SAUCE让多智能体大模型在可定制环境中同步异步对话，模拟真实群组互动。
SAUCE: Synchronous and Asynchronous User-Customizable Environment for Multi-Agent LLM Interaction
- 通过配置文件灵活接入多种大模型，支持任意主题讨论。
- 引入异步发言机制，模型自主决定何时说话，更贴近人类交流。
- 适合研究群体决策、社会互动等复杂场景，无需编程基础。
许多人类互动，如政治辩论，是在多人参与的群体环境中进行的，参与者数量不定，观点与目标各异。为探索此类复杂社交场景，我们提出SAUCE：一个可定制的Python平台，允许研究人员将各种大语言模型（LLMs）接入任意用户指定主题的讨论中。该平台自动处理模型实例化、响应调度、讨论历史管理及完整输出日志生成，所有功能均可通过配置文件自定义，几乎无需编码。SAUCE的创新之处在于其异步通信机制，模型不仅决定说什么，还自主决定何时发言，从而建模人类交流的重要特征。我们在两个初步实验中展示了SAUCE的吸引力，并邀请社区使用它进行各类群体模拟。
原文摘要 · Abstract (English)
Many human interactions, such as political debates, are carried out in group settings, where there are arbitrarily many participants, each with different views and agendas. To explore such complex social settings, we present SAUCE: a customizable Python platform, allowing researchers to plug-and-play various LLMs participating in discussions on any topic chosen by the user. Our platform takes care of instantiating the models, scheduling their responses, managing the discussion history, and producing a comprehensive output log, all customizable through configuration files, requiring little to no coding skills. A novel feature of SAUCE is our asynchronous communication feature, where models decide when to speak in addition to what to say, thus modeling an important facet of human communication. We show SAUCE's attractiveness in two initial experiments, and invite the community to use it in simulating various group simulations.
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