Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone
工作流概述
这是一个包含21个节点的复杂工作流，主要用于自动化处理各种任务。
工作流源代码
{
"id": "3Lih0LVosR8dZbla",
"meta": {
"instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
"templateCredsSetupCompleted": true
},
"name": "Create AI-Ready Vector Datasets for LLMs with Bright Data, Gemini & Pinecone",
"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"
}
],
"nodes": [
{
"id": "0a468953-e348-420e-a6b3-c55fb20d3cbf",
"name": "When clicking ‘Test workflow’",
"type": "n8n-nodes-base.manualTrigger",
"position": [
200,
-710
],
"parameters": {},
"typeVersion": 1
},
{
"id": "3725e480-246f-4f32-b0a7-b946cacbe830",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1236,
-60
],
"parameters": {
"text": "=Format the below search result
{{ $json.output.search_result }}",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.8
},
{
"id": "30a12b8e-02f5-4b2e-bf9f-20fd9658405e",
"name": "Pinecone Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
1628,
-10
],
"parameters": {
"mode": "insert",
"options": {},
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "hacker-news",
"cachedResultName": "hacker-news"
}
},
"credentials": {
"pineconeApi": {
"id": "wdfRQ6NE8yjCDFhY",
"name": "PineconeApi account"
}
},
"typeVersion": 1.1
},
{
"id": "1738dea6-fa4f-4a8d-a6fb-2f01feb1a6d5",
"name": "Embeddings Google Gemini",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
1612,
210
],
"parameters": {
"modelName": "models/text-embedding-004"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "e6443541-de71-4d26-ad58-d7c72868a190",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1760,
220
],
"parameters": {
"options": {},
"jsonData": "={{ $('Information Extractor with Data Formatter').item.json.output.search_result }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "09ffc8cd-096f-47fe-937d-f8ab4fb41266",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
1820,
410
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "90cc9aa4-0931-4c52-8734-e4e0de820205",
"name": "Google Gemini Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1240,
160
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "1090a4af-7e5d-446b-a537-3afe48cd4909",
"name": "Google Gemini Chat Model2",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
948,
-340
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "324c530c-0a03-411e-acb0-d82e9dc635cf",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
948,
160
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "3226a2d6-ade1-4d6a-95c5-0be4d787a947",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1400,
160
],
"parameters": {
"jsonSchemaExample": "[{
\"id\": \"<string>\",
\"title\": \"<string>\",
\"summary\": \"<string>\",
\"keywords\": [\"\"],
\"topics\": [\"\"]
}]"
},
"typeVersion": 1.2
},
{
"id": "a739a314-900a-4ef7-9cc2-1b65374e2e05",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
40,
-360
],
"parameters": {
"width": 480,
"height": 220,
"content": "## Note
Please make sure to set the URL for web crawling.
Web-Unlocker Product is being utilized for performing the web scrapping.
This workflow is utilizing the Basic LLM Chain, Information Extraction with the AI Agents for formatting, extracting and persisting the response in PineCone Vector Database"
},
"typeVersion": 1
},
{
"id": "3dca6d46-c423-4fb5-a6e4-c2aa2852d51c",
"name": "Set Fields - URL and Webhook URL",
"type": "n8n-nodes-base.set",
"notes": "Set the URL which you are interested to scrap the data",
"position": [
420,
-710
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "1c132dd6-31e4-453b-a8cf-cad9845fe55b",
"name": "url",
"type": "string",
"value": "https://news.ycombinator.com?product=unlocker&method=api"
},
{
"id": "90f3272b-d13d-44e2-8b4c-0943648cfce9",
"name": "webhook_url",
"type": "string",
"value": "https://webhook.site/bc804ce5-4a45-4177-a68a-99c80e5c86e6"
}
]
}
},
"notesInFlow": true,
"typeVersion": 3.4
},
{
"id": "216a3261-a398-484c-9bf4-ca5966b829b6",
"name": "Make a web request",
"type": "n8n-nodes-base.httpRequest",
"position": [
640,
-260
],
"parameters": {
"url": "https://api.brightdata.com/request",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "zone",
"value": "web_unlocker1"
},
{
"name": "url",
"value": "={{ $json.url }}"
},
{
"name": "format",
"value": "raw"
}
]
},
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "0c74e21c-3007-4297-b6ab-8ee17f4c6436",
"name": "Structured JSON Data Formatter",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
860,
-560
],
"parameters": {
"text": "=Format the below response and produce a textual data. Output the response as per the below JSON schema.
Here's the input: {{ $json.data }}
Here's the JSON schema:
[{
\"rank\": { \"type\": \"integer\" },
\"title\": { \"type\": \"string\" },
\"site\": { \"type\": \"string\" },
\"points\": { \"type\": \"integer\" },
\"user\": { \"type\": \"string\" },
\"age\": { \"type\": \"string\" },
\"comments\": { \"type\": \"string\" }
}]",
"messages": {
"messageValues": [
{
"message": "You are an expert data formatter"
}
]
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "012d4bb0-2b58-47cd-9cea-b4e0dced9082",
"name": "Webhook for structured data",
"type": "n8n-nodes-base.httpRequest",
"position": [
1314,
-860
],
"parameters": {
"url": "={{ $json.webhook_url }}",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "response",
"value": "={{ $json.text }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "93b35e5e-6f52-4aeb-8f1b-39cc495beefe",
"name": "Webhook for structured AI agent response",
"type": "n8n-nodes-base.httpRequest",
"position": [
1750,
-660
],
"parameters": {
"url": "={{ $json.webhook_url }}",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "response",
"value": "={{ $json.output }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "251b4251-255c-48c6-999b-02227fa2de9b",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
800,
-620
],
"parameters": {
"width": 360,
"height": 420,
"content": "## AI Data Formatter
"
},
"typeVersion": 1
},
{
"id": "f62463cd-6be3-4942-a636-de980a3154b4",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1560,
-160
],
"parameters": {
"color": 4,
"width": 520,
"height": 720,
"content": "## Vector Database Persistence
"
},
"typeVersion": 1
},
{
"id": "ad20cc91-766a-4a57-be54-6f0d09a784eb",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1260,
-920
],
"parameters": {
"color": 3,
"width": 680,
"height": 440,
"content": "## Webhook Notification Handler
"
},
"typeVersion": 1
},
{
"id": "37ab5c0f-d36e-4131-844d-20a22d3f2861",
"name": "Information Extractor with Data Formatter",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
860,
-60
],
"parameters": {
"text": "={{ $json.data }}",
"options": {
"systemPromptTemplate": "You are an expert HTML extractor. Your job is to analyze the search result and extract the content as a collection on items"
},
"attributes": {
"attributes": [
{
"name": "search_result",
"description": "Search Response"
}
]
}
},
"typeVersion": 1
},
{
"id": "e04e189a-8ba9-4ef4-9a49-fc13daf00828",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
800,
-160
],
"parameters": {
"color": 5,
"width": 720,
"height": 720,
"content": "## Data Extraction/Formatting with the AI Agent
"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "799fb406-600d-45a5-b926-24b8844f33a5",
"connections": {
"AI Agent": {
"main": [
[
{
"node": "Pinecone Vector Store",
"type": "main",
"index": 0
},
{
"node": "Webhook for structured AI agent response",
"type": "main",
"index": 0
}
]
]
},
"Make a web request": {
"main": [
[
{
"node": "Structured JSON Data Formatter",
"type": "main",
"index": 0
},
{
"node": "Information Extractor with Data Formatter",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Pinecone Vector Store": {
"ai_tool": [
[]
]
},
"Embeddings Google Gemini": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Information Extractor with Data Formatter",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "AI Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Google Gemini Chat Model1": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Google Gemini Chat Model2": {
"ai_languageModel": [
[
{
"node": "Structured JSON Data Formatter",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured JSON Data Formatter": {
"main": [
[
{
"node": "Webhook for structured data",
"type": "main",
"index": 0
}
]
]
},
"Set Fields - URL and Webhook URL": {
"main": [
[
{
"node": "Make a web request",
"type": "main",
"index": 0
},
{
"node": "Webhook for structured data",
"type": "main",
"index": 0
},
{
"node": "Webhook for structured AI agent response",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"When clicking ‘Test workflow’": {
"main": [
[
{
"node": "Set Fields - URL and Webhook URL",
"type": "main",
"index": 0
}
]
]
},
"Information Extractor with Data Formatter": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
}
}
}功能特点
- 自动检测新邮件
- AI智能内容分析
- 自定义分类规则
- 批量处理能力
- 详细的处理日志
技术分析
节点类型及作用
- Manualtrigger
- @N8N/N8N Nodes Langchain.Agent
- @N8N/N8N Nodes Langchain.Vectorstorepinecone
- @N8N/N8N Nodes Langchain.Embeddingsgooglegemini
- @N8N/N8N Nodes Langchain.Documentdefaultdataloader
复杂度评估
配置难度：
维护难度：
扩展性：
实施指南
前置条件
- 有效的Gmail账户
- n8n平台访问权限
- Google API凭证
- AI分类服务订阅
配置步骤
- 在n8n中导入工作流JSON文件
- 配置Gmail节点的认证信息
- 设置AI分类器的API密钥
- 自定义分类规则和标签映射
- 测试工作流执行
- 配置定时触发器（可选）
关键参数
| 参数名称 | 默认值 | 说明 |
|---|---|---|
| maxEmails | 50 | 单次处理的最大邮件数量 |
| confidenceThreshold | 0.8 | 分类置信度阈值 |
| autoLabel | true | 是否自动添加标签 |
最佳实践
优化建议
- 定期更新AI分类模型以提高准确性
- 根据邮件量调整处理批次大小
- 设置合理的分类置信度阈值
- 定期清理过期的分类规则
安全注意事项
- 妥善保管API密钥和认证信息
- 限制工作流的访问权限
- 定期审查处理日志
- 启用双因素认证保护Gmail账户
性能优化
- 使用增量处理减少重复工作
- 缓存频繁访问的数据
- 并行处理多个邮件分类任务
- 监控系统资源使用情况
故障排除
常见问题
邮件未被正确分类
检查AI分类器的置信度阈值设置，适当降低阈值或更新训练数据。
Gmail认证失败
确认Google API凭证有效且具有正确的权限范围，重新进行OAuth授权。
调试技巧
- 启用详细日志记录查看每个步骤的执行情况
- 使用测试邮件验证分类逻辑
- 检查网络连接和API服务状态
- 逐步执行工作流定位问题节点
错误处理
工作流包含以下错误处理机制：
- 网络超时自动重试（最多3次）
- API错误记录和告警
- 处理失败邮件的隔离机制
- 异常情况下的回滚操作