用自然语言对话自动生成可执行的数据迁移配置
LeafData: An Agentic System for Data Migration
- 通过对话逐步收集用户需求并验证数据结构
- 支持关系型数据库、文件系统等多源数据迁移
- 生成的配置可直接被调度平台使用，无需手动编码
现代数据迁移依赖JSON配置来定义数据连接、管道逻辑和编排行为，需要用户具备领域知识，过程耗时且易出错。本文提出LeafData，一个智能系统，将用户意图转化为经过验证的可执行JSON配置。LeafData由前端聊天机器人和后端服务组成：聊天机器人逐步收集信息并进行基于模式的验证，后端服务处理已验证输入并生成可被编排平台直接使用的JSON配置文件。该系统支持跨多种数据源和连接器的异构数据迁移，包括关系型数据库、文件系统、文档型数据库及REST API，实现从意图到管道执行的端到端自动化。
原文摘要 · Abstract (English)
Modern data migration relies on JSON configuration to define data connection, pipeline logic, and orchestration behavior. This requires domain knowledge from users and is time-consuming and error-prone. In this paper, we present LeafData, an agentic system that converts user intent into validated and executable JSON configuration for data migration. Specifically, LeafData comprises a frontend chatbot and the backend service. The chatbot incrementally collects required information from users and performs schema-driven validation, while the backend service processes validated inputs and generates JSON configuration artifacts. These artifacts are directly consumable by orchestration platforms, enabling end-to-end pipeline generation and execution without manual coding. LeafData supports heterogeneous data migration across various data sources and connectors including relational databases, file-based systems, document-oriented databases, and REST APIs.
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