This workflow follows the Googlegemini → HTTP Request 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": "BrightData Flow For Interview Generation",
"nodes": [
{
"parameters": {
"httpMethod": "POST",
"path": "generate-interview-question",
"responseMode": "responseNode",
"options": {}
},
"type": "n8n-nodes-base.webhook",
"typeVersion": 2.1,
"position": [
-832,
96
],
"id": "5f7dae66-36b1-4327-a978-fed32e601724",
"name": "Webhook"
},
{
"parameters": {
"url": "={{ $json.body.resumeUrl }}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
-128,
-176
],
"id": "81c00119-1130-4e10-9771-0e80cd1dc0d1",
"name": "HTTP Request"
},
{
"parameters": {
"operation": "pdf",
"options": {}
},
"type": "n8n-nodes-base.extractFromFile",
"typeVersion": 1,
"position": [
176,
-176
],
"id": "632595b6-a0d2-48c6-b251-0df8e08043e2",
"name": "Extract from File"
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "gpt-4o-mini",
"mode": "list",
"cachedResultName": "GPT-4O-MINI"
},
"messages": {
"values": [
{
"content": "Generate 10 Interview question with their answer depending on user resume data provided by user. Make sure response will be in question and answer field.",
"role": "system"
},
{
"content": "={{ $json.cleanedContent }}"
}
]
},
"jsonOutput": true,
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.openAi",
"typeVersion": 1.8,
"position": [
1344,
-176
],
"id": "a9e2a696-9f4a-44dc-a32c-4f3297d8c9d4",
"name": "Message a model",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1.4,
"position": [
1696,
-176
],
"id": "e96558f2-b4f4-4072-92c6-9a573b74e43c",
"name": "Respond to Webhook"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "2854bb55-f7ee-4308-acb7-dfc53b6794a7",
"leftValue": "={{ $json.body.resumeUrl }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "exists",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
-560,
96
],
"id": "2e9f8040-d550-46f0-88aa-cf6b2e02c99f",
"name": "If"
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "gpt-4o-mini",
"mode": "list",
"cachedResultName": "GPT-4O-MINI"
},
"messages": {
"values": [
{
"content": "Depends on User Job Title and Job Description, generate 10 interview questions. Give me question and answer inside questions object list with field question and answer.",
"role": "system"
},
{
"content": "={{ $json.cleanedContent }}"
}
]
},
"jsonOutput": true,
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.openAi",
"typeVersion": 1.8,
"position": [
368,
352
],
"id": "1bafe0d3-4138-4257-89f4-efb7f985ccc1",
"name": "Message a model1",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"options": {}
},
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1.4,
"position": [
720,
352
],
"id": "23ac5b61-0a6d-4fd3-b6e0-d52675a105d4",
"name": "Respond to Webhook1"
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "models/gemini-1.5-flash",
"mode": "list",
"cachedResultName": "models/gemini-1.5-flash"
},
"messages": {
"values": [
{
"content": "=Extract the following fields from {{ $json.text }}:\n\n- jobTitle: The primary or most recent job title.\n- yoe: Total years of professional experience (YOE).\n- keywords: List of up to 5 relevant skills or technologies found in the resume.\n\nReturn your answer strictly in the following JSON format only with no other fields:\n{\n \"jobTitle\": \"...\",\n \"yoe\": ...,\n \"keywords\": [ ... ]\n}"
}
]
},
"jsonOutput": true,
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.googleGemini",
"typeVersion": 1,
"position": [
384,
-176
],
"id": "30dcbb55-1b58-4b8a-93b3-22f8f710701c",
"name": "Message a model2",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"zone": {
"__rl": true,
"mode": "list",
"value": "web_unlocker1"
},
"country": {
"__rl": true,
"mode": "list",
"value": "us"
},
"url": "=https://www.linkedin.com/jobs/search/?keywords={{ encodeURIComponent($json.jobTitle) }}",
"requestOptions": {}
},
"type": "@brightdata/n8n-nodes-brightdata.brightData",
"typeVersion": 1,
"position": [
896,
-176
],
"id": "f207f94b-8038-46e4-a3fb-2de41b022b83",
"name": "Access and extract data from a specific URL",
"credentials": {
"brightdataApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"instructions": "const text = items[0].json.content.parts[0].text;\nconst arr = JSON.parse(text);\n// Return only the first object\nreturn [{ json: arr[0] }];",
"codeGeneratedForPrompt": "const text = items[0].json.content.parts[0].text;\nconst arr = JSON.parse(text);\n// Return only the first object\nreturn [{ json: arr[0] }];",
"jsCode": "const items = $input.all();\nconst arr = JSON.parse(items[0].json.content.parts[0].text);\nreturn [{ json: arr[0] }];\n"
},
"type": "n8n-nodes-base.aiTransform",
"typeVersion": 1,
"position": [
704,
-176
],
"id": "647ff9fe-1ffc-4332-85c0-f1f3a0e5a45a",
"name": "AI Transform"
},
{
"parameters": {
"jsCode": "const outputItems = [];\n\nfor (const item of $input.all()) {\n let htmlContent;\n \n if (typeof item.json === 'string') {\n htmlContent = item.json;\n } else if (Array.isArray(item.json)) {\n htmlContent = item.json[0]; \n } else if (item.json && typeof item.json === 'object') {\n htmlContent = item.json.html || item.json.body || item.json.content;\n }\n \n if (htmlContent && typeof htmlContent === 'string') {\n const originalSize = htmlContent.length;\n \n htmlContent = htmlContent\n .replace(/<script\\b[^<]*(?:(?!<\\/script>)<[^<]*)*<\\/script>/gi, '')\n .replace(/<style\\b[^<]*(?:(?!<\\/style>)<[^<]*)*<\\/style>/gi, '')\n .replace(/<nav\\b[^<]*(?:(?!<\\/nav>)<[^<]*)*<\\/nav>/gi, '')\n .replace(/<header\\b[^<]*(?:(?!<\\/header>)<[^<]*)*<\\/header>/gi, '')\n .replace(/<footer\\b[^<]*(?:(?!<\\/footer>)<[^<]*)*<\\/footer>/gi, '')\n .replace(/<!--[\\s\\S]*?-->/g, '') \n .replace(/<meta\\b[^>]*>/gi, '') \n .replace(/<link\\b[^>]*>/gi, ''); \n \n \n const cleanText = htmlContent\n .replace(/<[^>]+>/g, ' ')\n .replace(/\\s+/g, ' ') \n .replace(/\\n+/g, ' ') \n .trim();\n \n\n outputItems.push({\n json: {\n cleanedContent: cleanText,\n originalSize: originalSize,\n optimizedSize: cleanText.length,\n compressionRatio: Math.round((1 - cleanText.length / originalSize) * 100) + '%'\n }\n });\n }\n}\n\nreturn outputItems;"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1104,
-176
],
"id": "84b8be9e-5d1e-4a25-b927-5562f8379708",
"name": "Code"
},
{
"parameters": {
"zone": {
"__rl": true,
"mode": "list",
"value": "web_unlocker1"
},
"country": {
"__rl": true,
"mode": "list",
"value": "us"
},
"url": "=https://www.linkedin.com/jobs/search/?keywords={{ encodeURIComponent($json.body.jobTitle) }}",
"requestOptions": {}
},
"type": "@brightdata/n8n-nodes-brightdata.brightData",
"typeVersion": 1,
"position": [
-128,
352
],
"id": "d06863b7-d18a-4ff3-9472-9a4dc1ae2d25",
"name": "Access and extract data from a specific URL2",
"credentials": {
"brightdataApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "const outputItems = [];\n\nfor (const item of $input.all()) {\n let htmlContent;\n \n if (typeof item.json === 'string') {\n htmlContent = item.json;\n } else if (Array.isArray(item.json)) {\n htmlContent = item.json[0]; \n } else if (item.json && typeof item.json === 'object') {\n htmlContent = item.json.html || item.json.body || item.json.content;\n }\n \n if (htmlContent && typeof htmlContent === 'string') {\n const originalSize = htmlContent.length;\n \n htmlContent = htmlContent\n .replace(/<script\\b[^<]*(?:(?!<\\/script>)<[^<]*)*<\\/script>/gi, '')\n .replace(/<style\\b[^<]*(?:(?!<\\/style>)<[^<]*)*<\\/style>/gi, '')\n .replace(/<nav\\b[^<]*(?:(?!<\\/nav>)<[^<]*)*<\\/nav>/gi, '')\n .replace(/<header\\b[^<]*(?:(?!<\\/header>)<[^<]*)*<\\/header>/gi, '')\n .replace(/<footer\\b[^<]*(?:(?!<\\/footer>)<[^<]*)*<\\/footer>/gi, '')\n .replace(/<!--[\\s\\S]*?-->/g, '') \n .replace(/<meta\\b[^>]*>/gi, '') \n .replace(/<link\\b[^>]*>/gi, ''); \n \n \n const cleanText = htmlContent\n .replace(/<[^>]+>/g, ' ')\n .replace(/\\s+/g, ' ') \n .replace(/\\n+/g, ' ') \n .trim();\n \n\n outputItems.push({\n json: {\n cleanedContent: cleanText,\n originalSize: originalSize,\n optimizedSize: cleanText.length,\n compressionRatio: Math.round((1 - cleanText.length / originalSize) * 100) + '%'\n }\n });\n }\n}\n\nreturn outputItems;"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
176,
352
],
"id": "c2b4f827-d805-4975-8d3e-cb003ebece40",
"name": "Code1"
},
{
"parameters": {
"content": "Interview Question Generation by Scraping LinkedIn Based on Info Provided by User",
"height": 128,
"width": 320
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
176,
-400
],
"id": "29b59e35-7d26-4897-88d6-b1c00b38d2ef",
"name": "Sticky Note"
}
],
"connections": {
"Webhook": {
"main": [
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request": {
"main": [
[
{
"node": "Extract from File",
"type": "main",
"index": 0
}
]
]
},
"Extract from File": {
"main": [
[
{
"node": "Message a model2",
"type": "main",
"index": 0
}
]
]
},
"Message a model": {
"main": [
[
{
"node": "Respond to Webhook",
"type": "main",
"index": 0
}
]
]
},
"If": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
}
],
[
{
"node": "Access and extract data from a specific URL2",
"type": "main",
"index": 0
}
]
]
},
"Message a model1": {
"main": [
[
{
"node": "Respond to Webhook1",
"type": "main",
"index": 0
}
]
]
},
"Message a model2": {
"main": [
[
{
"node": "AI Transform",
"type": "main",
"index": 0
}
]
]
},
"Access and extract data from a specific URL": {
"main": [
[
{
"node": "Code",
"type": "main",
"index": 0
}
]
]
},
"AI Transform": {
"main": [
[
{
"node": "Access and extract data from a specific URL",
"type": "main",
"index": 0
}
]
]
},
"Code": {
"main": [
[
{
"node": "Message a model",
"type": "main",
"index": 0
}
]
]
},
"Access and extract data from a specific URL2": {
"main": [
[
{
"node": "Code1",
"type": "main",
"index": 0
}
]
]
},
"Code1": {
"main": [
[
{
"node": "Message a model1",
"type": "main",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "18d4293b-ae39-48cf-89ce-709a2a75d148",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "VG7F4v0oMZqoLQ5r",
"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.
brightdataApigooglePalmApiopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
BrightData Flow For Interview Generation. Uses httpRequest, openAi, googleGemini, @brightdata/n8n-nodes-brightdata. Webhook trigger; 15 nodes.
Source: https://gist.github.com/Arjunhg/2a62ca089cf4f1b3049c7284d77525ec — original creator credit. Request a take-down →
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