Agent development kits (ADKs) provide effective platforms and tooling for constructing agents, and their designs are critical to the constructed agents' performance, especially the functionality for agent topology, tools, and memory. However, current ADKs either lack sufficient functional support or rely on humans to manually design these components, limiting agents' generalizability and overall performance. We propose OpenSage, the first ADK that enables LLMs to automatically create agents with self-generated topology and toolsets while providing comprehensive and structured memory support. OpenSage offers effective functionality for agents to create and manage their own sub-agents and toolkits. It also features a hierarchical, graph-based memory system for efficient management and a specialized toolkit tailored to software engineering tasks. Extensive experiments across three state-of-the-art benchmarks with various backbone models demonstrate the advantages of OpenSage over existing ADKs. We also conduct rigorous ablation studies to demonstrate the effectiveness of our design for each component. We believe OpenSage can pave the way for the next generation of agent development, shifting the focus from human-centered to AI-centered paradigms.

翻译：智能体开发套件（ADK）为构建智能体提供了有效的平台与工具，其设计对构建出的智能体性能至关重要，尤其是智能体拓扑结构、工具与记忆功能。然而，当前ADK要么缺乏足够的功能支持，要么依赖人工手动设计这些组件，限制了智能体的泛化能力与整体性能。我们提出了OpenSage——首个使大语言模型能够自动创建具有自生成拓扑与工具集的智能体，并提供全面结构化记忆支持的ADK。OpenSage为智能体提供了创建与管理自身子智能体及工具包的有效功能。它还具备基于图结构的层级化记忆系统以实现高效管理，以及专为软件工程任务定制的工具包。在三个前沿基准测试中使用多种骨干模型进行的大量实验证明了OpenSage相较于现有ADK的优势。我们还通过严格的消融实验验证了各组件设计的有效性。我们相信OpenSage能为下一代智能体开发铺平道路，将开发重心从以人为中心转向以AI为中心的模式。