This paper introduces a computing framework that combines Flow-Based Programming (FBP) and Large Language Models (LLMs) to enable Just-In-Time Programming (JITP). JITP empowers users, regardless of their programming expertise, to actively participate in the development and automation process by leveraging their task-time algorithmic insights. By seamlessly integrating LLMs into the FBP workflow, the framework allows users to request and generate code in real-time, enabling dynamic code execution within a flow-based program. The paper explores the motivations, principles, and benefits of JITP, showcasing its potential in automating tasks, orchestrating data workflows, and accelerating software development. Through a fully implemented JITP framework using the Composable platform, we explore several examples and use cases to illustrate the benefits of the framework in data engineering, data science and software development. The results demonstrate how the fusion of FBP and LLMs creates a powerful and user-centric computing paradigm.

翻译：本文提出了一种结合流式编程（FBP）与大语言模型（LLM）的计算框架，用于实现即时编程（JITP）。JITP赋予用户（无论其编程能力如何）通过利用任务时算法洞察力积极参与开发和自动化过程的能力。通过将LLM无缝集成到FBP工作流中，该框架允许用户实时请求和生成代码，从而在流式程序中实现动态代码执行。本文探讨了JITP的动机、原理和优势，展示了其在任务自动化、数据工作流编排及加速软件开发中的潜力。基于Composable平台实现的全功能JITP框架，我们通过数据工程、数据科学和软件开发中的多个示例及用例，阐述了该框架的优势。结果表明，FBP与LLM的融合创造了一种强大且以用户为中心的计算范式。