My workflow 4

工作流概述

这是一个包含6个节点的中等工作流,主要用于自动化处理各种任务。

工作流源代码

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{
  "id": "mW6b4dMHkIDfnaIj",
  "meta": {
    "instanceId": "7b7fd5f72a378d0859f4d1cf8dd3c226094df4777ef6aca192ac32e815fe212a",
    "templateCredsSetupCompleted": true
  },
  "name": "My workflow 4",
  "tags": [],
  "nodes": [
    {
      "id": "9ae28c07-bb44-4e64-b38c-a74a9de81b2e",
      "name": "Receive Feedback",
      "type": "n8n-nodes-base.webhook",
      "position": [
        -440,
        540
      ],
      "webhookId": "89e8d5ec-d442-41ea-9ff1-93a9df0b2aa1",
      "parameters": {
        "path": "client-feedback",
        "options": {},
        "httpMethod": "POST"
      },
      "typeVersion": 1
    },
    {
      "id": "770bc041-1846-4ac1-b8dc-61756686f906",
      "name": "Prepare AI Prompt",
      "type": "n8n-nodes-base.function",
      "position": [
        -240,
        540
      ],
      "parameters": {
        "functionCode": "
const feedback = $json.feedback || \"No feedback provided.\";
return [{
  json: {
    prompt: `Analyze this client feedback: \"${feedback}\"\n\n1. Summarize the positive points.\n2. Suggest improvements.\n3. Generate a short social media post based on the positive elements.`
  }
}];
"
      },
      "typeVersion": 1
    },
    {
      "id": "0b3a469a-f6f4-4140-9c6f-fd7ba7689c5e",
      "name": "Analyze with AI",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -40,
        540
      ],
      "parameters": {
        "url": "https://api.deepseek.com/generate",
        "options": {},
        "authentication": "predefinedCredentialType",
        "jsonParameters": true
      },
      "typeVersion": 2
    },
    {
      "id": "bdbf3a85-e68f-4fe3-b0b4-d44578d11c31",
      "name": "Format AI Output",
      "type": "n8n-nodes-base.function",
      "position": [
        160,
        540
      ],
      "parameters": {
        "functionCode": "
const output = $json.response || $json.choices?.[0]?.text || \"No AI output.\";
const splitIndex = output.indexOf(\"3.\");
let summary = output;
let post = \"No post generated.\";

if (splitIndex !== -1) {
  summary = output.substring(0, splitIndex).trim();
  post = output.substring(splitIndex).replace(/^3\./, \"\").trim();
}

return [{
  json: {
    report: summary,
    post: post
  }
}];
"
      },
      "typeVersion": 1
    },
    {
      "id": "47093d4d-645b-4dc8-a5a4-1b35a649ac97",
      "name": "Send Feedback Report",
      "type": "n8n-nodes-base.emailSend",
      "position": [
        380,
        500
      ],
      "parameters": {
        "text": "={{ $json[\"report\"] }}",
        "options": {},
        "subject": "Client Feedback Summary",
        "toEmail": "team@email.com",
        "fromEmail": "your@email.com"
      },
      "typeVersion": 1
    },
    {
      "id": "e49a4898-00d9-4413-ac6d-87aafdfe6ff9",
      "name": "Send Social Draft",
      "type": "n8n-nodes-base.telegram",
      "position": [
        380,
        660
      ],
      "webhookId": "07598764-aee9-41ea-82c1-0ded0ac08b57",
      "parameters": {
        "text": "={{ $json[\"post\"] }}",
        "chatId": "YOUR_TELEGRAM_CHAT_ID",
        "additionalFields": {}
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "54d175ec-080f-4d2d-9d83-60dd36c8f11b",
  "connections": {
    "Analyze with AI": {
      "main": [
        [
          {
            "node": "Format AI Output",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Format AI Output": {
      "main": [
        [
          {
            "node": "Send Feedback Report",
            "type": "main",
            "index": 0
          },
          {
            "node": "Send Social Draft",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Receive Feedback": {
      "main": [
        [
          {
            "node": "Prepare AI Prompt",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Prepare AI Prompt": {
      "main": [
        [
          {
            "node": "Analyze with AI",
            "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

  • Webhook
  • Function
  • Httprequest
  • Emailsend
  • Telegram

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

  1. 在n8n中导入工作流JSON文件
  2. 配置Gmail节点的认证信息
  3. 设置AI分类器的API密钥
  4. 自定义分类规则和标签映射
  5. 测试工作流执行
  6. 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