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n8n 中文网amn8n.com

使用Paul Essays、Milvus和OpenAI构建带引用的RAG问答系统

高级

这是一个AI领域的自动化工作流，包含 25 个节点。主要使用 Set, Code, Html, Limit, SplitOut 等节点，结合人工智能技术实现智能自动化。 使用Paul Essays、Milvus和OpenAI构建带引用的RAG问答系统

前置要求
  • •可能需要目标 API 的认证凭证
  • •OpenAI API Key

使用的节点 (25)

Set
Code
Html
Limit
SplitOut
StickyNote
HttpRequest
ManualTrigger
ChatTrigger
LmChatOpenAi
EmbeddingsOpenAi
VectorStoreMilvus
InformationExtractor
DocumentDefaultDataLoader
TextSplitterRecursiveCharacterTextSplitter

分类

人工智能
工作流预览
可视化展示节点连接关系，支持缩放和平移
React Flow
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
  "id": "Hjyv9FkH5Oh6Yxw4",
  "meta": {
    "instanceId": "2c4c1e23e7b067270c08aab616bada21d0c384d16f212b23cf1143c6baa09219"
  },
  "name": "插入和检索文档",
  "tags": [
    {
      "id": "msnDWKHQmwMDxWQH",
      "name": "Milvus",
      "createdAt": "2025-04-16T12:48:14.539Z",
      "updatedAt": "2025-04-16T12:48:14.539Z"
    },
    {
      "id": "tnCpo8hq8uKrdASK",
      "name": "AI",
      "createdAt": "2025-04-16T12:47:57.976Z",
      "updatedAt": "2025-04-16T12:47:57.976Z"
    }
  ],
  "nodes": [
    {
      "id": "52044ccd-4e0d-4353-b612-cf8db1b55331",
      "name": "当点击\"执行工作流\"时",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -500,
        -100
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "b6993775-d21b-4ae8-a59c-43aef2b7002b",
      "name": "获取文章列表",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -220,
        -100
      ],
      "parameters": {
        "url": "http://www.paulgraham.com/articles.html",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "cbaeb236-5c93-4b34-a06b-ff0e5de8525f",
      "name": "提取文章名称",
      "type": "n8n-nodes-base.html",
      "position": [
        -20,
        -100
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "essay",
              "attribute": "href",
              "cssSelector": "table table a",
              "returnArray": true,
              "returnValue": "attribute"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "d92b6692-4a02-4519-b113-8a9172c71de9",
      "name": "拆分为项目",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        180,
        -100
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "essay"
      },
      "typeVersion": 1
    },
    {
      "id": "d16ba71b-10fc-454f-8bfc-a6826280a4e7",
      "name": "获取文章文本",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        580,
        -100
      ],
      "parameters": {
        "url": "=http://www.paulgraham.com/{{ $json.essay }}",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "c4fa74ea-6af5-410c-bf5c-9d8d3decf31b",
      "name": "限制为前 3 个",
      "type": "n8n-nodes-base.limit",
      "position": [
        380,
        -100
      ],
      "parameters": {
        "maxItems": 3
      },
      "typeVersion": 1
    },
    {
      "id": "3da8495b-62df-475d-b99d-e0f3c64266e3",
      "name": "仅提取文本",
      "type": "n8n-nodes-base.html",
      "position": [
        900,
        -100
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "data",
              "cssSelector": "body",
              "skipSelectors": "img,nav"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "4a9b5d5d-fc94-40b7-af0c-13d992bc1eb9",
      "name": "便签3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -300,
        -220
      ],
      "parameters": {
        "width": 1071.752021563343,
        "height": 285.66037735849045,
        "content": "## 抓取最新的 Paul Graham 文章"
      },
      "typeVersion": 1
    },
    {
      "id": "b8a7a288-186f-4444-b0de-33ed90009c0a",
      "name": "便签5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        820,
        -220
      ],
      "parameters": {
        "width": 625,
        "height": 607,
        "content": "## 加载到 Milvus 向量存储"
      },
      "typeVersion": 1
    },
    {
      "id": "c9e7b166-cc65-47e2-a437-9c00017b492a",
      "name": "递归字符文本分割器1",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1240,
        240
      ],
      "parameters": {
        "options": {},
        "chunkSize": 6000
      },
      "typeVersion": 1
    },
    {
      "id": "e1a75f27-7c8c-4d0d-9b0f-33fe9ec96fc6",
      "name": "生成响应",
      "type": "n8n-nodes-base.set",
      "position": [
        1240,
        560
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "11396286-0378-4c3a-86e1-c9ef51afbfc7",
              "name": "text",
              "type": "string",
              "value": "={{ $json.answer }} {{ $if(!$json.citations.isEmpty(), \"\\n\" + $json.citations.join(\"\"), '') }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "8b3497ad-5bc8-44b3-bdf4-3a028fe265ce",
      "name": "组合引用",
      "type": "n8n-nodes-base.set",
      "position": [
        1040,
        560
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "ace6185e-8b3d-4f89-ae36-dfe0c391a0a9",
              "name": "citations",
              "type": "array",
              "value": "={{ $json.citations.map(i => '[' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata.file_name + ', lines ' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata['loc.lines.from'] + '-' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata['loc.lines.to'] + ']') }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "0452cf15-145c-49dd-8803-4c8b8a7adbea",
      "name": "基于块回答查询",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
        680,
        560
      ],
      "parameters": {
        "text": "={{ $json.context }}\n\nQuestion: {{ $('When chat message received').first().json.chatInput }}\nHelpful Answer:",
        "options": {
          "systemPromptTemplate": "=Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer. Important: In your response, also include the the indexes of the chunks you used to generate the answer."
        },
        "schemaType": "manual",
        "inputSchema": "{\n  \"type\": \"object\",\n  \"required\": [\"answer\", \"citations\"],\n  \"properties\": {\n    \"answer\": {\n      \"type\": \"string\"\n    },\n    \"citations\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"number\"\n      }\n    }\n  }\n}"
      },
      "typeVersion": 1
    },
    {
      "id": "d385ac35-6f94-4101-99de-5ce1991f40c4",
      "name": "准备块",
      "type": "n8n-nodes-base.code",
      "position": [
        480,
        560
      ],
      "parameters": {
        "jsCode": "let out = \"\"\nfor (const i in $input.all()) {\n  let itemText = \"--- CHUNK \" + i + \" ---\\n\"\n  itemText += $input.all()[i].json.document.pageContent + \"\\n\"\n  itemText += \"\\n\"\n  out += itemText\n}\n\nreturn {\n  'context': out\n};"
      },
      "typeVersion": 2
    },
    {
      "id": "379837f2-4f96-43ff-8e87-722cbe6d652f",
      "name": "设置发送到模型的最大块数",
      "type": "n8n-nodes-base.set",
      "position": [
        -300,
        560
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "33f4addf-72f3-4618-a6ba-5b762257d723",
              "name": "chunks",
              "type": "number",
              "value": 4
            }
          ]
        },
        "includeOtherFields": true
      },
      "typeVersion": 3.4
    },
    {
      "id": "9bc391bb-df47-41df-b170-9df47a6b5e87",
      "name": "嵌入 OpenAI2",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        -100,
        780
      ],
      "parameters": {
        "model": "text-embedding-ada-002",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "hH2PTDH4fbS7fdPv",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "efb030f4-445b-4ba0-b5c9-95e4e5893664",
      "name": "当收到聊天消息时",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -540,
        560
      ],
      "webhookId": "cd2703a7-f912-46fe-8787-3fb83ea116ab",
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "c74943be-0008-4d4c-9dea-598a648a97a2",
      "name": "便签1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -380,
        440
      ],
      "parameters": {
        "color": 7,
        "width": 1594,
        "height": 529,
        "content": "确保您的表名与实际知识库结构匹配"
      },
      "typeVersion": 1
    },
    {
      "id": "2e27f3d8-e8a2-4647-80dd-f2643b224cb5",
      "name": "检索中的 Milvus 向量存储",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreMilvus",
      "position": [
        0,
        560
      ],
      "parameters": {
        "mode": "load",
        "topK": 2,
        "prompt": "answer the question",
        "milvusCollection": {
          "__rl": true,
          "mode": "list",
          "value": "my_collection",
          "cachedResultName": "my_collection"
        }
      },
      "credentials": {
        "milvusApi": {
          "id": "8tMHHoLiWXIAXa7S",
          "name": "Milvus account"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "a3cf7e0e-f681-4880-9ccf-5c42d5457c0f",
      "name": "Milvus 向量存储",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreMilvus",
      "position": [
        1120,
        -100
      ],
      "parameters": {
        "mode": "insert",
        "options": {
          "clearCollection": true
        },
        "milvusCollection": {
          "__rl": true,
          "mode": "list",
          "value": "my_collection",
          "cachedResultName": "my_collection"
        }
      },
      "credentials": {
        "milvusApi": {
          "id": "8tMHHoLiWXIAXa7S",
          "name": "Milvus account"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "4c4cc5a5-e880-466f-a298-4af53a2acbec",
      "name": "便签",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -700,
        -260
      ],
      "parameters": {
        "width": 280,
        "height": 180,
        "content": "## 步骤 1"
      },
      "typeVersion": 1
    },
    {
      "id": "18f42da4-42ea-4eb0-9c43-ef8bd31ab7ff",
      "name": "便签2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -680,
        460
      ],
      "parameters": {
        "height": 120,
        "content": "## Step 2\nChat and get citations in response"
      },
      "typeVersion": 1
    },
    {
      "id": "0af427ed-d901-4192-9fdc-986a63fd585b",
      "name": "Embeddings OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        1020,
        140
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "hH2PTDH4fbS7fdPv",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "3603852a-bf12-4289-9733-dcd29d12a4f6",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        1160,
        120
      ],
      "parameters": {
        "options": {},
        "jsonData": "={{ $('Extract Text Only').item.json.data }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "b49eb3ae-82cb-4d87-8f22-0789b3a14d83",
      "name": "OpenAI 聊天模型",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        680,
        780
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "hH2PTDH4fbS7fdPv",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "5dc48a1d-aaf0-4052-9666-28f9e76d198c",
  "connections": {
    "d385ac35-6f94-4101-99de-5ce1991f40c4": {
      "main": [
        [
          {
            "node": "0452cf15-145c-49dd-8803-4c8b8a7adbea",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "b6993775-d21b-4ae8-a59c-43aef2b7002b": {
      "main": [
        [
          {
            "node": "cbaeb236-5c93-4b34-a06b-ff0e5de8525f",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "c4fa74ea-6af5-410c-bf5c-9d8d3decf31b": {
      "main": [
        [
          {
            "node": "d16ba71b-10fc-454f-8bfc-a6826280a4e7",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "8b3497ad-5bc8-44b3-bdf4-3a028fe265ce": {
      "main": [
        [
          {
            "node": "e1a75f27-7c8c-4d0d-9b0f-33fe9ec96fc6",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "0af427ed-d901-4192-9fdc-986a63fd585b": {
      "ai_embedding": [
        [
          {
            "node": "a3cf7e0e-f681-4880-9ccf-5c42d5457c0f",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "3da8495b-62df-475d-b99d-e0f3c64266e3": {
      "main": [
        [
          {
            "node": "a3cf7e0e-f681-4880-9ccf-5c42d5457c0f",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "d16ba71b-10fc-454f-8bfc-a6826280a4e7": {
      "main": [
        [
          {
            "node": "3da8495b-62df-475d-b99d-e0f3c64266e3",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "b49eb3ae-82cb-4d87-8f22-0789b3a14d83": {
      "ai_languageModel": [
        [
          {
            "node": "0452cf15-145c-49dd-8803-4c8b8a7adbea",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "9bc391bb-df47-41df-b170-9df47a6b5e87": {
      "ai_embedding": [
        [
          {
            "node": "2e27f3d8-e8a2-4647-80dd-f2643b224cb5",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "3603852a-bf12-4289-9733-dcd29d12a4f6": {
      "ai_document": [
        [
          {
            "node": "a3cf7e0e-f681-4880-9ccf-5c42d5457c0f",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "cbaeb236-5c93-4b34-a06b-ff0e5de8525f": {
      "main": [
        [
          {
            "node": "d92b6692-4a02-4519-b113-8a9172c71de9",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "d92b6692-4a02-4519-b113-8a9172c71de9": {
      "main": [
        [
          {
            "node": "c4fa74ea-6af5-410c-bf5c-9d8d3decf31b",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "379837f2-4f96-43ff-8e87-722cbe6d652f": {
      "main": [
        [
          {
            "node": "2e27f3d8-e8a2-4647-80dd-f2643b224cb5",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "0452cf15-145c-49dd-8803-4c8b8a7adbea": {
      "main": [
        [
          {
            "node": "8b3497ad-5bc8-44b3-bdf4-3a028fe265ce",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "2e27f3d8-e8a2-4647-80dd-f2643b224cb5": {
      "main": [
        [
          {
            "node": "d385ac35-6f94-4101-99de-5ce1991f40c4",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "52044ccd-4e0d-4353-b612-cf8db1b55331": {
      "main": [
        [
          {
            "node": "b6993775-d21b-4ae8-a59c-43aef2b7002b",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "c9e7b166-cc65-47e2-a437-9c00017b492a": {
      "ai_textSplitter": [
        [
          {
            "node": "3603852a-bf12-4289-9733-dcd29d12a4f6",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    }
  }
}
常见问题

如何使用这个工作流？

复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。

这个工作流适合什么场景？

高级 - 人工智能

需要付费吗？

本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。

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144 节点Jay Emp0
内容创作
工作流信息
难度等级
高级
节点数量25
分类1
节点类型15
难度说明

适合高级用户，包含 16+ 个节点的复杂工作流

作者
Cheney Zhang

Cheney Zhang

@zc277584121

Algorithm engineer at Zilliz, dedicating to the application of vector databases in the AI ecosystem.

外部链接
在 n8n.io 查看 →

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分类

多模态 AI
1540
人工智能
1108
内容创作
695
AI 摘要总结
516
营销
419
AI 聊天机器人
251
工程
241
市场调研
203
杂项
193
其他
176
销售
162
IT 运维
156
文档提取
147
AI RAG 检索增强
146
构建模块
144
社交媒体
137
潜在客户开发
125
个人效率
117
开发运维
111
人力资源
101
客户支持
97
客户培育
87
客户关系管理
82
财务
81
产品
77
客服机器人
76
设计
70
工单管理
67
安全运维
57
发票处理
53
加密货币交易
49
文件管理
39
项目管理
35
内部知识库
32

分类: 34