This workflow follows the Agent → OpenAI Embeddings 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 →
{
"nodes": [
{
"id": "25a059ad-c3d1-4848-a729-cbb50254e94a",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
40,
980
],
"parameters": {},
"typeVersion": 1
},
{
"id": "3ae8469e-cbb4-436a-b5c2-2e6a146c5666",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-40,
600
],
"parameters": {
"color": 7,
"width": 2160,
"height": 1540,
"content": "# Try me out !\n## Dummy Ugly Workflow\n---\nTry mixing it up of changing some connections to see how this workflow gets positionned !\n\n1. **Save this workfow** (Ctrl + S)\n2. **Execute the Magic Positioning Node**\n3. **Reload the page** (Ctrl + R)\n..watch the magic !"
},
"typeVersion": 1
},
{
"id": "4a67e81f-1638-4047-b9e7-85247f4cc291",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
480,
1420
],
"parameters": {
"options": {}
},
"typeVersion": 1.2
},
{
"id": "56293367-e676-44d6-ac05-8432c8181299",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
420,
1660
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "cacdff1d-f65d-40f3-b0b5-9913a8e249ed",
"name": "Window Buffer Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
880,
1760
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "9ccd8613-ded7-421a-bf2d-95e6465d9a34",
"name": "Vector Store Retriever",
"type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
"position": [
1780,
1800
],
"parameters": {},
"typeVersion": 1
},
{
"id": "cc5df13b-2d2e-4c59-b3e3-dfbcbffcfdf9",
"name": "In-Memory Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
"position": [
1060,
1880
],
"parameters": {},
"typeVersion": 1
},
{
"id": "8c71b8fc-0699-4000-8021-fab3529690c6",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1660,
1940
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "83bbca90-f9aa-4aae-9f1b-68d7eb1e7272",
"name": "Question and Answer Chain",
"type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
"position": [
760,
1540
],
"parameters": {
"options": {}
},
"typeVersion": 1.4
},
{
"id": "6d124c93-a476-4b54-ad65-391eaf948605",
"name": "Switch",
"type": "n8n-nodes-base.switch",
"position": [
1360,
1220
],
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "",
"rightValue": ""
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "5f1ec5b3-385c-4421-9791-a612f61cc634",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "",
"rightValue": ""
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "737211eb-e4e2-4bb2-a32b-a6d819e158ba",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "",
"rightValue": ""
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "3a420a92-cd22-46d4-b2fa-1dffa6b28374",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "",
"rightValue": ""
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "29c0fce3-aefb-4caf-a076-a548c108b641",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "",
"rightValue": ""
}
]
}
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "886142ac-822e-4e25-875c-65632f682140",
"name": "IF",
"type": "n8n-nodes-base.if",
"position": [
440,
1480
],
"parameters": {},
"typeVersion": 1
},
{
"id": "3a247df2-ea43-40f0-a395-0ce160fcbc92",
"name": "Dummy Node",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1360,
1520
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "53e46b03-026a-4645-b9c7-e913eea62fe9",
"name": "Dummy Node (1)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
700,
900
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "0d9a5f0a-e224-41b9-8ef0-4ba16e71c237",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
920,
980
],
"parameters": {
"options": {},
"batchSize": "=1"
},
"typeVersion": 3
},
{
"id": "2442eccb-8f95-4c2d-ae93-7e216e93e7f4",
"name": "Dummy Node (2)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1140,
940
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "2de8782c-f848-44cc-87b1-307506cdca38",
"name": "Dummy Node (3)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
700,
1200
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "f1bb16c1-b330-4208-b629-5a6e074b9178",
"name": "Dummy Node (4)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
900,
1460
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "93c393c5-d258-431e-ba22-c7de7f6560f1",
"name": "Dummy Node (5)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1140,
1200
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "c55e1584-4bab-4406-9b6c-a7ba96828c4b",
"name": "Dummy Node (6)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1580,
980
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "612a7a10-242e-4bd0-b4bd-6089e1fcd78b",
"name": "Dummy Node (7)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1780,
1300
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "eb5d2519-2f1e-4841-b8e8-58333cf9293d",
"name": "Dummy Node (8)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1340,
1720
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "661d3849-155b-4911-b923-4cd2a4227202",
"name": "Dummy Node (9)",
"type": "n8n-nodes-base.noOp",
"notes": "Big description of what happens here",
"position": [
1580,
1640
],
"parameters": {},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "af2cca30-302d-47e1-bebc-3f6a92cef939",
"name": "Dummy Tool",
"type": "@n8n/n8n-nodes-langchain.toolHttpRequest",
"position": [
720,
1660
],
"parameters": {
"url": "https://www.example.com"
},
"typeVersion": 1.1
},
{
"id": "7dded6b7-c60a-45e4-a49f-338bf4b549b8",
"name": "Dummy Tool (1)",
"type": "@n8n/n8n-nodes-langchain.toolHttpRequest",
"position": [
680,
1760
],
"parameters": {
"url": "https://www.example.com"
},
"typeVersion": 1.1
},
{
"id": "d4f0d637-abda-4e79-ae6b-7af7050d6768",
"name": "OpenAI Chat Model (1)",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1360,
1880
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "e5ea3f5b-cd91-49b6-9191-f60a0d19bf40",
"name": "Update n8n Workflow",
"type": "n8n-nodes-base.n8n",
"position": [
700,
380
],
"parameters": {
"operation": "update",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $('POST /workflow/magic/position/id').last().json.body.workflow_id }}"
},
"requestOptions": {},
"workflowObject": "={{ $json.toJsonString() }}"
},
"credentials": {
"n8nApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "5df2795d-f1fa-437f-9444-92a0ec4003da",
"name": "Magic Positioning IA2S",
"type": "n8n-nodes-base.httpRequest",
"position": [
480,
380
],
"parameters": {
"url": "https://api.ia2s.app/webhook/workflow/magic/position",
"method": "POST",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "workflow",
"value": "={{ $json }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "f6820c3e-d0ec-45ef-92ce-b6a7466997fb",
"name": "POST /workflow/magic/position/id",
"type": "n8n-nodes-base.webhook",
"position": [
40,
380
],
"parameters": {
"path": "workflow/magic/positioning/id",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2
},
{
"id": "f0a4176b-1fa4-4884-8a51-ecc00af7d246",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-40,
-60
],
"parameters": {
"color": 6,
"width": 300,
"height": 380,
"content": "## Put this node in any workflow.\n1. **Save the workfow** (Ctrl + S)\n2. **Execute the Magic Positioning Node**\n3. **Reload the page** (Ctrl + R)\n..and voil\u00e0 !"
},
"typeVersion": 1
},
{
"id": "20d8af29-e07a-4205-a7b6-223b2cdb801a",
"name": "Get n8n Workflow",
"type": "n8n-nodes-base.n8n",
"position": [
260,
380
],
"parameters": {
"operation": "get",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.body.workflow_id }}"
},
"requestOptions": {}
},
"credentials": {
"n8nApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "468a95e2-11bc-4bf6-be8a-4eb5f89654ef",
"name": "Simple Webhook Response",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
920,
380
],
"parameters": {
"options": {},
"respondWith": "text",
"responseBody": "Workflow Updated"
},
"typeVersion": 1.1
},
{
"id": "496ba599-cf72-4ba1-8e50-2e369f199b6f",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
80,
1260
],
"parameters": {
"rule": {
"interval": [
{}
]
}
},
"typeVersion": 1.2
},
{
"id": "107e6cb3-673b-4554-b42c-c9d2d7a00ce9",
"name": "Magic Positioning",
"type": "n8n-nodes-base.httpRequest",
"position": [
40,
160
],
"parameters": {
"url": "=https://{{ \"n8n.your-instance-url.com\" }}/webhook/workflow/magic/positioning/id",
"method": "POST",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "workflow_id",
"value": "={{ $workflow.id }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "55e8a9fc-1699-4890-b73e-a6201259a559",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
300,
-60
],
"parameters": {
"color": 5,
"width": 400,
"height": 380,
"content": "# Setup :\n---\n\n1. **Open the Webhook node** \n('Post /workflow/magic/position/id')\n2. Copy the **Production URL**\n3. Go to the **'Magic Positioning' Http Request** Node\n4. **Paste the URL**\n5. Select your **n8n credentials** in the n8n nodes"
},
"typeVersion": 1
}
],
"connections": {
"IF": {
"main": [
[
{
"node": "Dummy Node",
"type": "main",
"index": 0
}
],
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Switch": {
"main": [
[
{
"node": "Dummy Node (6)",
"type": "main",
"index": 0
}
],
[
{
"node": "Dummy Node (7)",
"type": "main",
"index": 0
}
],
[
{
"node": "Dummy Node (8)",
"type": "main",
"index": 0
}
],
[
{
"node": "Dummy Node (9)",
"type": "main",
"index": 0
}
],
[
{
"node": "Question and Answer Chain",
"type": "main",
"index": 0
}
]
]
},
"Dummy Node": {
"main": [
[
{
"node": "Dummy Node (1)",
"type": "main",
"index": 0
},
{
"node": "Dummy Node (3)",
"type": "main",
"index": 0
}
]
]
},
"Dummy Tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Dummy Node (1)": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Dummy Node (2)": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"Dummy Node (3)": {
"main": [
[
{
"node": "Dummy Node (4)",
"type": "main",
"index": 0
}
]
]
},
"Dummy Node (5)": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Dummy Tool (1)": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[
{
"node": "Dummy Node (2)",
"type": "main",
"index": 0
}
],
[
{
"node": "Dummy Node (5)",
"type": "main",
"index": 0
}
]
]
},
"Get n8n Workflow": {
"main": [
[
{
"node": "Magic Positioning IA2S",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "IF",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "In-Memory Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Update n8n Workflow": {
"main": [
[
{
"node": "Simple Webhook Response",
"type": "main",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI Chat Model (1)": {
"ai_languageModel": [
[
{
"node": "Question and Answer Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"In-Memory Vector Store": {
"ai_vectorStore": [
[
{
"node": "Vector Store Retriever",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Magic Positioning IA2S": {
"main": [
[
{
"node": "Update n8n Workflow",
"type": "main",
"index": 0
}
]
]
},
"Vector Store Retriever": {
"ai_retriever": [
[
{
"node": "Question and Answer Chain",
"type": "ai_retriever",
"index": 0
}
]
]
},
"POST /workflow/magic/position/id": {
"main": [
[
{
"node": "Get n8n Workflow",
"type": "main",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "IF",
"type": "main",
"index": 0
}
]
]
}
}
}
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.
n8nApiopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
How this works
Automate complex, event-driven tasks with this workflow that leverages an AI agent to process incoming webhooks intelligently, delivering precise responses or actions without constant manual oversight. It's ideal for developers and automation enthusiasts handling dynamic data flows, such as real-time notifications or query processing, saving hours on repetitive monitoring. The core step involves the AI agent, powered by OpenAI's chat model and vector store retrieval, analysing events to generate context-aware outputs using embeddings for semantic search.
Use this workflow for scenarios requiring on-demand AI-driven decisions from webhooks, like customer support bots or data validation pipelines, especially when integrating with OpenAI tools. Avoid it for simple, rule-based automations lacking AI needs, or high-volume traffic exceeding memory buffer limits. Common variations include swapping the in-memory vector store for a persistent database or adding email integrations for alerts.
About this workflow
Webhook Schedule. Uses manualTrigger, stickyNote, agent, lmChatOpenAi. Event-driven trigger; 34 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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