屏幕的自然语言描述，如登录页面或产品详细信息卡，该插件将请求分解为离散的GUI功能，从自定义的32个原语库中检索匹配的组件，并将每个组件渲染为具有自动布局的完全可编辑的Figma层。该管道使用Gemini 2.5 Flash作为其大语言模型后端和一个此http URL服务。与现有的基于分解的工具不同，AI原型制作器引入了一个人工参与的编辑步骤，让用户在渲染之前审查、修改或扩展生成的功能列表，使用不同的技术栈和大语言模型家族，并支持多语言输入，能生成泰语、英语和中文的正确标注的界面。在初步评估中，使用AI原型制作器的参与者在固定时间窗口内完成的原型比手动制作的更多，并且专家从业者在九个质量维度上对人工智能生成的原型评价更高。
英文摘要
Graphical user interface (GUI) prototyping remains a time-consuming activity that demands both design expertise and considerable manual effort. As GUI prototypes are non-code artifacts that evolve alongside requirements throughout the development cycle, automating their generation is directly relevant to software maintenance and evolution. We present AI Prototyper, an open-source Figma plugin that automates GUI prototyping through a decomposition and retrieval-augmented generation (RAG) pipeline. Given a natural-language description of a desired screen, such as a login page or a product detail card, the plugin decomposes the request into discrete GUI features, retrieves matching components from a custom 32-primitive library, and renders each component as a fully editable Figma layer with auto-layout. The pipeline uses Gemini 2.5 Flash as its LLM back-end and a Node.js Express service. Unlike existing decomposition-based tools, AI Prototyper introduces a human-in-the-loop editing step that lets users review, modify, or extend the generated feature list before rendering, uses a different technology stack and LLM family, and supports multilingual input, producing correctly labelled interfaces in Thai, English, and Mandarin Chinese. In a preliminary evaluation, participants using AI Prototyper completed more prototypes in a fixed time window than those working manually, and expert practitioners rated the AI-generated prototypes higher across nine quality dimensions. A demonstration video is available at https://youtu.be/pRoFAH7MQaE. The source code and component library are available at https://github.com/tongsalangsingha/AI-prototyper-tool
CommentsAccepted at the 42nd IEEE International Conference on Software Maintenance and Evolution (ICSME 2026), Tool Demonstration and Data Showcase Track
