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

TL;DR

OxyGent is an open-source framework that enhances multi-agent systems with modularity, observability, and evolvability through a unified abstraction and an evolution engine, demonstrated via empirical evaluations.

Contribution

It introduces a unified Oxy abstraction and OxyBank engine, enabling scalable, observable, and evolvable multi-agent systems with dynamic planning and asset management.

Findings

Empirical evaluations demonstrate robustness and scalability.

Real-world case studies validate system effectiveness.

Framework facilitates continuous evolution of MAS.

Abstract

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.