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n8n-workflows/workflows/API Schema Extractor.json
Eliad Shahar 136eca34eb adding the workflow collection to git
2025-05-14 11:58:29 +03:00

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{
"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": [
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],
"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": [
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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": [
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],
"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": [
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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": [
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],
"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": [
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],
"parameters": {
"compare": "selectedFields",
"options": {},
"fieldsToCompare": "source.link"
},
"typeVersion": 2
},
{
"id": "d8203c40-aa0b-44b9-8dfd-aea250c8d109",
"name": "Filter Results",
"type": "n8n-nodes-base.filter",
"position": [
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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": [
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],
"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": [
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],
"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",
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],
"parameters": {
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"assignments": [
{
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"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": [
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4380
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "39bd90b4-e0f5-49b0-b4a7-55a3ae8eccb2",
"name": "Template to List",
"type": "n8n-nodes-base.splitOut",
"position": [
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],
"parameters": {
"options": {
"destinationFieldName": "query"
},
"fieldToSplitOut": "queries"
},
"typeVersion": 1
},
{
"id": "51a1da10-5ad0-4bac-9bec-55b5af3da702",
"name": "Query Templates",
"type": "n8n-nodes-base.set",
"position": [
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],
"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
},
{
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"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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"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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"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 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
}
]
]
}
}
}
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