Coffee Bot (Matrix)

工作流概述

这是一个包含5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

下载
{
  "id": "9",
  "name": "Coffee Bot (Matrix)",
  "nodes": [
    {
      "name": "Greetings",
      "type": "n8n-nodes-base.matrix",
      "position": [
        670,
        240
      ],
      "parameters": {
        "text": "👋 Happy Monday Groups for this week's virtual coffee are:",
        "roomId": "Enter your Room ID"
      },
      "credentials": {
        "matrixApi": "Matrix Creds"
      },
      "typeVersion": 1
    },
    {
      "name": "Employees in coffee chat channel",
      "type": "n8n-nodes-base.matrix",
      "position": [
        880,
        240
      ],
      "parameters": {
        "roomId": "Enter your Room ID",
        "filters": {
          "membership": ""
        },
        "resource": "roomMember"
      },
      "credentials": {
        "matrixApi": "Enter Your Matrix Credentials"
      },
      "typeVersion": 1
    },
    {
      "name": "Weekly trigger on monday1",
      "type": "n8n-nodes-base.cron",
      "position": [
        480,
        240
      ],
      "parameters": {
        "triggerTimes": {
          "item": [
            {
              "hour": 10,
              "mode": "everyWeek"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "name": "Divide into groups",
      "type": "n8n-nodes-base.function",
      "notes": "This still needs to be reconfigured to grab the information from the second Matrix node. Have an issue with the ",
      "position": [
        1090,
        240
      ],
      "parameters": {
        "functionCode": "const ideal_group_size = 3;
let groups = [];
let data_as_array = [];
let newItems = [];

// Take all the users and add them to an array
for (let j = 0; j < items.length; j++) {
  data_as_array.push({username: items[j].json.user_id});
}

// Fisher-Yates (aka Knuth) Shuffle
function shuffle(array) {
  var currentIndex = array.length, temporaryValue, randomIndex;

  // While there remain elements to shuffle...
  while (0 !== currentIndex) {

    // Pick a remaining element...
    randomIndex = Math.floor(Math.random() * currentIndex);
    currentIndex -= 1;

    // And swap it with the current element.
    temporaryValue = array[currentIndex];
    array[currentIndex] = array[randomIndex];
    array[randomIndex] = temporaryValue;
  }

  return array;
}

// Randomize the sequence of names in the array
data_as_array = shuffle(data_as_array);

// Create groups of ideal group size (3)
for (let i = 0; i < data_as_array.length; i += ideal_group_size) {
  groups.push(data_as_array.slice(i, i + ideal_group_size));
}

// Make sure that no group has just one person. If it does, take
// one from previous group and add it to that group 
for (let k = 0; k < groups.length; k++) {
  if (groups[k].length === 1) {
    groups[k].push(groups[k-1].shift());
  }
}

for (let l = 0; l < groups.length; l++) {
    newItems.push({json: {groupsUsername: groups[l].map(a=> a.username)}})
}

return newItems;
"
      },
      "typeVersion": 1
    },
    {
      "name": "Announce groups",
      "type": "n8n-nodes-base.matrix",
      "position": [
        1290,
        240
      ],
      "parameters": {
        "text": "=☀️ {{$node[\"Divide into groups\"].json[\"groupsUsername\"].join(', ')}}",
        "roomId": "!hobuowPzLuKnojiyfV:matrix.org"
      },
      "credentials": {
        "matrixApi": "Matrix Creds"
      },
      "typeVersion": 1
    }
  ],
  "active": true,
  "settings": {},
  "connections": {
    "Greetings": {
      "main": [
        [
          {
            "node": "Employees in coffee chat channel",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Divide into groups": {
      "main": [
        [
          {
            "node": "Announce groups",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Weekly trigger on monday1": {
      "main": [
        [
          {
            "node": "Greetings",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Employees in coffee chat channel": {
      "main": [
        [
          {
            "node": "Divide into groups",
            "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

  • Matrix
  • Cron
  • Function

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