This workflow follows the Chat Trigger → Execute Workflow 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 →
{
"meta": {
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "be902a85-fc31-442c-b308-a2350ec5aabb",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-760,
440
],
"parameters": {},
"typeVersion": 1
},
{
"id": "d229b686-9de4-4633-9dba-3e1fe71eedf1",
"name": "No Operation, do nothing1",
"type": "n8n-nodes-base.noOp",
"position": [
1820,
800
],
"parameters": {},
"typeVersion": 1
},
{
"id": "f583bc97-8da8-488e-ab04-5167dc7a7701",
"name": "Information Extractor",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
2420,
540
],
"parameters": {
"text": "={{ $json.buffer.reverse().toJsonString() }}",
"options": {
"systemPromptTemplate": "Eres un experto extrayendo informaci\u00f3n, tu objetivo es recolectar todos los mensajes. Procura no dejar duplicados. como resultado debes retornar un solo p\u00e1rrafo con todo los mensajes."
},
"schemaType": "fromJson",
"jsonSchemaExample": "{\n\t\"message\": \"all consolidated messages\"\n}"
},
"typeVersion": 1
},
{
"id": "5b719416-4886-4d38-9d00-30b6237db168",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
2440,
760
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-nano",
"cachedResultName": "gpt-4.1-nano"
},
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "3d149fc0-caa7-4361-9bf9-33b6252b39eb",
"name": "get wait seconds",
"type": "n8n-nodes-base.code",
"position": [
-260,
500
],
"parameters": {
"jsCode": "// Function: Compute waitSeconds\nconst wordCount = $json.message.split(' ').filter(w=>w).length;\nreturn [{ json: { \n context_id: $json.context_id,\n message: $json.message,\n waitSeconds: wordCount < 5 ? 45 : 30 \n}}];\n"
},
"typeVersion": 2
},
{
"id": "cc670735-d126-465f-b0a3-3a4c5e390fd7",
"name": "Set last_seen",
"type": "n8n-nodes-base.redis",
"position": [
280,
380
],
"parameters": {
"key": "=last_seen:{{ $json.context_id}}",
"ttl": "={{ $json.waitSeconds + 60 }}",
"value": "={{$now.toMillis()}}",
"expire": true,
"keyType": "string",
"operation": "set"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "20d97d1d-70d4-4c3c-aa12-b1aa31795240",
"name": "Get waiting_reply",
"type": "n8n-nodes-base.redis",
"position": [
180,
780
],
"parameters": {
"key": "=waiting_reply:{{$json.context_id}}",
"options": {},
"operation": "get",
"propertyName": "waiting_reply"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "7a2fc681-692f-4f72-9fab-f3ada4bda54b",
"name": "Mod input",
"type": "n8n-nodes-base.set",
"position": [
340,
800
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "7ff99444-753d-4ef7-865c-7115761526b8",
"name": "waiting_reply",
"type": "string",
"value": "={{ $json.waiting_reply }}"
},
{
"id": "58ad6981-c35a-4dd6-b1cd-7c446b85e738",
"name": "context_id",
"type": "string",
"value": "={{$('When Executed by Another Workflow').item.json.context_id }}"
},
{
"id": "bd0535a2-be03-436b-8a2e-222c3e26fd04",
"name": "message",
"type": "string",
"value": "={{$('When Executed by Another Workflow').item.json.message }}"
},
{
"id": "2f583f32-f231-4407-b773-c08b38d464f0",
"name": "waitSeconds",
"type": "number",
"value": "={{ $('get wait seconds').item.json.waitSeconds }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "84213bef-32be-4cd9-8387-cd76aff5cb38",
"name": "waiting_reply?",
"type": "n8n-nodes-base.if",
"position": [
540,
800
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "8136ea21-d798-41fd-81ed-5c0e7fda73c5",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.waiting_reply != null}}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "a8472217-aa83-4247-9d7d-3a471e24478a",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-740,
640
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "ba4c81ba-92e2-4bef-a9e2-6f8d4c0aa722",
"name": "Set waiting_reply",
"type": "n8n-nodes-base.redis",
"position": [
840,
720
],
"parameters": {
"key": "=waiting_reply:{{ $json.context_id }}",
"ttl": "={{ $json.waitSeconds }}",
"value": "true",
"expire": true,
"operation": "set"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "0ce783b6-b76b-4a5d-96ae-11708b7532ba",
"name": "Get buffer",
"type": "n8n-nodes-base.redis",
"position": [
1820,
600
],
"parameters": {
"key": "=buffer_in:{{ $('get wait seconds').item.json.context_id }}",
"options": {},
"operation": "get",
"propertyName": "buffer"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "21864061-1d1f-4528-a03f-1237e9c69a31",
"name": "Delete buffer_in",
"type": "n8n-nodes-base.redis",
"position": [
2940,
680
],
"parameters": {
"key": "=buffer_in:{{$json.context_id}}",
"operation": "delete"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "8828aa7b-6153-4677-84a8-3ef2f884792c",
"name": "Delete waiting_reply",
"type": "n8n-nodes-base.redis",
"position": [
2940,
840
],
"parameters": {
"key": "=waiting_reply:{{$json.context_id}}",
"operation": "delete"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "fc369067-7213-4d8c-b515-c34c4db997e4",
"name": "WaitSeconds",
"type": "n8n-nodes-base.wait",
"position": [
1020,
720
],
"parameters": {
"amount": "={{ $json.waitSeconds }} "
},
"typeVersion": 1.1
},
{
"id": "2daa2ab9-756a-4fdb-8573-b4570c58d6e5",
"name": "Buffer messages",
"type": "n8n-nodes-base.redis",
"position": [
-40,
440
],
"parameters": {
"list": "=buffer_in:{{$json.context_id}}",
"operation": "push",
"messageData": "={\"text\": \"{{ $json.message }}\", \"timestamp\": \"{{$now}}\"}"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "4d5bc5f0-11ce-4f7f-b44b-0514a5ab5671",
"name": "Set buffer_count increment",
"type": "n8n-nodes-base.redis",
"position": [
280,
560
],
"parameters": {
"key": "=buffer_count:{{$json.context_id}}",
"expire": "={{$json.waitSeconds + 60}}",
"operation": "incr"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "dcaee1a8-ea32-4a9d-b32f-f0418644027c",
"name": "Get last_seen",
"type": "n8n-nodes-base.redis",
"position": [
1220,
720
],
"parameters": {
"key": "=last_seen:{{$json.context_id}}",
"options": {},
"operation": "get",
"propertyName": "last_seen"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "908c4a4c-1c60-4e90-827a-064a0b4d6bfd",
"name": "Get buffer_count",
"type": "n8n-nodes-base.redis",
"position": [
1400,
720
],
"parameters": {
"key": "=buffer_count:{{ $('Mod input').item.json.context_id }}",
"options": {},
"operation": "get",
"propertyName": "count"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "1ceb472b-3944-4d74-994b-867ade006e4e",
"name": "Map ouput",
"type": "n8n-nodes-base.set",
"position": [
3140,
380
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "e8d80ab4-74a2-4c30-8500-8dddc5802eec",
"name": "message",
"type": "string",
"value": "={{ $json.output.message }}"
},
{
"id": "7e7fcee4-14b3-4393-b516-b07a53c018b3",
"name": "context_id",
"type": "string",
"value": "={{$('get wait seconds').item.json.context_id }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "0be7e5eb-1972-4a95-b5bf-4e564fc4ef7c",
"name": "Check Inactivity + Count",
"type": "n8n-nodes-base.if",
"position": [
1580,
720
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "0f294c51-0629-4ae1-a009-68c2f5fd30b5",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{$json.count != null && Number($json.count) >= 1}}",
"rightValue": ""
},
{
"id": "1626238d-fb00-4ce8-89df-a40a4f29f52a",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{$('Get last_seen').item.json.last_seen != null}}",
"rightValue": ""
},
{
"id": "df819099-1f6e-4bee-a017-32b729c836a3",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{($now.toMillis() - $('Get last_seen').item.json.last_seen) >= $('Mod input').item.json.waitSeconds * 1000}}",
"rightValue": ""
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2
},
{
"id": "0c3bd62b-8cf6-4b34-8010-ebe819db9667",
"name": "Delete waiting_reply1",
"type": "n8n-nodes-base.redis",
"position": [
2940,
1000
],
"parameters": {
"key": "=buffer_count:{{$json.context_id}}",
"operation": "delete"
},
"credentials": {
"redis": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "bbf45966-833b-4f5f-ae11-0578614eb156",
"name": "No Operation, do nothing2",
"type": "n8n-nodes-base.noOp",
"position": [
720,
540
],
"parameters": {},
"typeVersion": 1
},
{
"id": "5683eebf-ba51-4a6b-a803-de6acf1b1ea8",
"name": "Wait",
"type": "n8n-nodes-base.wait",
"position": [
2080,
880
],
"parameters": {
"amount": "={{ Math.max(0, Math.ceil(( $('Mod input').item.json.waitSeconds * 1000 - ($now.toMillis() - $('Get last_seen').item.json.last_seen)) / 1000)) }}"
},
"typeVersion": 1.1
},
{
"id": "c0478f60-944e-4c85-bb9c-9abe0d4238c0",
"name": "When Executed by Another Workflow",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
-480,
720
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "context_id"
},
{
"name": "message"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "91a650b7-ddd4-4dbf-a300-523f72f0bdb5",
"name": "Mock input data",
"type": "n8n-nodes-base.set",
"position": [
-500,
500
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "0543fdb7-4a22-4530-bdb7-ae7064732fae",
"name": "context_id",
"type": "string",
"value": "={{ $json.sessionId1 || '1lap075ha12' }}"
},
{
"id": "bead5646-a689-4deb-8f4b-b22aa97b51ca",
"name": "message",
"type": "string",
"value": "={{ $json.chatInput || 'Chat 2'}}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "cb450e32-7e19-469c-9a5c-3d9da5bf1dfa",
"name": "No Operation, do nothing3",
"type": "n8n-nodes-base.noOp",
"position": [
3320,
840
],
"parameters": {},
"typeVersion": 1
},
{
"id": "b463e405-3355-48a2-a043-42941d7025c3",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
2880,
660
],
"parameters": {
"color": 7,
"width": 700,
"height": 780,
"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n### \ud83e\uddf9 Buffer Cleanup\n\nAfter consolidation and reply:\n\n* **DELETE** keys:\n\n * `buffer_in:{{context_id}}`\n * `buffer_count:{{context_id}}`\n * `waiting_reply:{{context_id}}`\n"
},
"typeVersion": 1
},
{
"id": "1b5397f8-aa7e-4b2b-afb9-5da97d99e049",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-80,
60
],
"parameters": {
"color": 7,
"width": 920,
"height": 940,
"content": "### \ud83d\udce5 Input Buffer\n\n1. **Save incoming message**\n\n * Push the new message into Redis list `buffer_in:{{context_id}}`.\n2. **Update metadata**\n\n * Set `last_seen:{{context_id}}` to the current timestamp (with a TTL of `waitSeconds + 60`).\n * INCR the counter key `buffer_count:{{context_id}}` (also expiring after `waitSeconds + 60`).\n3. **Check \u201cwaiting\u201d flag**\n\n * GET `waiting_reply:{{context_id}}`.\n * If it\u2019s null (no batch in flight), SET it to `true` with TTL `waitSeconds` to block concurrent triggers."
},
"typeVersion": 1
},
{
"id": "edc07500-ccad-4e72-adc1-1a63a3a06609",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1180,
340
],
"parameters": {
"color": 7,
"width": 1200,
"height": 820,
"content": "### \u23f3 Inactivity & Threshold Check\n\n1. **Fetch state**\n\n * GET `last_seen:{{context_id}}` (when the last message arrived)\n * GET `buffer_count:{{context_id}}` (how many messages are queued)\n2. **Evaluate trigger**\n\n * **Inactivity:** `(now \u2013 last_seen) \u2265 waitSeconds * 1000`\n * **Or threshold:** `buffer_count \u2265 1` (or your desired batch size)\n3. **Branch**\n\n * **True:** proceed to \u201cGet buffer\u201d and consolidate.\n * **False:** exit (noOp) and let the waiting\u2010node/flag mechanism retry later."
},
"typeVersion": 1
}
],
"connections": {
"Wait": {
"main": [
[
{
"node": "Check Inactivity + Count",
"type": "main",
"index": 0
}
]
]
},
"Map ouput": {
"main": [
[]
]
},
"Mod input": {
"main": [
[
{
"node": "waiting_reply?",
"type": "main",
"index": 0
}
]
]
},
"Get buffer": {
"main": [
[
{
"node": "Information Extractor",
"type": "main",
"index": 0
}
]
]
},
"WaitSeconds": {
"main": [
[
{
"node": "Get last_seen",
"type": "main",
"index": 0
}
]
]
},
"Get last_seen": {
"main": [
[
{
"node": "Get buffer_count",
"type": "main",
"index": 0
}
]
]
},
"Set last_seen": {
"main": [
[
{
"node": "No Operation, do nothing2",
"type": "main",
"index": 0
}
]
]
},
"waiting_reply?": {
"main": [
[
{
"node": "No Operation, do nothing2",
"type": "main",
"index": 0
}
],
[
{
"node": "Set waiting_reply",
"type": "main",
"index": 0
}
]
]
},
"Buffer messages": {
"main": [
[
{
"node": "Set buffer_count increment",
"type": "main",
"index": 0
},
{
"node": "Set last_seen",
"type": "main",
"index": 0
},
{
"node": "Get waiting_reply",
"type": "main",
"index": 0
}
]
]
},
"Mock input data": {
"main": [
[
{
"node": "get wait seconds",
"type": "main",
"index": 0
}
]
]
},
"Delete buffer_in": {
"main": [
[
{
"node": "No Operation, do nothing3",
"type": "main",
"index": 0
}
]
]
},
"Get buffer_count": {
"main": [
[
{
"node": "Check Inactivity + Count",
"type": "main",
"index": 0
}
]
]
},
"get wait seconds": {
"main": [
[
{
"node": "Buffer messages",
"type": "main",
"index": 0
}
]
]
},
"Get waiting_reply": {
"main": [
[
{
"node": "Mod input",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Information Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Set waiting_reply": {
"main": [
[
{
"node": "WaitSeconds",
"type": "main",
"index": 0
}
]
]
},
"Delete waiting_reply": {
"main": [
[
{
"node": "No Operation, do nothing3",
"type": "main",
"index": 0
}
]
]
},
"Delete waiting_reply1": {
"main": [
[
{
"node": "No Operation, do nothing3",
"type": "main",
"index": 0
}
]
]
},
"Information Extractor": {
"main": [
[
{
"node": "Map ouput",
"type": "main",
"index": 0
},
{
"node": "Delete buffer_in",
"type": "main",
"index": 0
},
{
"node": "Delete waiting_reply",
"type": "main",
"index": 0
},
{
"node": "Delete waiting_reply1",
"type": "main",
"index": 0
}
]
]
},
"Check Inactivity + Count": {
"main": [
[
{
"node": "Get buffer",
"type": "main",
"index": 0
}
],
[
{
"node": "No Operation, do nothing1",
"type": "main",
"index": 0
}
]
]
},
"No Operation, do nothing1": {
"main": [
[
{
"node": "Wait",
"type": "main",
"index": 0
}
]
]
},
"Set buffer_count increment": {
"main": [
[
{
"node": "No Operation, do nothing2",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Mock input data",
"type": "main",
"index": 0
}
]
]
},
"When Executed by Another Workflow": {
"main": [
[
{
"node": "get wait seconds",
"type": "main",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "Mock input data",
"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.
openAiApiredis
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How this works
This workflow enables you to pause automation processes intelligently by waiting for specific conditions in Redis, ensuring timely responses without constant polling. It's ideal for developers and teams building event-driven systems, such as chatbots or real-time notifications, where delays need to be dynamic based on user interactions. The key step involves extracting information from incoming events via the Information Extractor node, then using OpenAI's chat model to calculate optimal wait times before storing and checking states in Redis, streamlining complex, responsive chains.
Use this workflow when handling asynchronous replies in AI-powered applications, like moderating user queries in a support system, to avoid unnecessary resource drain. Avoid it for simple, linear tasks without state management needs, as the 30-node complexity suits advanced scenarios only. Common variations include integrating with chatTrigger for live messaging or executeWorkflowTrigger to chain into larger automations.
About this workflow
Wait Redis. Uses manualTrigger, noOp, informationExtractor, lmChatOpenAi. Event-driven trigger; 30 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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