[{"data":1,"prerenderedAt":1411},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"compare-openhuman-vs-openmanus":9,"compare-a-openhuman":10,"compare-b-openmanus":687},{"tools":4,"reviews":5},78,26,{"tools":4,"reviews":5,"playbooks":7,"news":8},22,21,null,{"id":11,"title":12,"alternatives":13,"api_compatible":9,"body":17,"category":620,"chinese_friendly":250,"cover":621,"description":622,"domestic":623,"extension":624,"faq":625,"free":623,"github":9,"languages":641,"lastVerified":9,"meta":644,"models":9,"navigation":253,"notSuitable":9,"opensource":253,"path":645,"pillar":646,"platforms":647,"priceTable":651,"pricing":660,"published":661,"relatedPlaybooks":662,"relatedReviews":664,"score":666,"self_host":253,"seo":667,"seoTitle":9,"slug":668,"sources":669,"stem":676,"suitable":9,"tagline":677,"tags":678,"updated":661,"verdict":685,"website":281,"__hash__":686},"tools\u002Ftools\u002Fagent\u002Fgeneral\u002Fopenhuman.md","OpenHuman",[14,15,16],"agent\u002Fgeneral\u002Fopenmanus","agent\u002Fgeneral\u002Fhermes-agent","agent\u002Fplatform\u002Fcoze",{"type":18,"value":19,"toc":608},"minimark",[20,25,29,32,35,124,127,144,148,153,176,181,204,207,275,284,287,299,302,469,472,516,520,549,552,572,575,604],[21,22,24],"h2",{"id":23},"tldr","TL;DR",[26,27,28],"p",{},"OpenHuman 是 TinyHumans 团队 2026-05 推出的开源个人 AI 超级智能助手，7.8k+ GitHub stars。差异点：Rust（Tauri）桌面优先架构 + 118+ 第三方 OAuth 集成 + Memory Tree 长期记忆系统（10 亿 token 容量）+ TokenJuice 智能压缩（省 80% token）+ 智能模型路由 + 桌面吉祥物 + Google Meet 参会 + 语音交互 + Obsidian 知识库兼容。20 分钟自动同步你的数字生活，构建本地私有的个人记忆库。",[26,30,31],{},"适合：追求个人 AI 助手真正了解你的知识工作者；Obsidian 用户；跨越多个工具的协作场景；关注数据隐私的用户。不适合：追求极致轻量单功能工具；需要完全离线运行（OAuth 和模型调用需网络）；无法接受 Early Beta 产品的不稳定。",[21,33,34],{"id":34},"核心能力",[36,37,38,46,52,58,64,70,76,82,88,94,100,106,112,118],"ul",{},[39,40,41,45],"li",{},[42,43,44],"strong",{},"Memory Tree 长期记忆系统","：自动抓取邮件、文档、聊天记录 → 智能评分 → 层级摘要树 → 本地 SQLite 存储 + Obsidian 兼容 .md 文件",[39,47,48,51],{},[42,49,50],{},"118+ 第三方 OAuth 集成","：Gmail \u002F Outlook \u002F Notion \u002F GitHub \u002F Slack \u002F Google Calendar \u002F Stripe \u002F Linear \u002F Jira 等",[39,53,54,57],{},[42,55,56],{},"TokenJuice 智能压缩","：HTML→Markdown \u002F URL 缩短 \u002F 去重，最高省 80% token",[39,59,60,63],{},[42,61,62],{},"智能模型路由","：统一订阅，自动分配推理 \u002F 快速 \u002F 多模态 \u002F 本地模型",[39,65,66,69],{},[42,67,68],{},"桌面吉祥物","：有表情、会说话的桌面小伙伴，响应环境变化",[39,71,72,75],{},[42,73,74],{},"Google Meet 参会","：以真实参与者身份加入线上会议",[39,77,78,81],{},[42,79,80],{},"语音交互","：STT 语音输入 + ElevenLabs TTS 语音输出 + 唇形同步",[39,83,84,87],{},[42,85,86],{},"后台持续思考","：即使不主动交互，也在后台分析和整理信息",[39,89,90,93],{},[42,91,92],{},"自动同步","：每 20 分钟自动遍历所有活跃连接，拉取最新数据",[39,95,96,99],{},[42,97,98],{},"Obsidian 兼容","：记忆以 Markdown 形式存储，可直接用 Obsidian 查看\u002F编辑",[39,101,102,105],{},[42,103,104],{},"本地优先","：核心数据存储在本地 SQLite，不上传云端",[39,107,108,111],{},[42,109,110],{},"本地加密","：数据在设备端加密存储",[39,113,114,117],{},[42,115,116],{},"Ollama 支持","：可运行本地 LLM，敏感任务完全不上云",[39,119,120,123],{},[42,121,122],{},"GPL-3.0 开源","：完整源码可审计、可定制",[21,125,126],{"id":126},"价格",[36,128,129,135,141],{},[39,130,131,134],{},[42,132,133],{},"统一订阅","：价格待定（Early Beta）；一价全包所有模型 + 自动路由",[39,136,137,140],{},[42,138,139],{},"自托管","：$0；GPL-3.0 协议，需自备 LLM API 或本地 Ollama 模型",[39,142,143],{},"自托管一次中等任务 API 费用 $0.02-0.5（取决于模型选择）",[21,145,147],{"id":146},"实测个人-ai-助手场景","实测（个人 AI 助手场景）",[26,149,150],{},[42,151,152],{},"亮点：",[36,154,155,158,161,164,167,170,173],{},[39,156,157],{},"Memory Tree 让 AI 真正拥有\"长期记忆\"，不是每次对话从零开始",[39,159,160],{},"118+ 集成开箱即用，OAuth 一键连接，无需手动配置 API",[39,162,163],{},"TokenJuice 压缩效果显著，实测 token 消耗降低 60-80%",[39,165,166],{},"桌面 UI 设计精美，吉祥物交互有趣，不是命令行工具",[39,168,169],{},"自动同步机制省心，不用手动通知 AI 新信息",[39,171,172],{},"Obsidian 兼容让记忆透明可读，用户完全掌控自己的数据",[39,174,175],{},"智能模型路由省去手动切换模型的麻烦",[26,177,178],{},[42,179,180],{},"踩坑：",[36,182,183,186,189,192,195,198,201],{},[39,184,185],{},"Early Beta 阶段，功能迭代快，偶尔有 breaking change",[39,187,188],{},"中文支持依赖底层模型，部分场景效果不如英文",[39,190,191],{},"OAuth 连接器稳定性参差不齐，部分服务偶尔断连",[39,193,194],{},"桌面吉祥物 CPU\u002F内存占用不低，低配机器略卡",[39,196,197],{},"文档尚在完善中，部分功能缺少详细说明",[39,199,200],{},"自动同步频率固定 20 分钟，无法手动触发即时同步",[39,202,203],{},"隐私边界需关注：虽然数据本地存储，但 OAuth 连接和模型调用涉及网络",[21,205,206],{"id":206},"上手",[208,209,214],"pre",{"className":210,"code":211,"language":212,"meta":213,"style":213},"language-bash shiki shiki-themes github-light github-dark","# macOS \u002F Linux\ncurl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Ftinyhumansai\u002Fopenhuman\u002Fmain\u002Fscripts\u002Finstall.sh | bash\n\n# Windows (PowerShell)\nirm https:\u002F\u002Fraw.githubusercontent.com\u002Ftinyhumansai\u002Fopenhuman\u002Fmain\u002Fscripts\u002Finstall.ps1 | iex\n","bash","",[215,216,217,226,248,255,261],"code",{"__ignoreMap":213},[218,219,222],"span",{"class":220,"line":221},"line",1,[218,223,225],{"class":224},"sJ8bj","# macOS \u002F Linux\n",[218,227,229,233,237,241,245],{"class":220,"line":228},2,[218,230,232],{"class":231},"sScJk","curl",[218,234,236],{"class":235},"sj4cs"," -fsSL",[218,238,240],{"class":239},"sZZnC"," https:\u002F\u002Fraw.githubusercontent.com\u002Ftinyhumansai\u002Fopenhuman\u002Fmain\u002Fscripts\u002Finstall.sh",[218,242,244],{"class":243},"szBVR"," |",[218,246,247],{"class":231}," bash\n",[218,249,251],{"class":220,"line":250},3,[218,252,254],{"emptyLinePlaceholder":253},true,"\n",[218,256,258],{"class":220,"line":257},4,[218,259,260],{"class":224},"# Windows (PowerShell)\n",[218,262,264,267,270,272],{"class":220,"line":263},5,[218,265,266],{"class":231},"irm",[218,268,269],{"class":239}," https:\u002F\u002Fraw.githubusercontent.com\u002Ftinyhumansai\u002Fopenhuman\u002Fmain\u002Fscripts\u002Finstall.ps1",[218,271,244],{"class":243},[218,273,274],{"class":231}," iex\n",[26,276,277,278],{},"或从官网下载安装包：",[279,280,281],"a",{"href":281,"rel":282},"https:\u002F\u002Ftinyhumans.ai\u002Fopenhuman",[283],"nofollow",[26,285,286],{},"首次启动后：",[288,289,290,293,296],"ol",{},[39,291,292],{},"完成 OAuth 授权连接你的邮箱 \u002F 日历 \u002F 文档 \u002F 代码仓库",[39,294,295],{},"等待 2-5 分钟初始数据同步（Memory Tree 自动构建）",[39,297,298],{},"开始对话——AI 已经知道你的工作背景和习惯",[21,300,301],{"id":301},"对比",[303,304,305,326],"table",{},[306,307,308],"thead",{},[309,310,311,315,317,320,323],"tr",{},[312,313,314],"th",{},"维度",[312,316,12],{},[312,318,319],{},"Claude Cowork",[312,321,322],{},"OpenClaw",[312,324,325],{},"Hermes Agent",[327,328,329,346,362,378,395,411,425,441,454],"tbody",{},[309,330,331,335,338,341,344],{},[332,333,334],"td",{},"形态",[332,336,337],{},"桌面应用",[332,339,340],{},"桌面+CLI",[332,342,343],{},"终端",[332,345,343],{},[309,347,348,351,354,357,360],{},[332,349,350],{},"开源",[332,352,353],{},"✅ GPL-3.0",[332,355,356],{},"❌ 专有",[332,358,359],{},"✅ MIT",[332,361,359],{},[309,363,364,367,370,373,376],{},[332,365,366],{},"上手难度",[332,368,369],{},"✅ UI 优先，几分钟",[332,371,372],{},"✅ 桌面",[332,374,375],{},"⚠️ 终端",[332,377,375],{},[309,379,380,383,386,389,392],{},[332,381,382],{},"长期记忆",[332,384,385],{},"✅ Memory Tree",[332,387,388],{},"⚠️ 对话级",[332,390,391],{},"⚠️ 依赖插件",[332,393,394],{},"✅ 自学习",[309,396,397,400,403,406,409],{},[332,398,399],{},"集成数量",[332,401,402],{},"118+ OAuth",[332,404,405],{},"少",[332,407,408],{},"需自建",[332,410,408],{},[309,412,413,415,418,421,423],{},[332,414,92],{},[332,416,417],{},"✅ 20分钟",[332,419,420],{},"❌",[332,422,420],{},[332,424,420],{},[309,426,427,430,433,436,439],{},[332,428,429],{},"模型路由",[332,431,432],{},"✅ 内置智能",[332,434,435],{},"❌ 单一",[332,437,438],{},"⚠️ 手动",[332,440,438],{},[309,442,443,445,448,450,452],{},[332,444,68],{},[332,446,447],{},"✅",[332,449,420],{},[332,451,420],{},[332,453,420],{},[309,455,456,459,461,464,467],{},[332,457,458],{},"隐私",[332,460,104],{},[332,462,463],{},"云端",[332,465,466],{},"本地",[332,468,466],{},[21,470,471],{"id":471},"避坑",[36,473,474,480,486,492,498,504,510],{},[39,475,476,479],{},[42,477,478],{},"Early Beta 不稳定","：功能迭代快，关键工作建议备份记忆数据",[39,481,482,485],{},[42,483,484],{},"中文效果","：依赖底层模型，GPT-4o \u002F Claude 中文效果好，本地模型待验证",[39,487,488,491],{},[42,489,490],{},"OAuth 断连","：部分服务 token 会过期，需定期检查连接状态",[39,493,494,497],{},[42,495,496],{},"TokenJuice 精度","：压缩虽好，处理合同\u002F账单等敏感内容需注意细节丢失",[39,499,500,503],{},[42,501,502],{},"资源占用","：桌面吉祥物 + 后台同步建议 8GB+ 内存",[39,505,506,509],{},[42,507,508],{},"网络依赖","：OAuth 连接和远程模型调用需要稳定网络",[39,511,512,515],{},[42,513,514],{},"隐私边界","：虽然数据本地存储，但 OAuth 连接意味着服务商可知你的连接状态",[21,517,519],{"id":518},"适合-不适合","适合 \u002F 不适合",[36,521,522,525,528,531,534,537,540,543,546],{},[39,523,524],{},"✅ 追求个人 AI 助手真正了解你的知识工作者",[39,526,527],{},"✅ Obsidian 用户，希望 AI 自动维护知识库",[39,529,530],{},"✅ 工作流跨越多个工具（Gmail \u002F Slack \u002F Notion \u002F GitHub）",[39,532,533],{},"✅ 关注数据隐私，希望敏感信息保留在本地",[39,535,536],{},"✅ 愿意尝试 Early Beta，能接受快速迭代",[39,538,539],{},"❌ 追求极致轻量，不需要那么多集成功能",[39,541,542],{},"❌ 对隐私要求极高，希望完全离线运行",[39,544,545],{},"❌ 无法接受 Beta 产品的粗糙边缘和偶发 bug",[39,547,548],{},"❌ 需要中文深度优化（当前英文体验最佳）",[21,550,551],{"id":551},"相关阅读",[36,553,554,560,566],{},[39,555,556],{},[279,557,559],{"href":558},"\u002Fagent\u002Fgeneral\u002Fopenmanus.html","OpenManus 工具卡：开源版 Manus",[39,561,562],{},[279,563,565],{"href":564},"\u002Fagent\u002Fgeneral\u002Fhermes-agent.html","Hermes Agent 工具卡：自学习 AI Agent",[39,567,568],{},[279,569,571],{"href":570},"\u002Fagent\u002Fplatform\u002Fcoze.html","Coze 平台评测",[21,573,574],{"id":574},"来源",[288,576,577,584,590,597],{},[39,578,579,580],{},"OpenHuman GitHub 主仓库 + TinyHumans 组织 ",[279,581,582],{"href":582,"rel":583},"https:\u002F\u002Fgithub.com\u002Ftinyhumansai\u002Fopenhuman",[283],[39,585,586,587],{},"OpenHuman 官网 ",[279,588,281],{"href":281,"rel":589},[283],[39,591,592,593],{},"OpenHuman 文档 ",[279,594,595],{"href":595,"rel":596},"https:\u002F\u002Ftinyhumans.gitbook.io\u002Fopenhuman",[283],[39,598,599,600],{},"OpenHuman Discord ",[279,601,602],{"href":602,"rel":603},"https:\u002F\u002Fdiscord.tinyhumans.ai\u002F",[283],[605,606,607],"style",{},"html pre.shiki code .sJ8bj, html code.shiki .sJ8bj{--shiki-default:#6A737D;--shiki-dark:#6A737D}html pre.shiki code .sScJk, html code.shiki .sScJk{--shiki-default:#6F42C1;--shiki-dark:#B392F0}html pre.shiki code .sj4cs, html code.shiki .sj4cs{--shiki-default:#005CC5;--shiki-dark:#79B8FF}html pre.shiki code .sZZnC, html code.shiki .sZZnC{--shiki-default:#032F62;--shiki-dark:#9ECBFF}html pre.shiki code .szBVR, html code.shiki .szBVR{--shiki-default:#D73A49;--shiki-dark:#F97583}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":213,"searchDepth":250,"depth":250,"links":609},[610,611,612,613,614,615,616,617,618,619],{"id":23,"depth":228,"text":24},{"id":34,"depth":228,"text":34},{"id":126,"depth":228,"text":126},{"id":146,"depth":228,"text":147},{"id":206,"depth":228,"text":206},{"id":301,"depth":228,"text":301},{"id":471,"depth":228,"text":471},{"id":518,"depth":228,"text":519},{"id":551,"depth":228,"text":551},{"id":574,"depth":228,"text":574},"general","\u002Fimg\u002Ftools\u002Fopenhuman.svg","OpenHuman 真实评测：TinyHumans 团队 2026-05 开源的个人 AI 超级智能助手，7.8k+ GitHub stars。GPL-3.0 协议 + Rust（Tauri）架构 + 桌面 UI 优先 + 118+ 第三方 OAuth 集成 + Memory Tree 长期记忆系统（10亿 token 容量）+ TokenJuice 智能压缩（省 80% token）+ 智能模型路由 + 桌面吉祥物 + Google Meet 参会 + 语音交互 + Obsidian 知识库兼容。20 分钟自动同步你的邮箱、日历、文档、代码仓库，构建本地私有的个人记忆库。",false,"md",[626,629,632,635,638],{"q":627,"a":628},"OpenHuman 和 ChatGPT \u002F Claude 有什么不同？","ChatGPT \u002F Claude 是通用对话 AI，每次对话从零开始，没有你的长期记忆。OpenHuman 通过 Memory Tree 系统持续学习你的邮件、日历、文档、代码仓库，构建一个持续更新的个人记忆库。它知道『你是谁』而非只是『你问了什么』。",{"q":630,"a":631},"OpenHuman 的数据安全如何？","核心记忆数据存储在本地 SQLite 数据库，不上传云端。数据在设备端加密存储。可通过 Ollama 运行本地 LLM 实现敏感任务完全离线。但 OAuth 连接和远程模型调用仍涉及网络传输。",{"q":633,"a":634},"Memory Tree 是什么？","OpenHuman 的核心记忆系统。所有接入数据（邮件、文档、聊天记录）被转化为 ≤3000 token 的 Markdown 块，经智能评分后折叠成层级摘要树，存入本地 SQLite。同时生成 .md 文件同步到 Obsidian 知识库。记忆容量可达 10 亿 token。",{"q":636,"a":637},"TokenJuice 有什么用？","TokenJuice 是 OpenHuman 的智能压缩层，在数据进入 LLM 前进行预处理——HTML 转 Markdown、长 URL 缩短、重复内容去重等，最高可降低 80% 的 token 消耗，大幅降低 API 成本和响应延迟。",{"q":639,"a":640},"支持哪些第三方服务？","118+ 第三方 OAuth 集成，涵盖：Gmail \u002F Outlook（邮件）、Notion \u002F Google Docs \u002F Obsidian（文档）、GitHub \u002F GitLab（代码）、Slack \u002F Discord（沟通）、Google Calendar \u002F Outlook Calendar（日历）、Google Drive \u002F Dropbox（存储）、Stripe（支付）、Linear \u002F Jira（项目）等。",[642,643],"en","multi",{},"\u002Ftools\u002Fagent\u002Fgeneral\u002Fopenhuman","agent",[648,649,650],"linux","macos","windows",[652,656],{"plan":133,"price":653,"features":654,"notes":655},"待定","全部模型 + 自动路由 + 118+ 集成 + Memory Tree + TokenJuice","Early Beta 定价可能调整",{"plan":139,"price":657,"features":658,"notes":659},"$0","GPL-3.0 协议 + 全部功能 + 可接 Ollama 本地模型","需自备 LLM API","统一订阅制（一价全包，自动模型路由）\u002F 自备 LLM API 可选","2026-07-17",[663],"onboarding\u002Fpersonal-ai-agent",[665],"openhuman-deep-review",{"power":257,"ux":263,"price":257,"cn_support":250,"stability":250},{"title":12,"description":622},"agent\u002Fgeneral\u002Fopenhuman",[670,672,674],{"name":671,"url":582,"accessed":661},"OpenHuman GitHub（TinyHumans 组织）",{"name":673,"url":281,"accessed":661},"OpenHuman 官网",{"name":675,"url":595,"accessed":661},"OpenHuman 文档","tools\u002Fagent\u002Fgeneral\u002Fopenhuman","TinyHumans 团队开源个人 AI 超级智能——118+ 集成 \u002F Memory Tree \u002F TokenJuice 压缩 \u002F 桌面优先",[679,680,681,646,682,683,684],"opensource","personal-ai","memory-tree","desktop","obsidian","rust","想要一个真正懂你、记得你、能自动学习的个人 AI 助手——OpenHuman 是目前开源社区最完整的选择。Memory Tree + 118+ 集成 + TokenJuice 压缩 + 桌面 UI 设计，让 AI 从『聊天工具』升级为『数字分身』。适合注重隐私、使用多平台工具的知识工作者。Early Beta 阶段，功能迭代快，适合愿意尝鲜的用户。","04_vvWTbB6SIvLrj3ZPMYuag3r930_UxuzpUgV7DQjI",{"id":688,"title":689,"alternatives":690,"api_compatible":9,"body":694,"category":620,"chinese_friendly":257,"cover":1358,"description":1359,"domestic":623,"extension":624,"faq":1360,"free":623,"github":9,"languages":1373,"lastVerified":9,"meta":1375,"models":9,"navigation":253,"notSuitable":9,"opensource":253,"path":1376,"pillar":646,"platforms":1377,"priceTable":1379,"pricing":1383,"published":1384,"relatedPlaybooks":1385,"relatedReviews":1387,"score":1389,"self_host":253,"seo":1390,"seoTitle":9,"slug":14,"sources":1391,"stem":1401,"suitable":9,"tagline":1402,"tags":1403,"updated":1394,"verdict":1409,"website":1320,"__hash__":1410},"tools\u002Ftools\u002Fagent\u002Fgeneral\u002Fopenmanus.md","OpenManus",[691,692,693],"agent\u002Fplatform\u002Flangflow","agent\u002Fplatform\u002Fn8n","agent\u002Fprotocol\u002Fcomposio",{"type":18,"value":695,"toc":1346},[696,698,705,708,710,787,789,806,810,814,840,844,870,872,1015,1018,1026,1028,1199,1201,1261,1263,1289,1291,1311,1313,1343],[21,697,24],{"id":23},[26,699,700,701,704],{},"OpenManus 是 MetaGPT 核心团队 2025-03 推出的开源 Manus 替代方案，52,000+ GitHub stars。差异点：MIT 协议 + Python 模块化架构 + 多 agent orchestration（",[215,702,703],{},"run_flow.py","）+ Playwright 浏览器自动化 + MCP 工具协议支持 + DataAnalysis 内置模式 + OpenManus-RL 强化学习分支 + 自定义工具基类（BaseTool）+ 多模型（GPT-4o \u002F Claude \u002F Qwen VL Plus）。零邀请码、零订阅、零供应商绑定。",[26,706,707],{},"适合：想自托管复刻 Manus 体验的开发者；研究 \u002F 学术 \u002F 教育用通用 agent 实现学习；隐私敏感 + 不愿数据上 Manus 商业云；预算紧（只付 LLM API）；中国大陆开发者（搭配 Qwen \u002F DeepSeek 本地化）。不适合：非开发者 \u002F 不会折腾 Python + Playwright；要 GUI \u002F 上手即用；生产级稳定（项目演进快，文档滞后）。",[21,709,34],{"id":34},[36,711,712,721,727,733,739,745,751,757,763,769,775,781],{},[39,713,714,717,718,720],{},[42,715,716],{},"多 agent orchestration","：",[215,719,703],{}," 编排多个专门 agent 协作",[39,722,723,726],{},[42,724,725],{},"Playwright 浏览器自动化","：截图 + DOM 操作 + 表单填写 + 信息抓取",[39,728,729,732],{},[42,730,731],{},"MCP 协议支持","：可调用 MCP server（filesystem \u002F GitHub \u002F Postgres）",[39,734,735,738],{},[42,736,737],{},"DataAnalysis 模式","：内置 CSV \u002F 数据分析 agent",[39,740,741,744],{},[42,742,743],{},"OpenManus-RL","：强化学习微调分支",[39,746,747,750],{},[42,748,749],{},"BaseTool 自定义工具","：Python 继承基类快速添加新工具",[39,752,753,756],{},[42,754,755],{},"多模态","：文本 + 视觉输入 + 浏览器截图回环",[39,758,759,762],{},[42,760,761],{},"多 LLM provider","：GPT-4o \u002F Claude 3.5 \u002F Qwen VL Plus \u002F DeepSeek \u002F Gemini",[39,764,765,768],{},[42,766,767],{},"核心 agent 引擎","：reasoning + planning + execution 三阶段",[39,770,771,774],{},[42,772,773],{},"Web UI 监控","：实时看 AI thinking process",[39,776,777,780],{},[42,778,779],{},"任务可视化","：步骤拆解 + 执行树",[39,782,783,786],{},[42,784,785],{},"MIT 协议","：个人 + 商用全免费",[21,788,126],{"id":126},[36,790,791,797,800,803],{},[39,792,793,796],{},[42,794,795],{},"Free \u002F OSS","：$0；MIT 协议",[39,798,799],{},"真实成本 = LLM API（GPT-4o ~$5\u002FM input + $15\u002FM output \u002F Claude \u002F Qwen 等）",[39,801,802],{},"一次中等任务（10-20 步）API 费用 $0.05-0.5",[39,804,805],{},"本地 Qwen2.5 32B \u002F DeepSeek 走 vLLM \u002F Ollama 路径 $0",[21,807,809],{"id":808},"实测开发者-自托管-研究场景","实测（开发者 \u002F 自托管 \u002F 研究场景）",[26,811,812],{},[42,813,152],{},[36,815,816,819,822,825,828,831,834,837],{},[39,817,818],{},"52k stars 印证社区认同度 + 活跃度",[39,820,821],{},"MetaGPT 团队背景保证架构质量",[39,823,824],{},"多 agent 协作场景比单 agent 实现稳得多",[39,826,827],{},"Playwright 浏览器自动化非常完整",[39,829,830],{},"MCP 协议接入打通 Claude \u002F Cursor 生态",[39,832,833],{},"DataAnalysis 内置 agent 模式开箱即用",[39,835,836],{},"中文支持自然（Qwen VL Plus 接入）",[39,838,839],{},"自托管 + 数据本地，隐私 \u002F 合规友好",[26,841,842],{},[42,843,180],{},[36,845,846,849,852,855,858,861,864,867],{},[39,847,848],{},"项目演进快，breaking change 偶发（pin commit 跑生产）",[39,850,851],{},"文档滞后新功能 1-2 个月",[39,853,854],{},"无官方 GUI，监控 UI 在做但不完整",[39,856,857],{},"需要 Python 3.12+ + Playwright 依赖（首次安装 chromium 慢）",[39,859,860],{},"LLM API 配置非平凡（多 provider \u002F key \u002F 模型选择）",[39,862,863],{},"浏览器任务遇到 CAPTCHA \u002F 反爬偶尔卡死",[39,865,866],{},"中文 prompt 效果依赖底层模型",[39,868,869],{},"生产部署需自己加监控 \u002F 错误恢复 \u002F 重试",[21,871,206],{"id":206},[208,873,875],{"className":210,"code":874,"language":212,"meta":213,"style":213},"git clone https:\u002F\u002Fgithub.com\u002FFoundationAgents\u002FOpenManus.git\ncd OpenManus\npython3.12 -m venv .venv && source .venv\u002Fbin\u002Factivate  # 或 .venv\\Scripts\\activate\npip install -r requirements.txt\nplaywright install chromium\n\n# 配 LLM API\ncp config\u002Fconfig.example.toml config\u002Fconfig.toml\n# 编辑 config.toml 填 OPENAI \u002F ANTHROPIC \u002F DEEPSEEK key\n\n# 单 agent 模式\npython main.py\n\n# 多 agent 模式\npython run_flow.py\n",[215,876,877,888,896,923,937,947,952,958,970,976,981,987,996,1001,1007],{"__ignoreMap":213},[218,878,879,882,885],{"class":220,"line":221},[218,880,881],{"class":231},"git",[218,883,884],{"class":239}," clone",[218,886,887],{"class":239}," https:\u002F\u002Fgithub.com\u002FFoundationAgents\u002FOpenManus.git\n",[218,889,890,893],{"class":220,"line":228},[218,891,892],{"class":235},"cd",[218,894,895],{"class":239}," OpenManus\n",[218,897,898,901,904,907,910,914,917,920],{"class":220,"line":250},[218,899,900],{"class":231},"python3.12",[218,902,903],{"class":235}," -m",[218,905,906],{"class":239}," venv",[218,908,909],{"class":239}," .venv",[218,911,913],{"class":912},"sVt8B"," && ",[218,915,916],{"class":235},"source",[218,918,919],{"class":239}," .venv\u002Fbin\u002Factivate",[218,921,922],{"class":224},"  # 或 .venv\\Scripts\\activate\n",[218,924,925,928,931,934],{"class":220,"line":257},[218,926,927],{"class":231},"pip",[218,929,930],{"class":239}," install",[218,932,933],{"class":235}," -r",[218,935,936],{"class":239}," requirements.txt\n",[218,938,939,942,944],{"class":220,"line":263},[218,940,941],{"class":231},"playwright",[218,943,930],{"class":239},[218,945,946],{"class":239}," chromium\n",[218,948,950],{"class":220,"line":949},6,[218,951,254],{"emptyLinePlaceholder":253},[218,953,955],{"class":220,"line":954},7,[218,956,957],{"class":224},"# 配 LLM API\n",[218,959,961,964,967],{"class":220,"line":960},8,[218,962,963],{"class":231},"cp",[218,965,966],{"class":239}," config\u002Fconfig.example.toml",[218,968,969],{"class":239}," config\u002Fconfig.toml\n",[218,971,973],{"class":220,"line":972},9,[218,974,975],{"class":224},"# 编辑 config.toml 填 OPENAI \u002F ANTHROPIC \u002F DEEPSEEK key\n",[218,977,979],{"class":220,"line":978},10,[218,980,254],{"emptyLinePlaceholder":253},[218,982,984],{"class":220,"line":983},11,[218,985,986],{"class":224},"# 单 agent 模式\n",[218,988,990,993],{"class":220,"line":989},12,[218,991,992],{"class":231},"python",[218,994,995],{"class":239}," main.py\n",[218,997,999],{"class":220,"line":998},13,[218,1000,254],{"emptyLinePlaceholder":253},[218,1002,1004],{"class":220,"line":1003},14,[218,1005,1006],{"class":224},"# 多 agent 模式\n",[218,1008,1010,1012],{"class":220,"line":1009},15,[218,1011,992],{"class":231},[218,1013,1014],{"class":239}," run_flow.py\n",[26,1016,1017],{},"试任务示例：",[208,1019,1024],{"className":1020,"code":1022,"language":1023},[1021],"language-text","> 帮我做一份『2026 开源 AI Agent 框架』竞品对比，含表格 + 引用 + 趋势分析，输出为 markdown 文件\n","text",[215,1025,1022],{"__ignoreMap":213},[21,1027,301],{"id":301},[303,1029,1030,1047],{},[306,1031,1032],{},[309,1033,1034,1036,1038,1041,1044],{},[312,1035,314],{},[312,1037,689],{},[312,1039,1040],{},"LangChain",[312,1042,1043],{},"AutoGPT",[312,1045,1046],{},"CrewAI",[327,1048,1049,1065,1081,1094,1110,1123,1137,1151,1168,1182],{},[309,1050,1051,1053,1056,1059,1062],{},[332,1052,334],{},[332,1054,1055],{},"现成 agent 实现",[332,1057,1058],{},"building blocks",[332,1060,1061],{},"早期通用 agent",[332,1063,1064],{},"多 agent 框架",[309,1066,1067,1070,1073,1076,1079],{},[332,1068,1069],{},"浏览器自动化",[332,1071,1072],{},"✅ Playwright",[332,1074,1075],{},"–",[332,1077,1078],{},"部分",[332,1080,1075],{},[309,1082,1083,1086,1088,1090,1092],{},[332,1084,1085],{},"MCP",[332,1087,447],{},[332,1089,1078],{},[332,1091,1075],{},[332,1093,1075],{},[309,1095,1096,1099,1102,1105,1107],{},[332,1097,1098],{},"多 agent",[332,1100,1101],{},"✅ orchestration",[332,1103,1104],{},"需自搭",[332,1106,420],{},[332,1108,1109],{},"✅ 旗舰",[309,1111,1112,1115,1117,1119,1121],{},[332,1113,1114],{},"DataAnalysis 内置",[332,1116,447],{},[332,1118,1075],{},[332,1120,1075],{},[332,1122,1075],{},[309,1124,1125,1128,1131,1133,1135],{},[332,1126,1127],{},"RL 微调",[332,1129,1130],{},"✅ OpenManus-RL",[332,1132,1075],{},[332,1134,1075],{},[332,1136,1075],{},[309,1138,1139,1142,1145,1147,1149],{},[332,1140,1141],{},"协议",[332,1143,1144],{},"MIT",[332,1146,1144],{},[332,1148,1144],{},[332,1150,1144],{},[309,1152,1153,1156,1159,1162,1165],{},[332,1154,1155],{},"Stars",[332,1157,1158],{},"52k+",[332,1160,1161],{},"100k+",[332,1163,1164],{},"170k+",[332,1166,1167],{},"30k+",[309,1169,1170,1172,1175,1178,1180],{},[332,1171,206],{},[332,1173,1174],{},"中",[332,1176,1177],{},"难",[332,1179,1174],{},[332,1181,1174],{},[309,1183,1184,1187,1190,1193,1196],{},[332,1185,1186],{},"适合",[332,1188,1189],{},"自托管 Manus 复刻",[332,1191,1192],{},"底层 framework",[332,1194,1195],{},"学习经典",[332,1197,1198],{},"多 agent 协作",[21,1200,471],{"id":471},[36,1202,1203,1209,1219,1225,1231,1237,1243,1249,1255],{},[39,1204,1205,1208],{},[42,1206,1207],{},"pin commit 用生产","：项目演进快，main 分支偶尔 break",[39,1210,1211,1214,1215,1218],{},[42,1212,1213],{},"Playwright 依赖大","：首次 ",[215,1216,1217],{},"playwright install"," 下 chromium 慢，国内走镜像",[39,1220,1221,1224],{},[42,1222,1223],{},"LLM 选择","：日常用 GPT-4o-mini \u002F DeepSeek 省钱，复杂任务切 GPT-4o \u002F Claude Opus",[39,1226,1227,1230],{},[42,1228,1229],{},"本地化中文","：Qwen2.5 VL 32B + vLLM 部署可全本地 + 零成本",[39,1232,1233,1236],{},[42,1234,1235],{},"监控自加","：生产部署要加 prometheus + 错误重试 + 任务超时",[39,1238,1239,1242],{},[42,1240,1241],{},"浏览器反爬","：CAPTCHA 场景搭配 2captcha \u002F human-in-loop",[39,1244,1245,1248],{},[42,1246,1247],{},"OpenManus-RL 分支","：研究场景才需要，普通用户主仓库就够",[39,1250,1251,1254],{},[42,1252,1253],{},"MCP server","：信任来源很重要，能访问的目录 \u002F 工具要审慎",[39,1256,1257,1260],{},[42,1258,1259],{},"多 agent runaway","：复杂任务设 max_steps 防止失控烧 token",[21,1262,519],{"id":518},[36,1264,1265,1268,1271,1274,1277,1280,1283,1286],{},[39,1266,1267],{},"✅ 开发者 + 想自托管 Manus 风格 agent",[39,1269,1270],{},"✅ 研究 \u002F 学术 \u002F 教育用通用 agent 学习",[39,1272,1273],{},"✅ 隐私敏感 + 不愿数据上商业云",[39,1275,1276],{},"✅ 中国大陆开发者（Qwen \u002F DeepSeek 本地化）",[39,1278,1279],{},"❌ 非开发者 \u002F 不会 Python + Playwright",[39,1281,1282],{},"❌ 要 GUI \u002F 上手即用",[39,1284,1285],{},"❌ 生产级稳定（文档滞后 + 演进快）",[39,1287,1288],{},"❌ 团队协作 + 共享 workspace（用 Flowith \u002F Genspark Team）",[21,1290,551],{"id":551},[36,1292,1293,1299,1305],{},[39,1294,1295],{},[279,1296,1298],{"href":1297},"\u002Ftools\u002Fagent\u002Fplatform\u002Flangflow","Langflow 评测",[39,1300,1301],{},[279,1302,1304],{"href":1303},"\u002Ftools\u002Fagent\u002Fplatform\u002Fn8n","n8n 评测",[39,1306,1307],{},[279,1308,1310],{"href":1309},"\u002Ftools\u002Fagent\u002Fprotocol\u002Fcomposio","Composio 评测",[21,1312,574],{"id":574},[288,1314,1315,1322,1329,1336],{},[39,1316,1317,1318],{},"OpenManus GitHub 主仓库 + Foundation Agents 组织 ",[279,1319,1320],{"href":1320,"rel":1321},"https:\u002F\u002Fgithub.com\u002FFoundationAgents\u002FOpenManus",[283],[39,1323,1324,1325],{},"Foundation Agents — OpenManus 项目介绍 ",[279,1326,1327],{"href":1327,"rel":1328},"https:\u002F\u002Ffoundationagents.org\u002Fprojects\u002Fopenmanus\u002F",[283],[39,1330,1331,1332],{},"Toolsverse — OpenManus 评测 + 52k stars ",[279,1333,1334],{"href":1334,"rel":1335},"https:\u002F\u002Fthetoolsverse.com\u002Ftools\u002Fopenmanus",[283],[39,1337,1338,1339],{},"SoloSoft.dev — OpenManus 2026 Framework 综述 ",[279,1340,1341],{"href":1341,"rel":1342},"https:\u002F\u002Fwww.solosoft.dev\u002Fpost\u002Fopenmanus-agent-framework-2026\u002F",[283],[605,1344,1345],{},"html pre.shiki code .sScJk, html code.shiki .sScJk{--shiki-default:#6F42C1;--shiki-dark:#B392F0}html pre.shiki code .sZZnC, html code.shiki .sZZnC{--shiki-default:#032F62;--shiki-dark:#9ECBFF}html pre.shiki code .sj4cs, html code.shiki .sj4cs{--shiki-default:#005CC5;--shiki-dark:#79B8FF}html pre.shiki code .sVt8B, html code.shiki .sVt8B{--shiki-default:#24292E;--shiki-dark:#E1E4E8}html pre.shiki code .sJ8bj, html code.shiki .sJ8bj{--shiki-default:#6A737D;--shiki-dark:#6A737D}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":213,"searchDepth":250,"depth":250,"links":1347},[1348,1349,1350,1351,1352,1353,1354,1355,1356,1357],{"id":23,"depth":228,"text":24},{"id":34,"depth":228,"text":34},{"id":126,"depth":228,"text":126},{"id":808,"depth":228,"text":809},{"id":206,"depth":228,"text":206},{"id":301,"depth":228,"text":301},{"id":471,"depth":228,"text":471},{"id":518,"depth":228,"text":519},{"id":551,"depth":228,"text":551},{"id":574,"depth":228,"text":574},"\u002Fimg\u002Ftools\u002Fopenmanus.webp","OpenManus 真实评测：MetaGPT 核心成员 Xinbin Liang \u002F Jinyu Xiang \u002F Zhaoyang Yu \u002F Jiayi Zhang \u002F Sirui Hong 在 2025-03 推出的开源 Manus 替代方案，52,000+ GitHub stars。MIT 协议 + Python 模块化架构 + 多 agent orchestration（run_flow.py）+ Playwright 浏览器自动化 + MCP 工具支持 + DataAnalysis 内置模式 + OpenManus-RL 强化学习微调分支 + 自定义工具基类（BaseTool）。零邀请码、零订阅、零供应商绑定，唯一成本 = LLM API。",[1361,1364,1367,1370],{"q":1362,"a":1363},"OpenManus 和 Manus 是什么关系？","Manus 是商业 \u002F 邀请制的通用 AI agent 产品。OpenManus 是 MetaGPT 核心团队 2025-03 推出的开源复刻版，目标是『让所有人不靠邀请码就能用上类 Manus 能力』。功能覆盖：研究 \u002F 浏览器 \u002F 数据分析 \u002F 文件操作 \u002F 多步 reasoning。不是 Manus 官方出品。",{"q":1365,"a":1366},"和 LangChain \u002F AutoGPT \u002F CrewAI 怎么定位？","OpenManus 不是 framework，更像『可直接跑的通用 agent 实现』。LangChain 是 building block 框架；AutoGPT 是早期通用 agent；CrewAI 是多 agent 协作 framework。要『拉下来配 API 就能跑 Manus 风格任务』→ OpenManus；要『从底层搭自己的 agent』→ LangChain \u002F CrewAI；要『历史经典 + 学习』→ AutoGPT。OpenManus 内部用 LangChain-like 模块，可视为『现成实现』。",{"q":1368,"a":1369},"OpenManus-RL 是什么？","OpenManus 项目下的强化学习分支，提供 RL-based 微调方法优化 agent 性能。对研究 \u002F 高定制场景有价值，普通用户主仓库已经够用。",{"q":1371,"a":1372},"上手门槛？","需要 Python 3.12+ + 熟悉终端 + 自配 LLM API。无 GUI（虽然 web 监控界面在做）。documentation 偶尔滞后。非开发者建议先试 GUI 工具（Flowith \u002F Genspark），开发者 \u002F 研究者 + 想自托管 + 隐私敏感 → OpenManus。",[642,1374,643],"zh",{},"\u002Ftools\u002Fagent\u002Fgeneral\u002Fopenmanus",[648,649,650,1378],"docker",[1380],{"plan":795,"price":657,"features":1381,"notes":1382},"MIT 协议 + 全部功能 + 自托管 + 多 agent + 浏览器 + MCP + DataAnalysis + OpenManus-RL","LLM API 自付","MIT 完全免费开源 \u002F 用户自付 LLM API（GPT-4o \u002F Claude 3.5 \u002F Qwen VL Plus 任选）","2026-06-19",[1386],"onboarding\u002Fopen-source-general-agent",[665,1388],"openmanus-deep-review",{"power":263,"ux":250,"price":263,"cn_support":257,"stability":250},{"title":689,"description":1359},[1392,1395,1397,1399],{"name":1393,"url":1320,"accessed":1394},"OpenManus GitHub（FoundationAgents 组织）","2026-06-24",{"name":1396,"url":1327,"accessed":1394},"Foundation Agents — OpenManus 项目介绍",{"name":1398,"url":1334,"accessed":1394},"Toolsverse — OpenManus 评测 + 52k stars",{"name":1400,"url":1341,"accessed":1394},"SoloSoft.dev — OpenManus 2026 Framework 综述","tools\u002Fagent\u002Fgeneral\u002Fopenmanus","MetaGPT 团队开源版 Manus——52k+ stars \u002F MIT \u002F 多 agent + 浏览器自动化 + MCP + DataAnalysis",[679,1404,1405,1406,1407,1408],"multi-agent","browser-automation","mcp","metagpt","openmanus","想自托管复刻 Manus 全能 agent 体验 + 不愿等邀请码的开发者首选——浏览器 + 数据分析 + MCP 工具栈一站全。要 GUI \u002F 上手即用 \u002F 生产级稳定建议 Genspark \u002F Flowith 付费版。","bwDrZ3am1nVPoISuuo1SzArkD2h3Du6eKkMXUWgpesM",1784565440451]