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LinkedIn 자동 게시(含 GPT-4o 내용 및 이미지 생성 + Telegram 알림)

중급

이것은Social Media, Multimodal AI분야의자동화 워크플로우로, 7개의 노드를 포함합니다.주로 Set, Code, LinkedIn, Telegram, ManualTrigger 등의 노드를 사용하며. LinkedIn 자동 게시, GPT-4o로 내용 및 이미지 생성并보내기 Telegram 알림

사전 요구사항
  • LinkedIn API 인증 정보
  • Telegram Bot Token
  • OpenAI API Key
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
  "meta": {
    "instanceId": "559fe524ea9daad79a07a81fd3f64f8e3eeddd635511642951eaee3bf4d5ad7a",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "4a83a2f6-f6ab-4657-ab2a-c5594cc13aa7",
      "name": "make Linkedin 게시",
      "type": "n8n-nodes-base.linkedIn",
      "position": [
        432,
        -48
      ],
      "parameters": {
        "text": "={{ $('Generate Post Content').item.json.message.content.content }}",
        "person": "SKNqCfgpq4",
        "additionalFields": {
          "visibility": "PUBLIC"
        },
        "shareMediaCategory": "IMAGE"
      },
      "credentials": {
        "linkedInOAuth2Api": {
          "id": "VHltapEwLBeLEZ0g",
          "name": "LinkedIn account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "276f682f-15cb-4ecb-93f2-fb07f92603e7",
      "name": "상태 전송됨",
      "type": "n8n-nodes-base.telegram",
      "position": [
        688,
        -48
      ],
      "webhookId": "9373d46a-d5ad-40f4-93c0-7a44ff5fea37",
      "parameters": {
        "text": "=LinkedIn Post Sent Successfully  \n\nTag - {{ $('Get a random Tag').item.json.value }}\n\nURL - https://www.linkedin.com/feed/update/{{ $json.urn }}\n\nPosted At - {{ DateTime.now() }}",
        "chatId": "7281360444",
        "replyMarkup": "inlineKeyboard",
        "additionalFields": {
          "appendAttribution": false
        }
      },
      "credentials": {
        "telegramApi": {
          "id": "snxgmnTv52eI8TSD",
          "name": "Telegram account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "65b044fc-8595-4d00-9bbc-6f67a39a8d05",
      "name": "'워크플로 실행' 클릭 시",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -784,
        -48
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "1f6d49f5-4d49-4769-bd4a-2cdb5e28e125",
      "name": "이미지 생성",
      "type": "@n8n/n8n-nodes-langchain.openAi",
      "position": [
        192,
        -48
      ],
      "parameters": {
        "model": "gpt-image-1",
        "prompt": "={{ $json.message.content.prompt }}",
        "options": {},
        "resource": "image"
      },
      "credentials": {
        "openAiApi": {
          "id": "eXO8FZmhMVDhTRz9",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.8
    },
    {
      "id": "1fbd87ae-52ac-48e0-95d1-833ffc885a8b",
      "name": "랜덤 태그 가져오기",
      "type": "n8n-nodes-base.code",
      "position": [
        -560,
        -48
      ],
      "parameters": {
        "jsCode": "const devToTags = [\n  \"llm\",\n  \"ai\",\n  \"devops\",\n  \"cloudnative\",\n  \"observability\",\n  \"automation\",\n  \"opensource\",\n  \"cybersecurity\",\n  \"scalability\"\n];\n\nfunction getRandomValuesAsObjects(list, count) {\n  const randomValues = [];\n  for (let i = 0; i < count; i++) {\n    const randomIndex = Math.floor(Math.random() * list.length);\n    randomValues.push({ json: { value: list[randomIndex] } });\n  }\n  return randomValues;\n}\n\nreturn getRandomValuesAsObjects(devToTags, 1);\n"
      },
      "typeVersion": 2
    },
    {
      "id": "35d5303a-48a9-4b2b-945b-ca929e400553",
      "name": "예시 추가로 작성 스타일 설정",
      "type": "n8n-nodes-base.set",
      "position": [
        -352,
        -48
      ],
      "parameters": {
        "mode": "raw",
        "options": {},
        "jsonOutput": "{\n  \"posts\": [\n  \"Redis is open source YET AGAIN! But does it matter anymore? Here's the story: • 2009: Redis launched as open-source (BSD license). • 2018: Redis Labs introduced RSAL for modules like Redis Search, Graph etc. • 2024: Redis switched to a commercial license, as cloud providers copied Redis code without contributing back. • 2025: Redis is open source again with AGPL v3. But why? Big players like AWS, Google, and Oracle backed the Valkey fork—a fully open-source Redis alternative now under the Linux Foundation. Check out Valkey—\",\n  \"10x Faster Typescript COMPILER!!! Still there is an ongoing debate on why Microsoft didn't choose Rust or their own C# for this rewrite. Although, according to the team, Go was a better choice as it provided a similar structure and seamless transition. Had it been a ground-up rewrite and not a migration, Rust or C# would have been a better choice.\",\n  \"I recently started working on a Teams to Signal messenger bot after realizing that so many people outright hate using MS Teams, but since it's an industry standard, they cannot directly ditch it. My current goal is to support forwarding incoming text messages on Teams to a messenger like Signal. The second will be to give support for the reply mechanism from Signal and sync it to Teams. Coming to the technical stuff, I am thinking of using automation tools like Cypress or Playwright to do this. But it all boils down to the availability of public APIs of both messengers. I will try to document my progress here, as I might fail trying, like a lot of other times 😅 Let's see how it pans out. How would you approach this kind of problem?\",\n    \"Do you know about the require cache in Node.js? Lets say you have a js module that you have imported in a js file using require statement. It is highly possible that after a few iterations to your module code, the changes wont reflect even after you have reloaded the api server/modules. This happens because there is a module cache that happens. You need to invalidate it in order for the new changes to reflect. More on this here -\",\n    \"How important is Out-of-Box experience for an open source contributor? Nowadays I have been working on creating a seamless out-of-box experience for the new contributors of Sparrow API Tool. A poor app setup experience or hard-to-understand README file can be a serious dealbreaker for the community. I am emphasizing on the following things to make the setup as smooth as possible: 1) Created and hosted Docker images for various microservices like api-service and auth-service on DockerHub. 2) Created an all-in-one docker-compose file to set up everything from database to queue service in one command. 3) Created a migration script that generates a test user on app start—bypassing auth flow for instant contribution. 4) Documented multiple setup methods (Docker and non-Docker). 5) Pre-filled example .env files with required variables for copy-paste convenience. Let me know if you have suggestions to improve this further—I’m open to feedback!\"\n]\n}\n",
        "includeOtherFields": true
      },
      "typeVersion": 3.4,
      "alwaysOutputData": false
    },
    {
      "id": "7eaf45b6-e58f-41f5-83e6-ed168f039301",
      "name": "게시 콘텐츠 생성",
      "type": "@n8n/n8n-nodes-langchain.openAi",
      "position": [
        -160,
        -48
      ],
      "parameters": {
        "modelId": {
          "__rl": true,
          "mode": "id",
          "value": "gpt-4o"
        },
        "options": {},
        "messages": {
          "values": [
            {
              "role": "system",
              "content": "=Role: You are my LinkedIn content assistant. Your job is to write perfectly formatted LinkedIn posts that align with my brand voice, tone, and style (based on provided examples). Each post must revolve around a single keyword/tag and avoid unsupported formatting.\n\nCritical Formatting Rules:\n\nDont use bold, italics or bullets.\n\nWhenever you want to add points, use emojis or simple \"- \" before the start of each pointer \n\nDont use big hyphens that AI usually uses while generating content. Instead use comma(,)\n\nStructure:\n\nAn Engaging Hook\n\nPersonal POV (first-person: \"I’ve seen…\")\n\nInsights (trends/tools/case studies)\n\nClear spacing + new line wherever needed\n\nCTA/question (\"What’s your take?\")\n\nRelavant 4-5 treding hashtags\n\nTrends: \nTie to recent news, tools, or debates (no generic advice).\n\nImage Prompt Rules:\nSuggest an AI image prompt related to the post. Based on the post context, it can be:\n- App interface or UX concept\n- Visual metaphor (e.g. “scaling servers as rocket engines”)\n- Stack or architecture illustration\n- Abstract concept visuals (e.g. speed, chaos, control, balance)\n- Tech-product mockups or feature highlights\n- Flowcharts, only suggest if explaining a process, framework, or system\n\nResponse Format (Strictly JSON):\n```json\n{\n  \"content\": \"<LinkedIn-ready post with proper formatting and no markdown symbols>\",\n  \"prompt\": \"<AI image generation prompt – relevant, visual, descriptive>\"\n}"
            },
            {
              "role": "system",
              "content": "=Examples of my past writings. Use them to align the new post with my brand voice, tone, and style,\n\n{{ $json.posts.join(\"\\n\\n\") }}"
            },
            {
              "content": "=Use this tag to write a new article for Linkedin that follows my brand voice, style of writing, and tone. \nTag: {{ $json.value }}"
            }
          ]
        },
        "jsonOutput": true
      },
      "credentials": {
        "openAiApi": {
          "id": "eXO8FZmhMVDhTRz9",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.8
    }
  ],
  "pinData": {},
  "connections": {
    "1fbd87ae-52ac-48e0-95d1-833ffc885a8b": {
      "main": [
        [
          {
            "node": "35d5303a-48a9-4b2b-945b-ca929e400553",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "1f6d49f5-4d49-4769-bd4a-2cdb5e28e125": {
      "main": [
        [
          {
            "node": "4a83a2f6-f6ab-4657-ab2a-c5594cc13aa7",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "4a83a2f6-f6ab-4657-ab2a-c5594cc13aa7": {
      "main": [
        [
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            "node": "276f682f-15cb-4ecb-93f2-fb07f92603e7",
            "type": "main",
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    },
    "7eaf45b6-e58f-41f5-83e6-ed168f039301": {
      "main": [
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          {
            "node": "1f6d49f5-4d49-4769-bd4a-2cdb5e28e125",
            "type": "main",
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    "35d5303a-48a9-4b2b-945b-ca929e400553": {
      "main": [
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          {
            "node": "7eaf45b6-e58f-41f5-83e6-ed168f039301",
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    },
    "65b044fc-8595-4d00-9bbc-6f67a39a8d05": {
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            "type": "main",
            "index": 0
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        ]
      ]
    }
  }
}
자주 묻는 질문

이 워크플로우를 어떻게 사용하나요?

위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.

이 워크플로우는 어떤 시나리오에 적합한가요?

중급 - 소셜 미디어, 멀티모달 AI

유료인가요?

이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.

워크플로우 정보
난이도
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노드 수7
카테고리2
노드 유형6
난이도 설명

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저자

Hi, I’m Punit a DevOps & Cloud Engineer with a strong focus on automation and workflow orchestration using n8n. I specialize in building robust, scalable workflows that connect APIs, services, and internal tools to automate business processes end-to-end. Whether you need help setting up complex logic, integrating third-party tools, or deploying n8n in production, I’m here to help. Let’s work together to bring your automation ideas to life.

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