LinkedIn个人资料提取与JSON简历构建（Bright Data与Google Gemini）
高级
这是一个HR, AI领域的自动化工作流，包含 19 个节点。主要使用 Set, Code, Function, HttpRequest, ManualTrigger 等节点，结合人工智能技术实现智能自动化。 LinkedIn个人资料提取与JSON简历构建（Bright Data与Google Gemini）
前置要求
- •可能需要目标 API 的认证凭证
- •Google Gemini API Key
使用的节点 (19)
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"id": "V9lUeUsju5cwwmNc",
"meta": {
"instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
"templateCredsSetupCompleted": true
},
"name": "LinkedIn 个人资料提取并使用 Bright Data 和 Google Gemini 构建 JSON 简历",
"tags": [
{
"id": "Kujft2FOjmOVQAmJ",
"name": "Engineering",
"createdAt": "2025-04-09T01:31:00.558Z",
"updatedAt": "2025-04-09T01:31:00.558Z"
},
{
"id": "ZOwtAMLepQaGW76t",
"name": "Building Blocks",
"createdAt": "2025-04-13T15:23:40.462Z",
"updatedAt": "2025-04-13T15:23:40.462Z"
},
{
"id": "ddPkw7Hg5dZhQu2w",
"name": "AI",
"createdAt": "2025-04-13T05:38:08.053Z",
"updatedAt": "2025-04-13T05:38:08.053Z"
},
{
"id": "rKOa98eAi3IETrLu",
"name": "HR",
"createdAt": "2025-04-13T04:59:30.580Z",
"updatedAt": "2025-04-13T04:59:30.580Z"
}
],
"nodes": [
{
"id": "0bac88f2-4912-4b1e-b511-aab2c3b34db9",
"name": "当点击“测试工作流”时",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-580,
-140
],
"parameters": {},
"typeVersion": 1
},
{
"id": "df338f53-cb90-4529-befb-382735043ec2",
"name": "设置 URL 和 Bright Data 区域",
"type": "n8n-nodes-base.set",
"position": [
-360,
-140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "3aedba66-f447-4d7a-93c0-8158c5e795f9",
"name": "url",
"type": "string",
"value": "https://www.linkedin.com/in/ranjan-dailata"
},
{
"id": "4e7ee31d-da89-422f-8079-2ff2d357a0ba",
"name": "zone",
"type": "string",
"value": "web_unlocker1"
},
{
"id": "20518160-df56-49fe-9a42-05e9f9d743a5",
"name": "webhook_notification_url",
"type": "string",
"value": "https://webhook.site/c9118da2-1c54-460f-a83a-e5131b7098db"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "e3a859aa-b330-4ae5-b0fb-7cd621be6fb3",
"name": "执行 Bright Data Web 请求",
"type": "n8n-nodes-base.httpRequest",
"position": [
-140,
-140
],
"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 }}"
},
{
"name": "format",
"value": "raw"
},
{
"name": "data_format",
"value": "markdown"
}
]
},
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "078d4a98-9c45-4370-a579-06450798f1a1",
"name": "Markdown 到文本数据提取器",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
80,
-140
],
"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.\n\n{{ $json.data }}",
"messages": {
"messageValues": [
{
"message": "You are a markdown expert"
}
]
},
"promptType": "define"
},
"retryOnFail": true,
"typeVersion": 1.6
},
{
"id": "2ba19dce-4f9a-439d-b7ae-d701ddb03616",
"name": "用于 Markdown 到文本的 Google Gemini 聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
100,
80
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "a45dbef9-58f3-4730-8e1b-83419e1efc85",
"name": "技能提取器",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
456,
-440
],
"parameters": {
"text": "=Perform Data Mining and extract the skills from the provided resume\n\n {{ $json.text }}",
"options": {},
"schemaType": "manual",
"inputSchema": "{\n\t\"type\": \"array\",\n\t\"properties\": {\n\t\t\"skill\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n \"desc\": {\n\t\t\t\"type\": \"string\"\n\t\t}\n\t}\n}"
},
"retryOnFail": true,
"typeVersion": 1
},
{
"id": "955af989-3590-49ae-90be-df6424200e42",
"name": "用于技能提取器的 Google Gemini 聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
544,
-220
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "5c32bdeb-666b-4a0f-9722-0c62ec95ac9e",
"name": "为结构化数据提取创建二进制数据",
"type": "n8n-nodes-base.function",
"position": [
1052,
-40
],
"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
},
{
"id": "b9e899f3-a1a4-4dce-af96-1814fb3c03b7",
"name": "将结构化内容写入磁盘",
"type": "n8n-nodes-base.readWriteFile",
"position": [
1280,
-40
],
"parameters": {
"options": {},
"fileName": "=d:\\Json_Resume.json",
"operation": "write"
},
"typeVersion": 1
},
{
"id": "db74b347-713e-4ff6-9783-1d3f6b1895a6",
"name": "为结构化数据启动 Webhook 通知",
"type": "n8n-nodes-base.httpRequest",
"position": [
1060,
160
],
"parameters": {
"url": "={{ $('Set URL and Bright Data Zone').item.json.webhook_notification_url }}",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "json_resume",
"value": "={{ $('JSON Resume Extractor').item.json.output.toJsonString() }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "29d27cef-c868-4552-ab41-08276f56e6f9",
"name": "将结构化技能内容写入磁盘",
"type": "n8n-nodes-base.readWriteFile",
"position": [
1060,
-340
],
"parameters": {
"options": {},
"fileName": "=d:\\Resume_Skills.json",
"operation": "write"
},
"typeVersion": 1
},
{
"id": "c7a77bd9-955c-45ec-b6d7-e10717eda093",
"name": "为结构化技能提取创建二进制数据",
"type": "n8n-nodes-base.function",
"position": [
832,
-340
],
"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
},
{
"id": "46dc726e-c939-466b-b834-83f0aed2c95c",
"name": "便签4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-140,
-420
],
"parameters": {
"color": 5,
"width": 440,
"height": 240,
"content": "## LLM 使用"
},
"typeVersion": 1
},
{
"id": "a100ebc9-9253-4e80-93d9-60174a08e7d9",
"name": "便利贴5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-580,
-780
],
"parameters": {
"color": 7,
"width": 400,
"height": 340,
"content": "## 徽标"
},
"typeVersion": 1
},
{
"id": "097e223c-61e2-4c01-ab8c-3eb2cc48b165",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-580,
-420
],
"parameters": {
"width": 400,
"height": 240,
"content": "## 注意"
},
"typeVersion": 1
},
{
"id": "8260cf1a-bd5e-4c05-a898-e7f74ff1d268",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
360,
-520
],
"parameters": {
"color": 7,
"width": 1100,
"height": 960,
"content": "## 使用 LLM 进行结构化数据提取"
},
"typeVersion": 1
},
{
"id": "e06fcc12-c264-439f-84f2-1988587e21c6",
"name": "JSON 简历提取器",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
460,
80
],
"parameters": {
"text": "=Extract the resume in JSON format.\n {{ $json.text }}",
"options": {},
"schemaType": "manual",
"inputSchema": "{\n \"$schema\": \"http://json-schema.org/draft-07/schema#\",\n \"title\": \"JSON Resume\",\n \"type\": \"object\",\n \"properties\": {\n \"basics\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"label\": { \"type\": \"string\" },\n \"image\": { \"type\": \"string\", \"format\": \"uri\" },\n \"email\": { \"type\": \"string\", \"format\": \"email\" },\n \"phone\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" },\n \"summary\": { \"type\": \"string\" },\n \"location\": {\n \"type\": \"object\",\n \"properties\": {\n \"address\": { \"type\": \"string\" },\n \"postalCode\": { \"type\": \"string\" },\n \"city\": { \"type\": \"string\" },\n \"countryCode\": { \"type\": \"string\" },\n \"region\": { \"type\": \"string\" }\n }\n },\n \"profiles\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"network\": { \"type\": \"string\" },\n \"username\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" }\n }\n }\n }\n }\n },\n \"work\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"position\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" },\n \"startDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"endDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"summary\": { \"type\": \"string\" },\n \"highlights\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"volunteer\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"organization\": { \"type\": \"string\" },\n \"position\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" },\n \"startDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"endDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"summary\": { \"type\": \"string\" },\n \"highlights\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"education\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"institution\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" },\n \"area\": { \"type\": \"string\" },\n \"studyType\": { \"type\": \"string\" },\n \"startDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"endDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"score\": { \"type\": \"string\" },\n \"courses\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"awards\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"title\": { \"type\": \"string\" },\n \"date\": { \"type\": \"string\", \"format\": \"date\" },\n \"awarder\": { \"type\": \"string\" },\n \"summary\": { \"type\": \"string\" }\n }\n }\n },\n \"certificates\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"date\": { \"type\": \"string\", \"format\": \"date\" },\n \"issuer\": { \"type\": \"string\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" }\n }\n }\n },\n \"publications\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"publisher\": { \"type\": \"string\" },\n \"releaseDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" },\n \"summary\": { \"type\": \"string\" }\n }\n }\n },\n \"skills\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"level\": { \"type\": \"string\" },\n \"keywords\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"languages\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"language\": { \"type\": \"string\" },\n \"fluency\": { \"type\": \"string\" }\n }\n }\n },\n \"interests\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"keywords\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n }\n }\n }\n },\n \"references\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"reference\": { \"type\": \"string\" }\n }\n }\n },\n \"projects\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": { \"type\": \"string\" },\n \"startDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"endDate\": { \"type\": \"string\", \"format\": \"date\" },\n \"description\": { \"type\": \"string\" },\n \"highlights\": {\n \"type\": \"array\",\n \"items\": { \"type\": \"string\" }\n },\n \"url\": { \"type\": \"string\", \"format\": \"uri\" }\n }\n }\n }\n },\n \"required\": [\"basics\"]\n}\n"
},
"retryOnFail": true,
"typeVersion": 1
},
{
"id": "14c17907-10bb-45a8-b835-39251b742cbe",
"name": "Google Gemini聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
580,
260
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "9ec7af7d-72e6-410d-b52e-9eda3e193e30",
"name": "代码",
"type": "n8n-nodes-base.code",
"position": [
800,
80
],
"parameters": {
"jsCode": "return $input.first().json.output"
},
"typeVersion": 2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "bcad3928-6913-44b0-b9e5-efc6e738769c",
"connections": {
"Code": {
"main": [
[
{
"node": "Initiate a Webhook Notification for Structured Data",
"type": "main",
"index": 0
},
{
"node": "Create a binary data for Structured Data Extract",
"type": "main",
"index": 0
}
]
]
},
"Skill Extractor": {
"main": [
[
{
"node": "Create a binary data for Structured Skill Extract",
"type": "main",
"index": 0
}
]
]
},
"JSON Resume Extractor": {
"main": [
[
{
"node": "Code",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "JSON Resume Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Set URL and Bright Data Zone": {
"main": [
[
{
"node": "Perform Bright Data Web Request",
"type": "main",
"index": 0
}
]
]
},
"Perform Bright Data Web Request": {
"main": [
[
{
"node": "Markdown to Textual Data Extractor",
"type": "main",
"index": 0
}
]
]
},
"When clicking ‘Test workflow’": {
"main": [
[
{
"node": "Set URL and Bright Data Zone",
"type": "main",
"index": 0
}
]
]
},
"Markdown to Textual Data Extractor": {
"main": [
[
{
"node": "Skill Extractor",
"type": "main",
"index": 0
},
{
"node": "JSON Resume Extractor",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model for Skill Extractor": {
"ai_languageModel": [
[
{
"node": "Skill Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Create a binary data for Structured Data Extract": {
"main": [
[
{
"node": "Write the structured content to disk",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model for Markdown to Textual": {
"ai_languageModel": [
[
{
"node": "Markdown to Textual Data Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Create a binary data for Structured Skill Extract": {
"main": [
[
{
"node": "Write the structured skills content to disk",
"type": "main",
"index": 0
}
]
]
}
}
}常见问题
如何使用这个工作流？
复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景？
高级 - 人力资源, 人工智能
需要付费吗？
本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。
相关工作流推荐
使用Bright Data和OpenAI 4o mini的自动化简历职位匹配引擎
Bright Data MCP与OpenAI 4o mini的自动化简历职位匹配引擎
Set
Function
Split Out
+10
22 节点Ranjan Dailata
人力资源
使用Bright Data进行品牌内容提取、摘要与情感分析
使用Bright Data和Google Gemini提取和分析品牌内容
Set
Function
Http Request
+7
23 节点Ranjan Dailata
人工智能
使用Bright Data MCP服务器和Google Gemini进行LinkedIn网页抓取
使用Bright Data MCP服务器和Google Gemini提取和转换LinkedIn数据
Set
Code
Merge
+9
20 节点Ranjan Dailata
人工智能
Google趋势数据提取，使用Bright Data和Google Gemini进行摘要生成
使用Bright Data和Google Gemini的Google趋势数据提取与摘要生成
Set
Gmail
Function
+8
16 节点Ranjan Dailata
工程
法律案例研究提取器，使用Bright Data MCP和Google Gemini的数据挖掘器
法律案例研究提取器，使用Bright Data MCP和Google Gemini的数据挖掘器
Set
Code
Wait
+10
22 节点Ranjan Dailata
人工智能
使用Bright Data和Google Gemini进行结构化数据提取和数据挖掘
使用Bright Data和Google Gemini进行结构化数据提取和数据挖掘
Set
Function
Http Request
+6
18 节点Ranjan Dailata
工程
工作流信息
难度等级
高级
节点数量19
分类2
节点类型10
作者
Ranjan Dailata
@ranjancseA Professional based out of India specialized in handling AI-powered automations. Contact me at ranjancse@gmail.com
外部链接
在 n8n.io 查看 →
分享此工作流