Claude AI 텍스트 생성기를 사용하여 Lightroom에서 Instagram까지 자동화

• •대상 API의 인증 정보가 필요할 수 있음

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        "content": "### Lightroom → Instagram: Photos-to-Post Queue (n8n)\n\n**Purpose**  \nWatch a Lightroom Cloud album, store new assets in a **Photos** Data Table, and generate AI alt text for captions/accessibility.\n\n**Must-configure**\n- **Lightroom API:** OAuth (Adobe) + **X-API-Key**; set your **LR catalog ID** and **LR album ID**.\n- **n8n base URL:** Publicly reachable; used by the image proxy webhook.\n- **LLM credentials:** Anthropic (or equivalent) for alt text.\n- **Data Table (Photos) minimal schema:** `lr_asset_id` (unique), `lr_asset` (JSON string), `alt` (string).\n- **Schedule:** How often to poll the album.\n- **Dedupe:** Use **rowNotExists** on `lr_asset_id` to avoid duplicates.\n- **Params Node**"
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    {
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      "name": "HTTP 요청",
      "type": "n8n-nodes-base.httpRequest",
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        "url": "=https://lr.adobe.io/v2/catalogs/{{ $json[\"LR catalog ID\"] }}/albums/{{ $json[\"LR album ID\"] }}/assets?embed=asset ",
        "options": {
          "response": {
            "response": {
              "responseFormat": "text"
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        "sendHeaders": true,
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        "genericAuthType": "oAuth2Api",
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              "name": "X-API-Key",
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        "oAuth2Api": {
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          "name": "Lightroom Camille"
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          "name": "Instagram @camillerouxphoto"
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        "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"
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      "name": "분할",
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        "options": {},
        "fieldToSplitOut": "parsed.resources"
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    {
      "id": "6c46f47f-ba78-490f-90eb-b5d6f4a5f7cf",
      "name": "이미지 분석",
      "type": "@n8n/n8n-nodes-langchain.anthropic",
      "position": [
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      ],
      "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={{ $json.asset.id }}&format=1280 "
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        "operation": "rowNotExists",
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          "__rl": true,
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            "lr_asset": "={{ JSON.stringify($('Split Out').item.json.asset) }}",
            "lr_asset_id": "={{ $('Split Out').item.json.asset.id }}"
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              "type": "dateTime",
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              "removed": false,
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              "id": "ig_caption",
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              "id": "lr_asset",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": false,
              "required": false,
              "displayName": "lr_asset",
              "defaultMatch": false
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              "id": "alt",
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              "defaultMatch": false
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              "name": "LR catalog ID",
              "type": "string",
              "value": "..."
            },
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              "id": "ec256e0e-71d9-43bd-8913-99213526b776",
              "name": "LR API key",
              "type": "string",
              "value": "..."
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              "id": "fde215d4-14d4-4659-9f57-defdb3c4733f",
              "name": "LR album ID",
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              "value": "..."
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        "width": 512,
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        "content": "## STEP1 = Download the image list from Lightroom Cloud\n\n"
      },
      "typeVersion": 1
    },
    {
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      "name": "메모지2",
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      "position": [
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        "content": "## STEP2 = Split and sort them\n\n\n"
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        "content": "## STEP3 = Analyse them with IA then save them in the Data Table\n\n\n"
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