This workflow follows the Agent → Airtable 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": "Agent Nodes",
"nodes": [
{
"parameters": {
"options": {}
},
"id": "ece04891-3085-4ae0-8624-249163d16313",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
4400,
2000
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
4800,
2000
],
"id": "9e24b4b1-01d8-4014-908b-d5c850acb93b",
"name": "OpenAI Chat Model1",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"authentication": "oAuth2",
"operation": "sendAndWait",
"user": {
"__rl": true,
"value": "U08S4Q86MR7",
"mode": "list",
"cachedResultName": "cole"
},
"message": "=please APPROVE or DECLINE this message:\n\n{{ $('When Executed by Another Workflow').item.json.message }}",
"approvalOptions": {
"values": {
"approvalType": "double"
}
},
"options": {}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
3100,
1920
],
"id": "0e195e86-9740-4e45-a481-e3c60a3b6bfb",
"name": "Slack",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "gpt-4.1-mini",
"options": {}
},
"id": "42d1ec0f-380e-4a35-9390-36e250efaf1a",
"name": "OpenAI Chat Model3",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
2340,
2060
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"leftValue": "={{ $json.data.approved }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"id": "0a675740-e73f-4332-b2dc-e628e2499676"
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "APPROVED"
},
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "8b61a1ad-7442-429b-a541-3f5d280a0788",
"leftValue": "={{ $json.data.approved }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "false",
"singleValue": true
}
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "DENIED"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.switch",
"typeVersion": 3.2,
"position": [
3340,
1920
],
"id": "60bd7d77-2049-445b-81e3-00b356101390",
"name": "Switch1"
},
{
"parameters": {
"authentication": "oAuth2",
"select": "channel",
"channelId": {
"__rl": true,
"value": "C08RSGUJK1R",
"mode": "list",
"cachedResultName": "research"
},
"text": "=Here is the APPROVED message: \n\n{{ $('When Executed by Another Workflow').item.json.message }}",
"otherOptions": {
"includeLinkToWorkflow": false
}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
3620,
1800
],
"id": "65fd189b-150f-4cdb-bcc3-2508222a69f7",
"name": "Slack1",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"authentication": "oAuth2",
"select": "channel",
"channelId": {
"__rl": true,
"value": "C08RSGUJK1R",
"mode": "list",
"cachedResultName": "research"
},
"text": "=Here is the DECLINED message: \n\n{{ $('When Executed by Another Workflow').item.json.message }}",
"otherOptions": {
"includeLinkToWorkflow": false
}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
3620,
2020
],
"id": "036dfd39-9bfd-4d7f-84d6-41121e1284cb",
"name": "Slack2",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "gpt-4.1-mini",
"options": {}
},
"id": "792ccb86-263c-4145-8712-24fd93af3ae9",
"name": "OpenAI Chat Model4",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
-960,
2040
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"errorMessage": "An error has occured!"
},
"type": "n8n-nodes-base.stopAndError",
"typeVersion": 1,
"position": [
7200,
2020
],
"id": "df755e83-8410-4bbf-ad94-574e94ee2992",
"name": "Stop and Error",
"executeOnce": false,
"alwaysOutputData": false,
"notesInFlow": false,
"onError": "continueRegularOutput"
},
{
"parameters": {
"authentication": "oAuth2",
"operation": "sendAndWait",
"user": {
"__rl": true,
"value": "U08S4Q86MR7",
"mode": "list",
"cachedResultName": "cole"
},
"message": "=Please APPROVE or DECLINE this message",
"approvalOptions": {
"values": {
"approvalType": "double"
}
},
"options": {}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
6740,
1900
],
"id": "ff3bd817-8e25-4013-882c-de268fd4b5f6",
"name": "Slack3",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"leftValue": "={{ $json.data.approved }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"id": "0a675740-e73f-4332-b2dc-e628e2499676"
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "APPROVED"
},
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "8b61a1ad-7442-429b-a541-3f5d280a0788",
"leftValue": "={{ $json.data.approved }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "false",
"singleValue": true
}
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "DENIED"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.switch",
"typeVersion": 3.2,
"position": [
6940,
1900
],
"id": "1206e685-c523-4d9b-8112-89c9807623ff",
"name": "Switch2"
},
{
"parameters": {
"authentication": "oAuth2",
"select": "channel",
"channelId": {
"__rl": true,
"value": "C08RSGUJK1R",
"mode": "list",
"cachedResultName": "research"
},
"text": "=Message is approved",
"otherOptions": {
"includeLinkToWorkflow": false
}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
7200,
1800
],
"id": "214787f9-b740-4e20-8604-2818f1422cec",
"name": "Slack4",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {},
"type": "n8n-nodes-base.errorTrigger",
"typeVersion": 1,
"position": [
7420,
1920
],
"id": "9a09e569-76c2-42f9-8eb5-6bb595a1953a",
"name": "Error Trigger"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
6560,
1900
],
"id": "9dfb40f6-67c2-4abb-aaa5-187bc27b97d3",
"name": "When clicking \u2018Test workflow\u2019"
},
{
"parameters": {
"promptType": "define",
"text": "={{ $json.output }}",
"hasOutputParser": true,
"messages": {
"messageValues": [
{
"message": "=\nYou are a standalone food critic Agent. You operate as the final check in the workflow to ensure that the final response follows the following guidelines for Output Check, Format Validator, Content Filter:\n\n\t\u2022\tContent Filter \u2013 Ensure the response includes where the dish originates and a description of the dish \n\nEXAMPLE: \nName: Moussaka\nDescription: Originating in Greece, moussaka is a layered casserole of tender eggplant slices and spiced ground lamb (or beef), all topped with a silky b\u00e9chamel sauce and baked until golden and bubbling. It\u2019s a comforting dish that combines Mediterranean flavors\u2014olive oil, cinnamon, and tomato\u2014with a rich, creamy finish.\n\n\n\t\u2022\tOutput Check \u2013 ensure name and description are present \n\t\nOutput false for 'valid' and your feedback for 'feedback' if the response from the other agent didn't follow the guidelines for the output check, content filter, etc.\n\nOutput true for 'valid' if it did. Don't be too picky.\n\n"
}
]
}
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.6,
"position": [
4820,
1800
],
"id": "813ac4e1-2637-4eab-9dab-d7a4b27d3be1",
"name": "Critic Node"
},
{
"parameters": {
"operation": "search",
"base": {
"__rl": true,
"value": "appu9xcTfFpUJ1pwp",
"mode": "list",
"cachedResultName": "Restaurant",
"cachedResultUrl": "https://airtable.com/appu9xcTfFpUJ1pwp"
},
"table": {
"__rl": true,
"value": "tblb2LYwGNnjfF9eb",
"mode": "list",
"cachedResultName": "Dishes",
"cachedResultUrl": "https://airtable.com/appu9xcTfFpUJ1pwp/tblb2LYwGNnjfF9eb"
},
"options": {}
},
"type": "n8n-nodes-base.airtableTool",
"typeVersion": 2.1,
"position": [
2160,
560
],
"id": "c1be2df1-90d3-4d32-b733-1a2c1a0324e1",
"name": "Menu Table",
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"content": "## LLM, Memory, and Tool Nodes\n",
"height": 485,
"width": 656,
"color": 4
},
"id": "5e4c4532-410e-4fe6-9b63-75602247cff3",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-1060,
1720
]
},
{
"parameters": {
"content": "## User Input and Control Nodes\n\n",
"height": 545,
"width": 1656,
"color": 6
},
"id": "3c1183ae-3396-4d5c-b41c-d312415698a9",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
2220,
1700
]
},
{
"parameters": {
"content": "## Guardrail Node",
"height": 565,
"width": 1556
},
"id": "ba1a9e46-dca6-4c2b-98d9-aaf8ba2fe2d3",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
4320,
1700
]
},
{
"parameters": {
"content": "## Fallback Node\n",
"height": 525,
"width": 1416,
"color": 3
},
"id": "6e46a3d0-bad8-43c5-bea2-3beadb2f7791",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
6460,
1720
]
},
{
"parameters": {},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
-780,
2040
],
"id": "722d3e32-58be-4667-b5d6-d105e3e2dd73",
"name": "Postgres Chat Memory",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "={{ $json.chatInput }}",
"options": {
"systemMessage": "=here is the current date/time : {{ $now }}"
}
},
"id": "c9f389de-8e6c-4513-8490-6e96a452a66c",
"name": "AI Agent1",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
-860,
1820
]
},
{
"parameters": {
"model": "gpt-4.1-mini",
"options": {}
},
"id": "0e25d4f7-c69f-486a-bf84-09a094fe7225",
"name": "OpenAI Chat Model8",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
260,
2040
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"content": "## More Detailed Memory Nodes\n",
"height": 505,
"width": 1676,
"color": 5
},
"id": "38c6c3e9-8790-4b2d-a22f-a3904f63c2f2",
"name": "Sticky Note11",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
80,
1720
]
},
{
"parameters": {
"sessionIdType": "customKey",
"sessionKey": "={{ $('When chat message received').item.json.sessionId }}"
},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
440,
2040
],
"id": "3b01a694-3e29-4e66-bad1-1375c9af6c5f",
"name": "Postgres Chat Memory1",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": {
"__rl": true,
"value": "gpt-4.1-mini",
"mode": "list",
"cachedResultName": "gpt-4.1-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
700,
2040
],
"id": "e9a7578a-370f-4f93-bf77-138deac6853d",
"name": "OpenAI Chat Model2",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "get",
"documentURL": "15sBOoqCJjIggmtG9aEFPFe3AFS_G6iMOZQmT6wkkRVM"
},
"type": "n8n-nodes-base.googleDocs",
"typeVersion": 2,
"position": [
160,
1820
],
"id": "9fe93f1f-f7af-4f56-a60b-f03dd169e53c",
"name": "Get Memories",
"credentials": {
"googleDocsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "update",
"documentURL": "15sBOoqCJjIggmtG9aEFPFe3AFS_G6iMOZQmT6wkkRVM",
"actionsUi": {
"actionFields": [
{
"action": "insert",
"text": "={{ $json.text }}"
}
]
}
},
"type": "n8n-nodes-base.googleDocs",
"typeVersion": 2,
"position": [
1360,
1820
],
"id": "08c53829-9c6c-4a19-9d50-165880617248",
"name": "Save Memories",
"credentials": {
"googleDocsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "=User message:\n\n{{ $('When chat message received').item.json.chatInput }}\n\nBased on the user message above, extract any key memories that should be stored for later converastions. Just output nothing (an empty string) if there are no important memories to be made here. Otherwise if there are good memories, output just those to store directly in the memory bank"
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.6,
"position": [
740,
1820
],
"id": "307da2bf-3f0c-419d-ae06-894be3658497",
"name": "Extract Memories"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "ffe35d80-0ebf-4b26-b292-dc870fd83413",
"leftValue": "={{ $json.text }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
1100,
1820
],
"id": "6f9fa9b7-4001-4083-8832-3bf24430d244",
"name": "If"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "1ea78aec-3a4d-48f2-bf20-ba69229646f0",
"name": "output",
"value": "={{ $('AI Agent2').item.json.output }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
1540,
2020
],
"id": "103fc4ab-2e8a-4870-a599-e09ecbf20d03",
"name": "Edit Fields"
},
{
"parameters": {
"promptType": "define",
"text": "={{ $('When chat message received').item.json.chatInput }}",
"options": {
"systemMessage": "You are an AI agent that recommeds dishes you don't do anything else."
}
},
"id": "e0cb6792-8940-4373-946f-1fe772ea0558",
"name": "AI Agent4",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
4440,
1800
]
},
{
"parameters": {
"promptType": "define",
"text": "=Here are your long term memories:\n\n{{ $json.content }}\n\nThen here is the user message, this is what you need to respond to:\n\n{{ $('When chat message received').item.json.chatInput }}",
"options": {
"systemMessage": "=here is the current date/time : {{ $now }}"
}
},
"id": "0e4f7b89-c1bf-4d9d-8261-a433db6d9107",
"name": "AI Agent2",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
380,
1820
]
},
{
"parameters": {
"promptType": "define",
"text": "={{ $json.chatInput }}",
"options": {
"systemMessage": ""
}
},
"id": "31b2544f-a10e-42d9-846f-b5018a9fd7fb",
"name": "AI Agent3",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
2380,
1840
]
},
{
"parameters": {
"jsonSchemaExample": "{\n\t\"valid\": false,\n\t\"feedback\": \"Make sure you include the origin of the dish!\"\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.2,
"position": [
5000,
2000
],
"id": "2372ff88-525e-4441-bae9-3f837d31e55f",
"name": "Structured Output Parser3"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "7dbaedb8-9254-4df9-be0c-2895594ce919",
"leftValue": "={{ $json.output.valid }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
5180,
1800
],
"id": "90e38fbc-ddde-409a-8b9f-85845dd6145b",
"name": "If1"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "8649ff8f-56ad-431a-a701-2f3a06ca43d9",
"name": "output",
"value": "={{ $('AI Agent4').item.json.output }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
5460,
1760
],
"id": "d2396497-528d-44c1-96a7-e0e288ef4d4e",
"name": "Edit Fields1"
},
{
"parameters": {
"sessionIdType": "customKey",
"sessionKey": "={{ $('When chat message received').item.json.sessionId }}"
},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
4560,
2000
],
"id": "74519110-60ea-4b59-bd26-337d66405f41",
"name": "Postgres Chat Memory2",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"id": "26923d2a-da6f-452e-91fe-9bba2f1f8c71",
"name": "OpenAI Chat Model9",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
5320,
2120
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "=Any feedback from the critque agent:\n\n{{ $json?.output?.feedback || \"\" }}\n\nUser message:\n\n{{ $('When chat message received').item.json.chatInput }}",
"options": {
"systemMessage": "You are an AI agent that recommeds dishes you don't do anything else."
}
},
"id": "e093cb43-00cd-4258-b023-0374b7ca79a0",
"name": "AI Agent5",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
5380,
1940
]
},
{
"parameters": {
"sessionIdType": "customKey",
"sessionKey": "={{ $('When chat message received').item.json.sessionId }}"
},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
5480,
2120
],
"id": "b0b7f6c7-d42b-4fdb-a7c6-aedcc9f5fac7",
"name": "Postgres Chat Memory4",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"authentication": "oAuth2",
"select": "user",
"user": {
"__rl": true,
"value": "U08S4Q86MR7",
"mode": "list",
"cachedResultName": "cole"
},
"text": "={{ $json.execution.error.message }}",
"otherOptions": {
"includeLinkToWorkflow": false
}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
7620,
1920
],
"id": "99df8edd-0391-44a6-9051-06fb560941d3",
"name": "Slack7",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"name": "send_slack_message",
"description": "Sends a slack message based on the message you provide",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{$workflow.id}}",
"cachedResultName": "={{$workflow.id}}"
},
"workflowInputs": {
"mappingMode": "defineBelow",
"value": {
"message": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('message', ``, 'string') }}"
},
"matchingColumns": [
"message"
],
"schema": [
{
"id": "message",
"displayName": "message",
"required": false,
"defaultMatch": false,
"display": true,
"canBeUsedToMatch": true,
"type": "string",
"removed": false
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"typeVersion": 2.1,
"position": [
2580,
2060
],
"id": "805905a4-e56b-4284-bc95-f492df1af7db",
"name": "Call n8n Workflow Tool"
},
{
"parameters": {
"workflowInputs": {
"values": [
{
"name": "message"
}
]
}
},
"type": "n8n-nodes-base.executeWorkflowTrigger",
"typeVersion": 1.1,
"position": [
2840,
1920
],
"id": "1f7fc925-4ba4-4043-9dc1-aa330b5ba7c4",
"name": "When Executed by Another Workflow"
},
{
"parameters": {
"operation": "create",
"base": {
"__rl": true,
"value": "appu9xcTfFpUJ1pwp",
"mode": "list",
"cachedResultName": "Restaurant",
"cachedResultUrl": "https://airtable.com/appu9xcTfFpUJ1pwp"
},
"table": {
"__rl": true,
"value": "tblb2LYwGNnjfF9eb",
"mode": "list",
"cachedResultName": "Dishes",
"cachedResultUrl": "https://airtable.com/appu9xcTfFpUJ1pwp/tblb2LYwGNnjfF9eb"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"Dish Name": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Dish_Name', ``, 'string') }}",
"Dish Description": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Dish_Description', ``, 'string') }}"
},
"matchingColumns": [],
"schema": [
{
"id": "Dish Name",
"displayName": "Dish Name",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": false
},
{
"id": "Dish Description",
"displayName": "Dish Description",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": false
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"type": "n8n-nodes-base.airtableTool",
"typeVersion": 2.1,
"position": [
-600,
2040
],
"id": "a516c86b-57a5-4300-8184-afbde021771e",
"name": "Airtable2",
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"id": "2b5c8aa1-42e6-4123-80f0-a7bf3bf7ae86",
"name": "OpenAI Chat Model5",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1,
"position": [
1820,
560
],
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"content": "## Full Example",
"height": 765,
"width": 3116
},
"id": "0d501fbf-8f09-472f-9182-f1fed473f7be",
"name": "Sticky Note12",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1460,
200
]
},
{
"parameters": {
"promptType": "define",
"text": "=Your memories from the user:\n\n{{ $json.content }}\n\nThe user request:\n\n{{ $('When chat message received').item.json.chatInput }}",
"hasOutputParser": true,
"options": {
"systemMessage": "You are an AI agent that recommeds dishes you don't do anything else."
}
},
"id": "55364710-4f52-457c-a5b6-cbcb51ae732c",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
1980,
320
]
},
{
"parameters": {
"sessionIdType": "customKey",
"sessionKey": "={{ $('When chat message received').item.json.sessionId }}"
},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
2020,
560
],
"id": "9a70b4ec-91d1-4113-8246-e67d1e61c058",
"name": "Postgres Chat Memory5",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsonSchemaExample": "{\n\t\"dish name\": \"Harvest Moon Risotto\",\n\t\"dish description\": \"A creamy Arborio rice dish studded with tender roasted butternut squash and wilted spinach, enriched by a sage-infused brown butter and finished with a shower of freshly grated Parmesan and toasted pepitas for a nutty crunch.\"\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.2,
"position": [
2420,
780
],
"id": "8c2fc9a2-f226-4565-9440-272ae2986453",
"name": "Structured Output Parser4"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
"typeVersion": 1,
"position": [
2320,
560
],
"id": "b8674dfd-902c-498d-9f16-4f3ae48c4b26",
"name": "Auto-fixing Output Parser1"
},
{
"parameters": {
"model": {
"__rl": true,
"value": "gpt-4.1-mini",
"mode": "list",
"cachedResultName": "gpt-4.1-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
2240,
760
],
"id": "6c6909f4-17a0-47fe-8b63-36f073c02760",
"name": "OpenAI Chat Model13",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": {
"__rl": true,
"value": "gpt-4.1-mini",
"mode": "list",
"cachedResultName": "gpt-4.1-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
3360,
560
],
"id": "5f30ab05-9c76-4569-a0e2-a4f24251023a",
"name": "OpenAI Chat Model10",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "get",
"documentURL": "15sBOoqCJjIggmtG9aEFPFe3AFS_G6iMOZQmT6wkkRVM"
},
"type": "n8n-nodes-base.googleDocs",
"typeVersion": 2,
"position": [
1760,
320
],
"id": "939438cf-08ea-49a1-9432-5079e8e25bf3",
"name": "Get Memories1",
"credentials": {
"googleDocsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "update",
"documentURL": "15sBOoqCJjIggmtG9aEFPFe3AFS_G6iMOZQmT6wkkRVM",
"actionsUi": {
"actionFields": [
{
"action": "insert",
"text": "={{ $json.text }}"
}
]
}
},
"type": "n8n-nodes-base.googleDocs",
"typeVersion": 2,
"position": [
3980,
340
],
"id": "7d142773-9fab-4e47-9163-75aaf8a78018",
"name": "Save Memories1",
"credentials": {
"googleDocsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "=User message:\n\n{{ $('When chat message received').item.json.chatInput }}\n\nBased on the user message above, extract any key memories that should be stored for later converastions. Just output nothing (an empty string) if there are no important memories to be made here. Otherwise if there are good memories, output just those to store directly in the memory bank"
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.6,
"position": [
3420,
340
],
"id": "83c6dc72-c6f4-4768-85b0-4f05fd71582e",
"name": "Extract Memories1"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "ffe35d80-0ebf-4b26-b292-dc870fd83413",
"leftValue": "={{ $json.text }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
3780,
460
],
"id": "653b3871-9876-4318-b4cb-af9b224dcfd5",
"name": "If2"
},
{
"parameters": {
"errorMessage": "The dish has been rejected!"
},
"type": "n8n-nodes-base.stopAndError",
"typeVersion": 1,
"position": [
2980,
600
],
"id": "e5db54c6-9c66-4895-8daf-1db6cacd1fe1",
"name": "Stop and Error2",
"executeOnce": false,
"alwaysOutputData": false,
"notesInFlow": false,
"onError": "continueRegularOutput"
},
{
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"leftValue": "={{ $json.data.approved }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"id": "0a675740-e73f-4332-b2dc-e628e2499676"
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "APPROVED"
},
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "8b61a1ad-7442-429b-a541-3f5d280a0788",
"leftValue": "={{ $json.data.approved }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "false",
"singleValue": true
}
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "DENIED"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.switch",
"typeVersion": 3.2,
"position": [
2680,
420
],
"id": "f314b057-47ae-41dc-980a-298e8bfedf73",
"name": "Switch"
},
{
"parameters": {
"authentication": "oAuth2",
"select": "channel",
"channelId": {
"__rl": true,
"value": "C08RSGUJK1R",
"mode": "list",
"cachedResultName": "research"
},
"text": "=[CONFIRMED] here is the APPROVED dish:\n\ndish name: {{ $('AI Agent').item.json.output['dish name'] }}\n\ndish description: {{ $('AI Agent').item.json.output['dish description'] }}",
"otherOptions": {
"includeLinkToWorkflow": false
}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
2980,
340
],
"id": "4ade5845-90f6-4a0c-802b-a77c81a7123d",
"name": "Slack8",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"authentication": "oAuth2",
"operation": "sendAndWait",
"user": {
"__rl": true,
"value": "U08S4Q86MR7",
"mode": "list",
"cachedResultName": "cole"
},
"message": "=Please APPROVE or DECLINE this dish based on ingredient availability\n\ndish name: {{ $json.output['dish name'] }}\n\ndish discription: {{ $json.output['dish description'] }}",
"approvalOptions": {
"values": {
"approvalType": "double"
}
},
"options": {}
},
"type": "n8n-nodes-base.slack",
"typeVersion": 2.3,
"position": [
2420,
320
],
"id": "6c57a7de-4d51-4960-a64b-c92d5779cfd6",
"name": "Slack9",
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "create",
"base": {
"__rl": true,
"value": "appu9xcTfFpUJ1pwp",
"mode": "list",
"cachedResultName": "Restaurant",
"cachedResultUrl": "https://airtable.com/appu9xcTfFpUJ1pwp"
},
"table": {
"__rl": true,
"value": "tblb2LYwGNnjfF9eb",
"mode": "list",
"cachedResultName": "Menu",
"cachedResultUrl": "https://airtable.com/appu9xcTfFpUJ1pwp/tblb2LYwGNnjfF9eb"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"Dish Name": "={{ $('AI Agent').item.json.output['dish name'] }}",
"Dish Description": "={{ $('AI Agent').item.json.output['dish description'] }}"
},
"matchingColumns": [],
"schema": [
{
"id": "Dish Name",
"displayName": "Dish Name",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": false
},
{
"id": "Dish Description",
"displayName": "Dish Description",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": false
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"type": "n8n-nodes-base.airtable",
"typeVersion": 2.1,
"position": [
3180,
340
],
"id": "53345af8-3613-4f90-a4c5-c9563aac30b1",
"name": "Airtable",
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "=Summarize the dish created:\n\nName: {{ $('AI Agent').item.json.output['dish name'] }}\nDescription: {{ $('AI Agent').item.json.output['dish description'] }}\n\nAnd also give a sentence about how tasty the dish is and what makes it so good."
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.6,
"position": [
4200,
500
],
"id": "11f55028-1a6f-4451-829b-96439f0fa96c",
"name": "Basic LLM Chain"
},
{
"parameters": {
"model": {
"__rl": true,
"value": "gpt-4.1-mini",
"mode": "list",
"cachedResultName": "gpt-4.1-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
4280,
680
],
"id": "d5b284e9-640d-44c1-9d76-f86c3da96cee",
"name": "OpenAI Chat Model6",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"content": "",
"height": 360,
"width": 560,
"color": 4
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-1020,
1320
],
"id": "26b2c5cf-5b7d-4ac4-9975-cd33b8f8cde5",
"name": "Sticky Note1"
},
{
"parameters": {
"content": "",
"height": 380,
"width": 1060,
"color": 5
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
380,
1320
],
"id": "99a0121b-712a-4418-bfb0-b06437d174e3",
"name": "Sticky Note2"
},
{
"parameters": {
"content": "",
"height": 460,
"width": 1000,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
2520,
1220
],
"id": "5359216e-986f-4810-bbc3-52ec564c5628",
"name": "Sticky Note3"
},
{
"parameters": {
"content": "",
"height": 380,
"width": 860,
"color": 3
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
6720,
1320
],
"id": "90e8dad2-a2b7-4d8b-b1e4-be123fdd7931",
"name": "Sticky Note5"
},
{
"parameters": {
"content": "",
"height": 340,
"width": 1200
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
4480,
1340
],
"id": "61782241-ef1c-4465-9cc5-b707e66ffd08",
"name": "Sticky Note4"
},
{
"parameters": {
"content": "",
"height": 520,
"width": 1240
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
2420,
-340
],
"id": "c562ccf3-9b6d-4fe3-b8e8-9bade0aa4d75",
"name": "Sticky Note7"
},
{
"parameters": {
"content": "# \ud83e\udd16 The Seven Node Blueprint for AI Agents \ud83e\udd16\n\n## **Agents are just graphs.**\n\nViewing AI agents as graphs provides a powerful mental model for designing systems. This approach breaks down complex agents into interconnected nodes, each with specific responsibilities. By thinking in graphs, we can:\n\n- **Modularize functionality** for better maintenance\n- **Scale complexity** through simple component connections\n- **Improve resilience** with explicit error handling paths\n- **Enable transparency** by making information flow visible\n\nThis is how you can design complex systems with ease (when necessary).\n\n## Node Types\n\n### 1\ufe0f\u20e3 LLM Node \ud83e\udde0\n\n**Purpose**: Reasoning, generation, and decision-making\n\n**Examples**: Planning, content generation, summarization\n\n**Why it's useful**: Acts as the \"brain\" that processes information and coordinates between components, handling ambiguity and novel situations.\n\n### 2\ufe0f\u20e3 Tool Node \ud83d\udee0\ufe0f\n\n**Purpose**: Executes external tools or APIs\n\n**Examples**: Web search, code execution, database queries\n\n**Why it's useful**: Extends capabilities beyond language processing, connecting the agent to external systems and real-time data.\n\n### 3\ufe0f\u20e3 Control Node \u2699\ufe0f\n\n**Purpose**: Handles logic, branching, and deterministic rules\n\n**Examples**: Routing, conditionals, filters\n\n**Why it's useful**: Introduces predictability and enables consistent handling of different cases and business logic.\n\n### 4\ufe0f\u20e3 Memory Node \ud83d\udcda\n\n**Purpose**: Reads/writes to memory for stateful context\n\n**Examples**: Vector DBs, conversation history, user preferences\n\n**Why it's useful**: Maintains context over time, enabling personalization and self-evolution.\n\n### 5\ufe0f\u20e3 Guardrail Node \ud83d\udea7\n\n**Purpose**: Validates outputs and enforces constraints\n\n**Examples**: Content filtering, format validation, safety checks\n\n**Why it's useful**: Ensures outputs meet required standards, preventing harmful or incorrect responses.\n\n### 6\ufe0f\u20e3 Fallback Node \ud83d\udd04\n\n**Purpose**: Responds to failures with retries or alternate flows\n\n**Examples**: Retries, escalation paths, default responses\n\n**Why it's useful**: Provides graceful degradation when things go wrong rather than complete failure.\n\n### 7\ufe0f\u20e3 User Input Node \ud83d\udc65\n\n**Purpose**: Brings humans into the loop for clarification or decisions\n\n**Examples**: Confirmations, clarification requests, approvals\n\n**Why it's useful**: Leverages human judgment for critical situations where AI might not be sufficient.\n\n## Building with the Blueprint\n\nWhen designing agents as graphs:\n\n1. **Start simple**, then add complexity as needed\n2. **Identify natural breakpoints** for different node types\n3. **Plan for failures** with fallbacks and validation\n4. **Balance automation with control** through human touchpoints\n5. **Visualize the flow** to spot bottlenecks or unnecessary complexity\n\nBy thoughtfully combining these node types, we can build AI systems that are more capable, reliable, and aligned with human needs.",
"height": 1940,
"width": 960,
"color": 5
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-2460,
100
],
"id": "97211dd6-aaf1-44b2-a8bd-dee5501b6b41",
"name": "Sticky Note14"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
1320,
320
],
"id": "d45bdd05-775e-42e6-b984-afc4aeab543a",
"name": "When chat message received"
}
],
"connections": {
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent4",
"type": "ai_languageModel",
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},
"When clicking \u2018Test workflow\u2019": {
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"Menu Table": {
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"Postgres Chat Memory": {
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"OpenAI Chat Model8": {
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"OpenAI Chat Model2": {
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"AI Agent3": {
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"Structured Output Parser3": {
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"If1": {
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"Postgres Chat Memory2": {
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"OpenAI Chat Model9": {
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"Postgres Chat Memory4": {
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},
"Call n8n Workflow Tool": {
"ai_tool": [
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"type": "ai_tool",
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},
"When Executed by Another Workflow": {
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{
"node": "Slack",
"type": "main",
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},
"Airtable2": {
"ai_tool": [
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"type": "ai_tool",
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},
"OpenAI Chat Model5": {
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{
"node": "AI Agent",
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"AI Agent": {
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"Postgres Chat Memory5": {
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"Structured Output Parser4": {
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"OpenAI Chat Model13": {
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"Save Memories1": {
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"Get Memories1": {
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"Switch": {
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"Slack8": {
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"OpenAI Chat Model6": {
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"When chat message received": {
"main": [
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{
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}
},
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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.
airtableTokenApigoogleDocsOAuth2ApiopenAiApipostgresslackOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
How this works
This workflow harnesses AI agent nodes to automate intelligent responses in Slack channels, saving teams hours of manual coordination by handling queries and escalations seamlessly. It's designed for support or collaboration teams who rely on Slack for daily communication and want to integrate OpenAI's chat capabilities without building from scratch. The key step involves chaining multiple lmChatOpenAi nodes to process incoming events, route decisions via switches, and trigger targeted Slack messages or errors, ensuring context-aware interactions that adapt to conversation flow.
Use this workflow when your team receives frequent Slack queries needing AI-driven replies, such as customer support tickets or internal FAQs, especially if integrated with tools like Airtable for data lookup. Avoid it for simple notifications without conversational depth, as the 72-node complexity suits advanced scenarios only. Common variations include adding more chainLlm nodes for multi-turn dialogues or swapping Slack for email outputs in non-team environments.
About this workflow
Agent Nodes. Uses lmChatOpenAi, slack, stopAndError, errorTrigger. Event-driven trigger; 72 nodes.
Source: https://github.com/DPabloFlores/ottomator-agents/blob/main/7-node-agent-blueprint/7_Node_Agent_Blueprint_With_Examples.json — original creator credit. Request a take-down →
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