Visual programming has the potential of providing novice programmers with a low-code experience to build customized processing pipelines. Existing systems typically require users to build pipelines from scratch, implying that novice users are expected to set up and link appropriate nodes from a blank workspace. In this paper, we introduce InstructPipe, an AI assistant for prototyping machine learning (ML) pipelines with text instructions. We contribute two large language model (LLM) modules and a code interpreter as part of our framework. The LLM modules generate pseudocode for a target pipeline, and the interpreter renders the pipeline in the node-graph editor for further human-AI collaboration. Both technical and user evaluation (N=16) shows that InstructPipe empowers users to streamline their ML pipeline workflow, reduce their learning curve, and leverage open-ended commands to spark innovative ideas.

翻译：可视化编程有望为编程新手提供低代码体验，以构建定制化处理流程。现有系统通常要求用户从零开始搭建流程，这意味着新手用户需要从空白工作区中设置并连接合适的节点。本文提出InstructPipe，一种基于文本指令快速构建机器学习流程的AI助手。我们贡献了两个大语言模型模块与一个代码解释器作为框架核心。大语言模型模块为目标流程生成伪代码，解释器则在节点图编辑器中渲染流程，以支持进一步的人机协作。技术评估与用户评估（N=16）均表明，InstructPipe能帮助用户优化机器学习流程工作流、降低学习门槛，并通过开放式指令激发创新思路。