AgentScope 1.0让开发者更轻松构建智能体应用。
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
- 抽象核心组件,提供统一接口和可扩展模块。
- 基于ReAct范式与异步设计,提升交互效率。
- 内置实用智能体,支持可视化开发与安全部署。
随着大语言模型的快速发展,智能体已具备结合内在知识与动态工具使用的能力,显著增强解决真实任务的能力。为此,AgentScope 1.0 在新版本中实现重大升级,全面支持灵活高效的工具化智能体-环境交互,助力构建智能体应用。我们抽象了智能体应用的核心组件,提供统一接口与可扩展模块,使开发者能便捷地集成最新模型和MCPs。同时,将智能体行为建立在ReAct范式基础上,基于系统性异步设计构建高级智能体级基础设施,丰富了人机与机机交互模式,并提升执行效率。在此基础上,集成多个针对具体场景的内置智能体。此外,提供可扩展的评估模块(带可视化界面),使长轨迹智能体应用的开发更易管理与追踪。还配备运行时沙箱,保障智能体安全执行,并支持快速生产部署。这些改进为构建可扩展、自适应、高效的智能体应用提供了实用基础。
原文摘要 · Abstract (English)
Driven by rapid advancements of Large Language Models (LLMs), agents are empowered to combine intrinsic knowledge with dynamic tool use, greatly enhancing their capacity to address real-world tasks. In line with such an evolution, AgentScope introduces major improvements in a new version (1.0), towards comprehensively supporting flexible and efficient tool-based agent-environment interactions for building agentic applications. Specifically, we abstract foundational components essential for agentic applications and provide unified interfaces and extensible modules, enabling developers to easily leverage the latest progress, such as new models and MCPs. Furthermore, we ground agent behaviors in the ReAct paradigm and offer advanced agent-level infrastructure based on a systematic asynchronous design, which enriches both human-agent and agent-agent interaction patterns while improving execution efficiency. Building on this foundation, we integrate several built-in agents tailored to specific practical scenarios. AgentScope also includes robust engineering support for developer-friendly experiences. We provide a scalable evaluation module with a visual studio interface, making the development of long-trajectory agentic applications more manageable and easier to trace. In addition, AgentScope offers a runtime sandbox to ensure safe agent execution and facilitates rapid deployment in production environments. With these enhancements, AgentScope provides a practical foundation for building scalable, adaptive, and effective agentic applications.
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