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README.md

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<br><br>
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</p>
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## 🔔 News
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2019
- [2024.10.28] The release of muAgent V2.1, which offers one-click deployment capabilities, including KG-based agent orchestration, Java-based tool and agent registration and management, as well as a user-friendly drag-and-drop front-end product UI.
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- [2024.09.05] we release muAgent v2.0: An Innovative Agent Framework Driven By KG Engine.
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- [2024.04.01] muAgent is now open source, focusing on multi-agent orchestration and collaborating with technologies such as FunctionCall, RAG, and CodeInterpreter.
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## 📜 Contents
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- [🤝 Introduction](#-Introduction)
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- [🚀 QuickStart](#-QuickStart)
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- [🧭 Features](#-Features)
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- [🤗 Contribution](#-Contribution)
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- [🗂 Miscellaneous](#-Miscellaneous)
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- [📱 Contact Us](#-Contact-Us)
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- [muAgent: An Innovative Agent Framework Driven by KG Engine](#muagent-an-innovative-agent-framework-driven-by-kg-engine)
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- [🔔 News](#-news)
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- [📜 Contents](#-contents)
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- [🤝 Introduction](#-introduction)
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- [🚀 QuickStart](#-quickstart)
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- [EKG Services](#ekg-services)
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- [SDK](#sdk)
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- [🧭 Features](#-features)
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- [🤗 Contribution](#-contribution)
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- [🗂 Miscellaneous](#-miscellaneous)
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- [📱 Contact Us](#-contact-us)
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## 🤝 Introduction
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<p align="justify">
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A brand new Agent Framework driven by LLM and EKG(Eventic Knowledge Graph, Industry Knowledge Carrier),collaboratively utilizing MultiAgent, FunctionCall, CodeInterpreter, etc. Through canvas-based drag-and-drop and simple text writing, the large language model can assists you in executing various complex SOP under human guidance. It is compatbile with existing frameworks on the market and can achieve four core differentiating technical functions: Complex Reasoning, Online Collaboration, Human Interaction, Knowledge On-demand.
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This framework has been validated in multiple complex DevOps scenarios within Ant Group. At the sametime, come and experience the Undercover game we quickly built!
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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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For complete documentation, see: [CodeFuse-muAgent](https://codefuse.ai/docs/api-docs/MuAgent/overview/multi-agent).
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For more examples, see [demos](https://codefuse.ai/docs/api-docs/MuAgent/connector/customed_examples).
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### EKG Services
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# step4. start all container services, it might cost some time
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# after starting all services, open https://localhost:8000
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docker-compose up -d
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docker compose up -d
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```
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https://github.com/user-attachments/assets/7d5251a0-2864-438c-8897-b0445f0b1c30
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<https://github.com/user-attachments/assets/7d5251a0-2864-438c-8897-b0445f0b1c30>
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https://github.com/user-attachments/assets/34e5efea-f237-4b04-aeca-1f443ed7eb88
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<https://github.com/user-attachments/assets/34e5efea-f237-4b04-aeca-1f443ed7eb88>
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Now is beta version. Once the v1.0+ version is enhanced, we will release v1.0+ image for download.
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To Be Continued!
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### SDK
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### SDK
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We also provide a version of the SDK for using muagent.
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1. Installation
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```
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pip install codefuse-muagent
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```
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2. Code answer Prepare related llm and embedding model configurations
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you can see [docs](https://codefuse.ai/docs/api-docs/MuAgent/connector/customed_examples) and [~/examples](https://github.com/codefuse-ai/CodeFuse-muAgent/tree/main/examples)
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1. Installation
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```bash
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pip install codefuse-muagent
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```
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2. For Code answer Prepare related llm and embedding model configurations, see [ocs](https://codefuse.ai/docs/api-docs/MuAgent/connector/customed_examples) and [examples](https://github.com/codefuse-ai/CodeFuse-muAgent/tree/main/examples).
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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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- **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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Thank you for your interest in the muAgent project! We genuinely appreciate your feedback and invite you to share your suggestions, insights (including constructive criticism), and contributions.
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To facilitate this process, we encourage you to submit your feedback directly through GitHub Issues. There are numerous ways to engage with and contribute to the muAgent project, including code implementation, test development, documentation enhancements, and more.
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We welcome all forms of contributions and look forward to recognizing your efforts by adding you to our list of contributors. For more details, please refer to our [Contribution Guide](https://codefuse-ai.github.io/contribution/contribution).
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## 🗂 Miscellaneous
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### 📱 Contact Us
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<div align=center>
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<img src="docs/resources/wechat.png" alt="图片", width="180">
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</div>

README_zh.md

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## 🔔 更新
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- [2024.11.06] 量子位公众号专题报道:[文章链接](https://mp.weixin.qq.com/s/di_joj2NInGAGNqjDIsleA )
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- [2024.10.28] 发布 muAgent v2.1,提供 一键式部署能力,包括基于KG的Agent编排、基于java的工具/Agent注册和管理、可拖拉拽编辑的前端产品UI
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- [2024.09.05] 发布 muAgent v2.0 - EKG:一款由知识图谱引擎驱动的创新Agent产品框架
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- [2024.04.01] muAgent正式开源,聚焦多agent编排,协同FunctionCall、RAG、CodeInterpreter等技术
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- [2024.10.28] 发布 muAgent v2.1,提供一键式部署能力,包括基于 KG 的 Agent 编排、基于 Java 的工具/Agent 注册和管理、可拖拉拽编辑的前端产品 UI
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- [2024.09.05] 发布 muAgent v2.0 - EKG:一款由知识图谱引擎驱动的创新 Agent 产品框架
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- [2024.04.01] muAgent 正式开源,聚焦多 agent 编排,协同 FunctionCall、RAG 和 CodeInterpreter 等技术
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## 📜 目录
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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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- [muAgent: An Innovative Agent Framework Driven by KG Engine](#muagent-an-innovative-agent-framework-driven-by-kg-engine)
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- [🔔 更新](#-更新)
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- [📜 目录](#-目录)
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- [🤝 介绍](#-介绍)
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- [🚀 快速使用](#-快速使用)
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- [EKG 服务](#ekg-服务)
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- [SKD 版本](#skd-版本)
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- [🧭 关键技术](#-关键技术)
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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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## 🤝 介绍
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全新体验的Agent框架,将KG从知识获取来源直接升级为Agent编排引擎!基于LLM+ EKG(Eventic Knowledge Graph 行业知识承载)驱动,协同MultiAgent、FunctionCall、CodeInterpreter等技术,通过画布式拖拽、轻文字编写,让大模型在人的经验指导下帮助你实现各类复杂 SOP 流程。兼容现有市面各类Agent框架,同时可实现复杂推理、在线协同、人工交互、知识即用四大核心差异技术功能。这套框架目前在蚂蚁集团内多个复杂DevOps场景落地验证,同时来体验下我们快速搭建的谁是卧底游戏吧。
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全新体验的 Agent 框架,将 KG 从知识获取来源直接升级为 Agent 编排引擎!基于 LLM+ EKG(Eventic Knowledge Graph 行业知识承载)驱动,协同 MultiAgent、FunctionCall、CodeInterpreter 等技术,通过画布式拖拽、轻文字编写,让大模型在人的经验指导下帮助你实现各类复杂 SOP 流程。兼容现有市面各类 Agent 框架,同时可实现复杂推理、在线协同、人工交互、知识即用四大核心差异技术功能。这套框架目前在蚂蚁集团内多个复杂 DevOps 场景落地验证,同时来体验下我们快速搭建的谁是卧底游戏吧。
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</p>
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<img src="docs/resources/ekg-arch-zh.webp" alt="muAgent Architecture" width="770">
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## 🚀 快速使用
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完整文档见:[CodeFuse-muAgent](https://codefuse.ai/zh-CN/docs/api-docs/MuAgent/overview/multi-agent)
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更多[demo](https://codefuse.ai/zh-CN/docs/api-docs/MuAgent/connector/customed_examples)
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### EKG服务
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完整文档,参考 [CodeFuse-muAgent](https://codefuse.ai/zh-CN/docs/api-docs/MuAgent/overview/multi-agent)
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更多示例,参考 [Demo](https://codefuse.ai/zh-CN/docs/api-docs/MuAgent/connector/customed_examples)
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### EKG 服务
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```bash
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# 使用我们的EKG服务只需要四步!(beta版本,需要将本地代码打包到容器中)
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# 使用我们的 EKG 服务只需要四步!(beta 版本,需要将本地代码打包到容器中)
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# 第一步加载代码
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现在仍为beta版本,待v1.0版本完善后,会放出v1.0+的镜像以供下载。
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现在仍为 beta 版本,待 v1.0 版本完善后,会放出 v1.0+ 的镜像以供下载。
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敬请期待!
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敬请期待!
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2. 代码问答和相关配置,可以看 [docs](https://codefuse.ai/docs/api-docs/MuAgent/connector/customed_examples) 和代码示例 [examples](https://github.com/codefuse-ai/CodeFuse-muAgent/tree/main/examples)
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2. 代码问答和相关配置,参考 [文档](https://codefuse.ai/docs/api-docs/MuAgent/connector/customed_examples) 和 [代码示例](https://github.com/codefuse-ai/CodeFuse-muAgent/tree/main/examples)。
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## 🧭 关键技术
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- **图谱构建**:通过虚拟团队构建、场景意图划分,让你体验在线文档VS本地文档的差别;同时,文本语义输入的节点使用方式,让你感受有注释代码VS无注释代码的差别,充分体现在线协同的优势;面向海量存量文档(通用文本、流程画板等),支持文本智能解析、一键导入,以及经验拆分泛化
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- **图谱资产**:通过场景意图、事件流程、统一工具、组织人物四部分的统一图谱设计,满足各类SOP场景所需知识承载;工具在图谱的纳入进一步提升工具选择、参数填充的准确性,人物/智能体在图谱的纳入,让人可加入流程的推进,可灵活应用于多人文本游戏
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- **图谱推理**相比其他Agent框架纯模型推理、纯人工编排的推理模式,让大模型在人的经验/设计指导下做事,灵活、可控,同时面向未知局面,可自由探索,同时将成功探索经验总结、图谱沉淀,面向相似问题,少走弯路;整体流程唤起支持平台对接(规则配置)、语言触发,满足各类诉求
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- **图谱构建**:通过虚拟团队构建、场景意图划分,让你体验在线文档 VS 本地文档的差别;同时,文本语义输入的节点使用方式,让你感受有注释代码 VS 无注释代码的差别,充分体现在线协同的优势;面向海量存量文档(通用文本、流程画板等),支持文本智能解析、一键导入,以及经验拆分泛化
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- **图谱资产**:通过场景意图、事件流程、统一工具、组织人物四部分的统一图谱设计,满足各类 SOP 场景所需知识承载;工具在图谱的纳入进一步提升工具选择、参数填充的准确性,人物/智能体在图谱的纳入,让人可加入流程的推进,可灵活应用于多人文本游戏
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- **图谱推理**相比其他 Agent 框架纯模型推理、纯人工编排的推理模式,让大模型在人的经验/设计指导下做事,灵活、可控,同时面向未知局面,可自由探索,同时将成功探索经验总结、图谱沉淀,面向相似问题,少走弯路;整体流程唤起支持平台对接(规则配置)、语言触发,满足各类诉求
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- **调试运行**:图谱编辑完成后,可视调试,快速发现流程错误、修改优化,同时面向调试成功路径,关联配置自动沉淀,减少模型交互、模型开销,加速推理流程;此外,在线运行中,我们提供全链路可视化监控
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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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- **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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感谢您对muAgent项目的关注!我们欢迎您的任何建议、意见(包括批评)和贡献。
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为了更好促进项目的发展,我们鼓励您通过GitHub的Issues提交您对项目的各种建议、意见和评论
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感谢您对 muAgent 项目的关注!我们欢迎您的任何建议、意见(包括批评)和贡献
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参与Codefuse项目并为其作出贡献的方法有很多:代码实现、测试编写、文档完善等等。任何贡献我们都会非常欢迎,并将您加入贡献者列表,详见[Contribution Guide](https://codefuse-ai.github.io/contribution/contribution)
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为了更好促进项目的发展,我们鼓励您通过 GitHub 的 Issues 提交您对项目的各种建议、意见和评论。
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参与 Codefuse 项目并为其作出贡献的方法有很多:代码实现、测试编写、文档完善等等。任何贡献我们都会非常欢迎,并将您加入贡献者列表,详见 [Contribution Guide](https://codefuse-ai.github.io/contribution/contribution)。
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## 🗂 其他
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### 📱 联系我们
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<div align=center>
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<img src="docs/resources/wechat.png" alt="图片", width="180">
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</div>

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