插入和检索文档
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)
分类
工作流预览
可视化展示节点连接关系，支持缩放和平移
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": {
"Prepare chunks": {
"main": [
[
{
"node": "Answer the query based on chunks",
"type": "main",
"index": 0
}
]
]
},
"Fetch Essay List": {
"main": [
[
{
"node": "Extract essay names",
"type": "main",
"index": 0
}
]
]
},
"Limit to first 3": {
"main": [
[
{
"node": "Fetch essay texts",
"type": "main",
"index": 0
}
]
]
},
"Compose citations": {
"main": [
[
{
"node": "Generate response",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Milvus Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Extract Text Only": {
"main": [
[
{
"node": "Milvus Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Fetch essay texts": {
"main": [
[
{
"node": "Extract Text Only",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Answer the query based on chunks",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings OpenAI2": {
"ai_embedding": [
[
{
"node": "Milvus Vector Store in retrieval",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Milvus Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Extract essay names": {
"main": [
[
{
"node": "Split out into items",
"type": "main",
"index": 0
}
]
]
},
"Split out into items": {
"main": [
[
{
"node": "Limit to first 3",
"type": "main",
"index": 0
}
]
]
},
"Set max chunks to send to model": {
"main": [
[
{
"node": "Milvus Vector Store in retrieval",
"type": "main",
"index": 0
}
]
]
},
"Answer the query based on chunks": {
"main": [
[
{
"node": "Compose citations",
"type": "main",
"index": 0
}
]
]
},
"Milvus Vector Store in retrieval": {
"main": [
[
{
"node": "Prepare chunks",
"type": "main",
"index": 0
}
]
]
},
"When clicking \"Execute Workflow\"": {
"main": [
[
{
"node": "Fetch Essay List",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter1": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"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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工作流信息
难度等级
高级
节点数量25
分类1
节点类型15
作者
Cheney Zhang
@zc277584121Algorithm 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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