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[update reamd][update license version]
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README.md

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<p align="center">
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<a href="README.md"><img src="https://img.shields.io/badge/文档-中文版-yellow.svg" alt="ZH doc"></a>
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<a href="README_en.md"><img src="https://img.shields.io/badge/document-English-yellow.svg" alt="EN doc"></a>
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<img src="https://img.shields.io/github/license/codefuse-ai/CodeFuse-muAgent" alt="License">
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<a href="LICENSE.md"><img src="https://img.shields.io/badge/license-Apache%202.0-yellow" alt="License">
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<a href="https://github.com/codefuse-ai/CodeFuse-muAgent/issues">
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<img alt="Open Issues" src="https://img.shields.io/github/issues-raw/codefuse-ai/CodeFuse-muAgent" />
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</a>
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![](docs/resources/ekg-arch-en.webp)
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## 🚀 Quick Start
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## 🚀 QuickStart
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For complete documentation, see: [CodeFuse-muAgent](https://codefuse.ai/docs/api-docs/MuAgent/overview/multi-agent)
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For more [demos](https://codefuse.ai/docs/api-docs/MuAgent/connector/customed_examples)
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## Features
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## 🧭 Features
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- EKG Builder:Through the design of virtual teams, scene intentions, and semantic nodes, you can experience the differences between online and local documentation, or annotated versus unannotated code handover. For a vast amount of existing documents (text, diagrams, etc.), we support intelligent parsing, which is available for one-click import.
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- EKG Assets:Through comprehensive KG Schema design—including Intention Nodes, Workflow Nodes, Tool Nodes, and Character Nodes—we can meet various SOP Automation requirements. The inclusion of Tool Nodes in the KG enhances the accuracy of tool selection and parameter filling. Additionally, the incorporation of Characters (whether human or agents) in the KG allows for human-involved process advancement, making it flexible for use in multiplayer text-based games.
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- EKG Reasoning:Compared to purely model-based or entirely fix-flow Reasoning, our framework allows LLM to operate under human guidance-flexibility, control, and enabling exploration in unknown scenarios. Additionally, successful exploration experiences can be summarized and documented into KG, minimizing detours for similar issues.
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- Diagnose:After KG editing, visual interface allows for quick debugging, and successful Execution path configurations will be automatically documented, which reduces model interactions, accelerates inference, and minimizes LLM Token costs. Additionally, during online execution, we provide comprehensive end-to-end visual monitoring.
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- Memory:Unified message pooling design supports categorized message delivery and subscription based on the needs of different scenarios, like multi-agent. Additionally, through message retrievel, rerank and distillation, it facilitates long-context handling, improving the overall question-answer quality.
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- ActionSpace:Adhering to Swagger protocol, we provide tool registration, tool categorization, and permission management, facilitating LLM Function Calling. We offer a secure and trustworthy code execution environment, and ensuring precise code generation to meet the demands of various scenarios, including visual plot, numerical calculations, and table editing.
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## Contribution
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## 🤗 Contribution
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We are deeply grateful for your interest in the Codefuse project and warmly welcome any suggestions, opinions (including criticism), comments, and contributions.
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Feel free to raise your suggestions, opinions, and comments directly through GitHub Issues. There are numerous ways to participate in and contribute to the Codefuse project: code implementation, writing tests, process tool improvements, documentation enhancements, etc.

README_zh.md

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<p align="center">
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<a href="README_zh.md"><img src="https://img.shields.io/badge/文档-中文版-yellow.svg" alt="ZH doc"></a>
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<a href="README.md"><img src="https://img.shields.io/badge/document-English-yellow.svg" alt="EN doc"></a>
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<img src="https://img.shields.io/github/license/codefuse-ai/CodeFuse-muAgent" alt="License">
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<a href="LICENSE.md"><img src="https://img.shields.io/badge/license-Apache%202.0-yellow" alt="License">
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<a href="https://github.com/codefuse-ai/CodeFuse-muAgent/issues">
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<img alt="Open Issues" src="https://img.shields.io/github/issues-raw/codefuse-ai/CodeFuse-muAgent" />
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</a>
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- [🤝 介绍](#-介绍)
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- [🚀 快速使用](#-快速使用)
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- [🧭 关键技术](#-关键技术)
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- [🤗 贡献](#-贡献)
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- [🤗 贡献指南](#-贡献指南)
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- [🗂 其他](#-其他)
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- [📱 联系我们](#-联系我们)
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- 记忆管理:统一消息池设计,支持各类场景所需分门别类消息投递、订阅,隔离且互通,便于多Agent场景消息管理使用;同时面向超长上下文,支持消息检索、排序、蒸馏,提升整体问答质量
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- 操作空间:遵循Swagger协议,提供工具注册、权限管理、统一分类,方便LLM在工具调用中接入使用;提供安全可信代码执行环境,同时确保代码精准生成,满足可视绘图、数值计算、图表编辑等各类场景诉求
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## 贡献指南
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## 🤗 贡献指南
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非常感谢您对 Codefuse 项目感兴趣,我们非常欢迎您对 Codefuse 项目的各种建议、意见(包括批评)、评论和贡献。
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您对 Codefuse 的各种建议、意见、评论可以直接通过 GitHub 的 Issues 提出。

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