Daily Language Learning

工作流概述

这是一个包含8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": "7",
  "name": "Daily Language Learning",
  "nodes": [
    {
      "name": "Daily trigger",
      "type": "n8n-nodes-base.cron",
      "position": [
        620,
        750
      ],
      "parameters": {
        "triggerTimes": {
          "item": [
            {
              "hour": 8
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "name": "Get top 3 articles",
      "type": "n8n-nodes-base.hackerNews",
      "position": [
        820,
        750
      ],
      "parameters": {
        "limit": 3,
        "resource": "all",
        "additionalFields": {
          "tags": [
            "front_page"
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "name": "Extract words",
      "type": "n8n-nodes-base.function",
      "position": [
        1020,
        750
      ],
      "parameters": {
        "functionCode": "const words = [];
const regex = /\d/g;
const newItems = [];

// Splits titles into words and removes numbers
// using regular expressions

for(let i=0; i < items.length; i++) {
  let split_titles = []; 
  split_titles = items[i].json.title.split(' ');
  for(let j=0; j < split_titles.length; j++) {
    if(regex.test(split_titles[j])) {
      continue;
    } else {
      words.push(split_titles[j]);
    }
  }
}

// Removes all duplicate words by converting the
// array into a set and then back into an array

const uniqueWords = [...new Set(words)];

// Transform the array to the data structure expected
// by n8n

for(let k=0; k < uniqueWords.length; k++) {
  newItems.push({json: { words: uniqueWords[k] }});
}

return newItems;"
      },
      "typeVersion": 1
    },
    {
      "name": "Translate",
      "type": "n8n-nodes-base.lingvaNex",
      "position": [
        1220,
        750
      ],
      "parameters": {
        "text": "={{$node[\"Extract words\"].json[\"words\"]}}",
        "options": {},
        "translateTo": "de_DE"
      },
      "credentials": {
        "lingvaNexApi": "LingvaNex"
      },
      "typeVersion": 1
    },
    {
      "name": "Filter data ",
      "type": "n8n-nodes-base.set",
      "position": [
        1420,
        750
      ],
      "parameters": {
        "values": {
          "string": [
            {
              "name": "English word",
              "value": "={{$node[\"Translate\"].json[\"source\"]}}"
            },
            {
              "name": "Translated word",
              "value": "={{$node[\"Translate\"].json[\"result\"]}}"
            }
          ]
        },
        "options": {},
        "keepOnlySet": true
      },
      "typeVersion": 1
    },
    {
      "name": "Save today's words",
      "type": "n8n-nodes-base.airtable",
      "position": [
        1620,
        850
      ],
      "parameters": {
        "table": "Table 1",
        "options": {},
        "operation": "append",
        "application": "app4Y6qcCHIO1cYNB"
      },
      "credentials": {
        "airtableApi": "Airtable"
      },
      "typeVersion": 1
    },
    {
      "name": "Craft message",
      "type": "n8n-nodes-base.function",
      "position": [
        1620,
        650
      ],
      "parameters": {
        "functionCode": "const number_of_words = 5;
const words = [];

// Crafts the words to be sent in en_word : translated_word format
// and adds them to an array

for(let i=0; i < number_of_words; i++) {
  words.push(items[i].json['English word'] + ' : ' + items[i].json['Translated word']);
}

// Takes all the items from the array and converts them into a comma
// separated string

const words_of_the_day = words.join(', ');

return [{json: {words_of_the_day: words_of_the_day}}];"
      },
      "typeVersion": 1
    },
    {
      "name": "Send SMS",
      "type": "n8n-nodes-base.vonage",
      "position": [
        1820,
        650
      ],
      "parameters": {
        "to": "+4915225152610",
        "from": "Vonage APIs",
        "message": "=Good morning, here are your words for today
{{$node[\"Craft message\"].json[\"words_of_the_day\"]}}",
        "additionalFields": {}
      },
      "credentials": {
        "vonageApi": "Vonage"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "settings": {},
  "connections": {
    "Translate": {
      "main": [
        [
          {
            "node": "Filter data ",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Filter data ": {
      "main": [
        [
          {
            "node": "Craft message",
            "type": "main",
            "index": 0
          },
          {
            "node": "Save today's words",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Craft message": {
      "main": [
        [
          {
            "node": "Send SMS",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Daily trigger": {
      "main": [
        [
          {
            "node": "Get top 3 articles",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Extract words": {
      "main": [
        [
          {
            "node": "Translate",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get top 3 articles": {
      "main": [
        [
          {
            "node": "Extract words",
            "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

  • Cron
  • Hackernews
  • Function
  • Lingvanex
  • Set

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