AgentScope：一个灵活而强大的多智能体平台

摘要

随着大型语言模型（LLMs）的快速发展，多智能体应用取得了显著进展。然而，协调智能体合作和LLMs不稳定性表现所带来的复杂性，给开发健壮高效的多智能体应用带来了显著挑战。为了解决这些挑战，我们提出了AgentScope，这是一个以开发者为中心的多智能体平台，其核心通信机制是消息交换。结合丰富的语法工具、内置资源和用户友好的交互，我们的通信机制显著降低了开发和理解的障碍。为了实现健壮灵活的多智能体应用，AgentScope提供了内置和可定制的容错机制，同时还配备了用于多模态数据生成、存储和传输的系统级支持。此外，我们设计了基于actor的分发框架，实现了本地和分布式部署之间的轻松转换，以及自动并行优化而无需额外努力。凭借这些特性，AgentScope赋予开发者构建充分发挥智能体潜力的应用的能力。我们已在https://github.com/modelscope/agentscope发布了AgentScope，并希望AgentScope能吸引更广泛的参与和创新在这个快速发展的领域。

English

With the rapid advancement of Large Language Models (LLMs), significant progress has been made in multi-agent applications. However, the complexities in coordinating agents' cooperation and LLMs' erratic performance pose notable challenges in developing robust and efficient multi-agent applications. To tackle these challenges, we propose AgentScope, a developer-centric multi-agent platform with message exchange as its core communication mechanism. Together with abundant syntactic tools, built-in resources, and user-friendly interactions, our communication mechanism significantly reduces the barriers to both development and understanding. Towards robust and flexible multi-agent application, AgentScope provides both built-in and customizable fault tolerance mechanisms while it is also armed with system-level supports for multi-modal data generation, storage and transmission. Additionally, we design an actor-based distribution framework, enabling easy conversion between local and distributed deployments and automatic parallel optimization without extra effort. With these features, AgentScope empowers developers to build applications that fully realize the potential of intelligent agents. We have released AgentScope at https://github.com/modelscope/agentscope, and hope AgentScope invites wider participation and innovation in this fast-moving field.

AgentScope：一个灵活而强大的多智能体平台

AgentScope: A Flexible yet Robust Multi-Agent Platform

摘要

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