[{"data":1,"prerenderedAt":1195},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"news-2026-dify-1-0-release":9},{"tools":4,"reviews":5},65,7,{"tools":4,"reviews":5,"playbooks":7,"news":8},10,8,{"id":10,"title":11,"body":12,"cover":1184,"description":1185,"extension":1186,"meta":1187,"navigation":420,"path":1188,"published":1189,"seo":1190,"sourceName":1191,"sourceUrl":1192,"stem":1193,"__hash__":1194},"news\u002Fnews\u002F2026\u002Fdify-1-0-release.md","Dify 1.0 正式发布：从 LLMOps 到 Agent OS 的进化",{"type":13,"value":14,"toc":1172},"minimark",[15,19,54,57,62,66,71,82,87,214,218,221,530,535,546,550,553,730,735,797,801,804,1026,1029,1110,1114,1117,1120,1141,1144,1147,1168],[16,17,18],"h2",{"id":18},"要点",[20,21,22,30,36,42,48],"ul",{},[23,24,25,29],"li",{},[26,27,28],"strong",{},"Agent Workflow","：可视化编排多 Agent 协作，拖拽配置条件和循环",[23,31,32,35],{},[26,33,34],{},"MCP 原生支持","：Dify 可作为 MCP Server 暴露工具，也可消费外部 MCP Server",[23,37,38,41],{},[26,39,40],{},"RAG 重构","：新增混合检索（向量 + 关键词 + 重排序），准确率提升 30%",[23,43,44,47],{},[26,45,46],{},"多模型 A\u002FB","：同一 workflow 分流到不同模型对比效果",[23,49,50,53],{},[26,51,52],{},"企业版","：SSO + RBAC + 审计日志，私有化部署",[16,55,56],{"id":56},"核心升级解读",[58,59,61],"h3",{"id":60},"_1-agent-workflow-可视化编排","1. Agent Workflow 可视化编排",[63,64,65],"p",{},"1.0 把工作流编排从代码级提升到了「拖拽级」：",[63,67,68],{},[26,69,70],{},"工作流画布：",[72,73,78],"pre",{"className":74,"code":76,"language":77},[75],"language-text","┌─────────────────────────────────────────────────────────────────┐\n│  Dify 1.0 Agent Workflow                                        │\n│                                                                  │\n│    ┌────────┐      ┌────────┐      ┌────────┐      ┌────────┐  │\n│    │ 开始   │ ───► │ LLM 1  │ ───► │ Agent  │ ───► │ 结束   │  │\n│    │ Trigger│      │ (分类) │      │ (执行) │      │ Response│  │\n│    └────────┘      └────────┘      └────────┘      └────────┘  │\n│                          │                                  │     │\n│                          ▼                                  │     │\n│                    ┌──────────┐                            │     │\n│                    │ 条件分支  │                            │     │\n│                    │ A: 意图A │ ───► Agent A               │     │\n│                    │ B: 意图B │ ───► Agent B               │     │\n│                    │ C: 其他 │ ───► Fallback              │     │\n│                    └──────────┘                            │     │\n└─────────────────────────────────────────────────────────────────┘\n","text",[79,80,76],"code",{"__ignoreMap":81},"",[63,83,84],{},[26,85,86],{},"支持的节点类型：",[88,89,90,106],"table",{},[91,92,93],"thead",{},[94,95,96,100,103],"tr",{},[97,98,99],"th",{},"节点类型",[97,101,102],{},"说明",[97,104,105],{},"适用场景",[107,108,109,123,136,149,162,175,188,201],"tbody",{},[94,110,111,117,120],{},[112,113,114],"td",{},[26,115,116],{},"LLM",[112,118,119],{},"调用大模型",[112,121,122],{},"分类、生成、总结",[94,124,125,130,133],{},[112,126,127],{},[26,128,129],{},"Agent",[112,131,132],{},"自主决策 Agent",[112,134,135],{},"多步骤任务、工具调用",[94,137,138,143,146],{},[112,139,140],{},[26,141,142],{},"Knowledge",[112,144,145],{},"RAG 检索",[112,147,148],{},"知识库问答",[94,150,151,156,159],{},[112,152,153],{},[26,154,155],{},"HTTP",[112,157,158],{},"调用外部 API",[112,160,161],{},"接入第三方服务",[94,163,164,169,172],{},[112,165,166],{},[26,167,168],{},"Condition",[112,170,171],{},"条件分支",[112,173,174],{},"意图路由",[94,176,177,182,185],{},[112,178,179],{},[26,180,181],{},"Loop",[112,183,184],{},"循环节点",[112,186,187],{},"批量处理、迭代",[94,189,190,195,198],{},[112,191,192],{},[26,193,194],{},"Code",[112,196,197],{},"自定义代码",[112,199,200],{},"复杂逻辑",[94,202,203,208,211],{},[112,204,205],{},[26,206,207],{},"Template",[112,209,210],{},"模板渲染",[112,212,213],{},"格式化输出",[58,215,217],{"id":216},"_2-mcp-双向支持","2. MCP 双向支持",[63,219,220],{},"1.0 实现 MCP 双向连接：",[72,222,226],{"className":223,"code":224,"language":225,"meta":81,"style":81},"language-yaml shiki shiki-themes github-light github-dark","# 方式 1：Dify 作为 MCP Server（暴露工具）\n# 其他 Agent（如 Claude Code）可以调用 Dify 里的 workflow\nserver:\n  name: dify-workflow\n  tools:\n    - name: customer-support\n      description: 处理客户咨询流程\n      input: { query: string }\n      output: { response: string, confidence: float }\n    \n    - name: order-status\n      description: 查询订单状态\n      input: { order_id: string }\n      output: { status: string, details: object }\n\n# 方式 2：Dify 消费外部 MCP Server\nclients:\n  - name: github\n    server_url: https:\u002F\u002Fgithub.com\u002Fmcp\u002Fservers\u002Fgithub\n    tools: [create-issue, search-repo, get-pr]\n  \n  - name: slack\n    server_url: https:\u002F\u002Fgithub.com\u002Fmcp\u002Fservers\u002Fslack\n    tools: [send-message, list-channels]\n","yaml",[79,227,228,237,243,254,267,275,289,299,318,346,351,363,373,389,415,422,428,436,449,460,485,491,503,513],{"__ignoreMap":81},[229,230,233],"span",{"class":231,"line":232},"line",1,[229,234,236],{"class":235},"sJ8bj","# 方式 1：Dify 作为 MCP Server（暴露工具）\n",[229,238,240],{"class":231,"line":239},2,[229,241,242],{"class":235},"# 其他 Agent（如 Claude Code）可以调用 Dify 里的 workflow\n",[229,244,246,250],{"class":231,"line":245},3,[229,247,249],{"class":248},"s9eBZ","server",[229,251,253],{"class":252},"sVt8B",":\n",[229,255,257,260,263],{"class":231,"line":256},4,[229,258,259],{"class":248},"  name",[229,261,262],{"class":252},": ",[229,264,266],{"class":265},"sZZnC","dify-workflow\n",[229,268,270,273],{"class":231,"line":269},5,[229,271,272],{"class":248},"  tools",[229,274,253],{"class":252},[229,276,278,281,284,286],{"class":231,"line":277},6,[229,279,280],{"class":252},"    - ",[229,282,283],{"class":248},"name",[229,285,262],{"class":252},[229,287,288],{"class":265},"customer-support\n",[229,290,291,294,296],{"class":231,"line":5},[229,292,293],{"class":248},"      description",[229,295,262],{"class":252},[229,297,298],{"class":265},"处理客户咨询流程\n",[229,300,301,304,307,310,312,315],{"class":231,"line":8},[229,302,303],{"class":248},"      input",[229,305,306],{"class":252},": { ",[229,308,309],{"class":248},"query",[229,311,262],{"class":252},[229,313,314],{"class":265},"string",[229,316,317],{"class":252}," }\n",[229,319,321,324,326,329,331,333,336,339,341,344],{"class":231,"line":320},9,[229,322,323],{"class":248},"      output",[229,325,306],{"class":252},[229,327,328],{"class":248},"response",[229,330,262],{"class":252},[229,332,314],{"class":265},[229,334,335],{"class":252},", ",[229,337,338],{"class":248},"confidence",[229,340,262],{"class":252},[229,342,343],{"class":265},"float",[229,345,317],{"class":252},[229,347,348],{"class":231,"line":7},[229,349,350],{"class":252},"    \n",[229,352,354,356,358,360],{"class":231,"line":353},11,[229,355,280],{"class":252},[229,357,283],{"class":248},[229,359,262],{"class":252},[229,361,362],{"class":265},"order-status\n",[229,364,366,368,370],{"class":231,"line":365},12,[229,367,293],{"class":248},[229,369,262],{"class":252},[229,371,372],{"class":265},"查询订单状态\n",[229,374,376,378,380,383,385,387],{"class":231,"line":375},13,[229,377,303],{"class":248},[229,379,306],{"class":252},[229,381,382],{"class":248},"order_id",[229,384,262],{"class":252},[229,386,314],{"class":265},[229,388,317],{"class":252},[229,390,392,394,396,399,401,403,405,408,410,413],{"class":231,"line":391},14,[229,393,323],{"class":248},[229,395,306],{"class":252},[229,397,398],{"class":248},"status",[229,400,262],{"class":252},[229,402,314],{"class":265},[229,404,335],{"class":252},[229,406,407],{"class":248},"details",[229,409,262],{"class":252},[229,411,412],{"class":265},"object",[229,414,317],{"class":252},[229,416,418],{"class":231,"line":417},15,[229,419,421],{"emptyLinePlaceholder":420},true,"\n",[229,423,425],{"class":231,"line":424},16,[229,426,427],{"class":235},"# 方式 2：Dify 消费外部 MCP Server\n",[229,429,431,434],{"class":231,"line":430},17,[229,432,433],{"class":248},"clients",[229,435,253],{"class":252},[229,437,439,442,444,446],{"class":231,"line":438},18,[229,440,441],{"class":252},"  - ",[229,443,283],{"class":248},[229,445,262],{"class":252},[229,447,448],{"class":265},"github\n",[229,450,452,455,457],{"class":231,"line":451},19,[229,453,454],{"class":248},"    server_url",[229,456,262],{"class":252},[229,458,459],{"class":265},"https:\u002F\u002Fgithub.com\u002Fmcp\u002Fservers\u002Fgithub\n",[229,461,463,466,469,472,474,477,479,482],{"class":231,"line":462},20,[229,464,465],{"class":248},"    tools",[229,467,468],{"class":252},": [",[229,470,471],{"class":265},"create-issue",[229,473,335],{"class":252},[229,475,476],{"class":265},"search-repo",[229,478,335],{"class":252},[229,480,481],{"class":265},"get-pr",[229,483,484],{"class":252},"]\n",[229,486,488],{"class":231,"line":487},21,[229,489,490],{"class":252},"  \n",[229,492,494,496,498,500],{"class":231,"line":493},22,[229,495,441],{"class":252},[229,497,283],{"class":248},[229,499,262],{"class":252},[229,501,502],{"class":265},"slack\n",[229,504,506,508,510],{"class":231,"line":505},23,[229,507,454],{"class":248},[229,509,262],{"class":252},[229,511,512],{"class":265},"https:\u002F\u002Fgithub.com\u002Fmcp\u002Fservers\u002Fslack\n",[229,514,516,518,520,523,525,528],{"class":231,"line":515},24,[229,517,465],{"class":248},[229,519,468],{"class":252},[229,521,522],{"class":265},"send-message",[229,524,335],{"class":252},[229,526,527],{"class":265},"list-channels",[229,529,484],{"class":252},[63,531,532],{},[26,533,534],{},"实际应用：",[20,536,537,540,543],{},[23,538,539],{},"Claude Code 通过 MCP 调用 Dify 里的客户咨询 workflow",[23,541,542],{},"Dify workflow 里调用 GitHub MCP 获取代码库信息",[23,544,545],{},"Slack MCP 发消息通知",[58,547,549],{"id":548},"_3-rag-pipeline-重构","3. RAG Pipeline 重构",[63,551,552],{},"1.0 的 RAG 从「向量检索」升级到「混合检索 + 重排序」：",[72,554,558],{"className":555,"code":556,"language":557,"meta":81,"style":81},"language-python shiki shiki-themes github-light github-dark","# 之前：纯向量检索\nquery_embedding = embed(\"如何配置 SSL\")\nresults = vector_db.search(query_embedding, top_k=5)\n# 问题：关键词不匹配时效果差\n\n# 现在：混合检索 + 重排序\n# Step 1: 向量检索\nvector_results = vector_db.search(embed(query), top_k=20)\n\n# Step 2: 关键词检索\nbm25_results = bm25.search(query, top_k=20)\n\n# Step 3: RRF 融合\nfused_results = reciprocal_rank_fusion(vector_results, bm25_results, top_k=10)\n\n# Step 4: LLM 重排序\nreranked = llm_rerank(query, fused_results, top_k=5)\n# 输出最相关的 5 条\n","python",[79,559,560,565,583,605,610,614,619,624,643,647,652,670,674,679,698,702,707,725],{"__ignoreMap":81},[229,561,562],{"class":231,"line":232},[229,563,564],{"class":235},"# 之前：纯向量检索\n",[229,566,567,570,574,577,580],{"class":231,"line":239},[229,568,569],{"class":252},"query_embedding ",[229,571,573],{"class":572},"szBVR","=",[229,575,576],{"class":252}," embed(",[229,578,579],{"class":265},"\"如何配置 SSL\"",[229,581,582],{"class":252},")\n",[229,584,585,588,590,593,597,599,603],{"class":231,"line":245},[229,586,587],{"class":252},"results ",[229,589,573],{"class":572},[229,591,592],{"class":252}," vector_db.search(query_embedding, ",[229,594,596],{"class":595},"s4XuR","top_k",[229,598,573],{"class":572},[229,600,602],{"class":601},"sj4cs","5",[229,604,582],{"class":252},[229,606,607],{"class":231,"line":256},[229,608,609],{"class":235},"# 问题：关键词不匹配时效果差\n",[229,611,612],{"class":231,"line":269},[229,613,421],{"emptyLinePlaceholder":420},[229,615,616],{"class":231,"line":277},[229,617,618],{"class":235},"# 现在：混合检索 + 重排序\n",[229,620,621],{"class":231,"line":5},[229,622,623],{"class":235},"# Step 1: 向量检索\n",[229,625,626,629,631,634,636,638,641],{"class":231,"line":8},[229,627,628],{"class":252},"vector_results ",[229,630,573],{"class":572},[229,632,633],{"class":252}," vector_db.search(embed(query), ",[229,635,596],{"class":595},[229,637,573],{"class":572},[229,639,640],{"class":601},"20",[229,642,582],{"class":252},[229,644,645],{"class":231,"line":320},[229,646,421],{"emptyLinePlaceholder":420},[229,648,649],{"class":231,"line":7},[229,650,651],{"class":235},"# Step 2: 关键词检索\n",[229,653,654,657,659,662,664,666,668],{"class":231,"line":353},[229,655,656],{"class":252},"bm25_results ",[229,658,573],{"class":572},[229,660,661],{"class":252}," bm25.search(query, ",[229,663,596],{"class":595},[229,665,573],{"class":572},[229,667,640],{"class":601},[229,669,582],{"class":252},[229,671,672],{"class":231,"line":365},[229,673,421],{"emptyLinePlaceholder":420},[229,675,676],{"class":231,"line":375},[229,677,678],{"class":235},"# Step 3: RRF 融合\n",[229,680,681,684,686,689,691,693,696],{"class":231,"line":391},[229,682,683],{"class":252},"fused_results ",[229,685,573],{"class":572},[229,687,688],{"class":252}," reciprocal_rank_fusion(vector_results, bm25_results, ",[229,690,596],{"class":595},[229,692,573],{"class":572},[229,694,695],{"class":601},"10",[229,697,582],{"class":252},[229,699,700],{"class":231,"line":417},[229,701,421],{"emptyLinePlaceholder":420},[229,703,704],{"class":231,"line":424},[229,705,706],{"class":235},"# Step 4: LLM 重排序\n",[229,708,709,712,714,717,719,721,723],{"class":231,"line":430},[229,710,711],{"class":252},"reranked ",[229,713,573],{"class":572},[229,715,716],{"class":252}," llm_rerank(query, fused_results, ",[229,718,596],{"class":595},[229,720,573],{"class":572},[229,722,602],{"class":601},[229,724,582],{"class":252},[229,726,727],{"class":231,"line":438},[229,728,729],{"class":235},"# 输出最相关的 5 条\n",[63,731,732],{},[26,733,734],{},"实测提升：",[88,736,737,753],{},[91,738,739],{},[94,740,741,744,747,750],{},[97,742,743],{},"指标",[97,745,746],{},"0.x 纯向量",[97,748,749],{},"1.0 混合 + 重排序",[97,751,752],{},"提升",[107,754,755,769,783],{},[94,756,757,760,763,766],{},[112,758,759],{},"召回率",[112,761,762],{},"72%",[112,764,765],{},"89%",[112,767,768],{},"+17%",[94,770,771,774,777,780],{},[112,772,773],{},"Precision@5",[112,775,776],{},"65%",[112,778,779],{},"91%",[112,781,782],{},"+26%",[94,784,785,788,791,794],{},[112,786,787],{},"MRR",[112,789,790],{},"68%",[112,792,793],{},"88%",[112,795,796],{},"+20%",[58,798,800],{"id":799},"_4-多模型-ab-测试","4. 多模型 A\u002FB 测试",[63,802,803],{},"1.0 支持同一个 workflow 同时跑多个模型：",[72,805,807],{"className":223,"code":806,"language":225,"meta":81,"style":81},"# A\u002FB 测试配置\nab_test:\n  enabled: true\n  routes:\n    - name: Claude-Sonnet\n      provider: anthropic\n      model: sonnet-4.5\n      weight: 50%\n      \n    - name: GPT-5\n      provider: openai\n      model: gpt-5\n      weight: 50%\n\n  metrics:\n    - name: 用户满意度\n      type: thumbs_up_down\n    - name: 响应准确率\n      type: manual_review\n    - name: 响应延迟\n      type: latency_ms\n\n  auto_switch: true\n  winner_metric: 用户满意度\n  threshold: 95% confidence\n",[79,808,809,814,821,831,838,849,859,869,879,884,895,904,913,921,925,932,943,953,964,973,984,993,997,1006,1015],{"__ignoreMap":81},[229,810,811],{"class":231,"line":232},[229,812,813],{"class":235},"# A\u002FB 测试配置\n",[229,815,816,819],{"class":231,"line":239},[229,817,818],{"class":248},"ab_test",[229,820,253],{"class":252},[229,822,823,826,828],{"class":231,"line":245},[229,824,825],{"class":248},"  enabled",[229,827,262],{"class":252},[229,829,830],{"class":601},"true\n",[229,832,833,836],{"class":231,"line":256},[229,834,835],{"class":248},"  routes",[229,837,253],{"class":252},[229,839,840,842,844,846],{"class":231,"line":269},[229,841,280],{"class":252},[229,843,283],{"class":248},[229,845,262],{"class":252},[229,847,848],{"class":265},"Claude-Sonnet\n",[229,850,851,854,856],{"class":231,"line":277},[229,852,853],{"class":248},"      provider",[229,855,262],{"class":252},[229,857,858],{"class":265},"anthropic\n",[229,860,861,864,866],{"class":231,"line":5},[229,862,863],{"class":248},"      model",[229,865,262],{"class":252},[229,867,868],{"class":265},"sonnet-4.5\n",[229,870,871,874,876],{"class":231,"line":8},[229,872,873],{"class":248},"      weight",[229,875,262],{"class":252},[229,877,878],{"class":265},"50%\n",[229,880,881],{"class":231,"line":320},[229,882,883],{"class":252},"      \n",[229,885,886,888,890,892],{"class":231,"line":7},[229,887,280],{"class":252},[229,889,283],{"class":248},[229,891,262],{"class":252},[229,893,894],{"class":265},"GPT-5\n",[229,896,897,899,901],{"class":231,"line":353},[229,898,853],{"class":248},[229,900,262],{"class":252},[229,902,903],{"class":265},"openai\n",[229,905,906,908,910],{"class":231,"line":365},[229,907,863],{"class":248},[229,909,262],{"class":252},[229,911,912],{"class":265},"gpt-5\n",[229,914,915,917,919],{"class":231,"line":375},[229,916,873],{"class":248},[229,918,262],{"class":252},[229,920,878],{"class":265},[229,922,923],{"class":231,"line":391},[229,924,421],{"emptyLinePlaceholder":420},[229,926,927,930],{"class":231,"line":417},[229,928,929],{"class":248},"  metrics",[229,931,253],{"class":252},[229,933,934,936,938,940],{"class":231,"line":424},[229,935,280],{"class":252},[229,937,283],{"class":248},[229,939,262],{"class":252},[229,941,942],{"class":265},"用户满意度\n",[229,944,945,948,950],{"class":231,"line":430},[229,946,947],{"class":248},"      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生态是差异化优势。",[16,1145,1146],{"id":1146},"相关阅读",[20,1148,1149,1156,1162],{},[23,1150,1151],{},[1152,1153,1155],"a",{"href":1154},"\u002Fagent\u002Fplatform\u002Fdify","Dify 完整评测",[23,1157,1158],{},[1152,1159,1161],{"href":1160},"\u002Freview\u002Fcoze-vs-dify","Coze vs Dify 横向对比",[23,1163,1164],{},[1152,1165,1167],{"href":1166},"\u002Fwiki\u002Fmcp","MCP 百科",[1169,1170,1171],"style",{},"html pre.shiki code .sJ8bj, html code.shiki .sJ8bj{--shiki-default:#6A737D;--shiki-dark:#6A737D}html pre.shiki code .sVt8B, html code.shiki .sVt8B{--shiki-default:#24292E;--shiki-dark:#E1E4E8}html pre.shiki code .szBVR, html code.shiki .szBVR{--shiki-default:#D73A49;--shiki-dark:#F97583}html pre.shiki code .sZZnC, html code.shiki .sZZnC{--shiki-default:#032F62;--shiki-dark:#9ECBFF}html pre.shiki code .s4XuR, html code.shiki .s4XuR{--shiki-default:#E36209;--shiki-dark:#FFAB70}html pre.shiki code .sj4cs, html code.shiki .sj4cs{--shiki-default:#005CC5;--shiki-dark:#79B8FF}html .default .shiki span {color: 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