使用GraphRAG与PDF/MD/文本文件对话（无需向量存储）
高级
这是一个Support, AI领域的自动化工作流，包含 20 个节点。主要使用 Set, Switch, GoogleDrive, HttpRequest, ManualTrigger 等节点，结合人工智能技术实现智能自动化。 使用GraphRAG与PDF/MD/文本文件对话（无需向量存储）
前置要求
- •Google Drive API 凭证
- •可能需要目标 API 的认证凭证
- •OpenAI API Key
使用的节点 (20)
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": "EQVZKxcCDzTNXLRp",
"meta": {
"instanceId": "2a26454b0172ffcb8d70ba77c235b1209f92cd71bf06c79ba609c7173b416d68",
"templateCredsSetupCompleted": true
},
"name": "Chat with PDF / MD / Text Files using GraphRAG (no vector store needed)",
"tags": [
{
"id": "66wgFoDi9Xjl74M3",
"name": "Support",
"createdAt": "2025-05-21T17:06:32.355Z",
"updatedAt": "2025-05-21T17:06:32.355Z"
},
{
"id": "kRM0hQV2zw7VxrON",
"name": "Research",
"createdAt": "2025-05-21T19:44:19.136Z",
"updatedAt": "2025-05-21T19:44:19.136Z"
},
{
"id": "sJk9cUvmMU8FkJXv",
"name": "AI",
"createdAt": "2025-05-20T13:16:15.636Z",
"updatedAt": "2025-05-20T13:16:15.636Z"
}
],
"nodes": [
{
"id": "011910a9-c2a0-49eb-b1eb-8043e0c2accc",
"name": "Search Google Drive",
"type": "n8n-nodes-base.googleDrive",
"position": [
-220,
-120
],
"parameters": {
"filter": {
"folderId": {
"__rl": true,
"mode": "list",
"value": "13tqp0SaI_v4jG1CFLAZo96isx-UBno4v",
"cachedResultUrl": "https://drive.google.com/drive/folders/13tqp0SaI_v4jG1CFLAZo96isx-UBno4v",
"cachedResultName": "GraphRAG"
}
},
"options": {},
"resource": "fileFolder",
"returnAll": true,
"queryString": "*"
},
"credentials": {
"googleDriveOAuth2Api": {
"id": "oz9iNMxcuQ2pxr1e",
"name": "Google Drive account"
}
},
"typeVersion": 3
},
{
"id": "22872ac5-14e4-4ea7-b792-30e19a02cb88",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
260,
-120
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "6456b7ac-f936-425a-a0ac-62fe118e985a",
"name": "Retrieve File",
"type": "n8n-nodes-base.googleDrive",
"position": [
500,
-80
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"id": "oz9iNMxcuQ2pxr1e",
"name": "Google Drive account"
}
},
"typeVersion": 3
},
{
"id": "8c1f2da9-fff4-457d-bc2e-7c84de3500b3",
"name": "Switch",
"type": "n8n-nodes-base.switch",
"position": [
740,
-20
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "pdf",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7b4e792b-ab6d-4b9b-88a1-d8e51bea6853",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "application/pdf"
}
]
},
"renameOutput": true
},
{
"outputKey": "text",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "09b7d7c5-5353-4719-b4e2-072e4da39948",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "text/plain"
}
]
},
"renameOutput": true
},
{
"outputKey": "md",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "cb2e6726-97d8-4541-8383-deafff9b18e6",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "text/markdown"
}
]
},
"renameOutput": true
},
{
"outputKey": "json",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "d2763a45-a592-47c8-868f-59dfcd17a71c",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "application/json"
}
]
},
"renameOutput": true
},
{
"outputKey": "docs",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0d9b561f-89c5-479e-a4e2-1f5f05fa8417",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": ""
}
]
},
"renameOutput": true
},
{
"outputKey": "csv",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "6b19deed-5d00-4796-bb9d-b4d87564a751",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{$binary[\"data\"].mimeType}}",
"rightValue": "csv"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "fe133ad7-bd7a-43e2-91a7-4b3dd2652490",
"name": "Extract from PDF",
"type": "n8n-nodes-base.extractFromFile",
"position": [
1020,
-240
],
"parameters": {
"options": {},
"operation": "pdf"
},
"typeVersion": 1
},
{
"id": "49f89141-a8ea-46c6-888d-cf9dafcc7c2a",
"name": "Extract from Text File",
"type": "n8n-nodes-base.extractFromFile",
"position": [
1020,
-60
],
"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1
},
{
"id": "a47d8f07-917e-44ed-a69e-5d6085981d36",
"name": "Extract from Markdown",
"type": "n8n-nodes-base.extractFromFile",
"position": [
1020,
140
],
"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1
},
{
"id": "a2298650-5408-45f8-accf-292ac669002a",
"name": "InfraNodus Save to Graph",
"type": "n8n-nodes-base.httpRequest",
"position": [
1480,
200
],
"parameters": {
"url": "https://infranodus.com/api/v1/graphAndStatements?doNotSave=false&includeGraph=false&includeGraphSummary=true&includeGraph=false",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "name",
"value": "graphrag_from_google_drive"
},
{
"name": "text",
"value": "={{ $json.data }}"
},
{
"name": "=categories",
"value": "=[filename: {{ $('Switch').item.json.name }}]"
},
{
"name": "contextSettings",
"value": "={{{ \"squareBracketsProcessing\":\"IGNORE_BRACKETS\"} }}"
}
]
},
"genericAuthType": "httpBearerAuth"
},
"credentials": {
"httpBearerAuth": {
"id": "FPDx6PA5CtzGEIQc",
"name": "InfraNodus DeeMeeTree API Key"
}
},
"typeVersion": 4.2
},
{
"id": "bb06d60a-01c7-4a1e-bc7a-901e1f7f175d",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
-480
],
"parameters": {
"color": 4,
"width": 2200,
"height": 980,
"content": "# Step 1: Upload Your PDF / MD / Text Files to InfraNodus GraphRAG\n\n## Copy your PDF files to a Google drive and then upload them to your InfraNodus knowledge graph\n\n### InfraNodus visualizes your text as a knowledge graph, showing the main topics and ideas inside. It also provides API access to the knowledge graph, so you can use it as a knowledge base instead of the complex vector store setup\n\n1. You need an [InfraNodus](https://infranodus.com) account to use this workflow. Get the API key at [https://infranodus.com/api-access](https://infranodus.com/api-access)\n2. Also, specify the **name of the graph** you want to save the files to in the InfraNodus HTTP node\n3. When the workflow finishes running, you can get a visualization of your knowledge base at [https://infranodus.com/your_user_name/your_graph_name/edit](https://infranodus.com/your_user_name/your_graph_name/edit)\n\n\n"
},
"typeVersion": 1
},
{
"id": "38707a4d-b397-43e7-b55c-da18a00bb480",
"name": "Map PDF to Text",
"type": "n8n-nodes-base.set",
"position": [
1320,
-100
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "fd160009-0b92-46fc-9e34-a1283b810e91",
"name": "data",
"type": "string",
"value": "={{ $json.text }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "49426e56-7d6c-4dc0-a279-348dea59cca2",
"name": "Convert File to PDF",
"type": "n8n-nodes-base.httpRequest",
"disabled": true,
"position": [
1720,
200
],
"parameters": {
"url": "https://v2.convertapi.com/convert/pdf/to/txt",
"method": "POST",
"options": {
"response": {
"response": {
"responseFormat": "text"
}
}
},
"sendBody": true,
"contentType": "multipart-form-data",
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "file",
"parameterType": "formBinaryData",
"inputDataFieldName": "data"
}
]
},
"genericAuthType": "httpBearerAuth",
"headerParameters": {
"parameters": [
{
"name": "Accept",
"value": "application/octet-stream"
}
]
}
},
"credentials": {
"httpBearerAuth": {
"id": "mDxLoJUWSmuTJsAC",
"name": "ConvertAPI"
}
},
"notesInFlow": true,
"typeVersion": 4.2
},
{
"id": "5d21b250-7b0f-4925-a858-5aa6badf5700",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1680,
-340
],
"parameters": {
"color": 2,
"width": 360,
"height": 840,
"content": "## Optional: Better PDF Conversion\n\n### Standard Map PDF to Text node will split your PDF files into very short chunks, which deteriorates retrieval. \n\nUse can use [ConvertAPI](https://convertapi.com?ref=4l54n) which is a high-quality convertor that will respect the layout of the original document and not cut the paragraphs into short chunks. \n\nHere is an HTTP node that makes a request to their API to convert the PDF into text. If you have a ConvertAPI account, you can replace the \"Map PDF to Text\" node in step 4 with this node. \n"
},
"typeVersion": 1
},
{
"id": "ceda9ea4-963b-4ffb-a741-6e7eb3fc7411",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"disabled": true,
"position": [
-520,
840
],
"webhookId": "a2cfd3b0-aaa4-4003-940d-e520e64830c6",
"parameters": {
"public": true,
"options": {
"title": "Talk to PDFs"
},
"initialMessages": "=Ask any question about the PDFs or write `/question` to generate an interesting question to discuss."
},
"typeVersion": 1.1
},
{
"id": "d78cf21e-753b-44d3-a2b4-493f85aa5129",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-240,
840
],
"parameters": {
"options": {
"systemMessage": "You provide information about the topic of user's interest. Always use the knowledge base attached to get the final response. "
}
},
"typeVersion": 1.9
},
{
"id": "02497c8b-89d6-4440-bc4d-d3906b9c4872",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-420,
1100
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "07wFa8Wa4mMRCHAj",
"name": "OpenAi account 2"
}
},
"typeVersion": 1.2
},
{
"id": "6d77fb59-fb03-4d22-ac40-4cf9bde25909",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
-260,
1100
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "978c8309-380d-4fc8-b238-e0d0148b77b9",
"name": "Knowledge Base GraphRAG",
"type": "n8n-nodes-base.httpRequestTool",
"position": [
100,
1060
],
"parameters": {
"url": "https://infranodus.com/api/v1/graphAndAdvice?doNotSave=true&addStats=true&optimize=develop&includeStatements=true&includeGraphSummary=true&includeGraph=false",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "name",
"value": "graphrag_from_google_drive"
},
{
"name": "requestMode",
"value": "response"
},
{
"name": "prompt",
"value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('parameters2_Value', `User query to send to the expert`, 'string') }}"
},
{
"name": "aiTopics",
"value": "true"
}
]
},
"genericAuthType": "httpBearerAuth",
"toolDescription": "You contain knowledge on the topic of user's interst"
},
"credentials": {
"httpBearerAuth": {
"id": "6lSuuSDajZrvI2GM",
"name": "InfraNodus API Key"
}
},
"typeVersion": 4.2
},
{
"id": "b005f83d-3d4a-42c8-b70a-63e267747fcd",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-560,
540
],
"parameters": {
"width": 2200,
"height": 700,
"content": "# Step 2: Chat with your PDF / MD / Text Files using [InfraNodus](https://infranodus.com) Graph RAG Knowledge Base\n\n## InfraNodus is used instead of the vector store. It combines traditional RAG and GraphRAG, providing a better topical overview of your knowledge base and having a better understanding of relations between entities in your documents.\n\n1. Deactivate the trigger node in Step 1 and activate the trigger Chat node here\n2. Provide your API key at [https://infranodus.com/api-access](https://infranodus.com/api-access) to the HTTP agent tool\n3. Specify the same **name of the graph** as in the Step 1, so you query the graph where saved the files. \n4. If you connect several knowledge bases, make sure to describe them well, so the agent knows what to query. Get the description from the InfraNodus Graph > Project Notes > RAG enhancement"
},
"typeVersion": 1
},
{
"id": "6a6ad150-670d-45d5-a69e-0bafaf8f2ac4",
"name": "Click ‘Test workflow’ to ingest the documents",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-500,
-120
],
"parameters": {},
"typeVersion": 1
},
{
"id": "0a148a3f-e898-4f83-9ebb-82da7f3f4633",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-540,
100
],
"parameters": {
"width": 680,
"height": 380,
"content": "## [InfraNodus](https://infranodus.com) Knowledege Graph Example\n\n"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "90ea1bad-6d21-4f20-81b4-0ba48cc7e7fa",
"connections": {
"8c1f2da9-fff4-457d-bc2e-7c84de3500b3": {
"main": [
[
{
"node": "fe133ad7-bd7a-43e2-91a7-4b3dd2652490",
"type": "main",
"index": 0
}
],
[
{
"node": "49f89141-a8ea-46c6-888d-cf9dafcc7c2a",
"type": "main",
"index": 0
}
],
[
{
"node": "a47d8f07-917e-44ed-a69e-5d6085981d36",
"type": "main",
"index": 0
}
],
[],
[]
]
},
"6456b7ac-f936-425a-a0ac-62fe118e985a": {
"main": [
[
{
"node": "8c1f2da9-fff4-457d-bc2e-7c84de3500b3",
"type": "main",
"index": 0
}
]
]
},
"6d77fb59-fb03-4d22-ac40-4cf9bde25909": {
"ai_memory": [
[
{
"node": "d78cf21e-753b-44d3-a2b4-493f85aa5129",
"type": "ai_memory",
"index": 0
}
]
]
},
"22872ac5-14e4-4ea7-b792-30e19a02cb88": {
"main": [
[],
[
{
"node": "6456b7ac-f936-425a-a0ac-62fe118e985a",
"type": "main",
"index": 0
}
]
]
},
"38707a4d-b397-43e7-b55c-da18a00bb480": {
"main": [
[
{
"node": "a2298650-5408-45f8-accf-292ac669002a",
"type": "main",
"index": 0
}
]
]
},
"fe133ad7-bd7a-43e2-91a7-4b3dd2652490": {
"main": [
[
{
"node": "38707a4d-b397-43e7-b55c-da18a00bb480",
"type": "main",
"index": 0
}
]
]
},
"02497c8b-89d6-4440-bc4d-d3906b9c4872": {
"ai_languageModel": [
[
{
"node": "d78cf21e-753b-44d3-a2b4-493f85aa5129",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"011910a9-c2a0-49eb-b1eb-8043e0c2accc": {
"main": [
[
{
"node": "22872ac5-14e4-4ea7-b792-30e19a02cb88",
"type": "main",
"index": 0
}
]
]
},
"a47d8f07-917e-44ed-a69e-5d6085981d36": {
"main": [
[
{
"node": "a2298650-5408-45f8-accf-292ac669002a",
"type": "main",
"index": 0
}
]
]
},
"49f89141-a8ea-46c6-888d-cf9dafcc7c2a": {
"main": [
[
{
"node": "a2298650-5408-45f8-accf-292ac669002a",
"type": "main",
"index": 0
}
]
]
},
"978c8309-380d-4fc8-b238-e0d0148b77b9": {
"ai_tool": [
[
{
"node": "d78cf21e-753b-44d3-a2b4-493f85aa5129",
"type": "ai_tool",
"index": 0
}
]
]
},
"a2298650-5408-45f8-accf-292ac669002a": {
"main": [
[
{
"node": "22872ac5-14e4-4ea7-b792-30e19a02cb88",
"type": "main",
"index": 0
}
]
]
},
"ceda9ea4-963b-4ffb-a741-6e7eb3fc7411": {
"main": [
[
{
"node": "d78cf21e-753b-44d3-a2b4-493f85aa5129",
"type": "main",
"index": 0
}
]
]
},
"6a6ad150-670d-45d5-a69e-0bafaf8f2ac4": {
"main": [
[
{
"node": "011910a9-c2a0-49eb-b1eb-8043e0c2accc",
"type": "main",
"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 - 客户支持, 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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129 节点Kumar Shivam
客户支持
Google Drive文件摄取至Supabase知识库
基于Supabase RAG和GPT-4o-mini的交互式知识库聊天
If
Set
Gmail
+
If
Set
Gmail
46 节点Immanuel
客户支持
AI Chatbot Agent：使用 InfraNodus 图 RAG 知识的专家小组
采用InfraNodus GraphRAG知识图谱技术的专家小组AI聊天机器人代理
Agent
Http Request Tool
Chat Trigger
+
Agent
Http Request Tool
Chat Trigger
14 节点InfraNodus
客户支持
AI驱动的RAG文档处理与聊天机器人 - Google Drive、Supabase、OpenAI
基于Google Drive、Supabase和OpenAI的AI驱动RAG文档处理与聊天机器人
Set
Code
Limit
+
Set
Code
Limit
35 节点Billy Christi
人工智能
工作流信息
难度等级
高级
节点数量20
分类2
节点类型13
作者
InfraNodus
@infranodusI'm Dmitry, the founder of InfraNodus — an AI text network analysis tool. I'm passionate about networks and data visualization and its ability to reveal what everyone else is missing and to highlight different perspectives. I'm sharing the n8n templates that make use of this unique capability of InfraNodus for multiple scenarios.
外部链接
在 n8n.io 查看 →
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