This workflow follows the Chainllm → Execute Workflow Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "My workflow 14",
"nodes": [
{
"parameters": {
"content": "# \ud83d\udcda [Join our Skool community for support, premium content and more!](https://www.skool.com/ai-agents-az/about?w4)\n\n## Be part of a growing community and help us create more content like this",
"height": 220,
"width": 860,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-260,
-420
],
"id": "44f740f1-7849-4d41-bf55-57bb89ad4c08",
"name": "Sticky Note6"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "5c28393f-6e8b-425b-babb-22eac9ad7238",
"name": "GOOGLE_API_KEY",
"value": "YOUR_GOOGLE_API_KEY_COMES_HERE",
"type": "string"
},
{
"id": "7f935132-6cb7-43a4-ae87-77336bd2cf82",
"name": "GOOGLE_CUSTOM_SEARCH",
"value": "YOUR_CUSTOM_SEARCH_ID_COMES_HERE",
"type": "string"
},
{
"id": "a848bf0c-0a5f-4acc-9412-aebd93c84380",
"name": "top_results",
"value": "={{ $json.top_results ?? 3 }}",
"type": "number"
},
{
"id": "c52bbef3-c0a6-4017-a403-abaaee216895",
"name": "context",
"value": "={{ $json.context }}",
"type": "string"
},
{
"id": "ae883a9e-7207-48ef-ad1f-9c86076e0308",
"name": "num_search_terms",
"value": "={{ $json.num_search_terms ?? 2 }}",
"type": "number"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
60,
400
],
"id": "77d185cd-6840-4178-b99d-ecbc681809dc",
"name": "configuration"
},
{
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"search_terms\": {\n \"type\": \"array\",\n \"description\": \"the google search terms\",\n \"items\": {\n \"type\": \"string\"\n }\n }\n },\n \"required\": [\n \"search_terms\"\n ]\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.2,
"position": [
600,
700
],
"id": "ce9663e3-b2fd-4a7f-a155-582882fc44f1",
"name": "Structured Output Parser"
},
{
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
1900,
900
],
"id": "d0d79be5-6a89-498d-91b4-ef33d5546d8f",
"name": "OpenAI Chat Model",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"fieldToSplitOut": "output.search_terms",
"options": {}
},
"type": "n8n-nodes-base.splitOut",
"typeVersion": 1,
"position": [
740,
400
],
"id": "03b39df2-67d3-428c-913e-6d7ccc7a6bda",
"name": "Split Out"
},
{
"parameters": {
"fieldToSplitOut": "items",
"options": {}
},
"type": "n8n-nodes-base.splitOut",
"typeVersion": 1,
"position": [
1180,
400
],
"id": "15cb99a2-74f2-4c16-8032-e3cbbe1c4856",
"name": "Split Out1"
},
{
"parameters": {
"operation": "extractHtmlContent",
"extractionValues": {
"values": [
{
"key": "data",
"cssSelector": "body",
"returnValue": "html"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.html",
"typeVersion": 1.2,
"position": [
2060,
400
],
"id": "2a2020a9-974d-4adc-b1d3-07f0e4cb6978",
"name": "HTML"
},
{
"parameters": {
"html": "={{ $json.data }}",
"options": {}
},
"type": "n8n-nodes-base.markdown",
"typeVersion": 1,
"position": [
2280,
400
],
"id": "035220d2-2759-46b3-ab8d-66f7005d2ff1",
"name": "Markdown"
},
{
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"summary\": {\n \"type\": \"string\",\n \"description\": \"the summary of the content\"\n }\n },\n \"required\": [\n \"summary\"\n ]\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.2,
"position": [
3000,
760
],
"id": "a90ed520-7f70-445c-916a-4a30a46623ae",
"name": "Structured Output Parser1"
},
{
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"relevant_to_context\": {\n \"type\": \"boolean\",\n \"description\": \"whether the researched content is relevant to the context\"\n }\n },\n \"required\": [\n \"relevant_to_article\"\n ]\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.2,
"position": [
3420,
740
],
"id": "d31c2a54-1b14-4d25-a3f0-21146531245d",
"name": "Structured Output Parser2"
},
{
"parameters": {
"aggregate": "aggregateAllItemData",
"destinationFieldName": "research_results",
"options": {}
},
"type": "n8n-nodes-base.aggregate",
"typeVersion": 1,
"position": [
4100,
400
],
"id": "255cd796-6d0f-4197-a4fa-60c85689bbc8",
"name": "Aggregate"
},
{
"parameters": {
"workflowInputs": {
"values": [
{
"name": "top_results",
"type": "number"
},
{
"name": "context"
},
{
"name": "num_search_terms",
"type": "number"
}
]
}
},
"type": "n8n-nodes-base.executeWorkflowTrigger",
"typeVersion": 1.1,
"position": [
-260,
400
],
"id": "642a7a80-84c0-47b3-b8d9-1e751d3152bc",
"name": "When Executed by Another Workflow"
},
{
"parameters": {
"content": "# Configure\n\n- Google API key\n- Google custom search id",
"height": 400,
"color": 3
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
0,
220
],
"id": "0b43d25d-8fa2-4097-8c77-89f088a0b977",
"name": "Sticky Note"
},
{
"parameters": {
"content": "# Google programmable search documentation\n\nhttps://developers.google.com/custom-search/v1/using_rest\nhttps://programmablesearchengine.google.com/controlpanel/all",
"height": 200,
"width": 620
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-260,
-40
],
"id": "6b7ab3e0-54b9-42b3-aa0f-da12b31a8e0e",
"name": "Sticky Note2"
},
{
"parameters": {
"promptType": "define",
"text": "=<Context>\n{{ $json.context }}\n</Context>\n\n<Instructions>\nI want to run a research on Google on the context above. \nHelp me to come up with search terms I can use.\nI need exactly {{ $json.num_search_terms }} search term(s) - no more no less. \nMake sure to be creative, and give me different ones so I can get diverse search results.\n</Instructions>",
"hasOutputParser": true
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.5,
"position": [
380,
400
],
"id": "06920cd4-00a0-494a-abad-71af227500de",
"name": "create search terms"
},
{
"parameters": {
"url": "https://www.googleapis.com/customsearch/v1",
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "key",
"value": "={{ $('configuration').item.json.GOOGLE_API_KEY }}"
},
{
"name": "cx",
"value": "={{ $('configuration').item.json.GOOGLE_CUSTOM_SEARCH }}"
},
{
"name": "q",
"value": "={{ $json['output.search_terms'] }}"
},
{
"name": "num",
"value": "={{ $('configuration').item.json.top_results }}"
},
{
"name": "siteSearch",
"value": "reddit.com"
},
{
"name": "siteSearchFilter",
"value": "e"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
960,
400
],
"id": "3dd1ea7f-8c0d-41f9-a91c-0e9f2026b09b",
"name": "search on Google",
"retryOnFail": true
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "c18ff56b-39fa-477c-a48d-bc65ad0a510d",
"leftValue": "={{ $json.mime }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "notExists",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.filter",
"typeVersion": 2.2,
"position": [
1400,
400
],
"id": "dc0c6d15-b885-430d-a0f6-0f2e7bbd9ca8",
"name": "remove documents"
},
{
"parameters": {
"url": "={{ $json.link }}",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "user-agent",
"value": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1620,
400
],
"id": "b50aa2c5-8fb9-4b37-a8e6-80b00db43922",
"name": "get the content of the link",
"retryOnFail": false,
"onError": "continueErrorOutput"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "99cf6ac1-d77b-491c-86dc-44555032f5b0",
"leftValue": "={{ $json.error }}",
"rightValue": "",
"operator": {
"type": "object",
"operation": "notExists",
"singleValue": true
}
},
{
"id": "e6dd1301-acb8-4dc4-83d0-4d5b1a7f2036",
"leftValue": "={{ $json.data }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "exists",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.filter",
"typeVersion": 2.2,
"position": [
1840,
400
],
"id": "22999b1a-9b5e-47ad-9ca9-5f7050bcc3ad",
"name": "filter out the errors"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "e70a34f7-b723-47fe-a62f-1a318c483959",
"leftValue": "={{ $json.data }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.filter",
"typeVersion": 2.2,
"position": [
2500,
400
],
"id": "35ded490-70d5-49d4-9b10-9d58498c0489",
"name": "filter empty results"
},
{
"parameters": {
"jsCode": "for (const item of $input.all()) {\n item.json.data = item.json.data.replace(/!\\[[^\\]]+\\]\\([^\\)]+\\)/g, \"\") // remove images\n item.json.data = item.json.data.replace(/\\[.*?\\]\\(.*?\\)/g, \"\") // remove links\n item.json.data = item.json.data.replace(/\\n{2,}/g, \"\") // remove extra new line characters\n}\n\nreturn $input.all();"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
2720,
400
],
"id": "e34ff673-58c4-4420-966e-2b5cca101ce7",
"name": "cleanup the markdown"
},
{
"parameters": {
"promptType": "define",
"text": "=I've collected research content using Google search.\n\nRead the research content, and analyze whether it is relevant to the context below.\nMake sure it's also useful, and contains relevant information for my context.\n\n<Context>\n{{ $('configuration').item.json.context }}\n</Context>\n\n<ResearchContentSummary>\n{{ $json.output.summary }}\n</ResearchContentSummary>",
"hasOutputParser": true
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.5,
"position": [
3300,
400
],
"id": "d703961f-4dce-4a9b-85e0-1e716a790663",
"name": "is it relevant?",
"retryOnFail": true
},
{
"parameters": {
"promptType": "define",
"text": "=Please summarize the following content for me. Make sure to capture all the information in a concise format. Don't miss anything important.\nIgnore generic website elements like cookie policies, etc.\n\n<Content>\n{{ $json.data }}\n</Content>",
"hasOutputParser": true
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.5,
"position": [
2940,
400
],
"id": "0ff51b30-b172-476e-8798-d7421d8b5b58",
"name": "summarize",
"retryOnFail": true
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "a72e5161-9b19-45fb-bb4f-5ae28d3da266",
"leftValue": "={{ $json.output.relevant_to_context }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.filter",
"typeVersion": 2.2,
"position": [
3660,
400
],
"id": "4e21d3c2-c059-48e2-ad58-9eeef5e43b9d",
"name": "filter irrelevant"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "53e16d12-8a90-4cf8-85e2-6aa2ef2ae3af",
"name": "summary",
"value": "={{ $('summarize').item.json.output.summary }}",
"type": "string"
},
{
"id": "1ca9f5a5-0e9a-47e6-9fef-079367dc4769",
"name": "title",
"value": "={{ $('remove documents').item.json.title }}",
"type": "string"
},
{
"id": "11c33d6b-d23c-4bc6-9003-b8ca022b3ada",
"name": "link",
"value": "={{ $('remove documents').item.json.link }}",
"type": "string"
},
{
"id": "eea8547b-2e21-4b71-a9dc-74639d658485",
"name": "snippet",
"value": "={{ $('remove documents').item.json.snippet }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
3880,
400
],
"id": "797834a5-9a83-4685-a94c-8cd3e31b596b",
"name": "set fields to return"
},
{
"parameters": {
"content": "# You can replace OpenAI with Ollama!",
"height": 320,
"width": 420
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1760,
740
],
"id": "98bfd96d-8cb6-4bd5-9e56-3a6fa1a648a3",
"name": "Sticky Note1"
}
],
"connections": {
"configuration": {
"main": [
[
{
"node": "create search terms",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "create search terms",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "create search terms",
"type": "ai_languageModel",
"index": 0
},
{
"node": "summarize",
"type": "ai_languageModel",
"index": 0
},
{
"node": "is it relevant?",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Split Out": {
"main": [
[
{
"node": "search on Google",
"type": "main",
"index": 0
}
]
]
},
"Split Out1": {
"main": [
[
{
"node": "remove documents",
"type": "main",
"index": 0
}
]
]
},
"HTML": {
"main": [
[
{
"node": "Markdown",
"type": "main",
"index": 0
}
]
]
},
"Markdown": {
"main": [
[
{
"node": "filter empty results",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser1": {
"ai_outputParser": [
[
{
"node": "summarize",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Structured Output Parser2": {
"ai_outputParser": [
[
{
"node": "is it relevant?",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"When Executed by Another Workflow": {
"main": [
[
{
"node": "configuration",
"type": "main",
"index": 0
}
]
]
},
"create search terms": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"search on Google": {
"main": [
[
{
"node": "Split Out1",
"type": "main",
"index": 0
}
]
]
},
"remove documents": {
"main": [
[
{
"node": "get the content of the link",
"type": "main",
"index": 0
}
]
]
},
"get the content of the link": {
"main": [
[
{
"node": "filter out the errors",
"type": "main",
"index": 0
}
]
]
},
"filter out the errors": {
"main": [
[
{
"node": "HTML",
"type": "main",
"index": 0
}
]
]
},
"filter empty results": {
"main": [
[
{
"node": "cleanup the markdown",
"type": "main",
"index": 0
}
]
]
},
"cleanup the markdown": {
"main": [
[
{
"node": "summarize",
"type": "main",
"index": 0
}
]
]
},
"is it relevant?": {
"main": [
[
{
"node": "filter irrelevant",
"type": "main",
"index": 0
}
]
]
},
"summarize": {
"main": [
[
{
"node": "is it relevant?",
"type": "main",
"index": 0
}
]
]
},
"filter irrelevant": {
"main": [
[
{
"node": "set fields to return",
"type": "main",
"index": 0
}
]
]
},
"set fields to return": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "a4736b82-ed72-48f3-a786-adf8dfce43bd",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "ucEHSGg73IPzhX1n",
"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.
openAiApi
Pro
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About this workflow
My workflow 14. Uses outputParserStructured, lmChatOpenAi, executeWorkflowTrigger, chainLlm. Event-driven trigger; 26 nodes.
Source: https://github.com/Ker102/Kaelux-Automate/blob/main/data/workflows/episodes/episode_4_deep_research.json — original creator credit. Request a take-down →
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