Gratitude Jar Reminder
工作流概述
这是一个包含9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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"instanceId": "558d88703fb65b2d0e44613bc35916258b0f0bf983c5d4730c00c424b77ca36a",
"templateCredsSetupCompleted": true
},
"name": "Gratitude Jar Reminder",
"tags": [],
"nodes": [
{
"id": "ac48becc-e207-489b-a8e4-a8f69780c626",
"name": "Trigger 2100 Bear Gratitude Jar Notice",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-80,
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],
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 21
}
]
}
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"typeVersion": 1.2
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{
"id": "37f46ac1-5c0b-4cdf-aa33-67fad80dafdd",
"name": "WriteReminder",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
180,
-100
],
"parameters": {
"text": "=Today is a wonderful day! 🌟 What or who brought a smile to your face today? 😊
",
"messages": {
"messageValues": [
{
"message": "You'll rewrite this message to send reminder to user to record good thing today."
}
]
},
"promptType": "define"
},
"typeVersion": 1.5
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{
"id": "816f8089-a54f-4860-a658-448ab53a08fd",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-180,
-240
],
"parameters": {
"width": 300,
"height": 360,
"content": "## Trigger
We schedule the trigger at 9.00 pm before going to bed. This flow is to reflect what is the great thing that happened today."
},
"typeVersion": 1
},
{
"id": "c7a620fe-2a50-4cfb-af91-8a4b4ca58adb",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
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-240
],
"parameters": {
"color": 5,
"width": 300,
"height": 360,
"content": "## Write Reminder
After getting the same reminder, we tend to ignore it. This is to generate variations of reminder by setting the temperature of the model at 0.9"
},
"typeVersion": 1
},
{
"id": "66b865a1-0a6c-4a3c-abb3-024ec7ff8b40",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 6,
"width": 300,
"height": 360,
"content": "## Reformatted
This is to reformat text to be able to send in Line Push API properly."
},
"typeVersion": 1
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{
"id": "adb8cf4e-de77-4490-a8da-b32122c3a730",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
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-240
],
"parameters": {
"color": 4,
"width": 300,
"height": 360,
"content": "## Push Message
Send push message via LINE"
},
"typeVersion": 1
},
{
"id": "6562967a-fae7-400a-913a-4cf68e70b40a",
"name": "Reformat Output from Chat Model",
"type": "n8n-nodes-base.set",
"position": [
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"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "90abc5a6-c9b9-4b0d-b433-c6f90816dba3",
"name": "posestoday",
"type": "string",
"value": "={{ $json.text.replaceAll(\"\n\",\"\\n\").replaceAll(\"\n\",\"\").removeMarkdown().removeTags().replaceAll('\"',\"\") }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "d2ab000a-6f3a-494f-807f-829cbb124685",
"name": "Azure OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatAzureOpenAi",
"position": [
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"parameters": {
"model": "4o",
"options": {
"temperature": 0.9
}
},
"credentials": {
"azureOpenAiApi": {
"id": "5AjoWhww5SQi2VXd",
"name": "Azure Open AI account"
}
},
"typeVersion": 1
},
{
"id": "c548df75-dc6c-472f-8992-77f0f57d4732",
"name": "Line Push Message",
"type": "n8n-nodes-base.httpRequest",
"position": [
940,
-100
],
"parameters": {
"url": "https://api.line.me/v2/bot/message/push",
"method": "POST",
"options": {},
"jsonBody": "={
\"to\": \"YOUR ID HERE\",
\"messages\":[
{
\"type\":\"text\",
\"text\":\"{{ $json.posestoday }}\"
}
]
} ",
"sendBody": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth"
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"credentials": {
"httpHeaderAuth": {
"id": "yiPG7xPwvDzsY0Qd",
"name": "Line @511dizji"
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"typeVersion": 4.2
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],
"active": true,
"pinData": {},
"settings": {
"timezone": "Asia/Bangkok",
"callerPolicy": "workflowsFromSameOwner",
"executionOrder": "v1"
},
"versionId": "19321d28-e96d-4f97-94a9-604b59b5b651",
"connections": {
"WriteReminder": {
"main": [
[
{
"node": "Reformat Output from Chat Model",
"type": "main",
"index": 0
}
]
]
},
"Azure OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "WriteReminder",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Reformat Output from Chat Model": {
"main": [
[
{
"node": "Line Push Message",
"type": "main",
"index": 0
}
]
]
},
"Trigger 2100 Bear Gratitude Jar Notice": {
"main": [
[
{
"node": "WriteReminder",
"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
- Scheduletrigger
- @N8N/N8N Nodes Langchain.Chainllm
- Stickynote
- Set
- @N8N/N8N Nodes Langchain.Lmchatazureopenai
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