Write a news-style post for a Telegram channel, tailored for a Ukrainian audience. Format the text in Markdown and use appropriate emojis to make it engaging and lively. Answer in Ukrainian. If the text does not contain information about Python innovation, return only the word 'False'. The post should not include any promotional content. Add hashtags at the end.At the end, add a link to the original source (https://arxiv.org/abs/2411.08932).

Text to generate the news post:
[2411.08932] PyGen: A Collaborative Human-AI Approach to Python Package Creation                                         Skip to main content      We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate       > cs > arXiv:2411.08932         Help | Advanced Search     All fields Title Author Abstract Comments Journal reference ACM classification MSC classification Report number arXiv identifier DOI ORCID arXiv author ID Help pages Full text     Search                open search       GO    open navigation menu   quick links  Login Help Pages About             Computer Science > Software Engineering   arXiv:2411.08932 (cs)            [Submitted on 13 Nov 2024] Title:PyGen: A Collaborative Human-AI Approach to Python Package Creation Authors:Saikat Barua, Mostafizur Rahman, Md Jafor Sadek, Rafiul Islam, Shehnaz Khaled, Md. Shohrab Hossain View a PDF of the paper titled PyGen: A Collaborative Human-AI Approach to Python Package Creation, by Saikat Barua and 5 other authors View PDF HTML (experimental)  Abstract:The principles of automation and innovation serve as foundational elements for advancement in contemporary science and technology. Here, we introduce Pygen, an automation platform designed to empower researchers, technologists, and hobbyists to bring abstract ideas to life as core, usable software tools written in Python. Pygen leverages the immense power of autoregressive large language models to augment human creativity during the ideation, iteration, and innovation process. By combining state-of-the-art language models with open-source code generation technologies, Pygen has significantly reduced the manual overhead of tool development. From a user prompt, Pygen automatically generates Python packages for a complete workflow from concept to package generation and documentation. The findings of our work show that Pygen considerably enhances the researcher's productivity by enabling the creation of resilient, modular, and well-documented packages for various specialized purposes. We employ a prompt enhancement approach to distill the user's package description into increasingly specific and actionable. While being inherently an open-ended task, we have evaluated the generated packages and the documentation using Human Evaluation, LLM-based evaluation, and CodeBLEU, with detailed results in the results section. Furthermore, we documented our results, analyzed the limitations, and suggested strategies to alleviate them. Pygen is our vision of ethical automation, a framework that promotes inclusivity, accessibility, and collaborative development. This project marks the beginning of a large-scale effort towards creating tools where intelligent agents collaborate with humans to improve scientific and technological development substantially. Our code and generated examples are open-sourced at [this https URL]          Comments: 33 pages, 13 figures   Subjects:  Software Engineering (cs.SE); Artificial Intelligence (cs.AI)  Cite as: arXiv:2411.08932 [cs.SE]     (or  arXiv:2411.08932v1 [cs.SE] for this version)                 https://doi.org/10.48550/arXiv.2411.08932   Focus to learn more                      arXiv-issued DOI via DataCite        Submission history From: Mostafizur Rahman [view email]       [v1]         Wed, 13 Nov 2024 03:16:18 UTC (1,224 KB)       Full-text links: Access Paper:   View a PDF of the paper titled PyGen: A Collaborative Human-AI Approach to Python Package Creation, by Saikat Barua and 5 other authorsView PDFHTML (experimental)TeX SourceOther Formats   view license         Current browse context: cs.SE   < prev    |    next >   new  |  recent  | 2024-11      Change to browse by:      cs cs.AI     References & Citations  NASA ADSGoogle Scholar Semantic Scholar     a export BibTeX citation Loading...     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