Workflow n8n

Automatise ta veille sur les réseaux sociaux

Collecte en continu posts et mentions, filtre par mots-clés et sentiments, déduplique les doublons, et envoie des alertes actionnables avec résumés et liens sources dans Slack/Notion. Tags clés : veille, réseaux sociaux, automation.

Catégorie: reseaux_sociaux · Tags: veille, réseaux sociaux, automation0

Vue d'ensemble du workflow n8n

Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.

Inscris-toi pour voir l'intégralité du workflow

Inscription gratuite

S'inscrire gratuitementBesoin d'aide ?
{
  "id": "mxeL3ryFF9XHcf9U",
  "meta": {
    "instanceId": "30a4552c4834a9b841576ac1861741b079d7cd74a111056aa611d1f476c3519c"
  },
  "name": "News to Content",
  "tags": [
    {
      "id": "LMoNhIfFqXz12oyB",
      "name": "Uclic",
      "createdAt": "2025-10-18T15:38:06.600Z",
      "updatedAt": "2025-10-18T15:38:06.600Z"
    }
  ],
  "nodes": [
    {
      "id": "7862a9a6-240c-4417-8f6d-0beea474e7fc",
      "name": "RSS Feed Trigger",
      "type": "n8n-nodes-base.rssFeedReadTrigger",
      "position": [
        -1440,
        432
      ],
      "parameters": {
        "feedUrl": "https://morss.it/https://techcrunch.com/feed/",
        "pollTimes": {
          "item": [
            {
              "mode": "everyHour"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "bf162b3c-4357-4314-8e35-6359957490e7",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -1296,
        624
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o",
          "cachedResultName": "gpt-4o"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "jvNEVczMAIjq1qib",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "f625e164-ea5e-4ddf-b0ab-ff34b8440a9c",
      "name": "Code",
      "type": "n8n-nodes-base.code",
      "position": [
        -896,
        432
      ],
      "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 markdown code blocks, escaped characters and parse JSON\n    let cleanedResponse = rawResponse\n      .replace(/```json\\n?/g, '')  // Remove opening markdown\n      .replace(/\\n?```/g, '')       // Remove closing markdown\n      .replace(/\\\\n/g, '')\n      .replace(/\\\\/g, '');\n    \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 with original article data if available\n    const rssData = $node[\"RSS Feed Trigger\"]?.json || {};\n    \n    parsedItems.push({\n      json: {\n        // Original article data (if available)\n        title: rssData.title || \"N/A\",\n        link: rssData.link || \"N/A\",\n        pubDate: rssData.pubDate || \"N/A\",\n        content: rssData['content:encoded'] || \"N/A\",\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    console.log(\"Parsing error:\", error.message);\n    console.log(\"Raw response:\", rawResponse);\n    \n    const rssData = $node[\"RSS Feed Trigger\"]?.json || {};\n    \n    parsedItems.push({\n      json: {\n        title: rssData.title || \"Parse Error\",\n        link: rssData.link || \"N/A\",\n        pubDate: rssData.pubDate || \"N/A\",\n        content: rssData['content:encoded'] || \"N/A\",\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": "f269601f-2bdf-4f71-b96a-caa1d707c197",
      "name": "Simple Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        -1136,
        640
      ],
      "parameters": {
        "sessionKey": "={{ $execution.id }}",
        "sessionIdType": "customKey"
      },
      "typeVersion": 1.3
    },
    {
      "id": "e28230aa-6e8b-47cd-944a-4b39c697523c",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -480,
        384
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "jvNEVczMAIjq1qib",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "cbd183f7-6379-4b4f-95c9-68576c064add",
      "name": "Code1",
      "type": "n8n-nodes-base.code",
      "position": [
        -160,
        176
      ],
      "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
    },
    {
      "id": "8dc291d0-f8f5-4aec-a0bb-5bfbd217371e",
      "name": "Store Content",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        0,
        0
      ],
      "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": [
            {
              "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",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Quality Score",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Quality Score",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Twitter Content",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Twitter Content",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "LinkedIn Content",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "LinkedIn Content",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Published (Yes/No)",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Published (Yes/No)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Performance Notes",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Performance Notes",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 922601424,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1f-Eott9X_hKkn9sx0lCG3iqKHb9xtMERsWq_fEBd_ns/edit#gid=922601424",
          "cachedResultName": "Generated Content"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1f-Eott9X_hKkn9sx0lCG3iqKHb9xtMERsWq_fEBd_ns",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1f-Eott9X_hKkn9sx0lCG3iqKHb9xtMERsWq_fEBd_ns/edit?usp=drivesdk",
          "cachedResultName": "Content Research System"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "zLpPnB2E6tcI02dz",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.7
    },
    {
      "id": "0838a27f-3c0f-47ef-bbd7-a5202fe8f49f",
      "name": "New for Review",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -288,
        512
      ],
      "parameters": {
        "columns": {
          "value": {
            "Link": "={{ $json.link }}",
            "Title": "={{ $json.title }}",
            "Summury": "={{ $json.summary }}",
            "Pub Date": "={{ $json.pubDate }}",
            "Content Angle": "={{ $json.content_angle }}",
            "Quality Score": "={{ $json.quality_score }}",
            "Relevance Score": "={{ $json.relevance_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": "Relevance Score",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Relevance Score",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Summury",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Summury",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Content Angle",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Content Angle",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Reviewer",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Reviewer",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Status",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Status",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Notes",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Notes",
              "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/1f-Eott9X_hKkn9sx0lCG3iqKHb9xtMERsWq_fEBd_ns/edit#gid=0",
          "cachedResultName": "For Review"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1f-Eott9X_hKkn9sx0lCG3iqKHb9xtMERsWq_fEBd_ns",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1f-Eott9X_hKkn9sx0lCG3iqKHb9xtMERsWq_fEBd_ns/edit?usp=drivesdk",
          "cachedResultName": "Content Research System"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "zLpPnB2E6tcI02dz",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.7
    },
    {
      "id": "3b8b68db-b6fd-4b02-a21d-0c1f3e98312b",
      "name": "Archive",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -288,
        672
      ],
      "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": 111046910,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1qlgo9kKDnD6j7GZ6AhKD3EVbFyQu6MfGNEsNCz9lizg/edit#gid=111046910",
          "cachedResultName": "Archive"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1qlgo9kKDnD6j7GZ6AhKD3EVbFyQu6MfGNEsNCz9lizg",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1qlgo9kKDnD6j7GZ6AhKD3EVbFyQu6MfGNEsNCz9lizg/edit?usp=drivesdk",
          "cachedResultName": "Content Research System"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "zLpPnB2E6tcI02dz",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.7
    },
    {
      "id": "d0cecd65-6451-42b5-82ab-49dd8cdc067b",
      "name": "LinkedIn Post",
      "type": "n8n-nodes-base.linkedIn",
      "position": [
        16,
        384
      ],
      "parameters": {
        "text": "={{ $json.linkedin_post }}",
        "postAs": "organization",
        "additionalFields": {}
      },
      "typeVersion": 1
    },
    {
      "id": "d24059c9-1171-4962-931d-42031a022730",
      "name": "X Post",
      "type": "n8n-nodes-base.twitter",
      "position": [
        16,
        192
      ],
      "parameters": {
        "text": "={{ $json.twitter_thread }}",
        "additionalFields": {}
      },
      "typeVersion": 2
    },
    {
      "id": "86bd7452-b8ea-49b1-930d-bf3e25f6cd8b",
      "name": "Content AI",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -464,
        192
      ],
      "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. Always write every content in French. \nOnly return the JSON object, nothing else."
        },
        "promptType": "define"
      },
      "typeVersion": 2.2
    },
    {
      "id": "a5c7c511-833b-4efe-8929-09e95fb187bf",
      "name": "Scoring AI",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -1232,
        432
      ],
      "parameters": {
        "text": "=Analyze this article: {{ $json.title }} - {{ $json['content:encoded'] }}",
        "options": {
          "systemMessage": "You are a content research assistant specializing in AI and automation topics.\n\nYour job is to analyze articles and determine their value for a content creator who focuses on:\n- AI tools and techniques\n- No-code automation platforms \n- Business automation workflows\n- AI news and developments\n\nIMPORTANT: You must respond with valid JSON in exactly this format:\n\n{\n  \"quality_score\": 8,\n  \"relevance_score\": 9,\n  \"key_topics\": \"AI tools\", \"automation\", \"business efficiency\",\n  \"summary\": \"Brief 2-3 sentence summary of the key points and main value.\",\n  \"content_angle\": \"Suggested angle for social media content creation\",\n  \"action\": \"PUBLISH\"\n}\n\nCRITICAL: Ensure all strings are properly quoted with double quotes. Arrays should contain quoted strings like [\"item1\", \"item2\", \"item3\"].\n\nScoring guidelines:\n- Quality Score (1-10): Based on source credibility, content depth, and usefulness\n- Relevance Score (1-10): How well it matches our AI/automation focus\n- Action: PUBLISH (scores 8+), REVIEW (scores 5-7), or ARCHIVE (scores <5)\n\nOnly return the JSON object, nothing else."
        },
        "promptType": "define"
      },
      "typeVersion": 2.2
    },
    {
      "id": "f65f71fb-6634-4248-bace-b0bd253e62bd",
      "name": "Quality Filter",
      "type": "n8n-nodes-base.if",
      "position": [
        -688,
        432
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "2588090c-6a4a-4609-a8f8-1c7e3cbdda12",
              "operator": {
                "type": "number",
                "operation": "gt"
              },
              "leftValue": "={{ $json.quality_score }}",
              "rightValue": 8
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "5d8f7f19-c70c-4da8-8711-e9986c299974",
      "name": "Quality Filter 2",
      "type": "n8n-nodes-base.if",
      "position": [
        -496,
        576
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "c488b7fd-18a5-432d-af06-7a9748db4778",
              "operator": {
                "type": "number",
                "operation": "gte"
              },
              "leftValue": "={{ $json.quality_score }}",
              "rightValue": 5
            }
          ]
        }
      },
      "typeVersion": 2.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "00ee8edd-e5d6-400d-97f6-4735fafeb9c9",
  "connections": {
    "Code": {
      "main": [
        [
          {
            "node": "Quality Filter",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Code1": {
      "main": [
        [
          {
            "node": "Store Content",
            "type": "main",
            "index": 0
          },
          {
            "node": "X Post",
            "type": "main",
            "index": 0
          },
          {
            "node": "LinkedIn Post",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Content AI": {
      "main": [
        [
          {
            "node": "Code1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Scoring AI": {
      "main": [
        [
          {
            "node": "Code",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Simple Memory": {
      "ai_memory": [
        [
          {
            "node": "Scoring AI",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Quality Filter": {
      "main": [
        [
          {
            "node": "Content AI",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Quality Filter 2",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Quality Filter 2": {
      "main": [
        [
          {
            "node": "New for Review",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Archive",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "RSS Feed Trigger": {
      "main": [
        [
          {
            "node": "Scoring AI",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Scoring AI",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "Content AI",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}