Visual programming provides beginner-level programmers with a coding-free experience to build their customized pipelines. Existing systems require users to build a pipeline entirely from scratch, implying that novice users need to set up and link appropriate nodes all by themselves, starting from a blank workspace. We present InstructPipe, an AI assistant that enables users to start prototyping machine learning (ML) pipelines with text instructions. We designed two LLM modules and a code interpreter to execute our solution. LLM modules generate pseudocode of a target pipeline, and the interpreter renders a pipeline in the node-graph editor for further human-AI collaboration. Technical evaluations reveal that InstructPipe reduces user interactions by 81.1% compared to traditional methods. Our user study (N=16) showed that InstructPipe empowers novice users to streamline their workflow in creating desired ML pipelines, reduce their learning curve, and spark innovative ideas with open-ended commands.

翻译：可视化编程为初级程序员提供了无需编码即可构建定制化管道的体验。现有系统要求用户从零开始构建管道，这意味着新手用户需从空白工作区出发，自行设置并连接相应节点。我们提出InstructPipe——一款让用户能够通过文本指令启动机器学习（ML）管道原型设计的AI助手。我们设计了两个大语言模型模块和一个代码解释器以执行本方案。LLM模块生成目标管道的伪代码，解释器则在节点图编辑器中渲染管道，支持后续人机协作。技术评估表明，与传统方法相比，InstructPipe将用户交互次数减少了81.1%。我们的用户研究（N=16）显示，InstructPipe使新手用户能够简化创建所需ML管道的工作流程，降低学习曲线，并通过开放式指令激发创新思维。