OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction

Agent Multi-agent Collaboration Autonomous Workflows
2026年04月28日
在复杂的工业环境中部署可投入生产使用的多智能体系统(MAS)仍面临诸多挑战,主要体现在可扩展性、可观测性以及自主演进能力等方面的固有局限。本文提出 OxyGent——一个开源框架,其核心创新在于两项关键技术:统一的“Oxy”抽象模型与“OxyBank”演进引擎。该统一抽象模型将智能体、工具、大语言模型(LLM)及推理流程统一封装为可插拔的原子化组件,从而支持类似乐高积木式的灵活系统构建,并实现对系统运行状态的非侵入式监控。为提升可观测性,OxyGent 引入了基于权限驱动的动态规划机制,以运行时动态生成的执行图替代僵化的预设工作流,进而提供自适应的可视化分析能力。此外,为支撑系统的持续演进,OxyBank 作为一个人工智能资产统一管理平台,可驱动自动化数据回传、智能标注以及模型与系统组件的协同演进。实证评估与多个真实工业场景案例表明,OxyGent 为多智能体系统提供了坚实、可靠且高度可扩展的基础架构。OxyGent 已依据 Apache License 2.0 协议完全开源,项目地址为:https://github.com/jd-opensource/OxyGent。
Deploying production-ready multi-agent systems (MAS) in complex industrial environments remains challenging due to limitations in scalability, observability, and autonomous evolution. We present OxyGent, an open-source framework driven by two core novelties: a unified Oxy abstraction and the OxyBank evolution engine. The unified abstraction encapsulates agents, tools, LLMs, and reasoning flows as pluggable atomic components, enabling Lego-like scalable system composition and non-intrusive monitoring. To enhance observability, OxyGent introduces permission-driven dynamic planning that replaces rigid workflows with execution graphs generated at runtime, providing adaptive visualizations. Furthermore, to support continuous evolution, OxyBank serves as an AI asset management platform that drives automated data backflow, annotation, and joint evolution. Empirical evaluations and real-world case studies show that OxyGent provides a robust and scalable foundation for MAS. OxyGent is fully open-sourced under the Apache License 2.0 at https://github.com/jd-opensource/OxyGent.
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