AI 기반 뉴스 모니터링 및 소셜 게시물 생성기 - OpenAI 및 Upload-Post

• •Google Sheets API 인증 정보
• •OpenAI API Key

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      "position": [
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      "parameters": {
        "width": 192,
        "height": 448,
        "content": "**Fetch**\n- RSS Feed Trigger"
      },
      "typeVersion": 1
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    {
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      "position": [
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      ],
      "parameters": {
        "width": 344,
        "height": 448,
        "content": "**Analyze & Score**\n- OpenAI Chat Model (Scoring)\n- Scoring AI"
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      "typeVersion": 1
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      "position": [
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      ],
      "parameters": {
        "width": 176,
        "height": 416,
        "content": "**Parse & Enrich**\n- Parse Scoring AI JSON"
      },
      "typeVersion": 1
    },
    {
      "id": "d5824fef-69dd-4344-97cb-54cb4326d789",
      "name": "섹션: 라우팅",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -2016,
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      ],
      "parameters": {
        "width": 400,
        "height": 448,
        "content": "**Route**\n- Quality Gate\n- Review vs Archive Filter"
      },
      "typeVersion": 1
    },
    {
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      ],
      "parameters": {
        "width": 380,
        "height": 416,
        "content": "**Content Generation**\n- OpenAI Chat Model (Content)\n- Content Generation AI\n- Parse Content AI JSON"
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      ],
      "parameters": {
        "width": 312,
        "height": 416,
        "content": "**Store & Publish**\n- Store Content (Google Sheets)\n- Publish to X, Threads, and LinkedIn"
      },
      "typeVersion": 1
    },
    {
      "id": "a1b9a4e6-7033-4f6a-b38f-17dd82a54c68",
      "name": "섹션: 검토 및 아카이브",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "width": 360,
        "height": 336,
        "content": "**Review & Archive**\n- New for Review (Sheet)\n- Archive (Sheet)"
      },
      "typeVersion": 1
    },
    {
      "id": "ecec5c9b-945a-4b90-be82-3eb918c402c6",
      "name": "RSS 피드 트리거",
      "type": "n8n-nodes-base.rssFeedReadTrigger",
      "position": [
        -2496,
        1488
      ],
      "parameters": {
        "feedUrl": "https://morss.it/https://techcrunch.com/feed/",
        "pollTimes": {
          "item": [
            {
              "mode": "everyHour"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "a589db79-e8da-4381-a537-21e515498a78",
      "name": "OpenAI 채팅 모델",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -2288,
        1664
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o",
          "cachedResultName": "gpt-4o"
        },
        "options": {}
      },
      "credentials": {
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          "id": "XJdxgMSXFgwReSsh",
          "name": "n8n key"
        }
      },
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    },
    {
      "id": "9772cc4e-e487-4383-b806-691736d3b0e4",
      "name": "코드",
      "type": "n8n-nodes-base.code",
      "position": [
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      ],
      "parameters": {
        "jsCode": "// Parse AI Agent JSON response\nconst items = $input.all();\nconst parsedItems = [];\n\nfor (const item of items) {\n  const rawResponse = item.json.output;\n  \n  try {\n    // Clean up escaped characters and parse the JSON response from AI\n    const cleanedResponse = rawResponse.replace(/\\\\n/g, '').replace(/\\\\/g, '');\n    const aiAnalysis = JSON.parse(cleanedResponse);\n    \n    // Handle key_topics - it might be a string or array\n    let topicsString = \"\";\n    if (Array.isArray(aiAnalysis.key_topics)) {\n      topicsString = aiAnalysis.key_topics.join(\", \");\n    } else if (typeof aiAnalysis.key_topics === 'string') {\n      topicsString = aiAnalysis.key_topics;\n    }\n    \n    // Combine original article data with parsed AI analysis\n    parsedItems.push({\n      json: {\n        // Original article data\n        title: $node[\"RSS Feed Trigger\"].json.title,\n        link: $node[\"RSS Feed Trigger\"].json.link,\n        pubDate: $node[\"RSS Feed Trigger\"].json.pubDate,\n        content: $node[\"RSS Feed Trigger\"].json['content:encoded'],\n        \n        // Parsed AI analysis\n        quality_score: aiAnalysis.quality_score || 5,\n        relevance_score: aiAnalysis.relevance_score || 5,\n        key_topics: topicsString,\n        summary: aiAnalysis.summary || \"No summary provided\",\n        content_angle: aiAnalysis.content_angle || \"No angle provided\",\n        action: aiAnalysis.action || \"REVIEW\"\n      }\n    });\n    \n  } catch (error) {\n    // Handle parsing errors gracefully\n    console.log(\"Parsing error:\", error.message);\n    console.log(\"Raw response:\", rawResponse);\n    \n    parsedItems.push({\n      json: {\n        title: $node[\"RSS Feed Trigger\"].json.title,\n        link: $node[\"RSS Feed Trigger\"].json.link,\n        pubDate: $node[\"RSS Feed Trigger\"].json.pubDate,\n        content: $node[\"RSS Feed Trigger\"].json['content:encoded'],\n        quality_score: 5,\n        relevance_score: 5,\n        key_topics: \"Parse Error\",\n        summary: \"AI response could not be parsed: \" + error.message,\n        content_angle: \"Manual review needed\",\n        action: \"REVIEW\"\n      }\n    });\n  }\n}\n\nreturn parsedItems;"
      },
      "typeVersion": 2
    },
    {
      "id": "95ce7b87-d6ff-4efe-a9b8-d516a3bf8f35",
      "name": "심플 메모리",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        -2192,
        1696
      ],
      "parameters": {
        "sessionKey": "={{ $execution.id }}",
        "sessionIdType": "customKey"
      },
      "typeVersion": 1.3
    },
    {
      "id": "9f585af3-e98e-4cb0-bdd3-ffc7409d5b9b",
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      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
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        1408
      ],
      "parameters": {
        "model": {
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          "mode": "list",
          "value": "gpt-4.1",
          "cachedResultName": "gpt-4.1"
        },
        "options": {}
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      "type": "n8n-nodes-base.code",
      "position": [
        -1216,
        1232
      ],
      "parameters": {
        "jsCode": "// Parse content creation AI response\nconst items = $input.all();\nconst contentItems = [];\n\nfor (const item of items) {\n  try {\n    const rawResponse = item.json.output;\n    const cleanedResponse = rawResponse.replace(/\\\\\\\\n/g, '').replace(/\\\\\\\\/g, '');\n    const contentData = JSON.parse(cleanedResponse);\n\n    // Get the original article data\n    const originalData = $node[\"Code\"].json; // Reference our enhanced parsing node\n\n    contentItems.push({\n      json: {\n        // Original article info\n        title: originalData.title,\n        link: originalData.link,\n        quality_score: originalData.quality_score,\n        relevance_score: originalData.relevance_score,\n        summary: originalData.summary,\n\n        // Generated content\n        twitter_thread: contentData.twitter_thread || [],\n        linkedin_post: contentData.linkedin_post || \"Content generation failed\",\n        content_ready: contentData.content_ready || false,\n\n        // Metadata\n        created_at: new Date().toISOString(),\n        platform_ready: true\n      }\n    });\n\n  } catch (error) {\n    // Handle parsing errors\n    contentItems.push({\n      json: {\n        title: $node[\"Code\"].json.title,\n        link: $node[\"Code\"].json.link,\n        twitter_thread: [\"Content generation failed\"],\n        linkedin_post: \"Content generation failed: \" + error.message,\n        content_ready: false,\n        error: error.message\n      }\n    });\n  }\n}\n\nreturn contentItems;\n"
      },
      "typeVersion": 2
    },
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      "id": "9263bf82-338b-4a87-b16b-f118b03adf1e",
      "name": "콘텐츠 저장",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -992,
        1232
      ],
      "parameters": {
        "columns": {
          "value": {
            "Article Link": "={{ $json.link }}",
            "Date Created": "={{ $now }}",
            "Article Title": "={{ $json.title }}",
            "Quality Score": "={{ $json.quality_score }}",
            "Twitter Content": "={{ $json.twitter_thread[0] }}{{ $json.twitter_thread[1] }}{{ $json.twitter_thread[2] }}{{ $json.twitter_thread[3] }}",
            "LinkedIn Content": "={{ $json.linkedin_post }}"
          },
          "schema": [
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              "id": "Date Created",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Date Created",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Article Title",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Article Title",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Article Link",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Article Link",
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              "canBeUsedToMatch": true
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              "display": true,
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              "canBeUsedToMatch": true
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              "id": "Twitter Content",
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              "displayName": "LinkedIn Content",
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              "canBeUsedToMatch": true
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              "id": "Published (Yes/No)",
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              "displayName": "Published (Yes/No)",
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              "canBeUsedToMatch": true
            },
            {
              "id": "Performance Notes",
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              "canBeUsedToMatch": true
            }
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          "mode": "list",
          "value": "gid=0",
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      "position": [
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        1568
      ],
      "parameters": {
        "columns": {
          "value": {
            "Link": "={{ $json.link }}",
            "Title": "={{ $json.title }}",
            "Summary": "={{ $json.summary }}",
            "Pub Date": "={{ $json.pubDate }}",
            "Content Angle": "={{ $json.content_angle }}",
            "Quality Score": "={{ $json.quality_score }}",
            "Relevance Score": "={{ $json.relevance_score }}"
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              "id": "Title",
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            },
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              "canBeUsedToMatch": true
            },
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              "canBeUsedToMatch": true
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              "canBeUsedToMatch": true
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          "__rl": true,
          "mode": "list",
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          "cachedResultName": "Content Research System"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
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      "name": "아카이브",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -1360,
        1728
      ],
      "parameters": {
        "columns": {
          "value": {
            "Link": "={{ $json.link }}",
            "Title": "={{ $json.title }}",
            "Reason": "={{ $json.summary }}",
            "Pub Date": "={{ $json.pubDate }}",
            "Quality Score": "={{ $json.quality_score }}"
          },
          "schema": [
            {
              "id": "Title",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Title",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Link",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Link",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Pub Date",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Pub Date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Quality Score",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Quality Score",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Reason",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Reason",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1lg_9P1CJ8QT2fT2UBZChtxr8TZhpca1LzgSzm65Eldo/edit#gid=0",
          "cachedResultName": "Hoja 1"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1lg_9P1CJ8QT2fT2UBZChtxr8TZhpca1LzgSzm65Eldo",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1lg_9P1CJ8QT2fT2UBZChtxr8TZhpca1LzgSzm65Eldo/edit?usp=drivesdk",
          "cachedResultName": "horoscopo"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "3IOU2VjBnR4hGohx",
          "name": "Google Sheets account"
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    },
    {
      "id": "6a76195f-77b3-45e6-b80c-a0e2a21a1124",
      "name": "콘텐츠 AI",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -1520,
        1248
      ],
      "parameters": {
        "text": "=Create social media content for this article:\n\nTitle: {{ $json.title }}\nSummary: {{ $json.summary }}\nSuggested Angle: {{ $json.content_angle }}\nLink: {{ $json.link }}\n\nArticle scored {{ $json.quality_score }}/10 for quality and {{ $json.relevance_score }}/10 for relevance.\n",
        "options": {
          "systemMessage": "You are an expert social media content creator specializing in AI and automation topics.\n\nYour job is to take high-quality articles and create engaging, platform-specific content that drives audience engagement and positions the author as a thought leader.\n\nFor each article, create content for these platforms:\n\nTWITTER THREAD (3-4 tweets):\n- Tweet 1: Hook that grabs attention and introduces the main insight\n- Tweet 2-3: Key takeaways with specific examples or data\n- Tweet 4: Call-to-action with link to original article\n- Use emojis strategically\n- Keep each tweet under 280 characters\n\nLINKEDIN POST:\n- Professional tone suitable for business audience\n- 150-200 word summary highlighting business value\n- Include 2-3 key insights from the article\n- End with an engaging question to drive comments\n- Use professional hashtags (#artificialintelligence #businessautomation #productivity)\n\nReturn your response as valid JSON in this exact format:\n{\n  \"twitter_thread\": [\"tweet 1 text\", \"tweet 2 text\", \"tweet 3 text\", \"tweet 4 text\"],\n  \"linkedin_post\": \"full linkedin post text here\",\n  \"content_ready\": true\n}\n\nFocus on value, insights, and engagement. Avoid being overly promotional."
        },
        "promptType": "define"
      },
      "typeVersion": 2.2
    },
    {
      "id": "c3014888-18b3-415d-902e-aec5e62fe703",
      "name": "점수 매기기 AI",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -2288,
        1488
      ],
      "parameters": {
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