This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "Use Vectors in RAG",
"nodes": [
{
"parameters": {
"operation": "download",
"fileId": {
"__rl": true,
"value": "https://docs.google.com/document/d/1pR-KsKsbadO7QP_NS2p1CMl0ZjQ7A6bk72oS5-hnRWs/edit?usp=sharing",
"mode": "url"
},
"options": {
"binaryPropertyName": "data",
"googleFileConversion": {
"conversion": {
"docsToFormat": "text/plain"
}
}
}
},
"id": "9107ce7d-7cb1-4277-8faa-6989febe1db1",
"name": "Get File Content",
"type": "n8n-nodes-base.googleDrive",
"typeVersion": 3,
"position": [
360,
1680
],
"executeOnce": true,
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsonMode": "expressionData",
"jsonData": "={{ $json.data }}",
"options": {}
},
"id": "ea756af3-65d8-4843-8777-6ecd1d89796f",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"typeVersion": 1,
"position": [
780,
1840
]
},
{
"parameters": {
"chunkSize": 500,
"chunkOverlap": 100
},
"id": "fa7bfedd-1c6b-4ad2-84e2-8ab01fe37b1a",
"name": "Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter",
"typeVersion": 1,
"position": [
820,
1980
]
},
{
"parameters": {
"operation": "text",
"options": {}
},
"id": "ee24a79a-c26f-49cd-b65a-250625b4650d",
"name": "Extract from File",
"type": "n8n-nodes-base.extractFromFile",
"typeVersion": 1,
"position": [
500,
1680
]
},
{
"parameters": {
"model": "text-embedding-3-large",
"options": {}
},
"id": "84c2f76e-48cc-4260-a89f-d0d3f97c7a2c",
"name": "Embeddings OpenAI1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1,
"position": [
600,
1880
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {},
"id": "704d3a69-e4c6-4e04-9628-7c5c26c0af2c",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
200,
1680
]
},
{
"parameters": {
"table": {
"__rl": true,
"value": "Carnot",
"mode": "list",
"cachedResultName": "Carnot"
},
"dataMode": "defineBelow",
"valuesToSend": {
"values": [
{
"column": "pageContent",
"value": "={{ $json.pageContent }}"
}
]
},
"options": {}
},
"id": "3d1dc074-ad37-4975-a954-74bd0be1fd85",
"name": "MySQL",
"type": "n8n-nodes-base.mySql",
"typeVersion": 2.4,
"position": [
1040,
1680
],
"credentials": {
"mySql": {
"name": "<your credential>"
}
}
},
{
"parameters": {},
"id": "9f600a58-189c-46d1-9e5b-c78ade8a8538",
"name": "Window Buffer Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.2,
"position": [
360,
1520
]
},
{
"parameters": {
"options": {}
},
"id": "3548a1c9-1b81-41b2-b256-002e1b702a3a",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
180,
1500
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"name": "user_documents",
"description": "Contains all the user's documents that you can check for context to answer user questions."
},
"id": "75a81214-0ee8-41b5-8cbf-bb06d3fa1c97",
"name": "Retrieve Documents",
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
740,
1280
]
},
{
"parameters": {
"options": {}
},
"id": "73df9a0f-d771-439d-9edd-2bbec4f00dcd",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
860,
1520
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "text-embedding-3-large",
"options": {}
},
"id": "2ff5658e-4eb2-44b4-94f4-1e056a4df869",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1,
"position": [
680,
1540
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"id": "a9d804ae-3435-4a9e-b28f-aab55e5ccde6",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
40,
1300
]
},
{
"parameters": {
"memoryKey": "user_documents"
},
"id": "cc644b24-f245-4cc5-9e86-86298dc1f8d2",
"name": "In-Memory Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
"typeVersion": 1,
"position": [
600,
1420
]
},
{
"parameters": {
"mode": "insert",
"memoryKey": "=user_documents",
"clearStore": true
},
"id": "81636bfe-295e-4cbf-b6ec-401365cc938d",
"name": "In-Memory Vector Store Inserter",
"type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
"typeVersion": 1,
"position": [
640,
1680
]
},
{
"parameters": {
"content": "Blank:\nhttps://docs.google.com/document/d/1A4Kq3gmTb9skuQ21dJuR67jfkowGaZQAFaQ1urH0-Mk/edit?usp=sharing\n\nMCC and Carnot:\nhttps://docs.google.com/document/d/1pR-KsKsbadO7QP_NS2p1CMl0ZjQ7A6bk72oS5-hnRWs/edit?usp=sharing",
"height": 193.48837209302337,
"width": 380.33222591362124
},
"id": "98cdf086-cea9-4782-8874-123bd43f24c8",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-20,
1960
]
},
{
"parameters": {
"options": {}
},
"id": "9a99b3c9-ff5d-44e7-9595-37f2938e7965",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
240,
1300
]
}
],
"connections": {
"Get File Content": {
"main": [
[
{
"node": "Extract from File",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "In-Memory Vector Store Inserter",
"type": "ai_document",
"index": 0
}
]
]
},
"Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings OpenAI1": {
"ai_embedding": [
[
{
"node": "In-Memory Vector Store Inserter",
"type": "ai_embedding",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "Get File Content",
"type": "main",
"index": 0
}
]
]
},
"Extract from File": {
"main": [
[
{
"node": "In-Memory Vector Store Inserter",
"type": "main",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Retrieve Documents": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Retrieve Documents",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "In-Memory Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"In-Memory Vector Store": {
"ai_vectorStore": [
[
{
"node": "Retrieve Documents",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"In-Memory Vector Store Inserter": {
"main": [
[
{
"node": "MySQL",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "41f31eb3-f8a7-4e90-ad99-6f3f93a84d37",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "YhVAqTWf0SmZALIk",
"tags": []
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleDriveOAuth2ApimySqlopenAiApi
Pro
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About this workflow
Use Vectors in RAG. Uses googleDrive, documentDefaultDataLoader, textSplitterCharacterTextSplitter, embeddingsOpenAi. Event-driven trigger; 17 nodes.
Source: https://github.com/DrCannata/AgenticAI/blob/6f191dd8412cd76bbb543deee739e1f150b4d041/n8n/Use_Vectors_in_RAG.json — original creator credit. Request a take-down →
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