New OpenAI Image Generation

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": "FyoPGDh8r3pxcGxo",
  "meta": {
    "instanceId": "bcc0fe85b176c2837affb21bb7d7397fad2549880e73dc1f7a42e76ae94fd996"
  },
  "name": "New OpenAI Image Generation",
  "tags": [
    {
      "id": "SGTGlhD84tHTcai7",
      "name": "image gen",
      "createdAt": "2025-04-07T09:41:10.936Z",
      "updatedAt": "2025-04-07T09:41:10.936Z"
    }
  ],
  "nodes": [
    {
      "id": "6b5f9234-351f-4f6b-a0ab-f0d30897f60a",
      "name": "Convert to File",
      "type": "n8n-nodes-base.convertToFile",
      "position": [
        320,
        400
      ],
      "parameters": {
        "options": {},
        "operation": "toBinary",
        "sourceProperty": "b64_json"
      },
      "typeVersion": 1.1
    },
    {
      "id": "9c60f827-bf37-486b-9026-0cbe97fd83b6",
      "name": "OpenAI - Generate Image",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -120,
        400
      ],
      "parameters": {
        "url": "https://api.openai.com/v1/images/generations",
        "method": "POST",
        "options": {},
        "jsonBody": "={
  \"model\": \"{{ $json.openai_image_model }}\",
  \"prompt\": \"{{ $json.image_prompt }}\",
  \"n\": {{ $json.number_of_images }},
  \"size\": \"{{ $json.size_of_image }}\",
  \"quality\": \"{{ $json.quality_of_image }}\"
}",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "authentication": "predefinedCredentialType",
        "headerParameters": {
          "parameters": [
            {
              "name": "Content-Type",
              "value": "application/json"
            }
          ]
        },
        "nodeCredentialType": "openAiApi"
      },
      "credentials": {
        "openAiApi": {
          "id": "KzjXYSuzUOCnnvzB",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "2dd04b96-5faf-48ec-a7b0-66a31866388d",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -560,
        400
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "629799c0-d2ff-4c5a-95d8-54d5afd3ac66",
      "name": "Set Variables",
      "type": "n8n-nodes-base.set",
      "position": [
        -340,
        400
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "2a5d52c2-5af1-4796-acba-4e1807fc7d7b",
              "name": "image_prompt",
              "type": "string",
              "value": "a 4-frame cartoon strip telling a joke about AI"
            },
            {
              "id": "c41a8091-d952-4f5a-ae24-3b0691bbce57",
              "name": "number_of_images",
              "type": "number",
              "value": 2
            },
            {
              "id": "00feec5a-19c8-43af-bf93-e0729d1391f8",
              "name": "quality_of_image",
              "type": "string",
              "value": "high"
            },
            {
              "id": "1b359a11-c05a-49c8-aa27-402b145fcbc1",
              "name": "size_of_image",
              "type": "string",
              "value": "1024x1024"
            },
            {
              "id": "6cf4ba85-d11a-48bb-9eaf-4084c9538d87",
              "name": "openai_image_model",
              "type": "string",
              "value": "=gpt-image-1"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "5f4e4bbe-7331-42dc-86a3-5d9de658ea07",
      "name": "Separate Image Outputs",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        100,
        400
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "data"
      },
      "typeVersion": 1
    },
    {
      "id": "0c0310a4-f354-4810-a967-ea002be09cc4",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -600,
        580
      ],
      "parameters": {
        "width": 1140,
        "height": 220,
        "content": "## [CLICK HERE to Watch Video](https://youtu.be/YmDezgolqzU?si=BgMjRm55-T_CYAs7)

OpenAI just dropped API access for their new image generation — and it changes everything. In this quick walkthrough, I show you exactly how to integrate it with n8n using an HTTP request node. Learn how to send prompts, convert base64 to binary, and automate image handling. This is a big one. Don’t miss it.

🔗 Official API Overview: https://openai.com/index/image-generation-api/
🔗 API Reference – Create Image: https://platform.openai.com/docs/api-reference/images/create

### *New:  Make.com scenario here: https://drive.google.com/file/d/1Uz-mA0LnUZ_tnUWBR2AAlVxs3LBlGKfk/view?usp=sharing
"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "c7fef832-b7ba-4cb1-ad36-7a82f81a7f90",
  "connections": {
    "Set Variables": {
      "main": [
        [
          {
            "node": "OpenAI - Generate Image",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Separate Image Outputs": {
      "main": [
        [
          {
            "node": "Convert to File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI - Generate Image": {
      "main": [
        [
          {
            "node": "Separate Image Outputs",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "Set Variables",
            "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

  • Converttofile
  • Httprequest
  • Manualtrigger
  • Set
  • Splitout

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