This workflow follows the HTTP Request → Informationextractor 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": "Web Scraper with AI",
"nodes": [
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
192,
-64
],
"id": "fad83590-8568-42a9-b449-3fb77bd1b843",
"name": "When clicking \u2018Execute workflow\u2019"
},
{
"parameters": {
"url": "https://books.toscrape.com",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
416,
-64
],
"id": "fb3f547b-c6b8-4149-8fbd-a8e899d927c7",
"name": "HTTP Request"
},
{
"parameters": {
"options": {}
},
"type": "n8n-nodes-base.convertToFile",
"typeVersion": 1.1,
"position": [
992,
-64
],
"id": "c0d201b0-3726-4beb-91d2-de51e3ddb37c",
"name": "Convert to File"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
720,
160
],
"id": "39dc544b-ca29-43f0-84df-a8e947c54a67",
"name": "Google Gemini Chat Model",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"text": "={{ $json.data }}",
"schemaType": "fromJson",
"jsonSchemaExample": "[\n {\n \"title\": \"Book Title 1\",\n \"url\": \"https://example.com/book1\"\n },\n {\n \"title\": \"Book Title 2\",\n \"url\": \"https://example.com/book2\"\n },\n {\n \"title\": \"Book Title 3\",\n \"url\": \"https://example.com/book3\"\n }\n]\n",
"options": {
"systemPromptTemplate": "You are an expert extraction algorithm.\nOnly extract relevant information from the text.\nIf you do not know the value of an attribute asked to extract, you may omit the attribute's value."
}
},
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"typeVersion": 1.2,
"position": [
640,
-64
],
"id": "b79f969d-ac95-4810-afd5-0c83349cd77d",
"name": "Information Extractor"
}
],
"connections": {
"When clicking \u2018Execute workflow\u2019": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request": {
"main": [
[
{
"node": "Information Extractor",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Information Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Information Extractor": {
"main": [
[
{
"node": "Convert to File",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "b154c0bb-38fb-4f25-9a50-3862710ee1b6",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "mFx1MlePYGPZE2mA",
"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.
googlePalmApi
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About this workflow
Web Scraper with AI. Uses httpRequest, lmChatGoogleGemini, informationExtractor. Event-driven trigger; 5 nodes.
Source: https://github.com/021up/n8n-learning/blob/main/ITHome/d10/Web_Scraper_with_AI.json — original creator credit. Request a take-down →
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