About this recipe
A recipe for Api Schema Extractor
Recipe Template
{
"nodes": [
{
"id": "2498bb93-176f-458c-acee-f541859df770",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
2460,
2820
],
"parameters": [],
"typeVersion": 1
},
{
"id": "c08bcf84-9336-44f9-b452-0c9469f18f48",
"name": "Web Search For API Schema",
"type": "n8n-nodes-base.httpRequest",
"onError": "continueRegularOutput",
"position": [
3100,
3820
],
"parameters": {
"url": "https:\/\/api.apify.com\/v2\/acts\/serping~fast-google-search-results-scraper\/run-sync-get-dataset-items",
"method": "POST",
"options": [],
"sendBody": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "searchTerms",
"value": "={{\n[\n `site:${$json.data.url.replace(\/^http[s]:\\\/\\\/\/, '').replace(\/\\\/$\/, '').replace('www.', '')} \"${$json.data.service}\" api developer (intext:reference OR intext:resource) (-inurl:support OR -inurl:help) (inurl:api OR intitle:api) -filetype:pdf`\n]\n}}"
},
{
"name": "resultsPerPage",
"value": "={{ 10 }}"
}
]
},
"genericAuthType": "httpHeaderAuth"
},
"typeVersion": 4.2
},
{
"id": "d5b19e3a-acd0-4b06-8d77-42de1f797dba",
"name": "Scrape Webpage Contents",
"type": "n8n-nodes-base.httpRequest",
"position": [
3940,
3720
],
"parameters": {
"url": "https:\/\/api.apify.com\/v2\/acts\/apify~web-scraper\/run-sync-get-dataset-items",
"options": {
"batching": {
"batch": {
"batchSize": 2,
"batchInterval": 30000
}
}
},
"jsonBody": "={\n \"startUrls\": [\n {\n \"url\": \"{{ $json.source.link }}\",\n \"method\": \"GET\"\n }\n ],\n \"breakpointLocation\": \"NONE\",\n \"browserLog\": false,\n \"closeCookieModals\": false,\n \"debugLog\": false,\n \"downloadCss\": false,\n \"downloadMedia\": false,\n \"excludes\": [\n {\n \"glob\": \"\/**\/*.{png,jpg,jpeg,pdf}\"\n }\n ],\n \"headless\": true,\n \"ignoreCorsAndCsp\": false,\n \"ignoreSslErrors\": false,\n \n \"injectJQuery\": true,\n \"keepUrlFragments\": false,\n \"linkSelector\": \"a[href]\",\n \"maxCrawlingDepth\": 1,\n \"maxPagesPerCrawl\": 1,\n \"maxRequestRetries\": 1,\n \"maxResultsPerCrawl\": 1,\n \"pageFunction\": \"\/\/ The function accepts a single argument: the \\\"context\\\" object.\\n\/\/ For a complete list of its properties and functions,\\n\/\/ see https:\/\/apify.com\/apify\/web-scraper#page-function \\nasync function pageFunction(context) {\\n\\n await new Promise(res => { setTimeout(res, 6000) });\\n \/\/ This statement works as a breakpoint when you're trying to debug your code. Works only with Run mode: DEVELOPMENT!\\n \/\/ debugger; \\n\\n \/\/ jQuery is handy for finding DOM elements and extracting data from them.\\n \/\/ To use it, make sure to enable the \\\"Inject jQuery\\\" option.\\n const $ = context.jQuery;\\n const title = $('title').first().text();\\n\\n \/\/ Clone the body to avoid modifying the original content\\n const bodyClone = $('body').clone();\\n bodyClone.find('iframe, img, script, style, object, embed, noscript, svg, video, audio').remove();\\n const body = bodyClone.html();\\n\\n \/\/ Return an object with the data extracted from the page.\\n \/\/ It will be stored to the resulting dataset.\\n return {\\n url: context.request.url,\\n title,\\n body\\n };\\n}\",\n \"postNavigationHooks\": \"\/\/ We need to return array of (possibly async) functions here.\\n\/\/ The functions accept a single argument: the \\\"crawlingContext\\\" object.\\n[\\n async (crawlingContext) => {\\n \/\/ ...\\n },\\n]\",\n \"preNavigationHooks\": \"\/\/ We need to return array of (possibly async) functions here.\\n\/\/ The functions accept two arguments: the \\\"crawlingContext\\\" object\\n\/\/ and \\\"gotoOptions\\\".\\n[\\n async (crawlingContext, gotoOptions) => {\\n \/\/ ...\\n },\\n]\\n\",\n \"proxyConfiguration\": {\n \"useApifyProxy\": true\n },\n \"runMode\": \"PRODUCTION\",\n \n \"useChrome\": false,\n \"waitUntil\": [\n \"domcontentloaded\"\n ],\n \"globs\": [],\n \"pseudoUrls\": [],\n \"proxyRotation\": \"RECOMMENDED\",\n \"maxConcurrency\": 50,\n \"pageLoadTimeoutSecs\": 60,\n \"pageFunctionTimeoutSecs\": 60,\n \"maxScrollHeightPixels\": 5000,\n \"customData\": {}\n}",
"sendBody": true,
"sendQuery": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpQueryAuth",
"queryParameters": {
"parameters": [
{
"name": "memory",
"value": "2048"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "5853ba7e-4068-4792-be5c-b8cf81ee89cb",
"name": "Results to List",
"type": "n8n-nodes-base.splitOut",
"position": [
3460,
3720
],
"parameters": {
"options": [],
"fieldToSplitOut": "origin_search.results"
},
"typeVersion": 1
},
{
"id": "8ed2e8ec-b2e3-474b-b19d-f38b518f274b",
"name": "Recursive Character Text Splitter1",
"type": "@n8n\/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
5800,
4020
],
"parameters": {
"options": [],
"chunkSize": 4000
},
"typeVersion": 1
},
{
"id": "e2a8137b-7da3-4032-bca2-c14465356f02",
"name": "Content Chunking @ 50k Chars",
"type": "n8n-nodes-base.set",
"position": [
5380,
3740
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "7753a4f4-3ec2-4c05-81df-3d5e8979a478",
"name": "=data",
"type": "array",
"value": "={{ new Array(Math.round($json.content.length \/ Math.min($json.content.length, 50000))).fill('').map((_,idx) => $json.content.substring(idx * 50000, idx * 50000 + 50000)) }}"
},
{
"id": "7973bcb4-f239-4619-85fc-c76e20386375",
"name": "service",
"type": "string",
"value": "={{ $json.service }}"
},
{
"id": "b46e44bc-ad01-4cf0-8b07-25eeb1fb5874",
"name": "url",
"type": "string",
"value": "={{ $json.url }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "6ef5866a-d992-4472-9221-27efbec8e7be",
"name": "Split Out Chunks",
"type": "n8n-nodes-base.splitOut",
"position": [
5540,
3740
],
"parameters": {
"include": "allOtherFields",
"options": [],
"fieldToSplitOut": "data"
},
"typeVersion": 1
},
{
"id": "5e43b4d8-cebf-43ed-866d-0b4cb2997853",
"name": "Default Data Loader",
"type": "@n8n\/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
5800,
3900
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "service",
"value": "={{ $json.service }}"
},
{
"name": "url",
"value": "={{ $json.url }}"
}
]
}
},
"jsonData": "={{ $json.data }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "d4b34767-be50-44ee-b778-18842034c276",
"name": "Set Embedding Variables",
"type": "n8n-nodes-base.set",
"position": [
4980,
3580
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "4008ae44-7998-4a6f-88c9-686f8b02e92b",
"name": "content",
"type": "string",
"value": "={{ $json.body }}"
},
{
"id": "f7381ac6-ef40-463c-ad2b-df2c31d3e828",
"name": "service",
"type": "string",
"value": "={{ $('EventRouter').first().json.data.service }}"
},
{
"id": "7eae99fd-75c7-4974-a128-641b8ada0cc2",
"name": "url",
"type": "string",
"value": "={{ $json.url }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "109b6c3a-9b16-40cc-9186-5045df387b52",
"name": "Execute Workflow Trigger",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
2420,
4200
],
"parameters": [],
"typeVersion": 1
},
{
"id": "31556ff2-6358-4bd4-8ec4-2797d993256e",
"name": "Execution Data",
"type": "n8n-nodes-base.executionData",
"position": [
2620,
4200
],
"parameters": {
"dataToSave": {
"values": [
{
"key": "eventType",
"value": "={{ $json.eventType }}"
},
{
"key": "executedById",
"value": "={{ $json.executedById }}"
},
{
"key": "service",
"value": "={{ $json.data.service }}"
}
]
}
},
"typeVersion": 1
},
{
"id": "b65b3d4d-f667-4f8f-a06f-847c3d7b83e0",
"name": "EventRouter",
"type": "n8n-nodes-base.switch",
"position": [
2800,
4200
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "research",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.eventType }}",
"rightValue": "research"
}
]
},
"renameOutput": true
},
{
"outputKey": "extraction",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "5418515e-ef6a-42e0-aeb9-8d0d35b898ca",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.eventType }}",
"rightValue": "extract"
}
]
},
"renameOutput": true
},
{
"outputKey": "generate",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0135165e-d211-44f3-92a4-a91858a57d99",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.eventType }}",
"rightValue": "generate"
}
]
},
"renameOutput": true
}
]
},
"options": []
},
"typeVersion": 3.2
},
{
"id": "541f7d9b-c8ff-44dc-8618-8550dbf0b951",
"name": "Google Gemini Chat Model",
"type": "@n8n\/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
4460,
3740
],
"parameters": {
"options": [],
"modelName": "models\/gemini-1.5-flash-latest"
},
"typeVersion": 1
},
{
"id": "617d6139-8417-4ecb-8f7c-558cd1c38ac3",
"name": "Successful Runs",
"type": "n8n-nodes-base.filter",
"position": [
4100,
3720
],
"parameters": {
"options": [],
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "cac77cce-0a5c-469e-ba80-9fb026f04b18",
"operator": {
"type": "string",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $json.body }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2,
"alwaysOutputData": true
},
{
"id": "1115db69-b414-46cd-a9a1-565ae98cbd91",
"name": "For Each Document...",
"type": "n8n-nodes-base.splitInBatches",
"position": [
5180,
3580
],
"parameters": {
"options": []
},
"typeVersion": 3
},
{
"id": "3f0e3764-2479-4d74-aca8-c3e830eac423",
"name": "Embeddings Google Gemini",
"type": "@n8n\/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
5680,
3900
],
"parameters": {
"modelName": "models\/text-embedding-004"
},
"typeVersion": 1
},
{
"id": "87d42766-d1a2-406d-b01c-044fd2fc8910",
"name": "Has API Documentation?",
"type": "@n8n\/n8n-nodes-langchain.textClassifier",
"position": [
4460,
3580
],
"parameters": {
"options": {
"fallback": "discard"
},
"inputText": "={{\n$json.body\n .replaceAll('\\n', '')\n .substring(0, 40000)\n}}",
"categories": {
"categories": [
{
"category": "contains_api_schema_documentation",
"description": "True if this document contains REST API schema documentation or definitions"
}
]
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "55939b49-d91c-42a1-9770-48cbe4008c9a",
"name": "Store Document Embeddings",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
5700,
3740
],
"parameters": {
"mode": "insert",
"options": [],
"qdrantCollection": {
"__rl": true,
"mode": "id",
"value": "={{ $('EventRouter').first().json.data.collection }}"
}
},
"typeVersion": 1
},
{
"id": "3e1da749-b8b9-42cb-818b-eabf4b114abb",
"name": "Embeddings Google Gemini1",
"type": "@n8n\/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
3700,
4520
],
"parameters": {
"modelName": "models\/text-embedding-004"
},
"typeVersion": 1
},
{
"id": "be0906d4-351f-4b3b-9f32-8e5ee68083c5",
"name": "Google Gemini Chat Model1",
"type": "@n8n\/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
4600,
4240
],
"parameters": {
"options": [],
"modelName": "models\/gemini-1.5-pro-002"
},
"typeVersion": 1
},
{
"id": "886415d5-c888-4b97-9fb5-02e6a14df4cc",
"name": "Extract API Operations",
"type": "@n8n\/n8n-nodes-langchain.informationExtractor",
"position": [
4600,
4100
],
"parameters": {
"text": "={{ $json.documents }}",
"options": {
"systemPromptTemplate": "=You have been given an extract of a webpage which should contain a list of web\/REST api operations.\nStep 1. Extract all REST (eg. GET,POST,PUT,DELETE) API operation endpoints from the page content and generate appropriate labels for the resource, operation, description, method for each.\n* \"resource\" refers to the API group, for example: \"\/v1\/api\/indicators\/list\" and \"\/v1\/api\/indicators\/create\" will both have the resource name of \"indicators\". Use the following template \"<domain>\" eg. \"entities\", \"posts\", \"credentials\".\n* \"operation\" refers to the action performed, use the following template \"<verb> <entity>\" eg. \"List entities\", \"Create post\", \"Update credentials\"\n* only use one HTTP verb for \"method\"\n* \"description\" should be limited to one sentence.\n* Examples of API urls: \"\/api\/\", \"\/api\/v1\/\", \"\/v1\/api\". API urls should not end with \"htm\" or html\".\n* Extract a maximum of 15 endpoints.\n* If the page content contains no api operations, return an empty array."
},
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"resource\": { \"type\": \"string\" },\n \"operation\": { \"type\": \"string\" },\n \"description\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\" },\n \"method\": { \"type\": \"string\" },\n \"documentation_url\": { \"type\": \"string\" }\n }\n }\n}"
},
"typeVersion": 1
},
{
"id": "76470e34-7c1f-44ce-81e2-047dcca3fa32",
"name": "Search in Relevant Docs",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
3700,
4380
],
"parameters": {
"mode": "load",
"topK": 5,
"prompt": "={{ $json.query }}",
"options": {
"searchFilterJson": "={{\n{\n \"must\": [\n {\n \"key\": \"metadata.service\",\n \"match\": {\n \"value\": $('EventRouter').first().json.data.service\n }\n }\n ]\n}\n}}"
},
"qdrantCollection": {
"__rl": true,
"mode": "id",
"value": "={{ $('EventRouter').first().json.data.collection }}"
}
},
"typeVersion": 1
},
{
"id": "49ca6a35-5b89-4ed5-bbab-250e09b4222f",
"name": "Wait",
"type": "n8n-nodes-base.wait",
"position": [
3780,
3160
],
"webhookId": "e9ad3ef0-7403-4e65-b0a4-4afdfb0cbc6d",
"parameters": {
"amount": 0
},
"typeVersion": 1.1
},
{
"id": "800cb05b-f5d1-47c8-869e-921915929f34",
"name": "Remove Dupes",
"type": "n8n-nodes-base.removeDuplicates",
"position": [
3780,
3720
],
"parameters": {
"compare": "selectedFields",
"options": [],
"fieldsToCompare": "source.link"
},
"typeVersion": 2
},
{
"id": "d8203c40-aa0b-44b9-8dfd-aea250c8d109",
"name": "Filter Results",
"type": "n8n-nodes-base.filter",
"position": [
3620,
3720
],
"parameters": {
"options": [],
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "42872456-411b-4d86-a9dd-b907d001ea1c",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.type }}",
"rightValue": "normal"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "5714dc09-fd67-4285-9434-ac97cd80dec1",
"name": "Research",
"type": "n8n-nodes-base.executeWorkflow",
"onError": "continueErrorOutput",
"position": [
3460,
2980
],
"parameters": {
"mode": "each",
"options": {
"waitForSubWorkflow": true
},
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}"
}
},
"typeVersion": 1.1
},
{
"id": "2a2d3271-b0b6-4a1a-94e1-9b01399ba88f",
"name": "Has Results?",
"type": "n8n-nodes-base.if",
"position": [
3280,
3820
],
"parameters": {
"options": [],
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "1223d607-45a8-44b1-b510-56fdbe013eba",
"operator": {
"type": "array",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $jmespath($json, 'origin_search.results') }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "b953082c-2d37-4549-80a7-d60535b8580e",
"name": "Response Empty",
"type": "n8n-nodes-base.set",
"position": [
3460,
3900
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "5bb23ce9-eb72-4868-9344-9e5d3952cc52",
"name": "response",
"type": "string",
"value": "no web results"
}
]
}
},
"executeOnce": true,
"typeVersion": 3.4
},
{
"id": "41e9c328-d145-4b71-93bb-e2c448a14be0",
"name": "Response OK",
"type": "n8n-nodes-base.set",
"position": [
5380,
3580
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "79598789-4468-4565-828f-fedc48be15c3",
"name": "response",
"type": "string",
"value": "ok"
}
]
}
},
"executeOnce": true,
"typeVersion": 3.4
},
{
"id": "5d0a7556-def9-4c70-8828-40b4d22904de",
"name": "Combine Docs",
"type": "n8n-nodes-base.aggregate",
"position": [
4020,
4380
],
"parameters": {
"options": [],
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "39bd90b4-e0f5-49b0-b4a7-55a3ae8eccb2",
"name": "Template to List",
"type": "n8n-nodes-base.splitOut",
"position": [
3280,
4200
],
"parameters": {
"options": {
"destinationFieldName": "query"
},
"fieldToSplitOut": "queries"
},
"typeVersion": 1
},
{
"id": "51a1da10-5ad0-4bac-9bec-55b5af3da702",
"name": "Query Templates",
"type": "n8n-nodes-base.set",
"position": [
3100,
4200
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "e2a02550-8f53-4f8d-bb83-68ee3606736e",
"name": "queries",
"type": "array",
"value": "=[\n\"What are the core functionalities, essential features, or primary use cases of {{ $json.data.service }}?\",\n\"Is there an API overview or API categories for {{ $json.data.service }}? What main APIs are listed or mentioned?\",\n\"What industry does {{ $json.data.service }} operate in? What is the most important of the services in the industry? Return the important service as the function.\",\n\"What REST apis (GET, POST, DELETE, PATCH) and\/or operations can you identify for {{ $json.data.service }}?\",\n\"Does {{ $json.data.service }} have any CURL examples? If you can, identify one such example and explain what it does.\"\n]"
}
]
}
},
"executeOnce": true,
"typeVersion": 3.3
},
{
"id": "414091b7-114b-4fc3-9755-2f87cfef239e",
"name": "Google Gemini Chat Model2",
"type": "@n8n\/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
3700,
4240
],
"parameters": {
"options": [],
"modelName": "models\/gemini-1.5-pro-002"
},
"typeVersion": 1
},
{
"id": "1f0f45ff-3bc9-4786-92e1-319244d020c0",
"name": "For Each Template...",
"type": "n8n-nodes-base.splitInBatches",
"position": [
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"parameters": {
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"height": 180,
"content": "## Stage 1 - Research for API Documentation\n- Fetch a list of services pending research from Database (Google Sheet)\n- Uses a search engine (Google) to find API Documentation for each service\n- Uses Webscraper (Apify) to read the contents of search results to filter irrelevant pages\n- Stores webpage contents and metadata into Vector Store (Qdrant)"
},
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},
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"type": "n8n-nodes-base.stickyNote",
"position": [
4000,
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"parameters": {
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"height": 180,
"content": "## Stage 2 - Extract API Operations From Documentation\n- Fetch a list of services pending extraction from Database (Google Sheet)\n- Query Vector store (Qdrant) to figure out service's products, solutions and offerings\n- Query Vector store (Qdrant) again for API documentation relevant to these products, solutions and offerings\n- Extract any API operations found in the API documentation results using LLM (Gemini)\n- Store extracted API operations into Database (Google Sheet)"
},
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},
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"parameters": {
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"height": 180,
"content": "## Stage 3 - Generate Custom Schema From API Operations\n- Fetch a list of services pending generation from Database (Google Sheet)\n- Fetch all API operations for each service from Database (Google Sheet)\n- Use Code node to combine and group all API operations for a service and convert to a custom schema\n- Upload the resulting custom schema to file storage (Google Drive)"
},
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"content": "## Stage 1 - Subworkflow"
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"index": 0
}
]
]
},
"Content Chunking @ 50k Chars": {
"main": [
[
{
"node": "Split Out Chunks",
"type": "main",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "Get All Research",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter1": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
}
}
}How to Use an n8n Template
1
Create a New Workflow
Click "New Workflow" in your n8n dashboard to get started.
2
Copy & Paste Template
First, copy this template:
Click here to copy the JSON
.
Then, in n8n, click the three dots (···) → "Import from file" and paste the JSON code.
3
Customize the Nodes
Go through each node in the workflow to update inputs like spreadsheet IDs, email addresses, or message content. Adjust field mappings to match your data.
4
Grant Access
For nodes that connect to external apps (like Google Sheets or Slack), you'll need to grant access. Connect your accounts using OAuth or an API key and save the credentials in the node.
5
Test It
Run the workflow by clicking "Execute Node" for each step or "Run Once" for the whole thing. Check the right sidebar to inspect data and debug any errors (they'll show up in red).
6
Activate Workflow
Once everything works as expected, click the "Activate" toggle to turn your workflow on. You're all set!