n8n 本地AI代理RAG模板
高级
这是一个Internal Wiki, AI RAG领域的自动化工作流，包含 41 个节点。主要使用 Set, Switch, Webhook, Postgres, Aggregate 等节点。 使用Ollama AI、智能RAG代理和PGVector的本地文档问答系统
前置要求
- •HTTP Webhook 端点（n8n 会自动生成）
- •PostgreSQL 数据库连接信息
- •OpenAI API Key
使用的节点 (41)
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": "dlA7uMt2f1hTW3xd",
"meta": {
"instanceId": "8cf060ebda3ec45b5ebb6a30779eaf0c03dfba83865feab3f32adb31b82caa08"
},
"name": "n8n 本地AI代理RAG模板",
"tags": [],
"nodes": [
{
"id": "397d00eb-8034-49e5-a8f6-0a0fd9b97d5b",
"name": "默认数据加载器",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
3312,
1280
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "=file_id",
"value": "={{ $('Set File ID').first().json.file_id }}"
},
{
"name": "file_title",
"value": "={{ $('Set File ID').first().json.file_title }}"
}
]
}
},
"jsonData": "={{ $json.data || $json.text || $json.concatenated_data }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "e57065a2-9087-48e9-839e-d9c5c5fb477f",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
2304,
144
],
"parameters": {
"color": 4,
"width": 583.4552380860637,
"height": 528.85546469693,
"content": "## RAG的代理工具"
},
"typeVersion": 1
},
{
"id": "f7efaf27-78fb-4429-beba-74ffcc700342",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
560,
688
],
"parameters": {
"color": 5,
"width": 3073,
"height": 867,
"content": "## 将Google Drive文件添加到向量数据库的工具"
},
"typeVersion": 1
},
{
"id": "a137d00b-fb01-408c-9963-645e2beb44d9",
"name": "提取文档文本",
"type": "n8n-nodes-base.extractFromFile",
"position": [
2512,
1280
],
"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "1aec304d-7264-4e65-8654-cb9294c96c82",
"name": "Postgres 聊天记忆",
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"position": [
1712,
512
],
"parameters": {},
"notesInFlow": false,
"typeVersion": 1
},
{
"id": "9c407f2b-4f6a-46d6-a607-225c1c628ae5",
"name": "设置文件ID",
"type": "n8n-nodes-base.set",
"position": [
992,
960
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "10646eae-ae46-4327-a4dc-9987c2d76173",
"name": "file_id",
"type": "string",
"value": "={{ $json.path }}"
},
{
"id": "f4536df5-d0b1-4392-bf17-b8137fb31a44",
"name": "file_type",
"type": "string",
"value": "={{ $json.path.split(/[\\\\/]/).pop().split('.').pop(); }}"
},
{
"id": "77d782de-169d-4a46-8a8e-a3831c04d90f",
"name": "file_title",
"type": "string",
"value": "={{ $json.path.split(/[\\\\/]/).pop().split('.').slice(0, -1).join('.'); }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "bc93aa94-10ec-4670-99f4-3bcec36be1ce",
"name": "便签2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1264,
208
],
"parameters": {
"width": 1035.6381264595484,
"height": 464.8027193303974,
"content": "## 带聊天界面的RAG AI代理"
},
"typeVersion": 1
},
{
"id": "8ccc451e-2fac-49b0-8700-085476add599",
"name": "响应Webhook",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
2128,
288
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "55abb8ac-7988-430a-ae41-5155471228a2",
"name": "编辑字段",
"type": "n8n-nodes-base.set",
"position": [
1568,
288
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9a9a245e-f1a1-4282-bb02-a81ffe629f0f",
"name": "chatInput",
"type": "string",
"value": "={{ $json?.chatInput || $json.body.chatInput }}"
},
{
"id": "b80831d8-c653-4203-8706-adedfdb98f77",
"name": "sessionId",
"type": "string",
"value": "={{ $json?.sessionId || $json.body.sessionId}}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "78b3fd17-23e9-4693-b782-918a5a8e5aed",
"name": "当收到聊天消息时",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
1312,
288
],
"webhookId": "e104e40e-6134-4825-a6f0-8a646d882662",
"parameters": {
"public": true,
"options": {}
},
"typeVersion": 1.1
},
{
"id": "06e362d1-d20c-407a-a75a-ed175c07439d",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
1312,
480
],
"webhookId": "bf4dd093-bb02-472c-9454-7ab9af97bd1d",
"parameters": {
"path": "bf4dd093-bb02-472c-9454-7ab9af97bd1d",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2
},
{
"id": "e8ba5c17-3426-4d76-b69b-ff91dff7958f",
"name": "提取PDF文本",
"type": "n8n-nodes-base.extractFromFile",
"position": [
2512,
720
],
"parameters": {
"options": {},
"operation": "pdf"
},
"typeVersion": 1
},
{
"id": "b40eb123-d7fc-4799-b248-4b9516aee49e",
"name": "聚合",
"type": "n8n-nodes-base.aggregate",
"position": [
2544,
912
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "0e3755e8-9532-447f-9137-f65d542c247e",
"name": "总结",
"type": "n8n-nodes-base.summarize",
"position": [
2752,
992
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "data",
"aggregation": "concatenate"
}
]
}
},
"typeVersion": 1
},
{
"id": "b185f2be-06bf-4a14-8d58-4b411a709f18",
"name": "RAG AI 智能体",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1792,
288
],
"parameters": {
"text": "={{ $json.chatInput }}",
"options": {
"systemMessage": "You are a personal assistant who helps answer questions from a corpus of documents. The documents are either text based (Txt, docs, extracted PDFs, etc.) or tabular data (CSVs or Excel documents).\n\nYou are given tools to perform RAG in the 'documents' table, look up the documents available in your knowledge base in the 'document_metadata' table, extract all the text from a given document, and query the tabular files with SQL in the 'document_rows' table.\n\nAlways start by performing RAG unless the users asks you to check a document or the question requires a SQL query for tabular data (fetching a sum, finding a max, something a RAG lookup would be unreliable for). If RAG doesn't help, then look at the documents that are available to you, find a few that you think would contain the answer, and then analyze those.\n\nAlways tell the user if you didn't find the answer. Don't make something up just to please them."
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "2ee45951-3553-49b7-9f79-3cef3d065e8a",
"name": "Switch",
"type": "n8n-nodes-base.switch",
"position": [
1840,
944
],
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Set File ID').item.json.file_type }}",
"rightValue": "pdf"
}
]
}
},
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "2ae7faa7-a936-4621-a680-60c512163034",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Set File ID').item.json.file_type }}",
"rightValue": "xlsx"
}
]
}
},
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fc193b06-363b-4699-a97d-e5a850138b0e",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Set File ID').item.json.file_type }}",
"rightValue": "=csv"
}
]
}
},
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b69f5605-0179-4b02-9a32-e34bb085f82d",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Set File ID').item.json.file_type }}",
"rightValue": "txt"
}
]
}
}
]
},
"options": {
"fallbackOutput": 3
}
},
"typeVersion": 3
},
{
"id": "20bf7dde-e073-4288-a9d6-34df3973b5c3",
"name": "从Excel提取",
"type": "n8n-nodes-base.extractFromFile",
"position": [
2320,
912
],
"parameters": {
"options": {},
"operation": "xlsx"
},
"typeVersion": 1
},
{
"id": "f1840995-3f1c-4f4e-9d78-bc9225ecbe2b",
"name": "设置模式",
"type": "n8n-nodes-base.set",
"position": [
3184,
848
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "f422e2e0-381c-46ea-8f38-3f58c501d8b9",
"name": "schema",
"type": "string",
"value": "={{ $('Extract from Excel').isExecuted ? $('Extract from Excel').first().json.keys().toJsonString() : $('Extract from CSV').first().json.keys().toJsonString() }}"
},
{
"id": "bb07c71e-5b60-4795-864c-cc3845b6bc46",
"name": "data",
"type": "string",
"value": "={{ $json.concatenated_data }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "b79ceb0b-f370-4ffb-9953-14b411acb5d9",
"name": "从CSV提取",
"type": "n8n-nodes-base.extractFromFile",
"position": [
2320,
1088
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "7067874e-4123-4a6c-a94d-89e4d1878309",
"name": "便签3",
"type": "n8n-nodes-base.stickyNote",
"position": [
560,
368
],
"parameters": {
"color": 3,
"width": 680,
"height": 300,
"content": "## 运行每个节点一次以设置数据库表"
},
"typeVersion": 1
},
{
"id": "130c53e8-d507-4b6f-b1cf-f79dbc571c46",
"name": "创建文档元数据表",
"type": "n8n-nodes-base.postgres",
"position": [
688,
464
],
"parameters": {
"query": "CREATE TABLE document_metadata (\n id TEXT PRIMARY KEY,\n title TEXT,\n created_at TIMESTAMP DEFAULT NOW(),\n schema TEXT\n);",
"options": {},
"operation": "executeQuery"
},
"typeVersion": 2.5
},
{
"id": "421d2123-b68a-4c51-a482-db5bdffd3f76",
"name": "创建文档行表（用于表格数据）",
"type": "n8n-nodes-base.postgres",
"position": [
992,
464
],
"parameters": {
"query": "CREATE TABLE document_rows (\n id SERIAL PRIMARY KEY,\n dataset_id TEXT REFERENCES document_metadata(id),\n row_data JSONB -- Store the actual row data\n);",
"options": {},
"operation": "executeQuery"
},
"typeVersion": 2.5
},
{
"id": "55ff6535-bedb-479f-b3da-eb45e1127e77",
"name": "列出文档",
"type": "n8n-nodes-base.postgresTool",
"position": [
1840,
512
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "document_metadata",
"cachedResultName": "document_metadata"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"options": {},
"operation": "select",
"returnAll": true,
"descriptionType": "manual",
"toolDescription": "Use this tool to fetch all available documents, including the table schema if the file is a CSV or Excel file."
},
"typeVersion": 2.5
},
{
"id": "ffcb630b-5119-4ff6-b85a-d77eeb8d5713",
"name": "获取文件内容",
"type": "n8n-nodes-base.postgresTool",
"position": [
1984,
512
],
"parameters": {
"query": "SELECT \n string_agg(text, ' ') as document_text\nFROM documents_pg\n WHERE metadata->>'file_id' = $1\nGROUP BY metadata->>'file_id';",
"options": {
"queryReplacement": "={{ $fromAI('file_id') }}"
},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Given a file ID, fetches the text from the document."
},
"typeVersion": 2.5
},
{
"id": "f504b2f4-ffb5-4ef7-ba93-753151b77d9e",
"name": "查询文档行",
"type": "n8n-nodes-base.postgresTool",
"position": [
2144,
512
],
"parameters": {
"query": "{{ $fromAI('sql_query') }}",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Run a SQL query - use this to query from the document_rows table once you know the file ID (which is the file path) you are querying. dataset_id is the file_id (file path) and you are always using the row_data for filtering, which is a jsonb field that has all the keys from the file schema given in the document_metadata table.\n\nExample query:\n\nSELECT AVG((row_data->>'revenue')::numeric)\nFROM document_rows\nWHERE dataset_id = '/data/shared/document.csv';\n\nExample query 2:\n\nSELECT \n row_data->>'category' as category,\n SUM((row_data->>'sales')::numeric) as total_sales\nFROM dataset_rows\nWHERE dataset_id = '/data/shared/document2.csv'\nGROUP BY row_data->>'category';"
},
"typeVersion": 2.5
},
{
"id": "4abe03ca-297c-4509-b0db-7bed4338a158",
"name": "遍历项目",
"type": "n8n-nodes-base.splitInBatches",
"position": [
800,
800
],
"parameters": {
"options": {
"reset": false
}
},
"typeVersion": 3
},
{
"id": "e382d750-85ba-492d-9d3e-eb839af0bfc1",
"name": "插入文档元数据",
"type": "n8n-nodes-base.postgres",
"position": [
1488,
832
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "document_metadata",
"cachedResultName": "document_metadata"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"value": {
"id": "={{ $('Set File ID').item.json.file_id }}",
"title": "={{ $('Set File ID').item.json.file_title }}"
},
"schema": [
{
"id": "id",
"type": "string",
"display": true,
"removed": false,
"required": true,
"displayName": "id",
"defaultMatch": true,
"canBeUsedToMatch": true
},
{
"id": "title",
"type": "string",
"display": true,
"required": false,
"displayName": "title",
"defaultMatch": false,
"canBeUsedToMatch": false
},
{
"id": "url",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "url",
"defaultMatch": false,
"canBeUsedToMatch": false
},
{
"id": "created_at",
"type": "dateTime",
"display": true,
"required": false,
"displayName": "created_at",
"defaultMatch": false,
"canBeUsedToMatch": false
},
{
"id": "schema",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "schema",
"defaultMatch": false,
"canBeUsedToMatch": false
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"id"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "upsert"
},
"executeOnce": true,
"typeVersion": 2.5
},
{
"id": "bbf6f704-b4a2-4ff2-ac09-27626526b35f",
"name": "插入表行",
"type": "n8n-nodes-base.postgres",
"position": [
2544,
1088
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "document_rows",
"cachedResultName": "document_rows"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"value": {
"row_data": "={{ $json.toJsonString().replaceAll(/'/g, \"''\") }}",
"dataset_id": "={{ $('Set File ID').item.json.file_id }}"
},
"schema": [
{
"id": "id",
"type": "number",
"display": true,
"removed": true,
"required": false,
"displayName": "id",
"defaultMatch": true,
"canBeUsedToMatch": true
},
{
"id": "dataset_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "dataset_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "row_data",
"type": "object",
"display": true,
"removed": false,
"required": false,
"displayName": "row_data",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"id"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"typeVersion": 2.5
},
{
"id": "3265a7df-dd40-421e-b1fb-53293a7460f8",
"name": "更新文档元数据模式",
"type": "n8n-nodes-base.postgres",
"position": [
3408,
848
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "document_metadata",
"cachedResultName": "document_metadata"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"value": {
"id": "={{ $('Set File ID').item.json.file_id }}",
"schema": "={{ $json.schema }}"
},
"schema": [
{
"id": "id",
"type": "string",
"display": true,
"removed": false,
"required": true,
"displayName": "id",
"defaultMatch": true,
"canBeUsedToMatch": true
},
{
"id": "title",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "title",
"defaultMatch": false,
"canBeUsedToMatch": false
},
{
"id": "url",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "url",
"defaultMatch": false,
"canBeUsedToMatch": false
},
{
"id": "created_at",
"type": "dateTime",
"display": true,
"required": false,
"displayName": "created_at",
"defaultMatch": false,
"canBeUsedToMatch": false
},
{
"id": "schema",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "schema",
"defaultMatch": false,
"canBeUsedToMatch": false
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"id"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "upsert"
},
"typeVersion": 2.5
},
{
"id": "53f9f045-bb08-4b22-a11e-dfd2c964b687",
"name": "便签9",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
0
],
"parameters": {
"color": 6,
"width": 540,
"height": 1320,
"content": "## 🚀 n8n 本地AI代理RAG模板"
},
"typeVersion": 1
},
{
"id": "cdee87fe-e154-47ab-9330-32dee5c213d3",
"name": "本地文件触发器",
"type": "n8n-nodes-base.localFileTrigger",
"position": [
608,
800
],
"parameters": {
"path": "/data/shared",
"events": [
"add",
"change"
],
"options": {
"usePolling": true,
"followSymlinks": true
},
"triggerOn": "folder"
},
"typeVersion": 1
},
{
"id": "67311475-7928-4ddc-957a-79817c98d26d",
"name": "从磁盘读取/写入文件",
"type": "n8n-nodes-base.readWriteFile",
"position": [
1648,
960
],
"parameters": {
"options": {
"dataPropertyName": "=data"
},
"fileSelector": "={{ $('Set File ID').item.json.file_id }}"
},
"typeVersion": 1
},
{
"id": "366e800a-9bd7-4822-a11c-f555800bbba6",
"name": "嵌入 Ollama",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"position": [
3072,
1280
],
"parameters": {
"model": "nomic-embed-text:latest"
},
"typeVersion": 1
},
{
"id": "be37cfb9-ea40-4244-87d7-b562be315573",
"name": "嵌入 Ollama1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"position": [
2560,
480
],
"parameters": {
"model": "nomic-embed-text:latest"
},
"typeVersion": 1
},
{
"id": "1306b972-2b24-4c62-846e-f1c5b3d0482c",
"name": "递归字符文本分割器",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
3200,
1408
],
"parameters": {
"options": {},
"chunkSize": 400
},
"typeVersion": 1
},
{
"id": "677ad468-8118-4f8f-9a47-f5429cdc7582",
"name": "Ollama（更改基础URL）",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1568,
512
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "qwen2.5:14b-8k",
"cachedResultName": "qwen2.5:14b-8k"
},
"options": {}
},
"typeVersion": 1.2
},
{
"id": "b3e23401-8868-4b3c-a3fe-37fda44419d5",
"name": "便签4",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
1344
],
"parameters": {
"color": 6,
"width": 540,
"height": 200,
"content": "## 注意"
},
"typeVersion": 1
},
{
"id": "987a6081-cdfd-457e-a2e5-4fa93fa018f4",
"name": "删除旧文档记录",
"type": "n8n-nodes-base.postgres",
"position": [
1168,
832
],
"parameters": {
"query": "DO $$\nBEGIN\n IF EXISTS (SELECT 1 FROM information_schema.tables WHERE table_name = 'documents_pg') THEN\n EXECUTE 'DELETE FROM documents_pg WHERE metadata->>''file_id'' LIKE ''%' || $1 || '%''';\n END IF;\nEND\n$$;",
"options": {
"queryReplacement": "={{ $json.file_id }}"
},
"operation": "executeQuery"
},
"typeVersion": 2.5
},
{
"id": "619a8a54-5fb8-4d8f-9cac-5a1c2a58f44b",
"name": "删除旧数据记录",
"type": "n8n-nodes-base.postgres",
"position": [
1328,
960
],
"parameters": {
"query": "DELETE FROM document_rows\nWHERE dataset_id LIKE '%' || $1 || '%';",
"options": {
"queryReplacement": "={{ $('Set File ID').item.json.file_id }}"
},
"operation": "executeQuery"
},
"typeVersion": 2.5
},
{
"id": "c975f943-3c05-45eb-9b11-4bd254845fbc",
"name": "Postgres PGVector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStorePGVector",
"position": [
3184,
1072
],
"parameters": {
"mode": "insert",
"options": {},
"tableName": "documents_pg"
},
"typeVersion": 1
},
{
"id": "9bba5830-ad14-454c-b653-48baf03844bb",
"name": "Postgres PGVector存储1",
"type": "@n8n/n8n-nodes-langchain.vectorStorePGVector",
"position": [
2464,
288
],
"parameters": {
"mode": "retrieve-as-tool",
"options": {},
"toolName": "documents",
"tableName": "documents_pg",
"toolDescription": "Use RAG to look up information in the knowledgebase."
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "43f092c7-957d-42d3-8ea5-26108c4cd991",
"connections": {
"Switch": {
"main": [
[
{
"node": "Extract PDF Text",
"type": "main",
"index": 0
}
],
[
{
"node": "Extract from Excel",
"type": "main",
"index": 0
}
],
[
{
"node": "Extract from CSV",
"type": "main",
"index": 0
}
],
[
{
"node": "Extract Document Text",
"type": "main",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Summarize",
"type": "main",
"index": 0
}
]
]
},
"Summarize": {
"main": [
[
{
"node": "Set Schema",
"type": "main",
"index": 0
},
{
"node": "Postgres PGVector Store",
"type": "main",
"index": 0
}
]
]
},
"Set Schema": {
"main": [
[
{
"node": "Update Schema for Document Metadata",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields": {
"main": [
[
{
"node": "RAG AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Set File ID": {
"main": [
[
{
"node": "Delete Old Doc Records",
"type": "main",
"index": 0
}
]
]
},
"RAG AI Agent": {
"main": [
[
{
"node": "Respond to Webhook",
"type": "main",
"index": 0
}
]
]
},
"List Documents": {
"ai_tool": [
[
{
"node": "RAG AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[],
[
{
"node": "Set File ID",
"type": "main",
"index": 0
}
]
]
},
"Extract PDF Text": {
"main": [
[
{
"node": "Postgres PGVector Store",
"type": "main",
"index": 0
}
]
]
},
"Extract from CSV": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
},
{
"node": "Insert Table Rows",
"type": "main",
"index": 0
}
]
]
},
"Embeddings Ollama": {
"ai_embedding": [
[
{
"node": "Postgres PGVector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Get File Contents": {
"ai_tool": [
[
{
"node": "RAG AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Embeddings Ollama1": {
"ai_embedding": [
[
{
"node": "Postgres PGVector Store1",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Extract from Excel": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
},
{
"node": "Insert Table Rows",
"type": "main",
"index": 0
}
]
]
},
"Local File Trigger": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Postgres PGVector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Query Document Rows": {
"ai_tool": [
[
{
"node": "RAG AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Postgres Chat Memory": {
"ai_memory": [
[
{
"node": "RAG AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Extract Document Text": {
"main": [
[
{
"node": "Postgres PGVector Store",
"type": "main",
"index": 0
}
]
]
},
"Delete Old Doc Records": {
"main": [
[
{
"node": "Delete Old Data Records",
"type": "main",
"index": 0
}
]
]
},
"Delete Old Data Records": {
"main": [
[
{
"node": "Insert Document Metadata",
"type": "main",
"index": 0
}
]
]
},
"Postgres PGVector Store": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Insert Document Metadata": {
"main": [
[
{
"node": "Read/Write Files from Disk",
"type": "main",
"index": 0
}
]
]
},
"Ollama (Change Base URL)": {
"ai_languageModel": [
[
{
"node": "RAG AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Postgres PGVector Store1": {
"ai_tool": [
[
{
"node": "RAG AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Read/Write Files from Disk": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"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 - 内部知识库, AI RAG 检索增强
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41
分类2
节点类型21
作者
Jadai kongolo
@jadai-ai-automationHi 👋 I'm Jadai kongolo. As an AI Automation Expert, I’m passionate about simplifying tech and empowering small businesses and young coders through AI automation. With my AI agency, Oki, I create efficient, n8n-powered workflows that save time, streamline operations, and boost growth for SMBs.
外部链接
在 n8n.io 查看 →
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