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使用 Claude AI 替代文本生成器从 Lightroom 到 Instagram 自动化

中级

这是一个Social Media, Multimodal AI领域的自动化工作流，包含 14 个节点。主要使用 Set, Code, Sort, SplitOut, DataTable 等节点。 使用 Claude AI 替代文本生成器从 Lightroom 到 Instagram 自动化

前置要求
  • •可能需要目标 API 的认证凭证

使用的节点 (14)

Set
Code
Sort
SplitOut
DataTable
StickyNote
HttpRequest
SplitInBatches
ScheduleTrigger
Anthropic

分类

社交媒体
多模态 AI
工作流预览
可视化展示节点连接关系，支持缩放和平移
React Flow
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
  "meta": {
    "instanceId": "57636d705a86a73b059f5900e8853e2c306d74773d27ee7f6c0fae07093009ef"
  },
  "nodes": [
    {
      "id": "466448fc-8554-49c7-a6e7-8e5ded1d43ea",
      "name": "便签",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -32,
        0
      ],
      "parameters": {
        "width": 464,
        "height": 400,
        "content": "### Lightroom → Instagram：照片到帖子队列 (n8n)"
      },
      "typeVersion": 1
    },
    {
      "id": "2694839a-5677-4a39-951d-d1d1a773d756",
      "name": "HTTP 请求",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        736,
        480
      ],
      "parameters": {
        "url": "=https://lr.adobe.io/v2/catalogs/{{ $json[\"LR catalog ID\"] }}/albums/{{ $json[\"LR album ID\"] }}/assets?embed=asset ",
        "options": {
          "response": {
            "response": {
              "responseFormat": "text"
            }
          }
        },
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "oAuth2Api",
        "headerParameters": {
          "parameters": [
            {
              "name": "X-API-Key",
              "value": "={{ $json[\"LR API key\"] }}"
            }
          ]
        }
      },
      "credentials": {
        "oAuth2Api": {
          "id": "nv3KEXFaYuFgl9pg",
          "name": "Lightroom Camille"
        },
        "httpBearerAuth": {
          "id": "HSch2E1Drk2LTOp0",
          "name": "Instagram @camillerouxphoto"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "387d3cfb-7315-4d17-a528-09e9c1e0688c",
      "name": "JavaScript 代码",
      "type": "n8n-nodes-base.code",
      "position": [
        960,
        480
      ],
      "parameters": {
        "jsCode": "/**\n * Nettoie le préfixe XSSI \"while(1){}\" des réponses Adobe Lightroom\n * puis parse en JSON. L'item résultant contient:\n *  - parsed: l'objet JSON parsé\n *  - raw: le texte brut nettoyé (optionnel, utile pour debug)\n *\n * Le code gère aussi les cas où l'entrée serait déjà un objet,\n * ou si la chaîne ne contient pas le préfixe.\n */\n\nfunction stripAdobePrefix(s) {\n  // supprime \"while(1){}\" avec ou sans espaces\n  const re = /^\\s*while\\s*\\(\\s*1\\s*\\)\\s*{\\s*}\\s*/;\n  return s.replace(re, '');\n}\n\nlet input = $json;\n\n// Si le node précédent a renvoyé la réponse sous un autre champ,\n// adapte cette ligne (par ex. input.body, input.data, etc.)\nif (typeof input !== 'string') {\n  // tente quelques emplacements possibles\n  if (typeof input.body === 'string') input = input.body;\n  else if (typeof input.data === 'string') input = input.data;\n  else if (typeof input.string === 'string') input = input.string;\n  else if (typeof input === 'object') {\n    // déjà un objet ? On renvoie tel quel.\n    return {\n      parsed: input,\n      raw: JSON.stringify(input),\n      _note: 'Entrée déjà objet — pas de nettoyage nécessaire.'\n    };\n  } else {\n    // fallback: stringify\n    input = JSON.stringify(input);\n  }\n}\n\nconst cleaned = stripAdobePrefix(input);\n\n// Essaie de parser proprement\ntry {\n  const parsed = JSON.parse(cleaned);\n  return {\n    parsed,\n    raw: cleaned\n  };\n} catch (err) {\n  // En cas d’erreur, on renvoie quand même la chaîne nettoyée pour debug\n  return {\n    parsed: null,\n    raw: cleaned,\n    error: `JSON.parse a échoué: ${err && err.message ? err.message : String(err)}`\n  };\n}\n"
      },
      "typeVersion": 2
    },
    {
      "id": "56501cf9-12bb-4e24-a27e-6d45d2b65c9d",
      "name": "分离输出",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        1184,
        480
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "parsed.resources"
      },
      "typeVersion": 1
    },
    {
      "id": "6c46f47f-ba78-490f-90eb-b5d6f4a5f7cf",
      "name": "分析图像",
      "type": "@n8n/n8n-nodes-langchain.anthropic",
      "position": [
        2336,
        512
      ],
      "parameters": {
        "text": "You are a photography-savvy describer. Analyze the image and write a factual, SEO-oriented English alt description (single paragraph, up to 500 characters). Focus on visible subject, composition/framing/perspective, lighting (type, direction, quality), colors/contrast, mood, setting/background, and any clearly legible text. Avoid guesses about brand, gear, identities, dates, or locations unless unambiguously visible. No sensitive attributes, no hashtags/emojis, no calls to action. Output only the paragraph.\n",
        "modelId": {
          "__rl": true,
          "mode": "list",
          "value": "claude-sonnet-4-5-20250929",
          "cachedResultName": "claude-sonnet-4-5-20250929"
        },
        "options": {},
        "resource": "image",
        "imageUrls": "={{ $('Params').item.json[\"n8n instance URL\"] }}/webhook/lr-image?catalogId={{ $('Params').item.json[\"LR catalog ID\"] }}&assetId={{ $json.asset.id }}&format=1280 "
      },
      "credentials": {
        "anthropicApi": {
          "id": "9xU4CUFgJLLaeCNB",
          "name": "Anthropic account"
        }
      },
      "retryOnFail": true,
      "typeVersion": 1
    },
    {
      "id": "86e95eea-9e5c-4791-ac93-938daee1f480",
      "name": "如果行不存在",
      "type": "n8n-nodes-base.dataTable",
      "position": [
        1632,
        480
      ],
      "parameters": {
        "filters": {
          "conditions": [
            {
              "keyName": "lr_asset_id",
              "keyValue": "={{ $json.asset.id }}"
            }
          ]
        },
        "operation": "rowNotExists",
        "dataTableId": {
          "__rl": true,
          "mode": "list",
          "value": "Z4VvX6MjrmHmlAiY",
          "cachedResultUrl": "/projects/wrMsdivh0K45jnU5/datatables/Z4VvX6MjrmHmlAiY",
          "cachedResultName": "Photos"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "28ffac78-712b-4405-a9e7-161edfb4bce4",
      "name": "插入行",
      "type": "n8n-nodes-base.dataTable",
      "position": [
        2560,
        512
      ],
      "parameters": {
        "columns": {
          "value": {
            "alt": "={{ $json.content[0].text }}",
            "lr_asset": "={{ JSON.stringify($('Split Out').item.json.asset) }}",
            "lr_asset_id": "={{ $('Split Out').item.json.asset.id }}"
          },
          "schema": [
            {
              "id": "lr_asset_id",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "lr_asset_id",
              "defaultMatch": false
            },
            {
              "id": "lr_album_id",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "lr_album_id",
              "defaultMatch": false
            },
            {
              "id": "ig_posted_at",
              "type": "dateTime",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "ig_posted_at",
              "defaultMatch": false
            },
            {
              "id": "ig_link",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "ig_link",
              "defaultMatch": false
            },
            {
              "id": "ig_caption",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "ig_caption",
              "defaultMatch": false
            },
            {
              "id": "lr_asset",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "lr_asset",
              "defaultMatch": false
            },
            {
              "id": "alt",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "alt",
              "defaultMatch": false
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "dataTableId": {
          "__rl": true,
          "mode": "list",
          "value": "Z4VvX6MjrmHmlAiY",
          "cachedResultUrl": "/projects/wrMsdivh0K45jnU5/datatables/Z4VvX6MjrmHmlAiY",
          "cachedResultName": "Photos"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0bfc2470-666e-4aa9-94a5-c5e781fd931d",
      "name": "排序",
      "type": "n8n-nodes-base.sort",
      "position": [
        1408,
        480
      ],
      "parameters": {
        "options": {},
        "sortFieldsUi": {
          "sortField": [
            {
              "fieldName": "asset.payload.captureDate"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "b4b23fa3-b7cb-441d-8d32-5d7e04745e38",
      "name": "计划触发器",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        0,
        480
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "hours"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "66066e44-0326-4f2e-9870-3c35818e75df",
      "name": "遍历项目",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        2080,
        480
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "7fbb8e78-78de-494e-b090-f1b1805c3714",
      "name": "参数",
      "type": "n8n-nodes-base.set",
      "position": [
        208,
        480
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "d354b020-5d5c-4270-8dfb-0dc02e9bd9db",
              "name": "LR catalog ID",
              "type": "string",
              "value": "..."
            },
            {
              "id": "ec256e0e-71d9-43bd-8913-99213526b776",
              "name": "LR API key",
              "type": "string",
              "value": "..."
            },
            {
              "id": "fde215d4-14d4-4659-9f57-defdb3c4733f",
              "name": "LR album ID",
              "type": "string",
              "value": "..."
            },
            {
              "id": "978ee1e9-3d6f-4d87-afaf-c9926a20b690",
              "name": "n8n instance URL",
              "type": "string",
              "value": "..."
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "43bc3fd0-5578-4070-bd2a-2562d20e5ded",
      "name": "便签1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        624,
        320
      ],
      "parameters": {
        "color": 5,
        "width": 512,
        "height": 400,
        "content": "## 步骤1 = 从 Lightroom Cloud 下载图像列表"
      },
      "typeVersion": 1
    },
    {
      "id": "642efa01-7722-4390-beaa-a3665d184133",
      "name": "便签2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1168,
        320
      ],
      "parameters": {
        "color": 5,
        "width": 720,
        "height": 400,
        "content": "## 步骤2 = 拆分并排序它们"
      },
      "typeVersion": 1
    },
    {
      "id": "267c95f8-1000-4ce7-8bd9-a2221f554923",
      "name": "便签3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1920,
        320
      ],
      "parameters": {
        "color": 5,
        "width": 848,
        "height": 400,
        "content": "## 步骤3 = 用 AI 分析它们然后保存到数据表中"
      },
      "typeVersion": 1
    }
  ],
  "pinData": {},
  "connections": {
    "Sort": {
      "main": [
        [
          {
            "node": "If row does not exist",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Params": {
      "main": [
        [
          {
            "node": "HTTP Request",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Split Out": {
      "main": [
        [
          {
            "node": "Sort",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Insert row": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "HTTP Request": {
      "main": [
        [
          {
            "node": "Code in JavaScript",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Analyze image": {
      "main": [
        [
          {
            "node": "Insert row",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Loop Over Items": {
      "main": [
        [],
        [
          {
            "node": "Analyze image",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "Params",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Code in JavaScript": {
      "main": [
        [
          {
            "node": "Split Out",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "If row does not exist": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
常见问题

如何使用这个工作流？

复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。

这个工作流适合什么场景？

中级 - 社交媒体, 多模态 AI

需要付费吗？

本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。

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工作流信息
难度等级
中级
节点数量14
分类2
节点类型10
难度说明

适合有一定经验的用户，包含 6-15 个节点的中等复杂度工作流

作者
Camille Roux

Camille Roux

@camilleroux
外部链接
在 n8n.io 查看 →

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