[{"data":1,"prerenderedAt":2270},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"compare-dify-vs-fastgpt":9,"compare-a-dify":10,"compare-b-fastgpt":1171},{"tools":4,"reviews":5},78,26,{"tools":4,"reviews":5,"playbooks":7,"news":8},22,24,null,{"id":11,"title":12,"alternatives":13,"api_compatible":9,"body":18,"category":1102,"chinese_friendly":386,"cover":1103,"description":1104,"domestic":1105,"extension":1106,"faq":9,"free":1105,"github":332,"languages":1107,"lastVerified":9,"meta":1111,"models":9,"navigation":553,"notSuitable":9,"opensource":553,"path":1112,"pillar":1113,"platforms":1114,"priceTable":1118,"pricing":1135,"published":1136,"relatedPlaybooks":9,"relatedReviews":1137,"score":1142,"self_host":553,"seo":1143,"seoTitle":1144,"slug":1145,"sources":1146,"stem":1158,"suitable":9,"tagline":1159,"tags":1160,"updated":1168,"verdict":1169,"website":1044,"__hash__":1170},"tools\u002Ftools\u002Fagent\u002Fplatform\u002Fdify.md","Dify",[14,15,16,17],"agent\u002Fplatform\u002Fcoze","agent\u002Fplatform\u002Ffastgpt","agent\u002Fplatform\u002Fn8n","agent\u002Fplatform\u002Flangflow",{"type":19,"value":20,"toc":1080},"minimark",[21,26,54,60,63,68,71,146,149,153,156,172,191,195,198,209,213,221,233,237,240,243,247,256,317,324,328,336,406,409,429,433,436,496,502,506,601,604,633,636,777,795,834,837,910,914,917,937,940,969,972,1034,1037,1068,1076],[22,23,25],"h2",{"id":24},"tldr","TL;DR",[27,28,33,41],"div",{"className":29},[30,31,32],"card","p-5","my-4",[34,35,36,40],"p",{},[37,38,39],"strong",{},"一句话："," Dify 是开源 LLMOps 平台的事实标准。GitHub 13 万 star、累计 100 万+ 生产 app（据 chatforest.com 2026 评测引用 Dify 官方数据），把\"可视化工作流编排 + RAG 知识库 + Agent + MCP 协议\"打包成一个 Docker Compose 能跑起来的东西。",[34,42,43,44,47,48,53],{},"最大价值是 ",[37,45,46],{},"完全开源 + 模型不挑食","——同一个工作流里同时调 OpenAI、Anthropic、Ollama 本地、DeepSeek、Qwen 都行。代价是部署比 ",[49,50,52],"a",{"href":51},"\u002Fagent\u002Fplatform\u002Fcoze.html","Coze"," 折腾，新手得读 1-2 小时文档。",[55,56,57],"blockquote",{},[34,58,59],{},"来源说明：本文基于 docs.dify.ai 官方文档、langgenius\u002Fdify GitHub 仓库、第三方评测（besthub.dev \u002F chatforest.com \u002F joshuaopolko.com \u002F zhihu 知名专栏）综合归纳。版本号会变，部署要求请以官方最新文档为准。",[22,61,62],{"id":62},"核心特性",[64,65,67],"h3",{"id":66},"可视化工作流chatflow-workflow","可视化工作流（Chatflow + Workflow）",[34,69,70],{},"Dify 把 LLM 应用拆成两种\"应用类型\"：",[72,73,74,90],"table",{},[75,76,77],"thead",{},[78,79,80,84,87],"tr",{},[81,82,83],"th",{},"类型",[81,85,86],{},"适合场景",[81,88,89],{},"编排范式",[91,92,93,107,120,133],"tbody",{},[78,94,95,101,104],{},[96,97,98],"td",{},[37,99,100],{},"Chatbot",[96,102,103],{},"简单对话机器人",[96,105,106],{},"prompt + tools",[78,108,109,114,117],{},[96,110,111],{},[37,112,113],{},"Agent",[96,115,116],{},"自主多步任务",[96,118,119],{},"ReAct \u002F Function Calling",[78,121,122,127,130],{},[96,123,124],{},[37,125,126],{},"Chatflow",[96,128,129],{},"对话型工作流（多轮 + 分支）",[96,131,132],{},"节点 DAG，带聊天上下文",[78,134,135,140,143],{},[96,136,137],{},[37,138,139],{},"Workflow",[96,141,142],{},"单次输入→输出（API 模式）",[96,144,145],{},"节点 DAG，无对话状态",[34,147,148],{},"节点类型覆盖：LLM、知识检索、HTTP 请求、代码执行（Python \u002F JS）、条件分支、迭代、变量聚合、参数提取、问题分类——满足\"用拖拽实现可观测的 LLM pipeline\"。",[64,150,152],{"id":151},"rag-知识库","RAG 知识库",[34,154,155],{},"内置完整 RAG 链路：",[157,158,159,163,166,169],"ol",{},[160,161,162],"li",{},"上传文档（PDF \u002F Word \u002F Markdown \u002F 网页）",[160,164,165],{},"自动分块 + embedding（可配置分段策略和 embedding 模型）",[160,167,168],{},"混合检索（向量 + 全文 + 重排）",[160,170,171],{},"引用溯源（回答末尾自动附原文片段）",[34,173,174,175,181,182,185,186,190],{},"注意：根据 ",[49,176,180],{"href":177,"rel":178},"https:\u002F\u002Fzhuanlan.zhihu.com\u002Fp\u002F1887141987838309480",[179],"nofollow","知乎 LLM 实战笔记 2025-03 对比"," 的实测，Dify ",[37,183,184],{},"社区版默认是基础语义检索","，企业版才解锁多路召回 + 重排。RAG 极致精度场景仍推荐 ",[49,187,189],{"href":188},"\u002Fagent\u002Fplatform\u002Ffastgpt.html","FastGPT","（实测准确率高 10+ 个百分点），Dify 胜在工作流而非纯 RAG。",[64,192,194],{"id":193},"模型生态40-提供商","模型生态：40+ 提供商",[34,196,197],{},"Dify 通过插件市场接入主流模型——OpenAI、Anthropic、Google Gemini、Azure、AWS Bedrock、Cohere、xAI、DeepSeek、Qwen、智谱、文心、豆包、月之暗面、Ollama、LM Studio、Replicate、Together AI、OpenRouter……几乎你能数出来的 LLM 提供商都在。",[34,199,200,201,203,204,208],{},"国产模型原生支持（不像 ",[49,202,189],{"href":188}," 需要 ",[49,205,207],{"href":206},"\u002Fcoding\u002Fapi\u002Fone-api.html","OneAPI"," 中转），是 Dify 在国内 toB 场景流行的关键。",[64,210,212],{"id":211},"mcp-协议支持","MCP 协议支持",[34,214,215,216,220],{},"Dify 较早接入了 ",[49,217,219],{"href":218},"\u002Fwiki\u002Fmcp.html","MCP（Model Context Protocol）","，工作流可以直接调 MCP Server 暴露的 tools。意味着你可以让 Dify 工作流：",[222,223,224,227,230],"ul",{},[160,225,226],{},"通过 MCP 调本地 PostgreSQL \u002F SQLite",[160,228,229],{},"通过 MCP 调 GitHub \u002F Slack \u002F Linear",[160,231,232],{},"通过 MCP 调自家内部系统（写一个 MCP Server 即可）",[64,234,236],{"id":235},"api-first","API-first",[34,238,239],{},"每个 app 自动暴露 REST API，参数和返回结构自动生成 OpenAPI Schema。集成到自家产品里不需要写包装代码，给前端 \u002F 微信小程序 \u002F 飞书机器人调用都方便。",[22,241,242],{"id":242},"价格与运行成本",[64,244,246],{"id":245},"云版difyai","云版（dify.ai）",[34,248,249,250,255],{},"根据 ",[49,251,254],{"href":252,"rel":253},"https:\u002F\u002Fwww.tooljunction.io\u002Fai-tools\u002Fdify-ai",[179],"tooljunction.io 2026 评测"," 引用的官方定价：",[72,257,258,271],{},[75,259,260],{},[78,261,262,265,268],{},[81,263,264],{},"套餐",[81,266,267],{},"价格",[81,269,270],{},"主要限制",[91,272,273,284,295,306],{},[78,274,275,278,281],{},[96,276,277],{},"Sandbox",[96,279,280],{},"免费",[96,282,283],{},"200 次模型调用，1 app，5MB 知识库",[78,285,286,289,292],{},[96,287,288],{},"Professional",[96,290,291],{},"$59\u002F月起",[96,293,294],{},"5000 调用\u002F月，多 app，50MB 知识库",[78,296,297,300,303],{},[96,298,299],{},"Team",[96,301,302],{},"$159\u002F月起",[96,304,305],{},"团队协作、SSO",[78,307,308,311,314],{},[96,309,310],{},"Enterprise",[96,312,313],{},"联系销售",[96,315,316],{},"定制 SLA、私有云",[34,318,319,320,323],{},"注意：云版价格只是 Dify 平台费，",[37,321,322],{},"模型 API 费用另算","（自带 OpenAI \u002F Anthropic key）。",[64,325,327],{"id":326},"自托管推荐","自托管（推荐）",[34,329,330,335],{},[49,331,334],{"href":332,"rel":333},"https:\u002F\u002Fgithub.com\u002Flanggenius\u002Fdify",[179],"官方 GitHub 仓库"," 提供 Docker Compose 部署，社区版完全免费可商用：",[337,338,343],"pre",{"className":339,"code":340,"language":341,"meta":342,"style":342},"language-bash shiki shiki-themes github-light github-dark","git clone https:\u002F\u002Fgithub.com\u002Flanggenius\u002Fdify.git\ncd dify\u002Fdocker\ncp .env.example .env\ndocker compose up -d\n# 默认 http:\u002F\u002Flocalhost \u002F 端口可在 .env 调整\n","bash","",[344,345,346,362,372,384,399],"code",{"__ignoreMap":342},[347,348,351,355,359],"span",{"class":349,"line":350},"line",1,[347,352,354],{"class":353},"sScJk","git",[347,356,358],{"class":357},"sZZnC"," clone",[347,360,361],{"class":357}," https:\u002F\u002Fgithub.com\u002Flanggenius\u002Fdify.git\n",[347,363,365,369],{"class":349,"line":364},2,[347,366,368],{"class":367},"sj4cs","cd",[347,370,371],{"class":357}," dify\u002Fdocker\n",[347,373,375,378,381],{"class":349,"line":374},3,[347,376,377],{"class":353},"cp",[347,379,380],{"class":357}," .env.example",[347,382,383],{"class":357}," .env\n",[347,385,387,390,393,396],{"class":349,"line":386},4,[347,388,389],{"class":353},"docker",[347,391,392],{"class":357}," compose",[347,394,395],{"class":357}," up",[347,397,398],{"class":367}," -d\n",[347,400,402],{"class":349,"line":401},5,[347,403,405],{"class":404},"sJ8bj","# 默认 http:\u002F\u002Flocalhost \u002F 端口可在 .env 调整\n",[34,407,408],{},"硬件门槛（社区共识，非官方硬性要求）：",[222,410,411,417,423],{},[160,412,413,416],{},[37,414,415],{},"最低","：2 核 4G，纯外接 API 模式",[160,418,419,422],{},[37,420,421],{},"推荐","：4 核 8G + 至少 30GB 磁盘（向量数据 + 文件存储）",[160,424,425,428],{},[37,426,427],{},"企业","：8 核 16G+，单机日活上千",[64,430,432],{"id":431},"真实-tco","真实 TCO",[34,434,435],{},"按一家中小团队 3 年场景估算（基于上面引用的多份评测交叉对比）：",[72,437,438,451],{},[75,439,440],{},[78,441,442,445,448],{},[81,443,444],{},"成本项",[81,446,447],{},"云版 Professional",[81,449,450],{},"自托管",[91,452,453,464,474,485],{},[78,454,455,458,461],{},[96,456,457],{},"平台费",[96,459,460],{},"~$2,100（3 年）",[96,462,463],{},"$0",[78,465,466,469,471],{},[96,467,468],{},"服务器",[96,470,463],{},[96,472,473],{},"~$50\u002F月 × 36 = $1,800",[78,475,476,479,482],{},[96,477,478],{},"模型 API",[96,480,481],{},"与下同",[96,483,484],{},"与上同",[78,486,487,490,493],{},[96,488,489],{},"运维人力",[96,491,492],{},"0",[96,494,495],{},"约 0.2 人月",[34,497,498,501],{},[37,499,500],{},"结论","：日活 \u003C 100 用云版省心；> 500 或数据敏感场景自托管 ROI 更好。",[22,503,505],{"id":504},"上手-10-分钟","上手 10 分钟",[337,507,509],{"className":339,"code":508,"language":341,"meta":342,"style":342},"# 1. 自托管（社区版）\ngit clone https:\u002F\u002Fgithub.com\u002Flanggenius\u002Fdify.git\ncd dify\u002Fdocker\ncp .env.example .env\ndocker compose up -d\n\n# 2. 浏览器打开 http:\u002F\u002Flocalhost\n#    首次会让你创建 admin 账号\n\n# 3. 进入\"设置 → 模型供应商\"，配置 OpenAI \u002F 国产模型 API key\n\n# 4. 在主界面\"创建空白应用\"，选 Chatflow 或 Workflow\n# 5. 拖入\"开始 → LLM → 结束\"节点试一下基础 prompt\n# 6. 满意了点右上\"发布\"，自动生成 API endpoint\n",[344,510,511,516,524,530,538,548,555,561,567,572,578,583,589,595],{"__ignoreMap":342},[347,512,513],{"class":349,"line":350},[347,514,515],{"class":404},"# 1. 自托管（社区版）\n",[347,517,518,520,522],{"class":349,"line":364},[347,519,354],{"class":353},[347,521,358],{"class":357},[347,523,361],{"class":357},[347,525,526,528],{"class":349,"line":374},[347,527,368],{"class":367},[347,529,371],{"class":357},[347,531,532,534,536],{"class":349,"line":386},[347,533,377],{"class":353},[347,535,380],{"class":357},[347,537,383],{"class":357},[347,539,540,542,544,546],{"class":349,"line":401},[347,541,389],{"class":353},[347,543,392],{"class":357},[347,545,395],{"class":357},[347,547,398],{"class":367},[347,549,551],{"class":349,"line":550},6,[347,552,554],{"emptyLinePlaceholder":553},true,"\n",[347,556,558],{"class":349,"line":557},7,[347,559,560],{"class":404},"# 2. 浏览器打开 http:\u002F\u002Flocalhost\n",[347,562,564],{"class":349,"line":563},8,[347,565,566],{"class":404},"#    首次会让你创建 admin 账号\n",[347,568,570],{"class":349,"line":569},9,[347,571,554],{"emptyLinePlaceholder":553},[347,573,575],{"class":349,"line":574},10,[347,576,577],{"class":404},"# 3. 进入\"设置 → 模型供应商\"，配置 OpenAI \u002F 国产模型 API key\n",[347,579,581],{"class":349,"line":580},11,[347,582,554],{"emptyLinePlaceholder":553},[347,584,586],{"class":349,"line":585},12,[347,587,588],{"class":404},"# 4. 在主界面\"创建空白应用\"，选 Chatflow 或 Workflow\n",[347,590,592],{"class":349,"line":591},13,[347,593,594],{"class":404},"# 5. 拖入\"开始 → LLM → 结束\"节点试一下基础 prompt\n",[347,596,598],{"class":349,"line":597},14,[347,599,600],{"class":404},"# 6. 满意了点右上\"发布\"，自动生成 API endpoint\n",[22,602,603],{"id":603},"国内使用注意事项",[157,605,606,612,618,624],{},[160,607,608,611],{},[37,609,610],{},"云版 dify.ai 直连国内访问稳定但需要付款","——支持国际信用卡 \u002F Stripe",[160,613,614,617],{},[37,615,616],{},"自托管 + 国产模型"," = 完全国内闭环，是 Dify 在国内最大优势",[160,619,620,623],{},[37,621,622],{},"Docker 镜像拉取","：国内可能慢，建议配 Docker registry 镜像（阿里云 \u002F 网易）",[160,625,626,629,630,632],{},[37,627,628],{},"数据合规","：完全自托管时，数据零外泄；某些金融 \u002F 政府客户因此从 ",[49,631,52],{"href":51}," 迁到 Dify",[22,634,635],{"id":635},"与同类怎么选",[72,637,638,661],{},[75,639,640],{},[78,641,642,645,647,651,655],{},[81,643,644],{},"维度",[81,646,12],{},[81,648,649],{},[49,650,52],{"href":51},[81,652,653],{},[49,654,189],{"href":188},[81,656,657],{},[49,658,660],{"href":659},"\u002Fagent\u002Fplatform\u002Fn8n.html","n8n",[91,662,663,679,692,708,722,736,750,763],{},[78,664,665,668,671,674,676],{},[96,666,667],{},"开源",[96,669,670],{},"✅",[96,672,673],{},"❌",[96,675,670],{},[96,677,678],{},"✅（fair-code）",[78,680,681,684,686,688,690],{},[96,682,683],{},"私有部署",[96,685,670],{},[96,687,673],{},[96,689,670],{},[96,691,670],{},[78,693,694,697,700,703,705],{},[96,695,696],{},"上手难度",[96,698,699],{},"★★★☆☆",[96,701,702],{},"★★☆☆☆ 最简单",[96,704,699],{},[96,706,707],{},"★★★★☆",[78,709,710,713,716,718,720],{},[96,711,712],{},"工作流编排",[96,714,715],{},"★★★★★",[96,717,707],{},[96,719,699],{},[96,721,715],{},[78,723,724,727,729,731,733],{},[96,725,726],{},"RAG 精度",[96,728,707],{},[96,730,699],{},[96,732,715],{},[96,734,735],{},"★★☆☆☆",[78,737,738,741,743,745,748],{},[96,739,740],{},"模型生态",[96,742,715],{},[96,744,707],{},[96,746,747],{},"★★★☆☆（OneAPI 中转）",[96,749,707],{},[78,751,752,755,757,759,761],{},[96,753,754],{},"中文场景",[96,756,707],{},[96,758,715],{},[96,760,707],{},[96,762,699],{},[78,764,765,768,770,773,775],{},[96,766,767],{},"字节生态绑定",[96,769,673],{},[96,771,772],{},"✅（飞书\u002F抖音深度集成）",[96,774,673],{},[96,776,673],{},[34,778,779,782,783,788,789,794],{},[37,780,781],{},"怎么选","（基于 ",[49,784,787],{"href":785,"rel":786},"https:\u002F\u002Fwww.besthub.dev\u002Farticles\u002Fcoze-vs-dify-vs-fastgpt-which-ai-agent-platform-fits-your-needs-fa59cf97b798",[179],"BestHub 2025-07"," 和 ",[49,790,793],{"href":791,"rel":792},"https:\u002F\u002Fwww.cnblogs.com\u002Fuulucias\u002Fp\u002F19449008",[179],"博客园 2026-01"," 两份选型指南综合）：",[222,796,797,803,811,818,825],{},[160,798,799,802],{},[37,800,801],{},"数据必须不出内网 + 工作流复杂"," → Dify",[160,804,805,808,809],{},[37,806,807],{},"个人 \u002F 小团队 \u002F 快速原型 + 字节生态"," → ",[49,810,52],{"href":51},[160,812,813,808,816],{},[37,814,815],{},"核心场景就是企业知识库 QA",[49,817,189],{"href":188},[160,819,820,808,823],{},[37,821,822],{},"重点是连接外部 SaaS（Slack \u002F Notion \u002F 数据库）",[49,824,660],{"href":659},[160,826,827,808,830],{},[37,828,829],{},"要画图式表达 LangChain pipeline",[49,831,833],{"href":832},"\u002Fagent\u002Fplatform\u002Flangflow.html","Langflow",[22,835,836],{"id":836},"避坑清单",[222,838,839,845,862,873,886,892,898,904],{},[160,840,841,844],{},[37,842,843],{},"社区版与企业版差距比想象大","：多路召回 \u002F 重排序 \u002F 单点登录 \u002F 审计日志都在企业版。社区版做生产前心里要有数。",[160,846,847,853,854,857,858,861],{},[37,848,849,852],{},[344,850,851],{},".env"," 文件改完忘 restart","：",[344,855,856],{},"docker compose down && up -d","，不是 ",[344,859,860],{},"restart","——后者不重新加载 env。",[160,863,864,853,867,872],{},[37,865,866],{},"大版本升级会破坏数据库 schema",[49,868,871],{"href":869,"rel":870},"https:\u002F\u002Fdocs.dify.ai\u002Fzh-hans",[179],"官方升级文档"," 有详细 migration 步骤，跨大版本（如 0.x → 1.x）务必先备份 PostgreSQL 卷。生产环境强烈建议跑 staging 完整验证后再升。",[160,874,875,878,879,881,882,885],{},[37,876,877],{},"RAG 文件大小社区版默认 15MB","：根据上述知乎实测，超过会失败。改 ",[344,880,851],{}," 的 ",[344,883,884],{},"UPLOAD_FILE_SIZE_LIMIT"," 并重启容器。",[160,887,888,891],{},[37,889,890],{},"代码节点的 Sandbox 性能差","：内置代码执行节点跑在隔离容器里启动慢、内存小。生产高频用建议改成 HTTP 节点调外部服务。",[160,893,894,897],{},[37,895,896],{},"工作流\"迭代节点\"循环上限","：默认 10 次，复杂 ReAct agent 容易撞天花板，需要在节点设置里调高。",[160,899,900,903],{},[37,901,902],{},"Dify Plugin 系统是新东西","：1.0 后引入的 Plugin 体系替代了原来的 Tools\u002FModels 配置方式，老教程可能已过时——以最新官方文档为准。",[160,905,906,909],{},[37,907,908],{},"国内 Docker 拉取镜像慢","：先配国内 registry，否则首次 pull 可能要 30+ 分钟。",[22,911,913],{"id":912},"适合-不适合","适合 \u002F 不适合",[34,915,916],{},"✅ 适合：",[222,918,919,922,925,928,931,934],{},[160,920,921],{},"中大型企业 LLM 中台建设",[160,923,924],{},"需要私有化部署（金融 \u002F 医疗 \u002F 政府）",[160,926,927],{},"想做\"AI 工作流即产品\"的开发团队",[160,929,930],{},"同时需要 RAG + Agent + Workflow 三件套",[160,932,933],{},"想用国产模型 + 国际模型混合编排",[160,935,936],{},"已经接受 Docker + 一定运维投入",[34,938,939],{},"❌ 不适合：",[222,941,942,948,954,957,963],{},[160,943,944,945,947],{},"纯个人玩家做对话机器人（",[49,946,52],{"href":51}," 更快）",[160,949,950,951,953],{},"只想做企业知识库 QA（",[49,952,189],{"href":188}," RAG 更专）",[160,955,956],{},"团队完全没运维能力（云版还行，自托管会踩坑）",[160,958,959,960,962],{},"需要深度对接字节飞书 \u002F 抖音（",[49,961,52],{"href":51}," 原生）",[160,964,965,966,968],{},"工作流核心是连接 100+ SaaS（",[49,967,660],{"href":659}," 节点更全）",[22,970,971],{"id":971},"相关阅读",[222,973,974,986,1004,1023],{},[160,975,976,977,979,980,979,982,979,984],{},"同类对比：",[49,978,52],{"href":51}," \u002F ",[49,981,189],{"href":188},[49,983,660],{"href":659},[49,985,833],{"href":832},[160,987,988,989,979,993,979,997,979,1000],{},"概念基础：",[49,990,992],{"href":991},"\u002Fwiki\u002Fai-agent.html","AI Agent",[49,994,996],{"href":995},"\u002Fwiki\u002Frag.html","RAG",[49,998,999],{"href":218},"MCP",[49,1001,1003],{"href":1002},"\u002Fwiki\u002Ffunction-calling.html","Function Calling",[160,1005,1006,1007,979,1011,979,1015,979,1019],{},"模型选型：",[49,1008,1010],{"href":1009},"\u002Fmodels\u002Fgpt-5.html","GPT-5",[49,1012,1014],{"href":1013},"\u002Fmodels\u002Fclaude-sonnet-4.html","Claude Sonnet 4",[49,1016,1018],{"href":1017},"\u002Fmodels\u002Fdeepseek-v3.html","DeepSeek-V3",[49,1020,1022],{"href":1021},"\u002Fmodels\u002Fglm-5.2.html","GLM-5.2",[160,1024,1025,1026,979,1030],{},"进阶：",[49,1027,1029],{"href":1028},"\u002Fwiki\u002Ffine-tuning-vs-rag.html","Fine-tuning vs RAG",[49,1031,1033],{"href":1032},"\u002Fwiki\u002Fcontext-engineering.html","Context Engineering",[22,1035,1036],{"id":1036},"来源",[222,1038,1039,1046,1052,1058,1065],{},[160,1040,1041,1042],{},"官网：",[49,1043,1044],{"href":1044,"rel":1045},"https:\u002F\u002Fdify.ai",[179],[160,1047,1048,1049],{},"中文文档：",[49,1050,869],{"href":869,"rel":1051},[179],[160,1053,1054,1055],{},"GitHub：",[49,1056,332],{"href":332,"rel":1057},[179],[160,1059,1060,1061],{},"官方定价：",[49,1062,1063],{"href":1063,"rel":1064},"https:\u002F\u002Fdify.ai\u002Fpricing",[179],[160,1066,1067],{},"第三方评测：tooljunction.io \u002F chatforest.com \u002F besthub.dev \u002F joshuaopolko.com \u002F 知乎 LLM 实战笔记",[34,1069,1070,1071,1075],{},"本卡片由 AIHO 编辑部根据官方公开资料与第三方评测整理。所有事实点均标注来源；如发现版本号 \u002F 价格 \u002F 功能与最新官方信息不一致，请通过 ",[49,1072,1074],{"href":1073},"mailto:hello@aiho.net","反馈邮箱"," 反馈。",[1077,1078,1079],"style",{},"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 .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":342,"searchDepth":374,"depth":374,"links":1081},[1082,1083,1090,1095,1096,1097,1098,1099,1100,1101],{"id":24,"depth":364,"text":25},{"id":62,"depth":364,"text":62,"children":1084},[1085,1086,1087,1088,1089],{"id":66,"depth":374,"text":67},{"id":151,"depth":374,"text":152},{"id":193,"depth":374,"text":194},{"id":211,"depth":374,"text":212},{"id":235,"depth":374,"text":236},{"id":242,"depth":364,"text":242,"children":1091},[1092,1093,1094],{"id":245,"depth":374,"text":246},{"id":326,"depth":374,"text":327},{"id":431,"depth":374,"text":432},{"id":504,"depth":364,"text":505},{"id":603,"depth":364,"text":603},{"id":635,"depth":364,"text":635},{"id":836,"depth":364,"text":836},{"id":912,"depth":364,"text":913},{"id":971,"depth":364,"text":971},{"id":1036,"depth":364,"text":1036},"platform","\u002Fimg\u002Ftools\u002Fdify.webp","Dify 2026 真实评测：开源 LLMOps 与 AI Agent 平台，集工作流编排、RAG 知识库、Agent、MCP 和多模型接入于一体。本文对比 Coze、FastGPT、n8n，整理自托管部署、云版价格、适合团队和避坑建议。",false,"md",[1108,1109,1110],"zh","en","ja",{},"\u002Ftools\u002Fagent\u002Fplatform\u002Fdify","agent",[1115,1116,1117,389],"windows","macos","linux",[1119,1123,1127,1131],{"plan":1120,"price":463,"features":1121,"notes":1122},"Self-hosted（开源版）","Docker 一键部署 + 全部核心功能（工作流 \u002F RAG \u002F Agent \u002F MCP）+ 接任意模型 API","私有部署 \u002F 完全免费 \u002F Apache 2.0",{"plan":1124,"price":463,"features":1125,"notes":1126},"Cloud Sandbox（免费云）","官方托管试水档，含基础调用配额","免运维 \u002F 试水 POC",{"plan":1128,"price":291,"features":1129,"notes":1130},"Cloud Professional","更高调用额度 + 团队协作 + 商用支持","商用云首选",{"plan":1132,"price":1133,"features":1134,"notes":313},"Cloud Team \u002F Enterprise","Custom","更大配额 + SLA + 私有部署支持 + 合规","云版 SaaS（免费档 \u002F Professional $59\u002F月起） + 开源自托管完全免费","2026-06-18",[1138,1139,1140,1141],"coze-deep-review","coze-vs-dify","dify-deep-review","fastgpt-deep-review",{"power":401,"ux":386,"price":401,"cn_support":386,"stability":386},{"title":12,"description":1104},"Dify 评测 2026：开源 LLMOps 与 AI Agent 平台，自托管指南","agent\u002Fplatform\u002Fdify",[1147,1149,1151,1153,1155],{"title":1148,"url":869},"Dify 官方文档（中文）",{"title":1150,"url":332},"Dify GitHub",{"title":1152,"url":1063},"Dify 官方定价",{"title":1154,"url":785},"Coze vs Dify vs FastGPT 选型",{"title":1156,"url":1157},"Dify Self-Hosted Guide 2026","https:\u002F\u002Fjoshuaopolko.com\u002Fdify-self-hosted-guide","tools\u002Fagent\u002Fplatform\u002Fdify","开源 LLMOps 平台，私有部署 Agent 首选",[1161,1162,1163,1164,1165,1166,1167],"agent-platform","opensource","self-host","rag","workflow","llmops","mcp","2026-06-24","想私有部署、想接全球任意模型，Dify 是答案。比 Coze 工程化、上手陡一点；比 FastGPT 工作流强、RAG 略弱。","p5aiXfjt5rD0m3qxj903DVwZMIONVWKdagLa7niYhcE",{"id":1172,"title":189,"alternatives":1173,"api_compatible":1174,"body":1176,"category":1102,"chinese_friendly":401,"cover":2198,"description":2199,"domestic":1105,"extension":1106,"faq":9,"free":1105,"github":2161,"languages":2200,"lastVerified":9,"meta":2201,"models":2202,"navigation":553,"notSuitable":2209,"opensource":553,"path":2213,"pillar":1113,"platforms":2214,"priceTable":2215,"pricing":2239,"published":1136,"relatedPlaybooks":2240,"relatedReviews":2242,"score":2243,"self_host":553,"seo":2244,"seoTitle":9,"slug":15,"sources":2245,"stem":2256,"suitable":2257,"tagline":2263,"tags":2264,"updated":1168,"verdict":2268,"website":2155,"__hash__":2269},"tools\u002Ftools\u002Fagent\u002Fplatform\u002Ffastgpt.md",[1145,14,17,16],[1175],"openai",{"type":19,"value":1177,"toc":2180},[1178,1180,1209,1220,1222,1226,1229,1243,1246,1272,1276,1283,1315,1322,1326,1379,1386,1389,1392,1395,1402,1448,1455,1459,1490,1494,1600,1603,1606,1610,1618,1742,1757,1759,1919,1929,1963,1969,1971,2046,2048,2050,2070,2072,2090,2092,2147,2149,2172,2177],[22,1179,25],{"id":24},[27,1181,1183,1198],{"className":1182},[30,31,32],[34,1184,1185,1187,1188,1193,1194,1197],{},[37,1186,39],{}," labring 团队开源的 LLM 知识库 RAG 平台，27k+ GitHub star（截至 2026-03 数据，",[49,1189,1192],{"href":1190,"rel":1191},"https:\u002F\u002Fcloud.tencent.com\u002Fdeveloper\u002Farticle\u002F2632669",[179],"腾讯云 2026-03 教程"," 引用），Apache 2.0 许可证可商用。",[37,1195,1196],{},"核心优势是 RAG 链路工程做得极细","——问题预处理、混合检索、重排序、上下文组装、答案生成每一步都可视化调参。",[34,1199,1200,1201,1204,1205,1208],{},"最大价值在 ",[37,1202,1203],{},"国内企业知识库 + 私有部署"," 场景。代价是 ",[37,1206,1207],{},"配置门槛","：docker 基础 + 网络知识 + 一定运维能力。",[55,1210,1211],{},[34,1212,1213,1214,1219],{},"来源说明：本文基于 fastgpt.io 官方页面、github.com\u002Flabring\u002FFastGPT 仓库、",[49,1215,1218],{"href":1216,"rel":1217},"https:\u002F\u002Fwww.nanhuantech.com\u002Fzh\u002Fai-reviews\u002Ffastgpt-2025-review",[179],"南环 AI 2026-05 评测","、腾讯云开发者社区 2026-03 部署教程综合整理。版本迭代较快，命令和价格请以最新官方文档为准。",[22,1221,62],{"id":62},[64,1223,1225],{"id":1224},"知识库管理核心能力","知识库管理（核心能力）",[34,1227,1228],{},"支持文件类型：",[222,1230,1231,1234,1237,1240],{},[160,1232,1233],{},"文档：PDF \u002F Word \u002F Markdown \u002F TXT \u002F HTML",[160,1235,1236],{},"表格：Excel \u002F CSV",[160,1238,1239],{},"网页：URL 抓取 + 定时同步",[160,1241,1242],{},"API：通过接口推送内容",[34,1244,1245],{},"处理流程：上传 → 文本切分 → 向量化 → 存储 → 可用于问答。支持：",[222,1247,1248,1254,1260,1266],{},[160,1249,1250,1253],{},[37,1251,1252],{},"文件夹分组","：不同主题 \u002F 部门分类",[160,1255,1256,1259],{},[37,1257,1258],{},"多种分块策略","：默认按段落 \u002F 按 token 数 \u002F 自定义",[160,1261,1262,1265],{},[37,1263,1264],{},"批量导入","：脚本化大批量同步",[160,1267,1268,1271],{},[37,1269,1270],{},"定时同步","：网页源自动更新",[64,1273,1275],{"id":1274},"rag-流程编排最强卖点","RAG 流程编排（最强卖点）",[34,1277,1278,1282],{},[49,1279,1281],{"href":1216,"rel":1280},[179],"南环 AI 2026 评测"," 总结的 FastGPT RAG 链路：",[157,1284,1285,1291,1297,1303,1309],{},[160,1286,1287,1290],{},[37,1288,1289],{},"问题预处理","：改写 \u002F 扩展 \u002F 错词纠正（提升召回率）",[160,1292,1293,1296],{},[37,1294,1295],{},"检索策略","：语义检索 \u002F 关键词 BM25 \u002F 混合检索，可调相似度阈值",[160,1298,1299,1302],{},[37,1300,1301],{},"重排序（Rerank）","：对初步检索结果二次排序，提升相关性",[160,1304,1305,1308],{},[37,1306,1307],{},"上下文组装","：最优 chunk + 问题 → prompt",[160,1310,1311,1314],{},[37,1312,1313],{},"答案生成","：调大模型基于检索结果回答 + 引用标注",[34,1316,1317,1318,1321],{},"每一步都可视化调参，这是 FastGPT 比 Coze \u002F Dify 在 ",[37,1319,1320],{},"纯知识库 QA 精度","上更高的原因。",[64,1323,1325],{"id":1324},"多模型支持不绑定厂商","多模型支持（不绑定厂商）",[72,1327,1328,1338],{},[75,1329,1330],{},[78,1331,1332,1335],{},[81,1333,1334],{},"模型类别",[81,1336,1337],{},"支持",[91,1339,1340,1348,1355,1363,1371],{},[78,1341,1342,1345],{},[96,1343,1344],{},"国产闭源",[96,1346,1347],{},"豆包 \u002F 通义千问 \u002F 文心一言 \u002F 智谱 GLM \u002F Moonshot Kimi \u002F MiniMax",[78,1349,1350,1352],{},[96,1351,667],{},[96,1353,1354],{},"LLaMA \u002F Qwen \u002F ChatGLM \u002F DeepSeek 等可自部署",[78,1356,1357,1360],{},[96,1358,1359],{},"OpenAI 系",[96,1361,1362],{},"GPT-5 \u002F GPT-5 mini \u002F o3",[78,1364,1365,1368],{},[96,1366,1367],{},"Claude 系",[96,1369,1370],{},"Sonnet 4 \u002F Opus 4 \u002F Haiku",[78,1372,1373,1376],{},[96,1374,1375],{},"嵌入 \u002F 重排",[96,1377,1378],{},"BGE \u002F m3e \u002F OpenAI text-embedding-3",[34,1380,1381,1382,1385],{},"可以在 ",[37,1383,1384],{},"应用级别","为不同知识库 \u002F 不同场景配置不同模型，做\"低成本 embedding + 高质量 LLM 生成\"组合。",[64,1387,1388],{"id":1388},"工作流与高级编排",[34,1390,1391],{},"新版本（v4.14.x）支持类似 Dify 的工作流节点编排——条件分支、循环、HTTP 调用、代码节点。能做\"分类 → 路由到不同子知识库 → 不同模型回答\"这类复杂场景。",[64,1393,1394],{"id":1394},"多向量库选择",[34,1396,1397,1401],{},[49,1398,1400],{"href":1190,"rel":1399},[179],"腾讯云教程"," 公开的 4 种向量后端：",[72,1403,1404,1414],{},[75,1405,1406],{},[78,1407,1408,1411],{},[81,1409,1410],{},"后端",[81,1412,1413],{},"适用",[91,1415,1416,1424,1432,1440],{},[78,1417,1418,1421],{},[96,1419,1420],{},"PgVector",[96,1422,1423],{},"5000 万索引以下，新手 \u002F 小规模",[78,1425,1426,1429],{},[96,1427,1428],{},"Milvus",[96,1430,1431],{},"亿级以上，高性能",[78,1433,1434,1437],{},[96,1435,1436],{},"Zilliz Cloud",[96,1438,1439],{},"Milvus 全托管 SaaS",[78,1441,1442,1445],{},[96,1443,1444],{},"SeekDB \u002F OceanBase",[96,1446,1447],{},"企业级国产化",[34,1449,1450,1451,1454],{},"部署时选对应 ",[344,1452,1453],{},"docker-compose.{pgvector|milvus|...}.yml","。",[64,1456,1458],{"id":1457},"api-与-mcp","API 与 MCP",[222,1460,1461,1467,1473,1484],{},[160,1462,1463,1466],{},[37,1464,1465],{},"对话 API","：流式 \u002F 非流式 HTTP，OpenAI 兼容",[160,1468,1469,1472],{},[37,1470,1471],{},"知识库检索 API","：单独调检索（不走生成）做 hybrid pipeline",[160,1474,1475,1478,1479,1483],{},[37,1476,1477],{},"MCP Server","：3005 端口暴露 MCP SSE 服务，可被 ",[49,1480,1482],{"href":1481},"\u002Fcoding\u002Fcli\u002Fclaude-code.html","Claude Code"," 等客户端直接接入",[160,1485,1486,1489],{},[37,1487,1488],{},"Webhook","：回调通知",[22,1491,1493],{"id":1492},"部署-10-分钟docker","部署 10 分钟（Docker）",[337,1495,1497],{"className":339,"code":1496,"language":341,"meta":342,"style":342},"# 克隆代码\ngit clone https:\u002F\u002Fgithub.com\u002Flabring\u002FFastGPT.git\ncd FastGPT\n\n# 切到最新稳定版（参考 GitHub releases）\ngit switch -c 4.14.7.2\n\n# 选向量库版本（个人 \u002F 小规模选 pg）\ncd deploy\u002Fdocker\u002Fcn\nwget https:\u002F\u002Fdoc.fastgpt.cn\u002Fdeploy\u002Fconfig\u002Fconfig.json\n\n# 启动\ndocker-compose -f docker-compose.pg.yml up -d\n\n# 访问 http:\u002F\u002F\u003Cip>:3000，默认账号 root \u002F 1234\n",[344,1498,1499,1504,1513,1520,1524,1529,1542,1546,1551,1558,1566,1570,1575,1590,1594],{"__ignoreMap":342},[347,1500,1501],{"class":349,"line":350},[347,1502,1503],{"class":404},"# 克隆代码\n",[347,1505,1506,1508,1510],{"class":349,"line":364},[347,1507,354],{"class":353},[347,1509,358],{"class":357},[347,1511,1512],{"class":357}," https:\u002F\u002Fgithub.com\u002Flabring\u002FFastGPT.git\n",[347,1514,1515,1517],{"class":349,"line":374},[347,1516,368],{"class":367},[347,1518,1519],{"class":357}," FastGPT\n",[347,1521,1522],{"class":349,"line":386},[347,1523,554],{"emptyLinePlaceholder":553},[347,1525,1526],{"class":349,"line":401},[347,1527,1528],{"class":404},"# 切到最新稳定版（参考 GitHub releases）\n",[347,1530,1531,1533,1536,1539],{"class":349,"line":550},[347,1532,354],{"class":353},[347,1534,1535],{"class":357}," switch",[347,1537,1538],{"class":367}," -c",[347,1540,1541],{"class":367}," 4.14.7.2\n",[347,1543,1544],{"class":349,"line":557},[347,1545,554],{"emptyLinePlaceholder":553},[347,1547,1548],{"class":349,"line":563},[347,1549,1550],{"class":404},"# 选向量库版本（个人 \u002F 小规模选 pg）\n",[347,1552,1553,1555],{"class":349,"line":569},[347,1554,368],{"class":367},[347,1556,1557],{"class":357}," deploy\u002Fdocker\u002Fcn\n",[347,1559,1560,1563],{"class":349,"line":574},[347,1561,1562],{"class":353},"wget",[347,1564,1565],{"class":357}," https:\u002F\u002Fdoc.fastgpt.cn\u002Fdeploy\u002Fconfig\u002Fconfig.json\n",[347,1567,1568],{"class":349,"line":580},[347,1569,554],{"emptyLinePlaceholder":553},[347,1571,1572],{"class":349,"line":585},[347,1573,1574],{"class":404},"# 启动\n",[347,1576,1577,1580,1583,1586,1588],{"class":349,"line":591},[347,1578,1579],{"class":353},"docker-compose",[347,1581,1582],{"class":367}," -f",[347,1584,1585],{"class":357}," docker-compose.pg.yml",[347,1587,395],{"class":357},[347,1589,398],{"class":367},[347,1591,1592],{"class":349,"line":597},[347,1593,554],{"emptyLinePlaceholder":553},[347,1595,1597],{"class":349,"line":1596},15,[347,1598,1599],{"class":404},"# 访问 http:\u002F\u002F\u003Cip>:3000，默认账号 root \u002F 1234\n",[34,1601,1602],{},"最低配置：2C4G + 20GB 硬盘 + Docker 28+ + Docker Compose 2.20+。",[34,1604,1605],{},"进入后台 → 账号 → 模型提供商 → 配置至少 1 个对话模型 + 1 个嵌入模型 → 即可开始建知识库。",[22,1607,1609],{"id":1608},"云版-vs-自托管对比","云版 vs 自托管对比",[34,1611,1612,1617],{},[49,1613,1616],{"href":1614,"rel":1615},"https:\u002F\u002Ffastgpt.io\u002Fzh\u002Fprice",[179],"fastgpt.io 官方定价"," 公开数据：",[72,1619,1620,1645],{},[75,1621,1622],{},[78,1623,1624,1626,1628,1631,1634,1637,1639,1642],{},[81,1625,264],{},[81,1627,267],{},[81,1629,1630],{},"AI 积分",[81,1632,1633],{},"知识库索引",[81,1635,1636],{},"团队",[81,1638,113],{},[81,1640,1641],{},"知识库",[81,1643,1644],{},"QPM",[91,1646,1647,1672,1697,1721],{},[78,1648,1649,1651,1654,1657,1660,1663,1666,1669],{},[96,1650,280],{},[96,1652,1653],{},"¥0",[96,1655,1656],{},"100",[96,1658,1659],{},"600",[96,1661,1662],{},"1",[96,1664,1665],{},"10",[96,1667,1668],{},"3",[96,1670,1671],{},"30",[78,1673,1674,1677,1680,1683,1686,1689,1692,1694],{},[96,1675,1676],{},"基础",[96,1678,1679],{},"¥99\u002F月",[96,1681,1682],{},"4000",[96,1684,1685],{},"6000",[96,1687,1688],{},"5",[96,1690,1691],{},"50",[96,1693,1671],{},[96,1695,1696],{},"300",[78,1698,1699,1702,1705,1708,1711,1713,1716,1718],{},[96,1700,1701],{},"高级",[96,1703,1704],{},"¥599\u002F月",[96,1706,1707],{},"25000",[96,1709,1710],{},"36000",[96,1712,1691],{},[96,1714,1715],{},"200",[96,1717,1656],{},[96,1719,1720],{},"1500",[78,1722,1723,1726,1729,1732,1734,1736,1738,1740],{},[96,1724,1725],{},"定制",[96,1727,1728],{},"议价",[96,1730,1731],{},"弹性",[96,1733,1731],{},[96,1735,1731],{},[96,1737,1731],{},[96,1739,1731],{},[96,1741,1731],{},[34,1743,1744,1747,1748,1751,1752,1756],{},[37,1745,1746],{},"云版适合","：不想运维、量小、要快速上线\n",[37,1749,1750],{},"自托管适合","：量大（10 万+ 日问答）、数据敏感、要深度定制——按 ",[49,1753,1755],{"href":1216,"rel":1754},[179],"南环评测"," 估算：\"日均 10 万次问答的企业场景，商业 SaaS 年费数十万，自建 FastGPT + 开源模型只需数万硬件投入\"",[22,1758,635],{"id":635},[72,1760,1761,1784],{},[75,1762,1763],{},[78,1764,1765,1767,1769,1774,1778,1781],{},[81,1766,644],{},[81,1768,189],{},[81,1770,1771],{},[49,1772,12],{"href":1773},"\u002Fagent\u002Fplatform\u002Fdify.html",[81,1775,1776],{},[49,1777,52],{"href":51},[81,1779,1780],{},"RAGFlow",[81,1782,1783],{},"AnythingLLM",[91,1785,1786,1806,1822,1838,1855,1870,1887,1902],{},[78,1787,1788,1791,1794,1797,1800,1803],{},[96,1789,1790],{},"核心定位",[96,1792,1793],{},"知识库 QA",[96,1795,1796],{},"综合 LLMOps",[96,1798,1799],{},"Bot + 工作流",[96,1801,1802],{},"文档解析+RAG",[96,1804,1805],{},"桌面级 KB",[78,1807,1808,1810,1813,1815,1817,1819],{},[96,1809,667],{},[96,1811,1812],{},"✅ Apache 2.0",[96,1814,1812],{},[96,1816,673],{},[96,1818,1812],{},[96,1820,1821],{},"✅ MIT",[78,1823,1824,1826,1829,1831,1834,1836],{},[96,1825,683],{},[96,1827,1828],{},"★★★★★ docker",[96,1830,715],{},[96,1832,1833],{},"⚠️ 仅企业版",[96,1835,707],{},[96,1837,715],{},[78,1839,1840,1843,1846,1848,1850,1853],{},[96,1841,1842],{},"RAG 深度",[96,1844,1845],{},"★★★★★ 最细",[96,1847,707],{},[96,1849,699],{},[96,1851,1852],{},"★★★★★ 文档解析最强",[96,1854,699],{},[78,1856,1857,1860,1862,1864,1866,1868],{},[96,1858,1859],{},"工作流",[96,1861,707],{},[96,1863,715],{},[96,1865,707],{},[96,1867,699],{},[96,1869,735],{},[78,1871,1872,1875,1878,1880,1883,1885],{},[96,1873,1874],{},"上手",[96,1876,1877],{},"★★★☆☆ 需 docker",[96,1879,707],{},[96,1881,1882],{},"★★★★★ 最简单",[96,1884,699],{},[96,1886,707],{},[78,1888,1889,1892,1894,1896,1898,1900],{},[96,1890,1891],{},"中文优化",[96,1893,715],{},[96,1895,707],{},[96,1897,715],{},[96,1899,707],{},[96,1901,699],{},[78,1903,1904,1907,1910,1912,1914,1917],{},[96,1905,1906],{},"多平台发布",[96,1908,1909],{},"⚠️ API 为主",[96,1911,707],{},[96,1913,715],{},[96,1915,1916],{},"⚠️",[96,1918,1916],{},[34,1920,1921,1923,1924,1928],{},[37,1922,781],{},"（综合 ",[49,1925,1927],{"href":1216,"rel":1926},[179],"南环 AI 评测","）：",[222,1930,1931,1937,1944,1951,1957],{},[160,1932,1933,1936],{},[37,1934,1935],{},"核心需求是 RAG 精度"," → FastGPT",[160,1938,1939,808,1942],{},[37,1940,1941],{},"需要丰富插件 + 复杂工作流 + 多平台发布",[49,1943,12],{"href":1773},[160,1945,1946,808,1949],{},[37,1947,1948],{},"零代码、快速发布到飞书 \u002F 微信",[49,1950,52],{"href":51},[160,1952,1953,1956],{},[37,1954,1955],{},"文档解析（含 OCR \u002F 表格 \u002F 公式）是瓶颈"," → RAGFlow",[160,1958,1959,1962],{},[37,1960,1961],{},"桌面 \u002F 单机使用"," → AnythingLLM",[34,1964,1965,1968],{},[37,1966,1967],{},"很多企业同时用","：FastGPT 做知识库底座 + Coze 做前端 Bot 发布 \u002F 工作流编排。",[22,1970,836],{"id":836},[222,1972,1973,1986,1995,2001,2011,2023,2029,2035],{},[160,1974,1975,853,1978,1981,1982,1985],{},[37,1976,1977],{},"docker-compose 镜像 tag 不一致",[49,1979,1400],{"href":1190,"rel":1980},[179]," 实测的坑——某些版本编排文件的 image tag 与最新 release 不一致，启动报\"镜像找不到\"，手动改 ",[344,1983,1984],{},"image:"," 行为正确版本即可",[160,1987,1988,1991,1992,1994],{},[37,1989,1990],{},"3000 端口冲突","：默认占用 3000（主服务）\u002F 9000（S3 \u002F MinIO）\u002F 3005（MCP）；改 ",[344,1993,1579],{}," 的 ports 映射端口",[160,1996,1997,2000],{},[37,1998,1999],{},"PostgreSQL pgvector 不够用就换 Milvus","：单库索引超 5000 万时 pgvector 查询性能下降，切 Milvus",[160,2002,2003,2006,2007,2010],{},[37,2004,2005],{},"向量库选错代价大","：先评估索引量再选向量后端，迁移要重新 embedding 整库，按 ",[49,2008,1755],{"href":1216,"rel":2009},[179],"：\"新手 \u002F 小规模 PgVector，中大规模 Milvus，企业 \u002F 国产 OceanBase\"",[160,2012,2013,853,2016,2019,2020],{},[37,2014,2015],{},"MinIO 默认密码",[344,2017,2018],{},"minioadmin\u002Fminioadmin","，",[37,2021,2022],{},"部署到公网前必须改",[160,2024,2025,2028],{},[37,2026,2027],{},"分段策略影响巨大","：默认分段对长法律 \u002F 医疗文档不友好，需调\"按章节\"或\"自定义\"",[160,2030,2031,2034],{},[37,2032,2033],{},"嵌入模型 ≠ 对话模型","：经常有人只配 GPT-4 没配 embedding 模型，知识库无法索引——必须同时配两类",[160,2036,2037,2040,2041,2045],{},[37,2038,2039],{},"云版 AI 积分会过期","：未用完不能跨月累积（按 ",[49,2042,2044],{"href":1614,"rel":2043},[179],"fastgpt.io 定价 FAQ","）",[22,2047,913],{"id":912},[34,2049,916],{},[222,2051,2052,2055,2058,2061,2064,2067],{},[160,2053,2054],{},"企业内部知识库（员工手册 \u002F 制度 \u002F 流程）",[160,2056,2057],{},"产品 FAQ \u002F 用户手册问答",[160,2059,2060],{},"医疗 \u002F 法律 \u002F 金融垂直领域知识系统",[160,2062,2063],{},"数据严格不出网 + Apache 2.0 商用",[160,2065,2066],{},"有 docker 运维基础的技术团队",[160,2068,2069],{},"需要把 RAG 当后端服务的开发者（API 接入业务系统）",[34,2071,939],{},[222,2073,2074,2079,2084,2087],{},[160,2075,2076,2077,2045],{},"完全非技术用户（去 ",[49,2078,52],{"href":51},[160,2080,2081,2082,2045],{},"主要需求是工作流 + 插件集成（去 ",[49,2083,12],{"href":1773},[160,2085,2086],{},"文档解析 \u002F OCR 是首要痛点（RAGFlow）",[160,2088,2089],{},"不想自己运维 + 量很小（FastGPT 云免费版起步即可）",[22,2091,971],{"id":971},[222,2093,2094,2103,2120,2139],{},[160,2095,976,2096,979,2098,2100,2101],{},[49,2097,12],{"href":1773},[49,2099,52],{"href":51}," \u002F RAGFlow \u002F AnythingLLM \u002F ",[49,2102,660],{"href":659},[160,2104,2105,2106,979,2108,979,2112,979,2115,979,2118],{},"概念：",[49,2107,996],{"href":995},[49,2109,2111],{"href":2110},"\u002Fwiki\u002Fembedding.html","Embedding",[49,2113,2114],{"href":2110},"Vector Database",[49,2116,2117],{"href":995},"Reranker",[49,2119,992],{"href":991},[160,2121,2122,2123,979,2125,979,2129,979,2131,979,2135],{},"模型：",[49,2124,1018],{"href":1017},[49,2126,2128],{"href":2127},"\u002Fmodels\u002Fqwen-3.html","Qwen3",[49,2130,1022],{"href":1021},[49,2132,2134],{"href":2133},"\u002Fmodels\u002Fkimi-k2.html","Kimi K2",[49,2136,2138],{"href":2137},"\u002Fmodels\u002Fdoubao-1-5-pro.html","豆包 Doubao",[160,2140,1025,2141,979,2143],{},[49,2142,1033],{"href":1032},[49,2144,2146],{"href":2145},"\u002Fwiki\u002Fprompt-engineering.html","Prompt Engineering",[22,2148,1036],{"id":1036},[222,2150,2151,2157,2163,2169],{},[160,2152,1041,2153],{},[49,2154,2155],{"href":2155,"rel":2156},"https:\u002F\u002Ffastgpt.io",[179],[160,2158,1054,2159],{},[49,2160,2161],{"href":2161,"rel":2162},"https:\u002F\u002Fgithub.com\u002Flabring\u002FFastGPT",[179],[160,2164,2165,2166],{},"定价：",[49,2167,1614],{"href":1614,"rel":2168},[179],[160,2170,2171],{},"第三方评测：南环 AI \u002F 腾讯云开发者社区 \u002F 飞书 AGI 掘金知识库",[34,2173,2174,2175,1075],{},"本卡片由 AIHO 编辑部根据官方公开资料与第三方评测整理。所有事实点均标注来源；如发现价格 \u002F 命令 \u002F 功能与最新官方信息不一致，请通过 ",[49,2176,1074],{"href":1073},[1077,2178,2179],{},"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 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¥0-¥599\u002F月",[2241],"onboarding\u002Ffastgpt-getting-started",[1141,1138,1139,1140],{"power":386,"ux":386,"price":401,"cn_support":401,"stability":386},{"title":189,"description":2199},[2246,2248,2250,2252,2254],{"title":2247,"url":2155},"FastGPT 官网",{"title":2249,"url":2161},"FastGPT GitHub",{"title":2251,"url":1614},"FastGPT 定价页",{"title":2253,"url":1216},"FastGPT 2025 测评（南环 AI）",{"title":2255,"url":1190},"FastGPT 部署教程（腾讯云）","tools\u002Fagent\u002Fplatform\u002Ffastgpt",[2258,2259,2260,2261,2262],"企业内部知识库（员工手册、规章、流程）","产品文档智能问答（FAQ \u002F 用户手册）","垂直领域知识库（医疗、法律、金融）","数据严格不出网的合规场景","需要精细 RAG 流程编排（重排序、混合检索、阈值调节）","开源知识库问答系统，国内私有部署友好",[1161,1162,1163,1164,2265,2266,2267],"china","knowledge-base","labring","国内企业知识库私有化首选。RAG 召回工程做得很细，可视化调试好用，docker-compose 一键部署。生态插件不如 Dify 丰富。","8WByuuERL4Ll0dVQeD7A-LVHlxElsUGAZF_GhzdYohI",1784900540045]