[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-Mintplex-Labs--openai-assistant-swarm":3,"tool-Mintplex-Labs--openai-assistant-swarm":62},[4,18,26,36,46,54],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",160411,2,"2026-04-18T23:33:24",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":42,"last_commit_at":43,"category_tags":44,"status":17},8272,"opencode","anomalyco\u002Fopencode","OpenCode 是一款开源的 AI 编程助手（Coding Agent），旨在像一位智能搭档一样融入您的开发流程。它不仅仅是一个代码补全插件，而是一个能够理解项目上下文、自主规划任务并执行复杂编码操作的智能体。无论是生成全新功能、重构现有代码，还是排查难以定位的 Bug，OpenCode 都能通过自然语言交互高效完成，显著减少开发者在重复性劳动和上下文切换上的时间消耗。\n\n这款工具专为软件开发者、工程师及技术研究人员设计，特别适合希望利用大模型能力来提升编码效率、加速原型开发或处理遗留代码维护的专业人群。其核心亮点在于完全开源的架构，这意味着用户可以审查代码逻辑、自定义行为策略，甚至私有化部署以保障数据安全，彻底打破了传统闭源 AI 助手的“黑盒”限制。\n\n在技术体验上，OpenCode 提供了灵活的终端界面（Terminal UI）和正在测试中的桌面应用程序，支持 macOS、Windows 及 Linux 全平台。它兼容多种包管理工具，安装便捷，并能无缝集成到现有的开发环境中。无论您是追求极致控制权的资深极客，还是渴望提升产出的独立开发者，OpenCode 都提供了一个透明、可信",144296,1,"2026-04-16T14:50:03",[13,45],"插件",{"id":47,"name":48,"github_repo":49,"description_zh":50,"stars":51,"difficulty_score":32,"last_commit_at":52,"category_tags":53,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",109154,"2026-04-18T11:18:24",[14,15,13],{"id":55,"name":56,"github_repo":57,"description_zh":58,"stars":59,"difficulty_score":32,"last_commit_at":60,"category_tags":61,"status":17},6121,"gemini-cli","google-gemini\u002Fgemini-cli","gemini-cli 是一款由谷歌推出的开源 AI 命令行工具，它将强大的 Gemini 大模型能力直接集成到用户的终端环境中。对于习惯在命令行工作的开发者而言，它提供了一条从输入提示词到获取模型响应的最短路径，无需切换窗口即可享受智能辅助。\n\n这款工具主要解决了开发过程中频繁上下文切换的痛点，让用户能在熟悉的终端界面内直接完成代码理解、生成、调试以及自动化运维任务。无论是查询大型代码库、根据草图生成应用，还是执行复杂的 Git 操作，gemini-cli 都能通过自然语言指令高效处理。\n\n它特别适合广大软件工程师、DevOps 人员及技术研究人员使用。其核心亮点包括支持高达 100 万 token 的超长上下文窗口，具备出色的逻辑推理能力；内置 Google 搜索、文件操作及 Shell 命令执行等实用工具；更独特的是，它支持 MCP（模型上下文协议），允许用户灵活扩展自定义集成，连接如图像生成等外部能力。此外，个人谷歌账号即可享受免费的额度支持，且项目基于 Apache 2.0 协议完全开源，是提升终端工作效率的理想助手。",100752,"2026-04-10T01:20:03",[45,13,15,14],{"id":63,"github_repo":64,"name":65,"description_en":66,"description_zh":67,"ai_summary_zh":68,"readme_en":69,"readme_zh":70,"quickstart_zh":71,"use_case_zh":72,"hero_image_url":73,"owner_login":74,"owner_name":75,"owner_avatar_url":76,"owner_bio":77,"owner_company":78,"owner_location":78,"owner_email":79,"owner_twitter":80,"owner_website":81,"owner_url":82,"languages":83,"stars":88,"forks":89,"last_commit_at":90,"license":91,"difficulty_score":32,"env_os":92,"env_gpu":93,"env_ram":92,"env_deps":94,"category_tags":99,"github_topics":100,"view_count":32,"oss_zip_url":78,"oss_zip_packed_at":78,"status":17,"created_at":120,"updated_at":121,"faqs":122,"releases":123},9457,"Mintplex-Labs\u002Fopenai-assistant-swarm","openai-assistant-swarm","Introducing the Assistant Swarm. An extension to the OpenAI Node SDK to automatically delegate work to any assistant you create in OpenAi through one united interface and manager. Now you can delegate work to a swarm of assistant all specialized with specific tasks you define.","openai-assistant-swarm 是一款专为 Node.js 开发者设计的开源扩展库，旨在将多个 OpenAI 自定义助手整合成一个高效协作的“智能集群”。在构建复杂的自主 AI 应用时，开发者往往需要手动管理不同助手之间的任务分配与协调，这不仅增加了代码复杂度，还难以实现真正的并行处理。openai-assistant-swarm 通过引入统一的“管理器”接口，完美解决了这一痛点。它允许用户创建一个主代理，由该代理自动、智能地将具体任务分发给具备特定专长的其他助手，并支持并行执行，从而大幅降低多智能体系统的开发门槛。\n\n作为 OpenAI 官方 Node SDK 的增强插件，openai-assistant-swarm 无缝集成了现有开发流程。只需简单安装并初始化，即可在 `beta.assistants` 对象上调用全新的 `.swarm` 方法，轻松实现对整个助手注册表的统一调度。这种设计让开发者无需再为“哪个助手该做什么”而耗费精力，只需关注业务逻辑本身。无论是希望构建高级自动化工作流的资深工程师，还是正在探索多智能体架构的研究人员，openai-assistant","openai-assistant-swarm 是一款专为 Node.js 开发者设计的开源扩展库，旨在将多个 OpenAI 自定义助手整合成一个高效协作的“智能集群”。在构建复杂的自主 AI 应用时，开发者往往需要手动管理不同助手之间的任务分配与协调，这不仅增加了代码复杂度，还难以实现真正的并行处理。openai-assistant-swarm 通过引入统一的“管理器”接口，完美解决了这一痛点。它允许用户创建一个主代理，由该代理自动、智能地将具体任务分发给具备特定专长的其他助手，并支持并行执行，从而大幅降低多智能体系统的开发门槛。\n\n作为 OpenAI 官方 Node SDK 的增强插件，openai-assistant-swarm 无缝集成了现有开发流程。只需简单安装并初始化，即可在 `beta.assistants` 对象上调用全新的 `.swarm` 方法，轻松实现对整个助手注册表的统一调度。这种设计让开发者无需再为“哪个助手该做什么”而耗费精力，只需关注业务逻辑本身。无论是希望构建高级自动化工作流的资深工程师，还是正在探索多智能体架构的研究人员，openai-assistant-swarm 都能提供强大且便捷的基础设施支持，帮助你将独立的 AI 助手迅速转化为一支配合默契的智能军团。","\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FMintplex-Labs_openai-assistant-swarm_readme_bbef4b7d6831.png\" alt=\"OpenAI Assistant Swarm Manager banner\">\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n    \u003Cb>OpenAI Assistant Swarm Manager: A library to turn your OpenAi assistants into an army\u003C\u002Fi>\u003C\u002Fb>.\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002F6UyHPeGZAC\" target=\"_blank\">\n      \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fchat-mintplex_labs-blue.svg?style=flat&logo=data:image\u002Fpng;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAAIGNIUk0AAHomAACAhAAA+gAAAIDoAAB1MAAA6mAAADqYAAAXcJy6UTwAAAH1UExURQAAAP\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002Fr6+ubn5+7u7\u002F3+\u002Fv39\u002Fenq6urq6\u002Fv7+97f39rb26eoqT1BQ0pOT4+Rkuzs7cnKykZKS0NHSHl8fdzd3ejo6UxPUUBDRdzc3RwgIh8jJSAkJm5xcvHx8aanqB4iJFBTVezt7V5hYlJVVuLj43p9fiImKCMnKZKUlaaoqSElJ21wcfT09O3u7uvr6zE0Nr6\u002FwCUpK5qcnf7+\u002Fnh7fEdKTHx+f0tPUOTl5aipqiouMGtubz5CRDQ4OsTGxufn515hY7a3uH1\u002FgXBydIOFhlVYWvX29qaoqCQoKs7Pz\u002FPz87\u002FAwUtOUNfY2dHR0mhrbOvr7E5RUy8zNXR2d\u002Ff39+Xl5UZJSx0hIzQ3Odra2\u002Fz8\u002FGlsbaGjpERHSezs7L\u002FBwScrLTQ4Odna2zM3Obm7u3x\u002FgKSmp9jZ2T1AQu\u002Fv71pdXkVISr2+vygsLiInKTg7PaOlpisvMcXGxzk8PldaXPLy8u7u7rm6u7S1tsDBwvj4+MPExbe4ueXm5s\u002FQ0Kyf7ewAAAAodFJOUwAABClsrNjx\u002FQM2l9\u002F7lhmI6jTB\u002FkA1GgKJN+nea6vy\u002FMLZQYeVKK3rVA5tAAAAAWJLR0QB\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\u002FBGf3cqCCiZOcnCe3QQIKHNRTpk6bDgpZjRkzg3pBQTBrdtCcuZCgluAD0vPmL1gIdvSixUuWgqNs2YJ+DUhkEYxuggkGmOQUcckrioPTJCOXEnZ5JS5YslbGnuyVERlDDFvGEUPOWvwqaH6RVkHKeuDMK6SKnHlVhTgx8jeTmqy6Eij7K6nLqiGyPwChsa1MUrnq1wAAACV0RVh0ZGF0ZTpjcmVhdGUAMjAyMy0xMC0wNFQwMDozODo0OSswMDowMB9V0a8AAAAldEVYdGRhdGU6bW9kaWZ5ADIwMjMtMTAtMDRUMDA6Mzg6NDkrMDA6MDBuCGkTAAAAKHRFWHRkYXRlOnRpbWVzdGFtcAAyMDIzLTEwLTA0VDAwOjM4OjQ5KzAwOjAwOR1IzAAAAABJRU5ErkJggg==\" alt=\"Discord\">\n  \u003C\u002Fa> |\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FMintplex-Labs\u002Fopenai-assistant-swarm\u002Fblob\u002Fmaster\u002FLICENSE\" target=\"_blank\">\n      \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fstatic\u002Fv1?label=license&message=MIT&color=white\" alt=\"License\">\n  \u003C\u002Fa> |\n   \u003Ca href=\"https:\u002F\u002Fmintplexlabs.com\" target=\"_blank\">\n    Mintplex Labs Inc\n  \u003C\u002Fa>|\n   \u003Ca href=\"https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@mintplex-labs\u002Fopenai-assistant-swarm\" target=\"_blank\">\n    NPM\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n## What is the Swarm Manager\nOpenAI's assistant API unlocks an incredible convience for developers who are building autonomous AI assistants or commonly called \"Agents\". This Node JS Library unlocks your entire registry of custom agents and their functions via a single API call. One agent \"manager\" can now easily delegate work to one or many other assistants in parallel in a smart and quick way so you can handle actions from delegated tasks easily.\n\nAll of the mental overhead of managing which assistant does what is now handled and wrapped up with a bow.\n\n## How does it work?\nThe Swarm Manager acts as an extension of the OpenAI NodeJS SDK - making available a new `.swarm` method available on `beta.assistants`.\n\nFirst, install the openai SDK for NodeJS\n```shell\nyarn add openai\n# or \nnpm install openai\n```\n\nNext install the `openai-assistant-swarm` package\n```shell\nyarn add @mintplex-labs\u002Fopenai-assistant-swarm\n# or \nnpm install @mintplex-labs\u002Fopenai-assistant-swarm\n```\n\nNow use the SDK as you normally would and run the extension function and initialize the agent swarm manager.\n```javascript\n\u002F\u002F Enable the client for OpenAi as you normally would\nconst OpenAIClient = (\n    new OpenAI({\n        apiKey: process.env.OPEN_AI_KEY\n    }));\n\n\u002F\u002F The simply call this function on the client to extend the OpenAI SDK to now have\n\u002F\u002F OpenAIClient.beta.assistants.swarm functions available.\nEnableSwarmAbilities(OpenAIClient, {\n  \u002F\u002F all options are OPTIONAL\n  debug: false, \u002F\u002F to see console log outputs of the process and playground links for debugging.\n  managerAssistantOptions: {\n         name: \"[AUTOMATED] ___Swarm Manager\", \u002F\u002F Name of created\u002Fmaintained agent by the library\n        model: \"gpt-4\", \u002F\u002F Use gpt-4 for better reasoning and calling.\n        instructions: 'Instructions you are going to give the agent manager to delegate tasks to'; \u002F\u002F Override the default instructions.\n    };\n});\n\n\u002F\u002F Initialize the swarm manager to create the swarm manager and also register it with\n\u002F\u002F your account. Swarm manager can be configured via options on `EnableSwarmAbilities`\nawait OpenAIClient.beta.assistants.swarm.init();\n\u002F\u002F Now all swarm management function are available to you!\n```\n\n## A simple example\n\nAn full example delegating a single input between 3 available assistants...\n```javascript\nimport OpenAI from 'openai';\nimport { EnableSwarmAbilities } from '@mintplex-labs\u002Fopenai-assistant-swarm';\nconst OpenAIClient = new OpenAI({apiKey: process.env.OPEN_AI_KEY});\nEnableSwarmAbilities(OpenAIClient);\nawait OpenAIClient.beta.assistants.swarm.init();\n\n\u002F\u002F Optional - set up listeners here to wait for specific events to return to the user since streaming is not available yet.\n\n\u002F\u002F Run the main process on a single text prompt to have work delegate between all of your assistants that are available.\nconst response = OpenAIClient.beta.assistants.swarm.delegateWithPrompt('What is the weather in New York city right now? Also what is the top stock for today?');\n\u002F\u002F For example. Given a Pirate bot, Weather Bot, and Stock Bot in your assistant registry on OpenAI.\n\u002F\u002F Run the below threads in parallel and return to you!\n\u002F\u002F |--> Will delegate to an existing Weather Bot\n\u002F\u002F |--> Will delegate to an existing Stock watcher Bot\n\u002F\u002F -> Pirate bot will not be invoked.\n\u002F\u002F -----\n\u002F\u002F The parent will respond with something like \"I've arranged for two of our assistants to handle your requests. For assistance with stocks I have delegated that task  to the Stock Bot, and for the weather update in San Francisco, our Weatherbot will provide the current conditions. They will take care of your needs shortly.\"\n\u002F\u002F\n\u002F\u002F You will then get a response once each child responds with either a completion or a `required_action` run you can handle in your codebase easily.\n\nconsole.log({\n  parentRun: response.parentRun, \u002F\u002F All information about the parent thread\n  subRuns: response.subRuns, \u002F\u002F array of runs created and their status for each spun-out child thread!\n})\n\n```\n\n## Available tools\n\n**Delegation via prompt**\n\nFirst, the main one you are probably interested in - delegation to sub-assistants. Its easy to set up and\nalso to listen to events and add into your current workflow.\n```javascript\n\u002F\u002F Set up an event listener for when the parent response is completed so you don't have to wait\n\u002F\u002F for parent + children responses to all complete.\n\u002F\u002F Useful to return the parent response early while you work on the subtask tool_calls that \n\u002F\u002F may or not be required depending on what happened.\nOpenAIClient.beta.assistants.swarm.emitter.on('parent_assistant_complete', (args) => {\n    console.group('Parent assistant response completed');\n    console.log(args.parentRun.playground) \u002F\u002F => https:\u002F\u002Fplatform.openai.com\u002Fplayground.... to debug thread & run in browser.\n    console.log(args.parentRun.textResponse) \u002F\u002F => Yarrh! Want to be speaking to the captain do ya? Ill go fetch them ya land lubber.\n    \u002F\u002F args.parentRun => The full Run object from OpenAI so you can get the thread_id and other properties like status.\n    console.log('\\n\\n')\n    console.groupEnd();\n});\n\n\u002F\u002F Set up an event listener for when the delegated assistant responses are completed so you don't have to wait\n\u002F\u002F for parent + children responses to all complete.\n\u002F\u002F From here you can handle all sub-run tool_calls if they are required to be run.\nOpenAIClient.beta.assistants.swarm.emitter.on('child_assistants_complete', (args) => {\n    console.group('Child assistant response completed');\n    console.log(args.subRuns.map((run) => run.textResponse)) \u002F\u002F => Yarrh! I am the captain of this vessel. Ye be after my treasure, Yar?\n    console.log(args.subRuns.map((run) => run.playground)) \u002F\u002F => https:\u002F\u002Fplatform.openai.com\u002Fplayground.... to debug thread & run in browser.\n    \u002F\u002F args.subRuns[x].run => The full Run object from OpenAI so you can get the thread_id and other properties like status.\n    console.log('\\n\\n')\n    console.groupEnd();\n});\n\n\u002F\u002F Set up and event listener to see every step event as it is completed:\nOpenAIClient.beta.assistants.swarm.emitter.on('poll_event', ({ data }) => {\n    console.group('Poll event!');\n    console.log({\n        status: data.status,\n        text: data.prompt || data.textResponse,\n        runId: data?.run?.id,\n        link: data.playground,\n        runStatus: data?.run?.status,\n    })\n    console.log('\\n\\n')\n    console.groupEnd();\n});\n\n\u002F\u002F Run the main process on a single text prompt to have work delegate between all of the possible assistants that are available.\nconst response = OpenAIClient.beta.assistants.swarm.delegateWithPrompt('Let me speak to the head pirate of this vessel! What say ye??');\n\u002F\u002F You can also just wait for the entire flow to finish instead of setting up listeners to keep the code more synchronous\nconsole.log({\n  parentRun: response.parentRun,\n  subRuns: response.subRuns,\n})\n\n\u002F\u002F You can also focus the given task or prompt on a subset of assistants that you know you want to handle delegated work.\n\u002F\u002F OpenAIClient.beta.assistants.swarm.delegateWithPrompt('Let me speak to the head pirate of this vessel! What say ye??', ['asst_lead_pirate']);\n```\n\n**Get all available assistants**\n\nRight now, you need to paginate assitants to see who is around to answer a question or handle a task. Now, you can just make one call and we handle pagination for you\n```javascript\nconst allAssistants = await OpenAIClient.beta.assistants.swarm.allAssistants();\nconsole.log(`Found ${allAssistants.length} assistants for this OpenAI Account`);\n\u002F\u002F will be an array of assistant objects you can filter or manage. The Swarm Manager will not appear here.\n```\n\n**Get many known assistants at once**\n\nYou are limited to fetching one assistant at a time via the API. Now you can get many at once\n```javascript\nconst assistantIds = ['asst_customer_success', 'asst_lead_pirate_manager', 'asst_that_was_deleted' ]\nconst specificAssistants = await OpenAIClient.beta.assistants.swarm.getAssistants(assistantIds);\nconsole.log(`Found ${specificAssistants.length} assistants from ${assistantIds.length} ids given.`);\n\u002F\u002F Will be an array of assistant objects you can filter or manage. The Swarm Manager will not appear here.\n\u002F\u002F Invalid assistants will not appear in the end result.\n```","\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FMintplex-Labs_openai-assistant-swarm_readme_bbef4b7d6831.png\" alt=\"OpenAI Assistant Swarm Manager 横幅\">\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n    \u003Cb>OpenAI 助手群管理器：将您的 OpenAI 助手转化为一支“军队”的库\u003C\u002Fi>\u003C\u002Fb>.\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002F6UyHPeGZAC\" target=\"_blank\">\n      \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fchat-mintplex_labs-blue.svg?style=flat&logo=data:image\u002Fpng;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAAIGNIUk0AAHomAACAhAAA+gAAAIDoAAB1MAAA6mAAADqYAAAXcJy6UTwAAAH1UExURQAAAP\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002F\u002Fr6+ubn5+7u7\u002F3+\u002Fv39\u002Fenq6urq6\u002Fv7+97f39rb26eoqT1BQ0pOT4+Rkuzs7cnKykZKS0NHSHl8fdzd3ejo6UxPUUBDRdzc3RwgIh8jJSAkJm5xcvHx8aanqB4iJFBTVezt7V5hYlJVVuLj43p9fiImKCMnKZKUlaaoqSElJ21wcfT09O3u7uvr6zE0Nr6\u002FwCUpK5qcnf7+\u002Fnh7fEdKTHx+f0tPUOTl5UZJSx0hIzQ4OsTGxufn515hY7a3uH1\u002FgEdXV0VISr9\u002Ff0tLiInKTg7PaOlpisvMcXGxzk8PldaXPLy8u7u7rm6u7S1tsDBwvj4+MPExbe4ueXm5s\u002FQ0Kyf7ewAAAAodFJOUwAABClsrNjx\u002FQM2l9\u002F7lhmI6jTB\u002FkA1GgKJN+nea6vy\u002FMLZQYeVKK3rVA5tAAAAAWJLR0QB\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\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\" alt=\"Discord\">\n  \u003C\u002Fa> |\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FMintplex-Labs\u002Fopenai-assistant-swarm\u002Fblob\u002Fmaster\u002FLICENSE\" target=\"_blank\">\n      \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fstatic\u002Fv1?label=license&message=MIT&color=white\" alt=\"许可证\">\n  \u003C\u002Fa> |\n   \u003Ca href=\"https:\u002F\u002Fmintplexlabs.com\" target=\"_blank\">\n    Mintplex Labs Inc\n  \u003C\u002Fa>|\n   \u003Ca href=\"https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002F@mintplex-labs\u002Fopenai-assistant-swarm\" target=\"_blank\">\n    NPM\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n## 什么是 Swarm 管理器？\nOpenAI 的助手 API 为开发构建自主 AI 助手（通常称为“代理”）的开发者提供了极大的便利。这个 Node.js 库通过一次 API 调用即可访问您整个自定义代理注册表及其功能。现在，一个代理“管理器”可以智能且快速地并行委派任务给一个或多个其他助手，从而让您轻松处理委派任务的操作。\n\n过去需要手动管理每个助手负责什么工作的繁琐工作，如今都由这个库自动完成，并以一种简洁的方式呈现出来。\n\n## 它是如何工作的？\nSwarm 管理器是 OpenAI Node.js SDK 的扩展——在 `beta.assistants` 上新增了一个 `.swarm` 方法。\n\n首先，安装 OpenAI 的 Node.js SDK：\n```shell\nyarn add openai\n# 或 \nnpm install openai\n```\n\n然后，安装 `openai-assistant-swarm` 包：\n```shell\nyarn add @mintplex-labs\u002Fopenai-assistant-swarm\n# 或 \nnpm install @mintplex-labs\u002Fopenai-assistant-swarm\n```\n\n接下来，像平常一样使用 SDK，调用扩展函数并初始化代理群管理器：\n```javascript\n\u002F\u002F 按照常规方式启用 OpenAI 客户端\nconst OpenAIClient = (\n    new OpenAI({\n        apiKey: process.env.OPEN_AI_KEY\n    }));\n\n\u002F\u002F 然后只需在客户端上调用此函数，即可扩展 OpenAI SDK，使其具备\n\u002F\u002F OpenAIClient.beta.assistants.swarm 相关功能。\nEnableSwarmAbilities(OpenAIClient, {\n  \u002F\u002F 所有选项均为可选\n  debug: false, \u002F\u002F 用于查看流程的控制台日志输出以及用于调试的 Playground 链接。\n  managerAssistantOptions: {\n         name: \"[AUTOMATED] ___Swarm Manager\", \u002F\u002F 由该库创建和维护的代理名称\n        model: \"gpt-4\", \u002F\u002F 使用 gpt-4 以获得更好的推理能力和调用能力。\n        instructions: '您将赋予代理管理器的任务委派指令'; \u002F\u002F 覆盖默认指令。\n    };\n});\n\n\u002F\u002F 初始化群管理器以创建群管理器，并将其注册到您的账户中。群管理器可以通过 EnableSwarmAbilities 中的选项进行配置。\nawait OpenAIClient.beta.assistants.swarm.init();\n\u002F\u002F 现在，所有群管理功能都已为您所用！\n```\n\n## 一个简单的示例\n\n以下是一个完整的示例，演示如何将单个输入委派给 3 个可用的助手……\n```javascript\nimport OpenAI from 'openai';\nimport { EnableSwarmAbilities } from '@mintplex-labs\u002Fopenai-assistant-swarm';\nconst OpenAIClient = new OpenAI({apiKey: process.env.OPEN_AI_KEY});\nEnableSwarmAbilities(OpenAIClient);\nawait OpenAIClient.beta.assistants.swarm.init();\n\n\u002F\u002F 可选——在此处设置监听器，等待特定事件返回给用户，因为目前尚不支持流式传输。\n\n\u002F\u002F 对单个文本提示运行主流程，以便在所有可用的助手之间委派任务。\nconst response = OpenAIClient.beta.assistants.swarm.delegateWithPrompt('纽约市现在的天气如何？今天最热门的股票是什么？');\n\u002F\u002F 例如，假设您的 OpenAI 助手注册表中有海盗机器人、天气机器人和股票机器人。\n\u002F\u002F 下面的线程会并行运行，并最终返回结果给您！\n\u002F\u002F |--> 将委派给现有的天气机器人\n\u002F\u002F |--> 将委派给现有的股票观察机器人\n\u002F\u002F -> 海盗机器人不会被调用。\n\u002F\u002F -----\n\u002F\u002F 主线程将回复类似如下的内容：“我已经安排了两位助手来处理您的请求。关于股票方面的协助，我已将任务委派给了股票机器人；至于旧金山的天气情况，我们的天气机器人将为您提供当前的天气状况。他们很快就会满足您的需求。”\n\u002F\u002F\n\u002F\u002F 当每个子线程完成任务或返回 `required_action` 时，您将收到响应，这些响应可以在您的代码库中轻松处理。\n\nconsole.log({\n  parentRun: response.parentRun, \u002F\u002F 主线程的所有信息\n  subRuns: response.subRuns, \u002F\u002F 为每个分叉出的子线程创建的运行数组及其状态！\n})\n\n```\n\n## 可用工具\n\n**通过提示进行委派**\n\n首先，你可能最感兴趣的主要功能——将任务委派给子助手。它的设置非常简单，同时也可以监听事件并将其融入到你当前的工作流中。\n```javascript\n\u002F\u002F 设置一个事件监听器，用于监听父级响应完成的事件，这样你就不用等待父级和所有子级的响应全部完成。\n\u002F\u002F 这在你需要提前返回父级响应，同时处理可能需要或不需要执行的子任务工具调用时非常有用。\nOpenAIClient.beta.assistants.swarm.emitter.on('parent_assistant_complete', (args) => {\n    console.group('父级助手响应已完成');\n    console.log(args.parentRun.playground) \u002F\u002F => https:\u002F\u002Fplatform.openai.com\u002Fplayground.... 用于在浏览器中调试线程和运行。\n    console.log(args.parentRun.textResponse) \u002F\u002F => 哎呀！你想跟船长说话吗？我这就去把他找来，你这个陆地笨蛋。\n    \u002F\u002F args.parentRun => OpenAI 返回的完整 Run 对象，你可以从中获取 thread_id 和其他属性，比如状态。\n    console.log('\\n\\n')\n    console.groupEnd();\n});\n\n\u002F\u002F 设置一个事件监听器，用于监听委派的子助手响应完成的事件，这样你就不用等待父级和所有子级的响应全部完成。\n\u002F\u002F 在这里，你可以处理所有子级 Run 的工具调用（如果需要的话）。\nOpenAIClient.beta.assistants.swarm.emitter.on('child_assistants_complete', (args) => {\n    console.group('子级助手响应已完成');\n    console.log(args.subRuns.map((run) => run.textResponse)) \u002F\u002F => 哎呀！我是这艘船的船长。你是来抢我的宝藏的吧？\n    console.log(args.subRuns.map((run) => run.playground)) \u002F\u002F => https:\u002F\u002Fplatform.openai.com\u002Fplayground.... 用于在浏览器中调试线程和运行。\n    \u002F\u002F args.subRuns[x].run => OpenAI 返回的完整 Run 对象，你可以从中获取 thread_id 和其他属性，比如状态。\n    console.log('\\n\\n')\n    console.groupEnd();\n});\n\n\u002F\u002F 设置一个事件监听器，以便在每个步骤事件完成后查看相关信息：\nOpenAIClient.beta.assistants.swarm.emitter.on('poll_event', ({ data }) => {\n    console.group('轮询事件！');\n    console.log({\n        状态: data.status,\n        文本: data.prompt 或 data.textResponse,\n        Run ID: data?.run?.id,\n        链接: data.playground,\n        Run 状态: data?.run?.status,\n    })\n    console.log('\\n\\n')\n    console.groupEnd();\n});\n\n\u002F\u002F 使用单个文本提示运行主流程，让工作在所有可用的助手之间自动委派。\nconst response = OpenAIClient.beta.assistants.swarm.delegateWithPrompt('让我跟这艘船的头号海盗说句话！你们怎么看？？');\n\u002F\u002F 你也可以直接等待整个流程结束，而不必设置监听器，从而使代码更加同步。\nconsole.log({\n  父级Run: response.parentRun,\n  子级Runs: response.subRuns,\n})\n\n\u002F\u002F 你还可以将给定的任务或提示聚焦到你已知想要处理委派工作的特定助手子集中。\n\u002F\u002F OpenAIClient.beta.assistants.swarm.delegateWithPrompt('让我跟这艘船的头号海盗说句话！你们怎么看？？', ['asst_lead_pirate']);\n```\n\n**获取所有可用助手**\n\n目前，你需要分页查询助手列表才能知道哪些助手可以回答问题或处理任务。现在，你只需一次调用，我们就会为你处理好分页问题。\n```javascript\nconst allAssistants = await OpenAIClient.beta.assistants.swarm.allAssistants();\nconsole.log(`在此 OpenAI 账户下找到了 ${allAssistants.length} 个助手`);\n\u002F\u002F 返回的是一个助手对象数组，你可以对其进行筛选或管理。Swarm 管理员不会出现在此列表中。\n```\n\n**一次性获取多个已知助手**\n\n通过 API，你每次只能获取一个助手。现在，你可以一次性获取多个助手。\n```javascript\nconst assistantIds = ['asst_customer_success', 'asst_lead_pirate_manager', 'asst_that_was_deleted' ]\nconst specificAssistants = await OpenAIClient.beta.assistants.swarm.getAssistants(assistantIds);\nconsole.log(`从提供的 ${assistantIds.length} 个 ID 中找到了 ${specificAssistants.length} 个助手。`);\n\u002F\u002F 返回的是一个助手对象数组，你可以对其进行筛选或管理。Swarm 管理员不会出现在此列表中。\n\u002F\u002F 无效的助手不会出现在最终结果中。\n```","# OpenAI Assistant Swarm Manager 快速上手指南\n\nOpenAI Assistant Swarm Manager 是一个 Node.js 库，旨在将您的 OpenAI Assistant（智能体）组建为一支协同工作的“军队”。它通过一个统一的 API 调用，让一个主管理智能体能够智能、并行地将任务分发给其他多个子智能体，从而轻松处理复杂的自主代理工作流。\n\n## 环境准备\n\n在开始之前，请确保您的开发环境满足以下要求：\n\n*   **运行时环境**: Node.js (推荐 v18 或更高版本)\n*   **包管理器**: npm 或 yarn\n*   **前置依赖**:\n    *   OpenAI Node.js SDK (`openai`)\n    *   OpenAI API Key (需在环境变量中配置 `OPEN_AI_KEY`)\n    *   已在 OpenAI 平台创建至少一个自定义 Assistant (用于被分发任务)\n\n> **提示**：国内开发者若遇到 npm\u002Fyarn 安装缓慢问题，可临时切换至国内镜像源：\n> ```bash\n> # npm 用户\n> npm config set registry https:\u002F\u002Fregistry.npmmirror.com\n> # yarn 用户\n> yarn config set registry https:\u002F\u002Fregistry.npmmirror.com\n> ```\n\n## 安装步骤\n\n首先安装官方的 OpenAI SDK，然后安装 `openai-assistant-swarm` 扩展库。\n\n**使用 npm:**\n```shell\nnpm install openai\nnpm install @mintplex-labs\u002Fopenai-assistant-swarm\n```\n\n**使用 yarn:**\n```shell\nyarn add openai\nyarn add @mintplex-labs\u002Fopenai-assistant-swarm\n```\n\n## 基本使用\n\n以下是最简单的使用示例，展示如何初始化 Swarm 管理器并将一个用户提示词分发给现有的多个智能体并行处理。\n\n### 1. 初始化与配置\n\n```javascript\nimport OpenAI from 'openai';\nimport { EnableSwarmAbilities } from '@mintplex-labs\u002Fopenai-assistant-swarm';\n\n\u002F\u002F 1. 像往常一样初始化 OpenAI 客户端\nconst OpenAIClient = new OpenAI({\n  apiKey: process.env.OPEN_AI_KEY\n});\n\n\u002F\u002F 2. 启用 Swarm 能力，扩展 beta.assistants 对象\nEnableSwarmAbilities(OpenAIClient, {\n  debug: false, \u002F\u002F 设为 true 可查看调试日志和 Playground 链接\n  managerAssistantOptions: {\n    name: \"[AUTOMATED] ___Swarm Manager\", \u002F\u002F 管理器智能体名称\n    model: \"gpt-4\",                       \u002F\u002F 推荐使用 gpt-4 以获得更好的推理能力\n    instructions: 'You are a manager that delegates tasks to other assistants.' \u002F\u002F 自定义指令\n  }\n});\n\n\u002F\u002F 3. 初始化 Swarm 管理器（会自动创建并注册管理器智能体）\nawait OpenAIClient.beta.assistants.swarm.init();\n```\n\n### 2. 执行任务分发\n\n调用 `delegateWithPrompt` 方法，传入自然语言指令。库会自动分析意图，并从您账户下的现有智能体中选择合适的一个或多个来并行执行任务。\n\n```javascript\n\u002F\u002F 执行分发：例如询问天气和股票，系统会自动分配给对应的 Weather Bot 和 Stock Bot\nconst response = await OpenAIClient.beta.assistants.swarm.delegateWithPrompt(\n  'What is the weather in New York city right now? Also what is the top stock for today?'\n);\n\n\u002F\u002F 查看结果\nconsole.log({\n  parentRun: response.parentRun, \u002F\u002F 父线程（管理器）的运行信息\n  subRuns: response.subRuns,     \u002F\u002F 子线程（被分发的智能体）的运行状态和结果数组\n});\n```\n\n### 3. (可选) 监听事件\n\n如果您需要实时获取进度或在子任务完成时立即处理，可以使用事件监听器：\n\n```javascript\n\u002F\u002F 监听父智能体（管理器）回复完成\nOpenAIClient.beta.assistants.swarm.emitter.on('parent_assistant_complete', (args) => {\n  console.log('管理器回复:', args.parentRun.textResponse);\n});\n\n\u002F\u002F 监听所有子智能体任务完成\nOpenAIClient.beta.assistants.swarm.emitter.on('child_assistants_complete', (args) => {\n  const results = args.subRuns.map((run) => run.textResponse);\n  console.log('子任务结果:', results);\n});\n```","某电商初创团队需要构建一个能自动处理用户售后请求的智能系统，涵盖订单查询、退货审核及物流追踪等多个环节。\n\n### 没有 openai-assistant-swarm 时\n- **开发耦合度高**：开发者需手动编写大量胶水代码，在主程序中硬编码逻辑来判断何时调用“订单助手”或“退货助手”，导致代码臃肿且难以维护。\n- **并发处理困难**：面对用户复杂的复合诉求（如同时咨询物流和申请退款），系统只能串行调用各个独立 Assistant，响应延迟显著增加，用户体验不佳。\n- **状态管理混乱**：不同专业助手之间的上下文传递需要人工拦截和转发，极易出现信息丢失或指令误解，导致任务执行中断。\n- **扩展性差**：每新增一个垂直领域的助手（如“优惠券核算”），都需要重构主调度逻辑，迭代周期长，无法快速响应业务变化。\n\n### 使用 openai-assistant-swarm 后\n- **统一接口调度**：通过 `.swarm` 方法即可将用户请求一次性分发给整个助手集群，openai-assistant-swarm 自动识别意图并路由给最匹配的专业助手，无需手动编写路由逻辑。\n- **智能并行执行**：系统能自动协调多个助手并行工作，例如同时让“物流助手”查轨迹、“财务助手”算退款，大幅缩短整体响应时间。\n- **自动化任务流转**：openai-assistant-swarm 内置的管理器自动处理助手间的上下文交接与结果汇总，确保复杂多步任务流畅完成，零信息损耗。\n- **即插即用扩展**：新创建的专用助手只需注册到集群中，openai-assistant-swarm 即可立即将其纳入调度网络，业务功能上线从数天缩短至分钟级。\n\nopenai-assistant-swarm 将分散的单点 AI 能力整合为协同作战的“智能军团”，让开发者从繁琐的流程编排中解放，专注于定义核心业务逻辑。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FMintplex-Labs_openai-assistant-swarm_bbef4b7d.png","Mintplex-Labs","Mintplex Labs","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002FMintplex-Labs_2d73495c.png","AI applications that are useful.",null,"team@mintplexlabs.com","mintplexlabs","https:\u002F\u002Fmintplexlabs.com","https:\u002F\u002Fgithub.com\u002FMintplex-Labs",[84],{"name":85,"color":86,"percentage":87},"TypeScript","#3178c6",100,607,88,"2026-04-17T21:55:35","MIT","未说明","不需要",{"notes":95,"python":93,"dependencies":96},"该工具是基于 Node.js 的库，而非 Python 项目。运行环境需要安装 Node.js 和 npm\u002Fyarn 包管理器。主要依赖为 OpenAI 官方 Node.js SDK 和 openai-assistant-swarm 扩展包。无需 GPU 支持，通过调用 OpenAI API 运行，因此内存需求取决于并发任务量而非本地模型加载。",[97,98],"openai","@mintplex-labs\u002Fopenai-assistant-swarm",[13,35,15,14,45],[101,102,103,104,105,106,107,108,109,110,111,112,113,97,114,115,116,117,118,119],"ai","ai-agents","ai-agents-framework","ai-assistant","ai-tools","autogpt","automation","function-calling","gpt-35-turbo","gpt-4-api","gpts","node-js","npm","openai-api","openai-assistant-api","openai-assistant-function-call","openai-assistants","openai-functions","openai-nodejs","2026-03-27T02:49:30.150509","2026-04-19T15:46:31.279692",[],[]]