RAG on living data
工作流概述
这是一个包含34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
{
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"meta": {
"instanceId": "fb8bc2e315f7f03c97140b30aa454a27bc7883a19000fa1da6e6b571bf56ad6d",
"templateCredsSetupCompleted": true
},
"name": "RAG on living data",
"tags": [],
"nodes": [
{
"id": "49086cdf-a38c-4cb8-9be9-d3e6ea5bdde5",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1740,
1040
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"id": "X7Jf0zECd3IkQdSw",
"name": "OpenAi (octionicsolutions)"
}
},
"typeVersion": 1
},
{
"id": "f0670721-92f4-422a-99c9-f9c2aa6fe21f",
"name": "Token Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterTokenSplitter",
"position": [
2380,
540
],
"parameters": {
"chunkSize": 500
},
"typeVersion": 1
},
{
"id": "fe80ecac-4f79-4b07-ad8e-60ab5f980cba",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
1180,
-200
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "81b79248-08e8-4214-872b-1796e51ad0a4",
"name": "Question and Answer Chain",
"type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
"position": [
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],
"parameters": {
"options": {}
},
"typeVersion": 1.3
},
{
"id": "e78f7b63-baef-4834-8f1b-aecfa9102d6c",
"name": "Vector Store Retriever",
"type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
"position": [
844,
715
],
"parameters": {},
"typeVersion": 1
},
{
"id": "1d5ffbd0-b2cf-4660-a291-581d18608ecd",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
704,
715
],
"parameters": {
"model": "gpt-4o",
"options": {}
},
"credentials": {
"openAiApi": {
"id": "X7Jf0zECd3IkQdSw",
"name": "OpenAi (octionicsolutions)"
}
},
"typeVersion": 1
},
{
"id": "37a3063f-aa21-4347-a72f-6dd316c58366",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
524,
495
],
"webhookId": "74479a54-418f-4de2-b70d-cfb3e3fdd5a7",
"parameters": {
"public": true,
"options": {}
},
"typeVersion": 1.1
},
{
"id": "5924bc01-1694-4b5c-8a06-7c46ee4c6425",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
520,
-200
],
"parameters": {
"rule": {
"interval": [
{
"field": "minutes",
"minutesInterval": 1
}
]
}
},
"typeVersion": 1.2
},
{
"id": "5067eda6-8bbe-407a-a6af-93e81be53661",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
620,
0
],
"parameters": {
"width": 329.16412916774584,
"height": 312.52803480051045,
"content": "## Switch trigger (optional)
If you are on the cloud plan, consider switching to the Notion Trigger Node instead, to save on executions."
},
"typeVersion": 1
},
{
"id": "33458828-484d-426b-a3d1-974a81c6162e",
"name": "Limit",
"type": "n8n-nodes-base.limit",
"position": [
1620,
-60
],
"parameters": {},
"typeVersion": 1
},
{
"id": "4d39503a-378e-4942-a5d4-8c62785aac44",
"name": "Limit1",
"type": "n8n-nodes-base.limit",
"position": [
2660,
-60
],
"parameters": {},
"typeVersion": 1
},
{
"id": "0e0b1391-3fe5-4d80-a2eb-a2483b79d9a6",
"name": "Delete old embeddings if exist",
"type": "n8n-nodes-base.supabase",
"position": [
1400,
-60
],
"parameters": {
"tableId": "documents",
"operation": "delete",
"filterType": "string",
"filterString": "=metadata->>id=eq.{{ $('Input Reference').item.json.id }}"
},
"credentials": {
"supabaseApi": {
"id": "DjIb4HMTYXhTU8Uc",
"name": "Supabase (VectorStore)"
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "4a8614e4-0a53-4731-bc68-57505d7d0a09",
"name": "Get page blocks",
"type": "n8n-nodes-base.notion",
"position": [
1840,
-60
],
"parameters": {
"blockId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Input Reference').item.json.id }}"
},
"resource": "block",
"operation": "getAll",
"returnAll": true,
"fetchNestedBlocks": true
},
"credentials": {
"notionApi": {
"id": "ObmaBA0dJss3JJPv",
"name": "Notion (octionicsolutions / Test)"
}
},
"executeOnce": true,
"typeVersion": 2.2
},
{
"id": "8c922895-49d6-4778-8356-6f6cf49e5420",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
2300,
260
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "id",
"value": "={{ $('Input Reference').item.json.id }}"
},
{
"name": "name",
"value": "={{ $('Input Reference').item.json.name }}"
}
]
}
}
},
"typeVersion": 1
},
{
"id": "8ad7ff2e-4bc2-4821-ae03-bab2dc11d947",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
2220,
400
],
"parameters": {
"width": 376.2098538932132,
"height": 264.37628764336097,
"content": "## Adjust chunk size and overlap
For more accurate search results, increase the overlap. For the *text-embedding-ada-002* model the chunk size plus overlap must not exceed 8191"
},
"typeVersion": 1
},
{
"id": "8078d59a-f45f-4e96-a8ec-6c2f1c328e84",
"name": "Input Reference",
"type": "n8n-nodes-base.noOp",
"position": [
960,
-200
],
"parameters": {},
"typeVersion": 1
},
{
"id": "aae6c517-a316-40e3-aee9-1cc4b448689f",
"name": "Notion Trigger",
"type": "n8n-nodes-base.notionTrigger",
"disabled": true,
"position": [
740,
120
],
"parameters": {
"event": "pagedUpdatedInDatabase",
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"databaseId": {
"__rl": true,
"mode": "list",
"value": "ec6dc7b4-9ce0-47f7-8025-ef09295999fd",
"cachedResultUrl": "https://www.notion.so/ec6dc7b49ce047f78025ef09295999fd",
"cachedResultName": "Knowledge Base"
}
},
"credentials": {
"notionApi": {
"id": "ObmaBA0dJss3JJPv",
"name": "Notion (octionicsolutions / Test)"
}
},
"typeVersion": 1
},
{
"id": "3a43d66d-d4e3-4ca1-aee9-85ac65160e45",
"name": "Get updated pages",
"type": "n8n-nodes-base.notion",
"position": [
740,
-200
],
"parameters": {
"filters": {
"conditions": [
{
"key": "Last edited time|last_edited_time",
"condition": "equals",
"lastEditedTime": "={{ $now.minus(1, 'minutes').toISO() }}"
}
]
},
"options": {},
"resource": "databasePage",
"operation": "getAll",
"databaseId": {
"__rl": true,
"mode": "list",
"value": "ec6dc7b4-9ce0-47f7-8025-ef09295999fd",
"cachedResultUrl": "https://www.notion.so/ec6dc7b49ce047f78025ef09295999fd",
"cachedResultName": "Knowledge Base"
},
"filterType": "manual"
},
"credentials": {
"notionApi": {
"id": "ObmaBA0dJss3JJPv",
"name": "Notion (octionicsolutions / Test)"
}
},
"typeVersion": 2.2
},
{
"id": "bbf1296f-4e2b-4a38-bdf3-ae2b63cc7774",
"name": "Sticky Note23",
"type": "n8n-nodes-base.stickyNote",
"position": [
900,
-300
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "This placeholder serves as a reference point so it is easier to swap the data source with a different service"
},
"typeVersion": 1
},
{
"id": "631e1e10-0b52-4a17-89a4-769ac563321f",
"name": "Sticky Note24",
"type": "n8n-nodes-base.stickyNote",
"position": [
1340,
-160
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "All chunks of a previous version of the document are being deleted by filtering the meta data by the given ID"
},
"typeVersion": 1
},
{
"id": "6c830c83-4b70-4719-8e2a-26846e60085c",
"name": "Sticky Note25",
"type": "n8n-nodes-base.stickyNote",
"position": [
1560,
-160
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "Reduce the active streams/items to just 1 to prevent the following nodes from double-processing"
},
"typeVersion": 1
},
{
"id": "46c8e4e4-0a5e-4ede-947b-5773710d4e55",
"name": "Sticky Note26",
"type": "n8n-nodes-base.stickyNote",
"position": [
1780,
-160
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "Retrieve all page contents/blocks"
},
"typeVersion": 1
},
{
"id": "0369e610-d074-4812-9d04-8615b42965a5",
"name": "Sticky Note27",
"type": "n8n-nodes-base.stickyNote",
"position": [
2600,
-160
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "Reduce the active streams/items to just 1 to prevent the following nodes from double-processing"
},
"typeVersion": 1
},
{
"id": "4f3bce54-1650-45fa-abb0-c881358c7e8d",
"name": "Sticky Note28",
"type": "n8n-nodes-base.stickyNote",
"position": [
2220,
-160
],
"parameters": {
"color": 7,
"width": 375.9283286479995,
"height": 275.841854198618,
"content": "Embed item and store in Vector Store. Depending on the length the content is being split up into multiple chunks/embeds"
},
"typeVersion": 1
},
{
"id": "44125921-e068-4a5d-a56b-b0e63c103556",
"name": "Supabase Vector Store1",
"type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
924,
935
],
"parameters": {
"options": {},
"tableName": {
"__rl": true,
"mode": "list",
"value": "documents",
"cachedResultName": "documents"
}
},
"credentials": {
"supabaseApi": {
"id": "DjIb4HMTYXhTU8Uc",
"name": "Supabase (VectorStore)"
}
},
"typeVersion": 1
},
{
"id": "467322a9-949d-4569-aac6-92196da46ba5",
"name": "Sticky Note30",
"type": "n8n-nodes-base.stickyNote",
"position": [
460,
400
],
"parameters": {
"color": 7,
"width": 730.7522093855692,
"height": 668.724737081502,
"content": "Simple chat bot to ask specific questions while having access to the context of the Notion Knowledge Base which was stored in the Vector Store"
},
"typeVersion": 1
},
{
"id": "27f078cf-b309-4dd1-a8ce-b4fc504d6e29",
"name": "Sticky Note31",
"type": "n8n-nodes-base.stickyNote",
"position": [
1660,
900
],
"parameters": {
"color": 7,
"width": 219.31927574471658,
"height": 275.841854198618,
"content": "Model used for both creating and reading embeddings"
},
"typeVersion": 1
},
{
"id": "2f59cba1-4318-47e7-bf0b-b908d4186b86",
"name": "Supabase Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
2280,
-60
],
"parameters": {
"mode": "insert",
"options": {},
"tableName": {
"__rl": true,
"mode": "list",
"value": "documents",
"cachedResultName": "documents"
}
},
"credentials": {
"supabaseApi": {
"id": "DjIb4HMTYXhTU8Uc",
"name": "Supabase (VectorStore)"
}
},
"typeVersion": 1
},
{
"id": "729849e7-0eff-40c2-ae00-ae660c1eec69",
"name": "Sticky Note32",
"type": "n8n-nodes-base.stickyNote",
"position": [
1120,
-300
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "Process each page/document separately."
},
"typeVersion": 1
},
{
"id": "3f632a24-ca0a-45c4-801d-041aa3f887a7",
"name": "Sticky Note29",
"type": "n8n-nodes-base.stickyNote",
"position": [
2220,
120
],
"parameters": {
"color": 7,
"width": 376.0759088111347,
"height": 275.841854198618,
"content": "Store additional meta data with each embed, especially the Notion ID, which can be later used to find all belonging entries of one page, even if they got split into multiple embeds."
},
"typeVersion": 1
},
{
"id": "ffaf3861-5287-4f57-8372-09216a18cb4d",
"name": "Sticky Note33",
"type": "n8n-nodes-base.stickyNote",
"position": [
460,
-300
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "Using a manual approach for polling data from Notion for more accuracy."
},
"typeVersion": 1
},
{
"id": "cbbedfc0-4d64-42a6-8f55-21e04887305f",
"name": "Sticky Note34",
"type": "n8n-nodes-base.stickyNote",
"position": [
680,
-300
],
"parameters": {
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "## Select Database
Choose the database which represents your Knowledge Base"
},
"typeVersion": 1
},
{
"id": "8b6767f2-1bc9-42fb-b319-f39f6734b9f2",
"name": "Sticky Note35",
"type": "n8n-nodes-base.stickyNote",
"position": [
2000,
-160
],
"parameters": {
"color": 7,
"width": 216.47293010628914,
"height": 275.841854198618,
"content": "Combine all contents to a single text formatted into one line which can be easily stored as an embed"
},
"typeVersion": 1
},
{
"id": "cdff1756-77d7-421e-8672-25c9862840b0",
"name": "Concatenate to single string",
"type": "n8n-nodes-base.summarize",
"position": [
2060,
-60
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "content",
"separateBy": "
",
"aggregation": "concatenate"
}
]
}
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "51075175-868a-4a3a-9580-5ad55e25ac71",
"connections": {
"Limit": {
"main": [
[
{
"node": "Get page blocks",
"type": "main",
"index": 0
}
]
]
},
"Limit1": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Notion Trigger": {
"main": [
[
{
"node": "Input Reference",
"type": "main",
"index": 0
}
]
]
},
"Token Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Get page blocks": {
"main": [
[
{
"node": "Concatenate to single string",
"type": "main",
"index": 0
}
]
]
},
"Input Reference": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[],
[
{
"node": "Delete old embeddings if exist",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Get updated pages",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Supabase Vector Store",
"type": "ai_embedding",
"index": 0
},
{
"node": "Supabase Vector Store1",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Get updated pages": {
"main": [
[
{
"node": "Input Reference",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Question and Answer Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Supabase Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Supabase Vector Store": {
"main": [
[
{
"node": "Limit1",
"type": "main",
"index": 0
}
]
]
},
"Supabase Vector Store1": {
"ai_vectorStore": [
[
{
"node": "Vector Store Retriever",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Vector Store Retriever": {
"ai_retriever": [
[
{
"node": "Question and Answer Chain",
"type": "ai_retriever",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Question and Answer Chain",
"type": "main",
"index": 0
}
]
]
},
"Concatenate to single string": {
"main": [
[
{
"node": "Supabase Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Delete old embeddings if exist": {
"main": [
[
{
"node": "Limit",
"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
- @N8N/N8N Nodes Langchain.Embeddingsopenai
- @N8N/N8N Nodes Langchain.Textsplittertokensplitter
- Splitinbatches
- @N8N/N8N Nodes Langchain.Chainretrievalqa
- @N8N/N8N Nodes Langchain.Retrievervectorstore
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