【Easy Issue/入门实战】Enhancement for agent work-patterns/智能体工作模式贡献

[LandJerry]

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agentUniverse has a rich set of multi-agent collaborative pattern components (serving as a collaborative pattern factory),which allows agents to perform their respective duties and maximize their capabilities when solving problems in different fields.

For example, in the PEER mode within agentUniverse: This pattern uses agents with different responsibilities—Plan, Execute, Express, and Review—to break down complex problems into manageable steps, execute the steps in sequence, and iteratively improve based on feedback, enhancing the performance of reasoning and analysis tasks. Typical use cases: Event interpretation, industry analysis.

We are exploring more collaborative pattern components, and below are two types of multi-agent modes available for reference:

GRR Mode: This mode includes three agents with distinct responsibilities—Generate, Review, and Rewrite—effectively generating content, reflecting on it, and making corrections, thereby improving performance in generation tasks.

IS Mode: This mode consists of two agents—Implementation and Supervision—where the Implementation agent executes the main process, and the Supervision agent monitors and provides feedback on the main process to ensure that it remains aligned with user goals.

======================== 中文版 ==============================

agentUniverse拥有丰富的多智能体协同模式组件（可视为一个协同模式工厂Pattern Factory），它能让智能体们各司其职在解决不同领域问题时发挥最大的能力；

以agentUniverse中的PEER模式为例： 该模式通过计划（Plan）、执行（Execute）、表达（Express）、评价（Review）四个不同职责的智能体，实现对复杂问题的多步拆解、分步执行，并基于评价反馈进行自主迭代，最终提升推理分析类任务表现。

我们正在探索更多的多智能体协同模式，下列是2类可供参考建设的多智能体模式：

1）GRR模式：该模式包含生成（Gen)、反思（Review）、修改（Rewrite）三个不同职责的智能体，实现对于用户指定内容的生成、思考并修正，最终提升生成类任务表现。

2）IS模式：改模式包含执行（implementation）、监督（supervision）两个智能体，由执行智能体进行主流程执行，由监督智能体对于主流程进行监督反馈，保证主流程执行过程与用户目标不产生偏离。