让AI自动完成从数据到报告的全流程分析，全程可追踪、可调试。
DA-Studio: An Agentic System for End-to-End Data Analysis
- 基于动作结构的后端，自动生成并执行分析步骤
- 在沙箱环境运行代码，保证安全且结果可验证
- 适合需要透明流程和可复现结果的研究人员
真实世界的数据分析是涉及异构输入的多步骤过程，而不仅仅是生成最终答案。一个实用的系统应能自主组织多步工作流，在受控沙箱环境中执行生成的代码，并通过可见的操作日志和中间产物保持可追溯性。现有基于大模型的分析工具往往只关注孤立子任务，缺乏对完整执行型工作流的支持。我们提出DA-Studio（数据分析工作室），一个交互式Web演示系统，实现端到端的数据分析，具备自主性、沙箱化和可追溯性。DA-Studio集成动作结构化的分析后端、沙箱执行环境及浏览器界面，支持任务配置、流式操作日志、中间产物预览、代码编辑与重运行、报告导出等功能。通过迭代的动作生成、代码执行与反馈整合，它从原始文件和自然语言请求中逐步构建可执行的分析步骤，并在整个过程中公开中间结果与产出物。
原文摘要 · Abstract (English)
Real-world data analysis is a multi-step process over heterogeneous inputs rather than merely producing a final answer. A practical system should autonomously organize multi-step workflows, execute generated code in a sandboxed and controllable environment, and remain inspectable through visible action traces and intermediate artifacts. Existing LLM-based analysis tools, however, often emphasize isolated subtasks, leaving limited support for complete execution-grounded workflows. We present DA-Studio (Data Analysis Studio), an interactive web-based demo system for end-to-end data analysis that is autonomous, sandboxed, and inspectable. DA-Studio integrates an action-structured analysis backend, a sandboxed execution workspace, and a browser interface for task setup, streamed action traces, artifact preview, code editing and rerunning, and report export. Through iterative action generation, code execution, and feedback incorporation, it incrementally constructs executable analysis steps from raw files and natural-language requests while exposing intermediate results and artifacts throughout the process.
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