{"ID":2844051,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.07257","arxiv_id":"2511.07257","title":"Bridging the Prototype-Production Gap: A Multi-Agent System for Notebooks Transformation","abstract":"The increasing adoption of Jupyter notebooks in data science and machine learning workflows has created a gap between exploratory code development and production-ready software systems. While notebooks excel at iterative development and visualization, they often lack proper software engineering principles, making their transition to production environments challenging. This paper presents Codelevate, a novel multi-agent system that automatically transforms Jupyter notebooks into well-structured, maintainable Python code repositories. Our system employs three specialized agents - Architect, Developer, and Structure - working in concert through a shared dependency tree to ensure architectural coherence and code quality. Our experimental results validate Codelevate's capability to bridge the prototype-to-production gap through autonomous code transformation, yielding quantifiable improvements in code quality metrics while preserving computational semantics.","short_abstract":"The increasing adoption of Jupyter notebooks in data science and machine learning workflows has created a gap between exploratory code development and production-ready software systems. While notebooks excel at iterative development and visualization, they often lack proper software engineering principles, making their...","url_abs":"https://arxiv.org/abs/2511.07257","url_pdf":"https://arxiv.org/pdf/2511.07257v1","authors":"[\"Hanya Elhashemy\",\"Youssef Lotfy\",\"Yongjian Tang\"]","published":"2025-11-10T16:05:10Z","proceeding":"cs.SE","tasks":"[\"cs.SE\",\"cs.MA\"]","methods":"[\"LoRA\"]","has_code":false}