Automated documentation of programming source code is a challenging task with significant practical and scientific implications for the developer community. We present a large language model (LLM)-based application that developers can use as a support tool to generate basic documentation for any publicly available repository. Over the last decade, several papers have been written on generating documentation for source code using neural network architectures. With the recent advancements in LLM technology, some open-source applications have been developed to address this problem. However, these applications typically rely on the OpenAI APIs, which incur substantial financial costs, particularly for large repositories. Moreover, none of these open-source applications offer a fine-tuned model or features to enable users to fine-tune. Additionally, finding suitable data for fine-tuning is often challenging. Our application addresses these issues which is available at https://pypi.org/project/readme-ready/.

翻译：编程源代码的自动化文档生成是一项具有挑战性的任务，对开发者社区具有重要的实践与科学意义。我们提出一个基于大语言模型的应用，开发者可将其作为辅助工具，为任何公开可用的代码库生成基础文档。过去十年间，已有若干研究论文探讨了使用神经网络架构生成源代码文档的方法。随着大语言模型技术的最新进展，一些开源应用已被开发用于解决此问题。然而，这些应用通常依赖OpenAI API，会产生高昂的经济成本，尤其对于大型代码库而言。此外，现有开源应用均未提供微调模型或允许用户进行微调的功能。同时，寻找适合微调的数据集也往往面临挑战。我们的应用解决了上述问题，可通过 https://pypi.org/project/readme-ready/ 获取。