youtube chapter generator

工作流概述

这是一个包含13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

下载

{
  "id": "SCUbdpVPX4USbQmr",
  "meta": {
    "instanceId": "7c617982c5622c49e1ea217f3ee01da25b7fb42fb9e969ce6e4e1b6c269ad0e5",
    "templateCredsSetupCompleted": true
  },
  "name": "youtube chapter generator",
  "tags": [
    {
      "id": "637Ga13eORejFbTG",
      "name": "youtube",
      "createdAt": "2025-04-06T16:41:11.086Z",
      "updatedAt": "2025-04-06T16:41:11.086Z"
    },
    {
      "id": "tfcUyZ2pGsRZFcje",
      "name": "chapters",
      "createdAt": "2025-04-06T16:41:28.633Z",
      "updatedAt": "2025-04-06T16:41:28.633Z"
    }
  ],
  "nodes": [
    {
      "id": "104fa4ce-cd86-4fff-b31c-0ef37fba6d93",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -800,
        -120
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "c3b45480-3098-40f9-a77f-ada54481b590",
      "name": "Get Caption ID",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -200,
        -120
      ],
      "parameters": {
        "url": "=https://www.googleapis.com/youtube/v3/captions?part=snippet&videoId={{ $json.id }}",
        "options": {},
        "authentication": "predefinedCredentialType",
        "nodeCredentialType": "youTubeOAuth2Api"
      },
      "credentials": {
        "youTubeOAuth2Api": {
          "id": "1TkjUqPfFCQ6NzL7",
          "name": "YouTube account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "fe08adc4-e6ef-47ae-a946-1e6d5a85e10e",
      "name": "Get Captions",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        20,
        -120
      ],
      "parameters": {
        "url": "=https://www.googleapis.com/youtube/v3/captions/{{ $json.items[0].id }}?tfmt=srt",
        "options": {},
        "authentication": "predefinedCredentialType",
        "nodeCredentialType": "youTubeOAuth2Api"
      },
      "credentials": {
        "youTubeOAuth2Api": {
          "id": "1TkjUqPfFCQ6NzL7",
          "name": "YouTube account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "0e15f334-9ff8-4a7e-85a9-4cf8cf10ea55",
      "name": "Extract Captions",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        240,
        -120
      ],
      "parameters": {
        "options": {},
        "operation": "text"
      },
      "typeVersion": 1
    },
    {
      "id": "af99a919-7ebc-4a6c-80be-83e2ffa68d05",
      "name": "Structured Captions",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        640,
        100
      ],
      "parameters": {
        "jsonSchemaExample": "{
	\"description\": \"California\"
	
}"
      },
      "typeVersion": 1.2
    },
    {
      "id": "414a41a2-0715-4a57-a606-9f3678b2472a",
      "name": "Get Video Meta Data",
      "type": "n8n-nodes-base.youTube",
      "position": [
        -420,
        -120
      ],
      "parameters": {
        "options": {},
        "videoId": "={{ $json.video_id }}",
        "resource": "video",
        "operation": "get"
      },
      "credentials": {
        "youTubeOAuth2Api": {
          "id": "1TkjUqPfFCQ6NzL7",
          "name": "YouTube account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "7304d9b1-5956-41c3-b78a-2c409d0aa726",
      "name": "Google Gemini Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        460,
        100
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-1.5-flash-8b-exp-0924"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "FshILEOmCAPVoGfW",
          "name": "Google Gemini(PaLM) Api account 2"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "867a6ad6-0712-4fbf-97fd-ab054b783172",
      "name": "Set Video ID",
      "type": "n8n-nodes-base.set",
      "position": [
        -640,
        -120
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "568762f7-e496-4550-8567-d49e2ce1676d",
              "name": "video_id",
              "type": "string",
              "value": "r1wqsrW2vmE"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "dcd0c9d7-1a69-45e8-98e9-b7cf7d12734e",
      "name": "Update Chapters",
      "type": "n8n-nodes-base.youTube",
      "position": [
        940,
        -120
      ],
      "parameters": {
        "title": "={{ $('Get Video Meta Data').item.json.snippet.title }}",
        "videoId": "={{ $('Get Captions').item.json.items[0].snippet.videoId }}",
        "resource": "video",
        "operation": "update",
        "categoryId": "22",
        "regionCode": "US",
        "updateFields": {
          "description": "={{ $json.output.description }}
Chapters
{{ $json.output.description }}"
        }
      },
      "credentials": {
        "youTubeOAuth2Api": {
          "id": "1TkjUqPfFCQ6NzL7",
          "name": "YouTube account"
        }
      },
      "typeVersion": 1,
      "alwaysOutputData": true
    },
    {
      "id": "916629c4-6e49-4432-88e8-626748cb3d24",
      "name": "Tag Chapters in Description",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        460,
        -120
      ],
      "parameters": {
        "text": "=This is an srt format data. please classify this data into chapters
based upon this transcript 
{{ $json.data }}
{
\"description\":\"00:00 Introduction
02:15 Topic One
05:30 Topic Two
10:45 Conclusion\"
}
",
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.6
    },
    {
      "id": "b0f56d68-b787-4ccc-8bb5-bdb5b04c3ae4",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -680,
        -200
      ],
      "parameters": {
        "width": 1040,
        "height": 440,
        "content": "
## Get Captions"
      },
      "typeVersion": 1
    },
    {
      "id": "0bcee6b5-0e8b-4f85-8f83-c829e785467a",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        378,
        -200
      ],
      "parameters": {
        "color": 4,
        "width": 420,
        "height": 440,
        "content": "## Generate Chapters
"
      },
      "typeVersion": 1
    },
    {
      "id": "0f90f6ec-2154-4945-b262-6531fef2334f",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        820,
        -200
      ],
      "parameters": {
        "color": 6,
        "width": 440,
        "height": 440,
        "content": "## Update Description
"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "27125160-7c64-4431-b243-832c1ae29d29",
  "connections": {
    "Get Captions": {
      "main": [
        [
          {
            "node": "Extract Captions",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set Video ID": {
      "main": [
        [
          {
            "node": "Get Video Meta Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get Caption ID": {
      "main": [
        [
          {
            "node": "Get Captions",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Extract Captions": {
      "main": [
        [
          {
            "node": "Tag Chapters in Description",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get Video Meta Data": {
      "main": [
        [
          {
            "node": "Get Caption ID",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Structured Captions": {
      "ai_outputParser": [
        [
          {
            "node": "Tag Chapters in Description",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Tag Chapters in Description",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Tag Chapters in Description": {
      "main": [
        [
          {
            "node": "Update Chapters",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "Set Video ID",
            "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

Manualtrigger
Httprequest
Extractfromfile
@N8N/N8N Nodes Langchain.Outputparserstructured
Youtube

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