AgentScope：一個靈活且堅固的多智能體平台

摘要

隨著大型語言模型（LLMs）的快速發展，多智能體應用取得了顯著進展。然而，在協調智能體合作和LLMs表現不穩定的複雜性方面，開發強大且高效的多智能體應用面臨顯著挑戰。為應對這些挑戰，我們提出AgentScope，一個以開發者為中心的多智能體平台，其核心通信機制為消息交換。結合豐富的語法工具、內建資源和用戶友好的互動，我們的通信機制顯著降低了開發和理解的障礙。為實現強大且靈活的多智能體應用，AgentScope提供內建和可定制的容錯機制，同時配備系統級支持，用於多模態數據的生成、存儲和傳輸。此外，我們設計了基於演員的分發框架，實現本地和分佈式部署之間的輕鬆轉換，以及無需額外努力的自動並行優化。憑藉這些功能，AgentScope賦予開發者構建充分發揮智能智能體潛力的應用的能力。我們已在https://github.com/modelscope/agentscope 上發布了AgentScope，並希望AgentScope能在這個快速發展的領域中吸引更廣泛的參與和創新。

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：一個靈活且堅固的多智能體平台

AgentScope: A Flexible yet Robust Multi-Agent Platform

摘要

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