[{"data":1,"prerenderedAt":1423},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"compare-langflow-vs-openmanus":9,"compare-a-langflow":10,"compare-b-openmanus":711},{"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":639,"chinese_friendly":251,"cover":640,"description":641,"domestic":642,"extension":643,"faq":644,"free":642,"github":9,"languages":657,"lastVerified":9,"meta":660,"models":9,"navigation":266,"notSuitable":9,"opensource":266,"path":661,"pillar":662,"platforms":663,"priceTable":667,"pricing":683,"published":684,"relatedPlaybooks":685,"relatedReviews":9,"score":687,"self_host":266,"seo":688,"seoTitle":9,"slug":689,"sources":690,"stem":701,"suitable":9,"tagline":702,"tags":703,"updated":694,"verdict":709,"website":693,"__hash__":710},"tools\u002Ftools\u002Fagent\u002Fplatform\u002Flangflow.md","Langflow",[14,15,16],"agent\u002Fplatform\u002Fn8n","agent\u002Fprotocol\u002Fcomposio","agent\u002Fgeneral\u002Fopenmanus",{"type":18,"value":19,"toc":627},"minimark",[20,25,29,32,35,112,115,141,147,151,156,182,187,213,216,292,295,319,322,476,479,535,539,565,568,589,592,623],[21,22,24],"h2",{"id":23},"tldr","TL;DR",[26,27,28],"p",{},"Langflow 是 2023 开源、2024 被 DataStax 收购的可视化 LangChain 画布。20,000+ GitHub stars、MIT 协议、Python 实现、与 Astra DB 向量库深度集成。差异点：拖拽式画布把 LangChain primitive 映射成节点 + RAG pipeline 原生组件 + 多 agent 工作流 + 节点可下钻到 Python 代码 + 自托管 \u002F Docker \u002F DataStax Astra 云托管 + Pinecone \u002F pgvector \u002F 主流向量库适配 + Visual GUI for building LangChain pipelines。Self-host 免费 \u002F Cloud Free + Paid ~$25\u002F月起。",[26,30,31],{},"适合：工程团队要可视化建 LangChain 流 + 不被 SaaS 锁住；合规 \u002F 数据驻留要求自托管；要 Astra DB 一站式 RAG；想用 LangChain 但讨厌纯代码协作。不适合：业务侧 + 非工程师（用 Dify \u002F Coze）；纯无代码偏好（Langflow 仍要懂 LangChain 概念）；轻量场景 + 不需要画布（直接写 LangChain 代码）。",[21,33,34],{"id":34},"核心能力",[36,37,38,46,52,58,64,70,76,82,88,94,100,106],"ul",{},[39,40,41,45],"li",{},[42,43,44],"strong",{},"可视化 LangChain 画布","：节点 = primitive，连线 = 数据流",[39,47,48,51],{},[42,49,50],{},"RAG pipeline 原生组件","：Chunking \u002F Embedding \u002F VectorStore \u002F Retriever",[39,53,54,57],{},[42,55,56],{},"多 agent 工作流","：编排多 agent 协作",[39,59,60,63],{},[42,61,62],{},"Python 下钻","：任意节点可写 custom Python",[39,65,66,69],{},[42,67,68],{},"向量库适配","：Astra DB \u002F Pinecone \u002F pgvector \u002F Weaviate \u002F Chroma",[39,71,72,75],{},[42,73,74],{},"API 部署","：流程一键导出为 REST API",[39,77,78,81],{},[42,79,80],{},"Real-time collaboration","：多用户同 project",[39,83,84,87],{},[42,85,86],{},"版本控制","：内置 versioning + revert",[39,89,90,93],{},[42,91,92],{},"数据可视化","：node output \u002F data flow 可视化调试",[39,95,96,99],{},[42,97,98],{},"角色权限","：user auth + RBAC",[39,101,102,105],{},[42,103,104],{},"Docker \u002F pip 安装","：5 分钟启动",[39,107,108,111],{},[42,109,110],{},"Astra-hosted cloud","：DataStax 托管选项",[21,113,114],{"id":114},"价格",[36,116,117,123,129,135],{},[39,118,119,122],{},[42,120,121],{},"Self-Host (OSS)","：$0；MIT 完全免费，自付 LLM API + 服务器",[39,124,125,128],{},[42,126,127],{},"Cloud Free","：$0；DataStax Astra-hosted 小流量",[39,130,131,134],{},[42,132,133],{},"Cloud Paid","：~$25\u002F月起；Astra DB + 更高额度 + 团队协作",[39,136,137,140],{},[42,138,139],{},"Enterprise","：联系销售；SSO + audit + 私有部署 + SLA",[142,143,144],"blockquote",{},[26,145,146],{},"自托管最低成本：$5-10\u002F月 VPS + LLM API token。Cloud Paid $25\u002F月适合不想运维的小团队。",[21,148,150],{"id":149},"实测rag-应用-内部工具搭建","实测（RAG 应用 + 内部工具搭建）",[26,152,153],{},[42,154,155],{},"亮点：",[36,157,158,161,164,167,170,173,176,179],{},[39,159,160],{},"画布直观，比纯写 LangChain 协作效率高 5x",[39,162,163],{},"节点下钻到 Python 让灵活度不被画布限制",[39,165,166],{},"Astra DB 集成省了配 vector store 时间",[39,168,169],{},"4.4\u002F5 用户评分（Propicked \u002F Tooliverse）",[39,171,172],{},"开源 + 自托管 + 数据驻留满足合规",[39,174,175],{},"多 agent 编排比裸 LangChain 调试容易",[39,177,178],{},"RAG pipeline 模板一键起 demo",[39,180,181],{},"与 DataStax 长期支持降低 abandon ware 风险",[26,183,184],{},[42,185,186],{},"踩坑：",[36,188,189,192,195,198,201,204,207,210],{},[39,190,191],{},"稳定性偶发：复杂流大流量下 node 偶尔失联（SelectHub 反馈）",[39,193,194],{},"第三方 API 依赖：external API 失败时错误处理弱",[39,196,197],{},"production readiness 不算 mission-critical（要自加 observability）",[39,199,200],{},"LangChain 升级偶尔 break 旧 flow",[39,202,203],{},"文档对新组件滞后 1-2 月",[39,205,206],{},"中文 UI 不完整，业务侧用户上手陡",[39,208,209],{},"大型 flow（100+ 节点）画布卡顿",[39,211,212],{},"多人协作偶发同步冲突",[21,214,215],{"id":215},"上手",[217,218,223],"pre",{"className":219,"code":220,"language":221,"meta":222,"style":222},"language-bash shiki shiki-themes github-light github-dark","# pip 安装\npip install langflow\nlangflow run  # http:\u002F\u002Flocalhost:7860\n\n# 或 Docker\ndocker run -p 7860:7860 langflowai\u002Flangflow:latest\n","bash","",[224,225,226,235,249,261,268,274],"code",{"__ignoreMap":222},[227,228,231],"span",{"class":229,"line":230},"line",1,[227,232,234],{"class":233},"sJ8bj","# pip 安装\n",[227,236,238,242,246],{"class":229,"line":237},2,[227,239,241],{"class":240},"sScJk","pip",[227,243,245],{"class":244},"sZZnC"," install",[227,247,248],{"class":244}," langflow\n",[227,250,252,255,258],{"class":229,"line":251},3,[227,253,254],{"class":240},"langflow",[227,256,257],{"class":244}," run",[227,259,260],{"class":233},"  # http:\u002F\u002Flocalhost:7860\n",[227,262,264],{"class":229,"line":263},4,[227,265,267],{"emptyLinePlaceholder":266},true,"\n",[227,269,271],{"class":229,"line":270},5,[227,272,273],{"class":233},"# 或 Docker\n",[227,275,277,280,282,286,289],{"class":229,"line":276},6,[227,278,279],{"class":240},"docker",[227,281,257],{"class":244},[227,283,285],{"class":284},"sj4cs"," -p",[227,287,288],{"class":244}," 7860:7860",[227,290,291],{"class":244}," langflowai\u002Flangflow:latest\n",[26,293,294],{},"试 RAG 流：",[296,297,298,301,304,307,310,313,316],"ol",{},[39,299,300],{},"新建 flow → 选 Document QA 模板",[39,302,303],{},"Document Loader 节点 → 上传 PDF",[39,305,306],{},"Splitter → Embedder（OpenAI 或本地）",[39,308,309],{},"VectorStore（Astra \u002F Chroma）",[39,311,312],{},"Retriever + ChatOpenAI → Chat Output",[39,314,315],{},"部署为 API → 拿到 endpoint",[39,317,318],{},"复杂场景下钻节点写 Python 自定义",[21,320,321],{"id":321},"对比",[323,324,325,346],"table",{},[326,327,328],"thead",{},[329,330,331,335,337,340,343],"tr",{},[332,333,334],"th",{},"维度",[332,336,12],{},[332,338,339],{},"Dify",[332,341,342],{},"n8n",[332,344,345],{},"Flowise",[347,348,349,367,383,399,413,429,442,459],"tbody",{},[329,350,351,355,358,361,364],{},[352,353,354],"td",{},"中心",[352,356,357],{},"LangChain primitive",[352,359,360],{},"LLMOps 全平台",[352,362,363],{},"通用 workflow",[352,365,366],{},"LangChain（JS）",[329,368,369,372,375,378,381],{},[352,370,371],{},"开源",[352,373,374],{},"✅ MIT",[352,376,377],{},"✅ AGPL",[352,379,380],{},"✅ Sustainable",[352,382,374],{},[329,384,385,388,391,394,396],{},[352,386,387],{},"自托管",[352,389,390],{},"✅ pip\u002FDocker",[352,392,393],{},"✅ Docker",[352,395,393],{},[352,397,398],{},"✅",[329,400,401,404,407,409,411],{},[352,402,403],{},"可视化",[352,405,406],{},"✅ 旗舰",[352,408,398],{},[352,410,398],{},[352,412,398],{},[329,414,415,418,421,424,427],{},[352,416,417],{},"代码下钻",[352,419,420],{},"✅ Python",[352,422,423],{},"部分",[352,425,426],{},"✅ JS",[352,428,426],{},[329,430,431,434,436,438,440],{},[352,432,433],{},"RAG 内置",[352,435,398],{},[352,437,398],{},[352,439,423],{},[352,441,398],{},[329,443,444,447,450,453,456],{},[352,445,446],{},"起价（云）",[352,448,449],{},"$25\u002F月",[352,451,452],{},"$59\u002F月（Team）",[352,454,455],{},"自托管 $0",[352,457,458],{},"–",[329,460,461,464,467,470,473],{},[352,462,463],{},"适合",[352,465,466],{},"工程 + LangChain",[352,468,469],{},"业务 + LLMOps",[352,471,472],{},"通用自动化",[352,474,475],{},"JS 生态",[21,477,478],{"id":478},"避坑",[36,480,481,487,493,499,505,511,517,523,529],{},[39,482,483,486],{},[42,484,485],{},"自托管推荐 Docker","：pip 版本依赖冲突难调",[39,488,489,492],{},[42,490,491],{},"生产加 observability","：langsmith \u002F sentry \u002F prometheus 必装",[39,494,495,498],{},[42,496,497],{},"Astra DB cloud free","：起步够用，付费版起步前算清成本",[39,500,501,504],{},[42,502,503],{},"复杂 flow 拆模块","：100+ 节点画布卡顿，拆成子 flow",[39,506,507,510],{},[42,508,509],{},"LangChain 版本 pin","：Langflow 升级前测试 flow 兼容性",[39,512,513,516],{},[42,514,515],{},"第三方 API 加重试","：custom Python 节点写 retry + fallback",[39,518,519,522],{},[42,520,521],{},"多人协作 lock","：同时编辑 flow 容易冲突，加 lock 流程",[39,524,525,528],{},[42,526,527],{},"中文场景","：UI 英文为主，业务侧用户先培训",[39,530,531,534],{},[42,532,533],{},"Self-host vs Cloud","：合规要 self-host，省心要 Cloud",[21,536,538],{"id":537},"适合-不适合","适合 \u002F 不适合",[36,540,541,544,547,550,553,556,559,562],{},[39,542,543],{},"✅ 工程团队要可视化建 LangChain 流",[39,545,546],{},"✅ 合规 \u002F 数据驻留要求自托管",[39,548,549],{},"✅ 要 Astra DB 一站式 RAG",[39,551,552],{},"✅ Python 团队 + 想画布 + 想下钻代码",[39,554,555],{},"❌ 业务侧 + 非工程师（用 Dify \u002F Coze）",[39,557,558],{},"❌ 纯无代码偏好",[39,560,561],{},"❌ 轻量场景 + 直接写 LangChain 更快",[39,563,564],{},"❌ JS 生态优先（用 Flowise）",[21,566,567],{"id":567},"相关阅读",[36,569,570,577,583],{},[39,571,572],{},[573,574,576],"a",{"href":575},"\u002Ftools\u002Fagent\u002Fplatform\u002Fn8n","n8n 评测",[39,578,579],{},[573,580,582],{"href":581},"\u002Ftools\u002Fagent\u002Fprotocol\u002Fcomposio","Composio 评测",[39,584,585],{},[573,586,588],{"href":587},"\u002Ftools\u002Fagent\u002Fgeneral\u002Fopenmanus","OpenManus 评测",[21,590,591],{"id":591},"来源",[296,593,594,602,609,616],{},[39,595,596,597],{},"Langflow 官网 + 定价 ",[573,598,599],{"href":599,"rel":600},"https:\u002F\u002Fwww.langflow.org\u002Fpricing",[601],"nofollow",[39,603,604,605],{},"AutomationAtlas — Langflow $25\u002Fmo 2026 Comparison ",[573,606,607],{"href":607,"rel":608},"https:\u002F\u002Fautomationatlas.io\u002Ftools\u002Flangflow",[601],[39,610,611,612],{},"xpay — LangFlow 2026 Visual AI Agent Builder（MIT + DataStax）",[573,613,614],{"href":614,"rel":615},"https:\u002F\u002Fwww.xpay.sh\u002Fresources\u002Fagentic-frameworks\u002Flangflow",[601],[39,617,618,619],{},"SelectHub — LangFlow Reviews 2026（稳定性 + 生产 readiness）",[573,620,621],{"href":621,"rel":622},"https:\u002F\u002Fwww.selecthub.com\u002Fp\u002Fai-agent-builder-software\u002Flangflow\u002F",[601],[624,625,626],"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 .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 .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":222,"searchDepth":251,"depth":251,"links":628},[629,630,631,632,633,634,635,636,637,638],{"id":23,"depth":237,"text":24},{"id":34,"depth":237,"text":34},{"id":114,"depth":237,"text":114},{"id":149,"depth":237,"text":150},{"id":215,"depth":237,"text":215},{"id":321,"depth":237,"text":321},{"id":478,"depth":237,"text":478},{"id":537,"depth":237,"text":538},{"id":567,"depth":237,"text":567},{"id":591,"depth":237,"text":591},"platform","\u002Fimg\u002Ftools\u002Flangflow.webp","Langflow 真实评测：2023 开源项目，2024 被 DataStax 收购，与 Astra DB 向量数据库平台深度集成。20,000+ GitHub stars、MIT 协议。差异点：拖拽式可视化画布映射 LangChain 原语 + RAG pipeline 原生组件 + 多 agent 工作流 + Python + 自托管（pip \u002F Docker）+ DataStax Astra 托管云 + Pinecone \u002F pgvector \u002F 主流向量库适配。Cloud 免费档 + 约 $25\u002F月起。",false,"md",[645,648,651,654],{"q":646,"a":647},"Langflow 和 Dify \u002F n8n \u002F Flowise 怎么选？","Langflow 强『可视化 LangChain 原语 + Python 代码可下钻 + 自托管 + Astra DB 集成』，工程导向。Dify 是 LLMOps 全平台（含 dataset \u002F app \u002F observability），业务侧更友好。n8n 是通用 workflow（非 LangChain 中心），70+ LangChain 节点是后加的。Flowise 是 Langflow 的同类竞品（JS 生态）。工程团队 + Python + 合规自托管 → Langflow；业务 + 完整 LLMOps → Dify；通用自动化 → n8n。",{"q":649,"a":650},"为什么被 DataStax 收购？","DataStax 是 Cassandra 商业公司 + Astra DB 向量数据库厂商。收购 Langflow 是为了把『可视化 LangChain builder』和『生产级 vector store』捆成一站式 RAG 解决方案。Langflow 主仓仍是 MIT 开源，但 cloud \u002F 企业版深度依赖 Astra。",{"q":652,"a":653},"可视化画布会不会限制灵活度？","Langflow 节点对应 LangChain primitive，可在任意节点下钻到 Python 代码 + 自定义。所以可视化层是『脚手架 + 协作工具』，不是『纯无代码黑盒』。复杂逻辑、custom tool、retriever 都能写代码扩展。",{"q":655,"a":656},"production readiness 如何？","用户反馈：原型 + 内部工具非常顺；大流量 \u002F 关键业务要自行加 observability \u002F 错误处理 \u002F 缓存。SelectHub 评测列出『稳定性偶发 + 第三方 API 依赖 + 非完全 production-ready』。生产部署建议 Astra-hosted cloud 或自托管 + 加 sentry \u002F langsmith \u002F prometheus。",[658,659],"en","multi",{},"\u002Ftools\u002Fagent\u002Fplatform\u002Flangflow","agent",[664,665,279,666],"self-host","cloud","web",[668,672,675,679],{"plan":121,"price":669,"features":670,"notes":671},"$0","MIT + pip\u002FDocker + 全部组件 + Pinecone\u002Fpgvector\u002FAstra 适配","自付 LLM API + 服务器",{"plan":127,"price":669,"features":673,"notes":674},"DataStax 托管 + 小流量","试水",{"plan":133,"price":676,"features":677,"notes":678},"~$25\u002F月起","Astra DB + 更高额度 + 更多并发 + 团队协作","按使用量阶梯",{"plan":139,"price":680,"features":681,"notes":682},"联系销售","SSO + audit + 私有部署 + SLA + 数据驻留","合规 \u002F 大客户","Self-host 完全免费 MIT \u002F Cloud Free + 付费起 ~$25·月（Astra-hosted）","2026-06-19",[686],"onboarding\u002Frag-app-workflow",{"power":263,"ux":270,"price":270,"cn_support":251,"stability":263},{"title":12,"description":641},"agent\u002Fplatform\u002Flangflow",[691,695,697,699],{"name":692,"url":693,"accessed":694},"Langflow 官网","https:\u002F\u002Fwww.langflow.org","2026-06-24",{"name":696,"url":607,"accessed":694},"AutomationAtlas — Langflow $25\u002Fmo 2026 Comparison",{"name":698,"url":614,"accessed":694},"xpay — LangFlow 2026 Visual AI Agent Builder",{"name":700,"url":621,"accessed":694},"SelectHub — LangFlow Reviews 2026","tools\u002Fagent\u002Fplatform\u002Flangflow","DataStax 出品的可视化 LangChain 画布——MIT 开源 + 20k+ stars + 自托管 + Astra DB 云托管",[704,705,706,707,708,254],"opensource","visual-builder","langchain","rag","datastax","工程团队要可视化建 LangChain 流 + 不被 SaaS 锁住 + 合规要求自托管的最佳选择。要纯无代码 + 业务侧 → Dify \u002F Coze；要纯代码 → 直接写 LangChain \u002F LlamaIndex。","1rR9AipW53n2GbQ36ydZc1QwSZ0HW7kgrrg9Q0bYGKs",{"id":712,"title":713,"alternatives":714,"api_compatible":9,"body":715,"category":1369,"chinese_friendly":263,"cover":1370,"description":1371,"domestic":642,"extension":643,"faq":1372,"free":642,"github":9,"languages":1385,"lastVerified":9,"meta":1387,"models":9,"navigation":266,"notSuitable":9,"opensource":266,"path":587,"pillar":662,"platforms":1388,"priceTable":1392,"pricing":1396,"published":684,"relatedPlaybooks":1397,"relatedReviews":1399,"score":1402,"self_host":266,"seo":1403,"seoTitle":9,"slug":16,"sources":1404,"stem":1413,"suitable":9,"tagline":1414,"tags":1415,"updated":694,"verdict":1421,"website":1331,"__hash__":1422},"tools\u002Ftools\u002Fagent\u002Fgeneral\u002Fopenmanus.md","OpenManus",[689,14,15],{"type":18,"value":716,"toc":1357},[717,719,726,729,731,808,810,827,831,835,861,865,891,893,1033,1036,1044,1046,1215,1217,1277,1279,1305,1307,1322,1324,1354],[21,718,24],{"id":23},[26,720,721,722,725],{},"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（",[224,723,724],{},"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。",[26,727,728],{},"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）。",[21,730,34],{"id":34},[36,732,733,742,748,754,760,766,772,778,784,790,796,802],{},[39,734,735,738,739,741],{},[42,736,737],{},"多 agent orchestration","：",[224,740,724],{}," 编排多个专门 agent 协作",[39,743,744,747],{},[42,745,746],{},"Playwright 浏览器自动化","：截图 + DOM 操作 + 表单填写 + 信息抓取",[39,749,750,753],{},[42,751,752],{},"MCP 协议支持","：可调用 MCP server（filesystem \u002F GitHub \u002F Postgres）",[39,755,756,759],{},[42,757,758],{},"DataAnalysis 模式","：内置 CSV \u002F 数据分析 agent",[39,761,762,765],{},[42,763,764],{},"OpenManus-RL","：强化学习微调分支",[39,767,768,771],{},[42,769,770],{},"BaseTool 自定义工具","：Python 继承基类快速添加新工具",[39,773,774,777],{},[42,775,776],{},"多模态","：文本 + 视觉输入 + 浏览器截图回环",[39,779,780,783],{},[42,781,782],{},"多 LLM provider","：GPT-4o \u002F Claude 3.5 \u002F Qwen VL Plus \u002F DeepSeek \u002F Gemini",[39,785,786,789],{},[42,787,788],{},"核心 agent 引擎","：reasoning + planning + execution 三阶段",[39,791,792,795],{},[42,793,794],{},"Web UI 监控","：实时看 AI thinking process",[39,797,798,801],{},[42,799,800],{},"任务可视化","：步骤拆解 + 执行树",[39,803,804,807],{},[42,805,806],{},"MIT 协议","：个人 + 商用全免费",[21,809,114],{"id":114},[36,811,812,818,821,824],{},[39,813,814,817],{},[42,815,816],{},"Free \u002F OSS","：$0；MIT 协议",[39,819,820],{},"真实成本 = LLM API（GPT-4o ~$5\u002FM input + $15\u002FM output \u002F Claude \u002F Qwen 等）",[39,822,823],{},"一次中等任务（10-20 步）API 费用 $0.05-0.5",[39,825,826],{},"本地 Qwen2.5 32B \u002F DeepSeek 走 vLLM \u002F Ollama 路径 $0",[21,828,830],{"id":829},"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）",[26,832,833],{},[42,834,155],{},[36,836,837,840,843,846,849,852,855,858],{},[39,838,839],{},"52k stars 印证社区认同度 + 活跃度",[39,841,842],{},"MetaGPT 团队背景保证架构质量",[39,844,845],{},"多 agent 协作场景比单 agent 实现稳得多",[39,847,848],{},"Playwright 浏览器自动化非常完整",[39,850,851],{},"MCP 协议接入打通 Claude \u002F Cursor 生态",[39,853,854],{},"DataAnalysis 内置 agent 模式开箱即用",[39,856,857],{},"中文支持自然（Qwen VL Plus 接入）",[39,859,860],{},"自托管 + 数据本地，隐私 \u002F 合规友好",[26,862,863],{},[42,864,186],{},[36,866,867,870,873,876,879,882,885,888],{},[39,868,869],{},"项目演进快，breaking change 偶发（pin commit 跑生产）",[39,871,872],{},"文档滞后新功能 1-2 个月",[39,874,875],{},"无官方 GUI，监控 UI 在做但不完整",[39,877,878],{},"需要 Python 3.12+ + Playwright 依赖（首次安装 chromium 慢）",[39,880,881],{},"LLM API 配置非平凡（多 provider \u002F key \u002F 模型选择）",[39,883,884],{},"浏览器任务遇到 CAPTCHA \u002F 反爬偶尔卡死",[39,886,887],{},"中文 prompt 效果依赖底层模型",[39,889,890],{},"生产部署需自己加监控 \u002F 错误恢复 \u002F 重试",[21,892,215],{"id":215},[217,894,896],{"className":219,"code":895,"language":221,"meta":222,"style":222},"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",[224,897,898,909,917,944,956,966,970,976,988,994,999,1005,1014,1019,1025],{"__ignoreMap":222},[227,899,900,903,906],{"class":229,"line":230},[227,901,902],{"class":240},"git",[227,904,905],{"class":244}," clone",[227,907,908],{"class":244}," https:\u002F\u002Fgithub.com\u002FFoundationAgents\u002FOpenManus.git\n",[227,910,911,914],{"class":229,"line":237},[227,912,913],{"class":284},"cd",[227,915,916],{"class":244}," OpenManus\n",[227,918,919,922,925,928,931,935,938,941],{"class":229,"line":251},[227,920,921],{"class":240},"python3.12",[227,923,924],{"class":284}," -m",[227,926,927],{"class":244}," venv",[227,929,930],{"class":244}," .venv",[227,932,934],{"class":933},"sVt8B"," && ",[227,936,937],{"class":284},"source",[227,939,940],{"class":244}," .venv\u002Fbin\u002Factivate",[227,942,943],{"class":233},"  # 或 .venv\\Scripts\\activate\n",[227,945,946,948,950,953],{"class":229,"line":263},[227,947,241],{"class":240},[227,949,245],{"class":244},[227,951,952],{"class":284}," -r",[227,954,955],{"class":244}," requirements.txt\n",[227,957,958,961,963],{"class":229,"line":270},[227,959,960],{"class":240},"playwright",[227,962,245],{"class":244},[227,964,965],{"class":244}," chromium\n",[227,967,968],{"class":229,"line":276},[227,969,267],{"emptyLinePlaceholder":266},[227,971,973],{"class":229,"line":972},7,[227,974,975],{"class":233},"# 配 LLM API\n",[227,977,979,982,985],{"class":229,"line":978},8,[227,980,981],{"class":240},"cp",[227,983,984],{"class":244}," config\u002Fconfig.example.toml",[227,986,987],{"class":244}," config\u002Fconfig.toml\n",[227,989,991],{"class":229,"line":990},9,[227,992,993],{"class":233},"# 编辑 config.toml 填 OPENAI \u002F ANTHROPIC \u002F DEEPSEEK key\n",[227,995,997],{"class":229,"line":996},10,[227,998,267],{"emptyLinePlaceholder":266},[227,1000,1002],{"class":229,"line":1001},11,[227,1003,1004],{"class":233},"# 单 agent 模式\n",[227,1006,1008,1011],{"class":229,"line":1007},12,[227,1009,1010],{"class":240},"python",[227,1012,1013],{"class":244}," main.py\n",[227,1015,1017],{"class":229,"line":1016},13,[227,1018,267],{"emptyLinePlaceholder":266},[227,1020,1022],{"class":229,"line":1021},14,[227,1023,1024],{"class":233},"# 多 agent 模式\n",[227,1026,1028,1030],{"class":229,"line":1027},15,[227,1029,1010],{"class":240},[227,1031,1032],{"class":244}," run_flow.py\n",[26,1034,1035],{},"试任务示例：",[217,1037,1042],{"className":1038,"code":1040,"language":1041},[1039],"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",[224,1043,1040],{"__ignoreMap":222},[21,1045,321],{"id":321},[323,1047,1048,1065],{},[326,1049,1050],{},[329,1051,1052,1054,1056,1059,1062],{},[332,1053,334],{},[332,1055,713],{},[332,1057,1058],{},"LangChain",[332,1060,1061],{},"AutoGPT",[332,1063,1064],{},"CrewAI",[347,1066,1067,1084,1098,1111,1127,1140,1154,1168,1185,1199],{},[329,1068,1069,1072,1075,1078,1081],{},[352,1070,1071],{},"形态",[352,1073,1074],{},"现成 agent 实现",[352,1076,1077],{},"building blocks",[352,1079,1080],{},"早期通用 agent",[352,1082,1083],{},"多 agent 框架",[329,1085,1086,1089,1092,1094,1096],{},[352,1087,1088],{},"浏览器自动化",[352,1090,1091],{},"✅ Playwright",[352,1093,458],{},[352,1095,423],{},[352,1097,458],{},[329,1099,1100,1103,1105,1107,1109],{},[352,1101,1102],{},"MCP",[352,1104,398],{},[352,1106,423],{},[352,1108,458],{},[352,1110,458],{},[329,1112,1113,1116,1119,1122,1125],{},[352,1114,1115],{},"多 agent",[352,1117,1118],{},"✅ orchestration",[352,1120,1121],{},"需自搭",[352,1123,1124],{},"❌",[352,1126,406],{},[329,1128,1129,1132,1134,1136,1138],{},[352,1130,1131],{},"DataAnalysis 内置",[352,1133,398],{},[352,1135,458],{},[352,1137,458],{},[352,1139,458],{},[329,1141,1142,1145,1148,1150,1152],{},[352,1143,1144],{},"RL 微调",[352,1146,1147],{},"✅ OpenManus-RL",[352,1149,458],{},[352,1151,458],{},[352,1153,458],{},[329,1155,1156,1159,1162,1164,1166],{},[352,1157,1158],{},"协议",[352,1160,1161],{},"MIT",[352,1163,1161],{},[352,1165,1161],{},[352,1167,1161],{},[329,1169,1170,1173,1176,1179,1182],{},[352,1171,1172],{},"Stars",[352,1174,1175],{},"52k+",[352,1177,1178],{},"100k+",[352,1180,1181],{},"170k+",[352,1183,1184],{},"30k+",[329,1186,1187,1189,1192,1195,1197],{},[352,1188,215],{},[352,1190,1191],{},"中",[352,1193,1194],{},"难",[352,1196,1191],{},[352,1198,1191],{},[329,1200,1201,1203,1206,1209,1212],{},[352,1202,463],{},[352,1204,1205],{},"自托管 Manus 复刻",[352,1207,1208],{},"底层 framework",[352,1210,1211],{},"学习经典",[352,1213,1214],{},"多 agent 协作",[21,1216,478],{"id":478},[36,1218,1219,1225,1235,1241,1247,1253,1259,1265,1271],{},[39,1220,1221,1224],{},[42,1222,1223],{},"pin commit 用生产","：项目演进快，main 分支偶尔 break",[39,1226,1227,1230,1231,1234],{},[42,1228,1229],{},"Playwright 依赖大","：首次 ",[224,1232,1233],{},"playwright install"," 下 chromium 慢，国内走镜像",[39,1236,1237,1240],{},[42,1238,1239],{},"LLM 选择","：日常用 GPT-4o-mini \u002F DeepSeek 省钱，复杂任务切 GPT-4o \u002F Claude Opus",[39,1242,1243,1246],{},[42,1244,1245],{},"本地化中文","：Qwen2.5 VL 32B + vLLM 部署可全本地 + 零成本",[39,1248,1249,1252],{},[42,1250,1251],{},"监控自加","：生产部署要加 prometheus + 错误重试 + 任务超时",[39,1254,1255,1258],{},[42,1256,1257],{},"浏览器反爬","：CAPTCHA 场景搭配 2captcha \u002F human-in-loop",[39,1260,1261,1264],{},[42,1262,1263],{},"OpenManus-RL 分支","：研究场景才需要，普通用户主仓库就够",[39,1266,1267,1270],{},[42,1268,1269],{},"MCP server","：信任来源很重要，能访问的目录 \u002F 工具要审慎",[39,1272,1273,1276],{},[42,1274,1275],{},"多 agent runaway","：复杂任务设 max_steps 防止失控烧 token",[21,1278,538],{"id":537},[36,1280,1281,1284,1287,1290,1293,1296,1299,1302],{},[39,1282,1283],{},"✅ 开发者 + 想自托管 Manus 风格 agent",[39,1285,1286],{},"✅ 研究 \u002F 学术 \u002F 教育用通用 agent 学习",[39,1288,1289],{},"✅ 隐私敏感 + 不愿数据上商业云",[39,1291,1292],{},"✅ 中国大陆开发者（Qwen \u002F DeepSeek 本地化）",[39,1294,1295],{},"❌ 非开发者 \u002F 不会 Python + Playwright",[39,1297,1298],{},"❌ 要 GUI \u002F 上手即用",[39,1300,1301],{},"❌ 生产级稳定（文档滞后 + 演进快）",[39,1303,1304],{},"❌ 团队协作 + 共享 workspace（用 Flowith \u002F Genspark Team）",[21,1306,567],{"id":567},[36,1308,1309,1314,1318],{},[39,1310,1311],{},[573,1312,1313],{"href":661},"Langflow 评测",[39,1315,1316],{},[573,1317,576],{"href":575},[39,1319,1320],{},[573,1321,582],{"href":581},[21,1323,591],{"id":591},[296,1325,1326,1333,1340,1347],{},[39,1327,1328,1329],{},"OpenManus GitHub 主仓库 + Foundation Agents 组织 ",[573,1330,1331],{"href":1331,"rel":1332},"https:\u002F\u002Fgithub.com\u002FFoundationAgents\u002FOpenManus",[601],[39,1334,1335,1336],{},"Foundation Agents — OpenManus 项目介绍 ",[573,1337,1338],{"href":1338,"rel":1339},"https:\u002F\u002Ffoundationagents.org\u002Fprojects\u002Fopenmanus\u002F",[601],[39,1341,1342,1343],{},"Toolsverse — OpenManus 评测 + 52k stars ",[573,1344,1345],{"href":1345,"rel":1346},"https:\u002F\u002Fthetoolsverse.com\u002Ftools\u002Fopenmanus",[601],[39,1348,1349,1350],{},"SoloSoft.dev — OpenManus 2026 Framework 综述 ",[573,1351,1352],{"href":1352,"rel":1353},"https:\u002F\u002Fwww.solosoft.dev\u002Fpost\u002Fopenmanus-agent-framework-2026\u002F",[601],[624,1355,1356],{},"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":222,"searchDepth":251,"depth":251,"links":1358},[1359,1360,1361,1362,1363,1364,1365,1366,1367,1368],{"id":23,"depth":237,"text":24},{"id":34,"depth":237,"text":34},{"id":114,"depth":237,"text":114},{"id":829,"depth":237,"text":830},{"id":215,"depth":237,"text":215},{"id":321,"depth":237,"text":321},{"id":478,"depth":237,"text":478},{"id":537,"depth":237,"text":538},{"id":567,"depth":237,"text":567},{"id":591,"depth":237,"text":591},"general","\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。",[1373,1376,1379,1382],{"q":1374,"a":1375},"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":1377,"a":1378},"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":1380,"a":1381},"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":1383,"a":1384},"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。",[658,1386,659],"zh",{},[1389,1390,1391,279],"linux","macos","windows",[1393],{"plan":816,"price":669,"features":1394,"notes":1395},"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）",[1398],"onboarding\u002Fopen-source-general-agent",[1400,1401],"openhuman-deep-review","openmanus-deep-review",{"power":270,"ux":251,"price":270,"cn_support":263,"stability":251},{"title":713,"description":1371},[1405,1407,1409,1411],{"name":1406,"url":1331,"accessed":694},"OpenManus GitHub（FoundationAgents 组织）",{"name":1408,"url":1338,"accessed":694},"Foundation Agents — OpenManus 项目介绍",{"name":1410,"url":1345,"accessed":694},"Toolsverse — OpenManus 评测 + 52k stars",{"name":1412,"url":1352,"accessed":694},"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",[704,1416,1417,1418,1419,1420],"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",1784565440470]