Les documents d’urbanisme (permis, plans, attestations) nécessitent des mises à jour régulières. L’automatisation détecte chaque échéance, programme les relances et archive les versions validées pour garantir la conformité réglementaire et préparer les contrôles.
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"name": "Structured Data Extract, Data Mining with Bright Data & Google Gemini",
"tags": [
{
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"name": "Engineering",
"createdAt": "2025-04-09T01:31:00.558Z",
"updatedAt": "2025-04-09T01:31:00.558Z"
},
{
"id": "ddPkw7Hg5dZhQu2w",
"name": "AI",
"createdAt": "2025-04-13T05:38:08.053Z",
"updatedAt": "2025-04-13T05:38:08.053Z"
}
],
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"content": "## NotennThis workflow deals with the structured data extraction by utilizing Bright Data Web Unlocker Product.nnThe Basic LLM Chain, Information Extraction, are being used to demonstrate the usage of the N8N AI capabilities.nn**Please make sure to set the web URL of your interest within the "Set URL and Bright Data Zone" node and update the Webhook Notification URL**"
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"content": "## LLM UsagesnnGoogle Gemini Flash Exp model is being used.nnBasic LLM Chain Data Extractor.nnInformation Extraction is being used for the handling the custom sentiment analysis with the structured response."
},
"typeVersion": 1
},
{
"id": "9795ac80-6ded-465d-bfcf-0c6ce120452f",
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"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
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],
"parameters": {
"text": "=You need to analyze the below markdown and convert to textual data. Please do not output with your own thoughts. Make sure to output with textual data only with no links, scripts, css etc.nn{{ $json.data }}",
"messages": {
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{
"message": "You are a markdown expert"
}
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{
"id": "3aedba66-f447-4d7a-93c0-8158c5e795f9",
"name": "url",
"type": "string",
"value": "https://www.bbc.com/news/world"
},
{
"id": "4e7ee31d-da89-422f-8079-2ff2d357a0ba",
"name": "zone",
"type": "string",
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"value": "={{ $json.output }}"
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"name": "Google Gemini Chat Model for Data Extract",
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"modelName": "models/gemini-2.0-flash-exp"
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"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
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{
"id": "0c1da174-9b9c-4067-9b2c-fa0cc8c33dc8",
"name": "Google Gemini Chat Model for Sentiment Analyzer",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
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],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
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"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
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},
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{
"id": "7fae589c-854d-429e-9e67-527a002fcabf",
"name": "Perform Bright Data Web Request",
"type": "n8n-nodes-base.httpRequest",
"position": [
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],
"parameters": {
"url": "https://api.brightdata.com/request",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "zone",
"value": "={{ $json.zone }}"
},
{
"name": "url",
"value": "={{ $json.url }}?product=unlocker&method=api"
},
{
"name": "format",
"value": "raw"
},
{
"name": "data_format",
"value": "markdown"
}
]
},
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
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"name": "Header Auth account"
}
},
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{
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"name": "Topic Extractor with the structured response",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
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],
"parameters": {
"text": "=Perform the topic analysis on the below content and output with the structured information.nnHere's the content:nn{{ $('Perform Bright Data Web Request').item.json.data }}",
"options": {
"systemPromptTemplate": "You are an expert data analyst."
},
"schemaType": "manual",
"inputSchema": "{n "$schema": "http://json-schema.org/draft-07/schema#",n "title": "TopicModelingResponseArray",n "type": "array",n "items": {n "type": "object",n "properties": {n "topic": {n "type": "string",n "description": "The identified topic or theme derived from the input text."n },n "score": {n "type": "number",n "minimum": 0,n "maximum": 1,n "description": "Confidence score representing how strongly this topic is reflected in the content."n },n "summary": {n "type": "string",n "description": "Brief explanation of the topicu2019s context within the text."n },n "keywords": {n "type": "array",n "description": "List of keywords associated with the topic.",n "items": {n "type": "string"n }n }n },n "required": ["topic", "score", "summary", "keywords"],n "additionalProperties": falsen }n}n"
},
"typeVersion": 1
},
{
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"name": "Trends by location and category with the structured response",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
1236,
-520
],
"parameters": {
"text": "=Perform the data analysis on the below content and output with the structured information by clustering the emerging trends by location and categorynnHere's the content:nn{{ $('Perform Bright Data Web Request').item.json.data }}",
"options": {
"systemPromptTemplate": "You are an expert data analyst."
},
"schemaType": "manual",
"inputSchema": "{n "$schema": "http://json-schema.org/draft-07/schema#",n "title": "EmergingTrendsClusteredByLocationAndCategory",n "type": "array",n "items": {n "type": "object",n "properties": {n "location": {n "type": "string",n "description": "Geographical region or city where the trend is observed."n },n "category": {n "type": "string",n "description": "Domain or industry related to the trend (e.g., Technology, Finance, Healthcare)."n },n "trends": {n "type": "array",n "items": {n "type": "object",n "properties": {n "trend": {n "type": "string",n "description": "A concise label for the emerging trend."n },n "score": {n "type": "number",n "minimum": 0,n "maximum": 1,n "description": "Confidence or prominence score of the trend."n },n "summary": {n "type": "string",n "description": "Short explanation describing the context and impact of the trend."n },n "mentions": {n "type": "array",n "items": {n "type": "string"n },n "description": "Keywords or phrases that commonly co-occur with the trend."n }n },n "required": ["trend", "score", "summary", "mentions"],n "additionalProperties": falsen }n }n },n "required": ["location", "category", "trends"],n "additionalProperties": falsen }n}n"
},
"typeVersion": 1
},
{
"id": "92203e9f-cf13-435e-bf78-3c39a6e1e6f6",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1324,
-300
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "1a252b74-6768-41a6-99dd-090e35c47065",
"name": "Initiate a Webhook Notification for trends by location and category",
"type": "n8n-nodes-base.httpRequest",
"position": [
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],
"parameters": {
"url": "https://webhook.site/3c36d7d1-de1b-4171-9fd3-643ea2e4dd76",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "summary",
"value": "={{ $json.output }}"
}
]
}
},
"typeVersion": 4.2
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{
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"name": "Create a binary file for topics",
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],
"parameters": {
"functionCode": "items[0].binary = {n data: {n data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')n }n};nreturn items;"
},
"typeVersion": 1
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{
"id": "2cf80339-0927-4f48-a13a-c610eaf4edca",
"name": "Write the topics file to disk",
"type": "n8n-nodes-base.readWriteFile",
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"parameters": {
"options": {},
"fileName": "d:\topics.json",
"operation": "write"
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"typeVersion": 1
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{
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"name": "Write the trends file to disk",
"type": "n8n-nodes-base.readWriteFile",
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"parameters": {
"options": {},
"fileName": "d:\trends.json",
"operation": "write"
},
"typeVersion": 1
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{
"id": "d38ca005-6ba3-4105-9fcd-058602ba16ce",
"name": "Create a binary data for tends",
"type": "n8n-nodes-base.function",
"position": [
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],
"parameters": {
"functionCode": "items[0].binary = {n data: {n data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')n }n};nreturn items;"
},
"typeVersion": 1
}
],
"active": false,
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"versionId": "6a81579d-1f3b-4ea2-821b-fff07b32ee7d",
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"Perform Bright Data Web Request": {
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},
"When clicking u2018Test workflowu2019": {
"main": [
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{
"node": "Set URL and Bright Data Zone",
"type": "main",
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}
]
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"Markdown to Textual Data Extractor": {
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"node": "Initiate a Webhook Notification for Markdown to Textual Data Extraction",
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{
"node": "Trends by location and category with the structured response",
"type": "main",
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},
"Google Gemini Chat Model for Data Extract": {
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"node": "Markdown to Textual Data Extractor",
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}
]
]
},
"Topic Extractor with the structured response": {
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"node": "Initiate a Webhook Notification for AI Sentiment Analyzer",
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{
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}
]
]
}
}
}