{
  "workflow": {
    "id": 4586,
    "name": "Automate LinkedIn engagement with Phantombuster, OpenAI GPT & Google Sheets tracking",
    "views": 1210,
    "recentViews": 0,
    "totalViews": 1210,
    "createdAt": "2025-06-02T08:48:48.133Z",
    "description": "\n\n## Workflow Overview\nThis sophisticated n8n automation is a powerful LinkedIn engagement and networking tool designed to revolutionize professional social media interaction. By intelligently combining web scraping, AI, and automation technologies, this workflow:\n\n1. **Discovers Relevant Content**: \n   - Automatically scrapes LinkedIn posts\n   - Identifies target profiles and recent content\n   - Ensures consistent networking opportunities\n\n2. **Generates Intelligent Interactions**:\n   - Uses AI to craft contextual, professional comments\n   - Ensures human-like, valuable engagement\n   - Maintains professional tone and relevance\n\n3. **Automates Engagement Process**:\n   - Likes and comments on selected posts\n   - Increases visibility and connection potential\n   - Builds professional network systematically\n\n4. **Comprehensive Activity Tracking**:\n   - Logs all interactions in Google Sheets\n   - Provides transparent engagement history\n   - Enables performance analysis and optimization\n\n## Key Benefits\n- 🤖 **Full Automation**: Consistent daily networking\n- 💡 **AI-Powered Interactions**: Intelligent, context-aware engagement\n- 📊 **Detailed Tracking**: Comprehensive interaction logging\n- 🌐 **Professional Visibility**: Strategic online presence management\n\n## Workflow Architecture\n\n### 🔹 Stage 1: Content Discovery\n- **Scheduled Trigger**: Daily post scanning\n- **Phantombuster Integration**: LinkedIn post scraping\n- **Targeted Profile Research**:\n  - Identifies recent posts\n  - Extracts critical post metadata\n\n### 🔹 Stage 2: AI-Powered Interaction\n- **OpenAI GPT Model**: Generates contextual comments\n- **Intelligent Analysis**:\n  - Understands post content\n  - Crafts personalized responses\n- **Professional Tone Maintenance**\n\n### 🔹 Stage 3: Engagement Automation\n- **Automated Liking**: Increases post visibility\n- **Intelligent Commenting**: \n  - Posts AI-generated comments\n  - Ensures meaningful interaction\n\n### 🔹 Stage 4: Performance Logging\n- **Google Sheets Integration**\n- **Comprehensive Activity Tracking**\n- **Interaction History Preservation**\n\n## Potential Use Cases\n- **Sales Professionals**: Lead generation and networking\n- **Marketers**: Increased brand visibility\n- **Recruiters**: Talent discovery and engagement\n- **Entrepreneurs**: Professional network expansion\n- **Content Creators**: Audience interaction and growth\n\n## Setup Requirements\n1. **Phantombuster Account**\n   - API key\n   - Configured LinkedIn scraping agents\n   - Profile URL list\n\n2. **OpenAI API**\n   - GPT model access\n   - API key for comment generation\n   - Preferred language model\n\n3. **Google Sheets**\n   - Connected Google account\n   - Prepared tracking spreadsheet\n   - Appropriate sharing settings\n\n4. **n8n Installation**\n   - Cloud or self-hosted instance\n   - Workflow configuration\n   - API credential management\n\n## Future Enhancement Suggestions\n- 🤖 Advanced sentiment analysis\n- 📊 Engagement performance metrics\n- 🎯 Intelligent post targeting\n- 🔍 Machine learning optimization\n- 🌐 Multi-platform support\n\n## Technical Considerations\n- Implement robust error handling\n- Use exponential backoff for API calls\n- Maintain flexible engagement strategies\n- Ensure compliance with platform guidelines\n\n## Ethical Guidelines\n- Respect professional networking etiquette\n- Maintain genuine, value-adding interactions\n- Avoid spammy or repetitive engagement\n- Prioritize quality over quantity\n\n\n## Connect With Me\n\n**Ready to revolutionize your professional networking?**\n\n📧 **Email**: Yaron@nofluff.online\n\n🎥 **YouTube**: [@YaronBeen](https://www.youtube.com/@YaronBeen/videos)\n\n💼 **LinkedIn**: [Yaron Been](https://www.linkedin.com/in/yaronbeen/)\n\n**Transform your LinkedIn strategy with intelligent, automated workflows!**\n\n#LinkedInAutomation #AINetworking #ProfessionalGrowth #CareerStrategy #NetworkingTech #AIMarketing #ProfessionalDevelopment #SocialMediaStrategy #ContentEngagement #BusinessIntelligence",
    "workflow": {
      "id": "kMppQ9OLVQ08LU6M",
      "meta": {
        "instanceId": "84ad02d6104594179f43f1ce9cfe3a81637b2faedb57dafcb9e649b7542988db",
        "templateCredsSetupCompleted": true
      },
      "name": "LinkedIn Post Engagement using Phantombuster",
      "tags": [],
      "nodes": [
        {
          "id": "9374a17f-fb35-4862-ba86-d52d0c616ee6",
          "name": "Daily Trigger - 9 AM",
          "type": "n8n-nodes-base.scheduleTrigger",
          "position": [
            0,
            0
          ],
          "parameters": {
            "rule": {
              "interval": [
                {
                  "triggerAtHour": 9
                }
              ]
            }
          },
          "typeVersion": 1.2
        },
        {
          "id": "c71ab77a-b12d-4966-a33f-d7204f5d31fd",
          "name": "LinkedIn Posts Scraper",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
            220,
            0
          ],
          "parameters": {
            "url": "https://api.phantombuster.com/api/v2/agent/launch",
            "method": "POST",
            "options": {},
            "jsonBody": "{\n  \"id\": \"YOUR_AGENT_ID\",\n  \"arguments\": {\n    \"profileUrls\": [\n      \"https://www.linkedin.com/in/USERNAME/\"\n    ],\n    \"numberOfPosts\": 1\n  },\n  \"save\": false\n}",
            "sendBody": true,
            "sendHeaders": true,
            "specifyBody": "json",
            "headerParameters": {
              "parameters": [
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                  "name": "X-Phantombuster-Key-1",
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          "typeVersion": 4.2
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        {
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          "name": "Fetch Scraper Results",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
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          ],
          "parameters": {
            "url": "https://api.phantombuster.com/api/v2/agent/fetch-output",
            "options": {},
            "sendQuery": true,
            "sendHeaders": true,
            "queryParameters": {
              "parameters": [
                {
                  "name": "id",
                  "value": "YOUR_AGENT_ID"
                }
              ]
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            "headerParameters": {
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                {
                  "name": "X-Phantombuster-Key-1",
                  "value": "YOUR_API_KEY"
                }
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          },
          "typeVersion": 4.2
        },
        {
          "id": "f7f1e974-9522-4692-9af8-1674bac0341a",
          "name": "Commenter Agent",
          "type": "@n8n/n8n-nodes-langchain.agent",
          "position": [
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          ],
          "parameters": {
            "text": "=You are a professional LinkedIn marketer. Your job is to write engaging, thoughtful, and relevant comments for posts to increase visibility and connection with the author.\n\nHere is the latest LinkedIn post:\n\nAuthor: {{ $json.authorName }}\nProfile: {{ $json.authorProfile }}\nPost URL: {{ $json.postUrl }}\nDate: {{ $json.date }}\nContent:\n\"\"\"\n{{ $json.text }}\n\"\"\"\n\nWrite a concise and personalized comment (1–2 sentences max) that:\n- Adds value to the conversation\n- Feels human and not generic\n- Avoids spammy language\n- Uses a positive and professional tone\n\nOnly return the comment text. Do not include quotation marks or any intro.",
            "options": {},
            "promptType": "define"
          },
          "typeVersion": 1.9
        },
        {
          "id": "d58b36e6-b24b-450b-9577-2da590c51d96",
          "name": "Comment Generation Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
          "position": [
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          ],
          "parameters": {
            "model": {
              "__rl": true,
              "mode": "list",
              "value": "gpt-4o-mini"
            },
            "options": {}
          },
          "credentials": {
            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
          "typeVersion": 1.2
        },
        {
          "id": "cd761bd8-1d94-4e28-ade5-a4e69b463124",
          "name": "Like LinkedIn Post",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
            1760,
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          ],
          "parameters": {
            "url": "https://api.phantombuster.com/api/v2/agent/launch",
            "method": "POST",
            "options": {},
            "jsonBody": "={\n  \"id\": \"YOUR_LIKER_AGENT_ID\",\n  \"arguments\": {\n    \"postUrls\": [\n      {{ $('Fetch Scraper Results').item.json.postUrl }}\n    ]\n  },\n  \"save\": false\n}",
            "sendBody": true,
            "sendHeaders": true,
            "specifyBody": "json",
            "headerParameters": {
              "parameters": [
                {
                  "name": "X-Phantombuster-Key-1",
                  "value": "YOUR_API_KEY"
                }
              ]
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        },
        {
          "id": "337498aa-ee44-4f92-bd46-7bbdc982960d",
          "name": "Post LinkedIn Comment",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
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          ],
          "parameters": {
            "url": "https://api.phantombuster.com/api/v2/agent/launch",
            "method": "POST",
            "options": {},
            "jsonBody": "={\n  \"id\": \"YOUR_COMMENTER_AGENT_ID\",\n  \"arguments\": {\n    \"postUrls\": [\n      {{ $('Fetch Scraper Results').item.json.postUrl }}\n    ],\n    \"comments\": [\n      {{ $json.output }}\n    ]\n  },\n  \"save\": false\n}",
            "sendBody": true,
            "sendHeaders": true,
            "specifyBody": "json",
            "headerParameters": {
              "parameters": [
                {
                  "name": "X-Phantombuster-Key-1",
                  "value": "YOUR_API_KEY"
                }
              ]
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          "typeVersion": 4.2
        },
        {
          "id": "27e6fab8-c8e9-4613-a8c1-1fb8306b9c46",
          "name": "Log Activity to Sheet",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
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          ],
          "parameters": {
            "columns": {
              "value": {
                "Comment": "={{ $('Commenter Agent').item.json.output }}",
                "PostUrl": "={{ $('Fetch Scraper Results').item.json.postUrl }}",
                "Post text": "={{ $('Fetch Scraper Results').item.json.text }}",
                "Timestamp": "={{ $('Fetch Scraper Results').item.json.timestamp }}",
                "AuthorName": "={{ $('Fetch Scraper Results').item.json.authorName }}",
                "AuthorProfile": "={{ $('Fetch Scraper Results').item.json.authorProfile }}"
              },
              "schema": [
                {
                  "id": "AuthorName",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "AuthorName",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "AuthorProfile",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "AuthorProfile",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "PostUrl",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "PostUrl",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Post text",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Post text",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Comment",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Comment",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Timestamp",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Timestamp",
                  "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/15h8fYaIVsC7HZf5-KsPA8tx-459ulURB5UEMC62Khzk/edit#gid=0",
              "cachedResultName": "Sheet1"
            },
            "documentId": {
              "__rl": true,
              "mode": "list",
              "value": "15h8fYaIVsC7HZf5-KsPA8tx-459ulURB5UEMC62Khzk",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/15h8fYaIVsC7HZf5-KsPA8tx-459ulURB5UEMC62Khzk/edit?usp=drivesdk",
              "cachedResultName": "LinkedIn auto liker and commenter"
            }
          },
          "credentials": {
            "googleSheetsOAuth2Api": {
              "id": "credential-id",
              "name": "googleSheetsOAuth2Api Credential"
            }
          },
          "typeVersion": 4.5
        },
        {
          "id": "6f8ccb5f-ddfd-4524-8098-51f027712203",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -40,
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          ],
          "parameters": {
            "color": 3,
            "width": 640,
            "height": 940,
            "content": "## 🔹 **Section 1: Trigger and Data Collection**\n\n### 📍Nodes Involved:\n\n* `Daily Trigger - 9 AM`\n* `Start LinkedIn Posts Scraper`\n* `Fetch Scraper Results`\n\n### ✅ **Purpose:**\n\nThis section is responsible for **automatically collecting LinkedIn post data** every day at a specific time.\n\n### 🔍 **Details:**\n\n1. **Daily Trigger - 9 AM**\n\n   * Starts the workflow automatically every day at 9 AM.\n   * Ensures the process runs consistently without manual intervention.\n\n2. **Start LinkedIn Posts Scraper**\n\n   * Sends a `POST` request to Phantombuster's API.\n   * Starts the \"LinkedIn Profile Posts Scraper\" Phantom to collect recent LinkedIn posts from specified profiles.\n\n3. **Fetch Scraper Results**\n\n   * Sends a `GET` request to retrieve the output from the scraping job.\n   * Extracts post data such as post ID, content, author, timestamp, etc.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "eca7d2c9-342f-4db0-a6b1-c5132f0af256",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            800,
            -680
          ],
          "parameters": {
            "color": 5,
            "width": 580,
            "height": 1080,
            "content": "## 🔹 **Section 2: AI-Based Content Analysis and Comment Generation**\n\n### 📍Nodes Involved:\n\n* `Generate LinkedIn Comment`\n* `Comment Generation Model`\n\n### ✅ **Purpose:**\n\nTo **analyze the content of each scraped LinkedIn post** and use AI to generate relevant and context-aware comments.\n\n### 🔍 **Details:**\n\n1. **Generate LinkedIn Comment**\n\n   * Acts as the AI Agent that facilitates the interaction between the post content and the AI model.\n   * Prepares the data (e.g., extracts post content) and sends it to the model.\n\n2. **Comment Generation Model**\n\n   * Powered by OpenAI's language model.\n   * Processes the post content and returns a thoughtful, engaging comment tailored to the post topic."
          },
          "typeVersion": 1
        },
        {
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          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1580,
            -820
          ],
          "parameters": {
            "color": 7,
            "width": 460,
            "height": 1140,
            "content": "## 🔹 **Section 3: Post Engagement Automation**\n\n### 📍Nodes Involved:\n\n* `Like LinkedIn Post`\n* `Post LinkedIn Comment`\n\n### ✅ **Purpose:**\n\nTo **interact with LinkedIn posts** by liking and commenting using the generated content.\n\n### 🔍 **Details:**\n\n1. **Like LinkedIn Post**\n\n   * Sends a `POST` request to Phantombuster to like the LinkedIn post.\n   * This increases engagement and visibility.\n\n2. **Post LinkedIn Comment**\n\n   * Sends a `POST` request with the AI-generated comment to the LinkedIn post.\n   * Engages the post author and audience in a meaningful way.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "36083131-b3de-4d8c-8d7c-941368fb6312",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            2180,
            -560
          ],
          "parameters": {
            "color": 2,
            "width": 480,
            "height": 720,
            "content": "## 🔹 **Section 4: Result Logging and Storage**\n\n### 📍Nodes Involved:\n\n* `Log Activity to Sheet`\n\n### ✅ **Purpose:**\n\nTo **store all the interactions and results in a structured format** for tracking and analysis.\n\n### 🔍 **Details:**\n\n1. **Log Activity to Sheet**\n\n   * Appends data (e.g., post URL, comment, status, timestamp) to a Google Sheets document.\n   * Helps maintain records, monitor performance, and debug issues if necessary.\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "9f6c0756-449a-45c4-ab49-080576be9651",
          "name": "Sticky Note9",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
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          "parameters": {
            "color": 4,
            "width": 1300,
            "height": 320,
            "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
          },
          "typeVersion": 1
        },
        {
          "id": "df8bc986-f7b8-4378-a0cd-737a15e0279e",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1920,
            -420
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          "parameters": {
            "color": 4,
            "width": 1289,
            "height": 3378,
            "content": "# 🔄 **Automated LinkedIn Engagement Workflow**\n\nThis workflow is designed to **automate the process of collecting LinkedIn posts**, analyzing them with AI, **engaging with them** (liking and commenting), and **logging the actions** in Google Sheets. It runs **daily at 9 AM**, ensuring consistent and timely interaction.\n\n---\n\n## 🧭 **Workflow Overview**\n\nThe workflow is divided into **4 key sections**:\n\n1. **Trigger & Data Collection**\n2. **AI Analysis & Comment Generation**\n3. **LinkedIn Post Engagement**\n4. **Logging & Storage**\n\nEach section is detailed below.\n\n---\n\n## 🔹 Section 1: Trigger & Data Collection\n\n### 📅 **Node: `Daily Trigger - 9 AM`**\n\n* **Type**: Schedule Trigger\n* **Purpose**: Initiates the workflow every day at 9:00 AM automatically.\n* **Benefit**: Removes the need for manual execution, ensuring timely and consistent operation.\n\n---\n\n### 🌐 **Node: `Start LinkedIn Posts Scraper`**\n\n* **Type**: HTTP Request (POST)\n* **Endpoint**: `https://api.phantombuster.com/…`\n* **Purpose**: Starts Phantombuster’s “LinkedIn Profile Posts Scraper” Phantom.\n* **Function**: Sends a request to begin scraping recent posts from specified LinkedIn profiles.\n* **Input**: List of profile URLs, authentication details.\n\n---\n\n### 🌐 **Node: `Fetch Scraper Results`**\n\n* **Type**: HTTP Request (GET)\n* **Endpoint**: `https://api.phantombuster.com/…`\n* **Purpose**: Retrieves the results of the scraping operation.\n* **Output**: JSON data of LinkedIn posts (content, timestamp, author, URL, post ID).\n\n---\n\n## 🔹 Section 2: AI Analysis & Comment Generation\n\n### 🤖 **Node: `Generate LinkedIn Comment`**\n\n* **Type**: AI Agent (Tool Integrator)\n* **Purpose**: Acts as the mediator between the scraped post content and the AI model.\n* **Function**:\n\n  * Extracts post content from the fetched data.\n  * Sends it to the AI for contextual understanding and comment generation.\n\n---\n\n### 🧠 **Node: `Comment Generation Model`**\n\n* **Type**: OpenAI Chat Model (e.g., GPT)\n* **Purpose**: Generates a personalized, thoughtful comment based on the LinkedIn post.\n* **Input**: Post content and context.\n* **Output**: Human-like comment relevant to the post's theme.\n\n---\n\n## 🔹 Section 3: LinkedIn Post Engagement\n\n### 👍 **Node: `Like LinkedIn Post`**\n\n* **Type**: HTTP Request (POST)\n* **Endpoint**: `https://api.phantombuster.com/…`\n* **Purpose**: Likes the target LinkedIn post.\n* **Function**:\n\n  * Increases post visibility.\n  * Adds a lightweight engagement action before commenting.\n\n---\n\n### 💬 **Node: `Post LinkedIn Comment`**\n\n* **Type**: HTTP Request (POST)\n* **Endpoint**: `https://api.phantombuster.com/…`\n* **Purpose**: Posts the AI-generated comment to the post.\n* **Function**:\n\n  * Completes the engagement cycle.\n  * Ensures comments are context-aware and professional.\n\n---\n\n## 🔹 Section 4: Logging & Storage\n\n### 📄 **Node: `Log Activity to Sheet`**\n\n* **Type**: Google Sheets (Append)\n\n* **Purpose**: Logs all workflow results into a Google Sheet.\n\n* **Data Logged**:\n\n  * Post URL\n  * Post content (optional)\n  * AI-generated comment\n  * Status of like/comment actions\n  * Timestamps\n\n* **Benefit**: Provides a centralized log for auditing, review, or further analytics.\n\n---\n\n## ✅ **Key Benefits of This Workflow**\n\n* **Automation**: Runs daily with zero manual effort.\n* **Intelligent Engagement**: AI-powered comment generation ensures relevance and tone.\n* **Tracking & Transparency**: Google Sheets logging ensures every step is recorded.\n* **Scalability**: Easily extendable to more profiles or engagement types.\n\n---\n\n## 📈 **Future Enhancements (Suggestions)**\n\n* Add error handling and retry logic for failed API calls.\n* Include sentiment analysis to refine comment tone.\n* Enable Slack/Email alerts for daily summary.\n* Add filters to only comment on posts with certain keywords or engagement levels.\n\n"
          },
          "typeVersion": 1
        }
      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
      },
      "versionId": "6db64df0-bacb-483a-833c-e23893831a22",
      "connections": {
        "Commenter Agent": {
          "main": [
            [
              {
                "node": "Like LinkedIn Post",
                "type": "main",
                "index": 0
              },
              {
                "node": "Post LinkedIn Comment",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Like LinkedIn Post": {
          "main": [
            [
              {
                "node": "Log Activity to Sheet",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Daily Trigger - 9 AM": {
          "main": [
            [
              {
                "node": "LinkedIn Posts Scraper",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Fetch Scraper Results": {
          "main": [
            [
              {
                "node": "Commenter Agent",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Post LinkedIn Comment": {
          "main": [
            [
              {
                "node": "Log Activity to Sheet",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "LinkedIn Posts Scraper": {
          "main": [
            [
              {
                "node": "Fetch Scraper Results",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Comment Generation Model": {
          "ai_languageModel": [
            [
              {
                "node": "Commenter Agent",
                "type": "ai_languageModel",
                "index": 0
              }
            ]
          ]
        }
      }
    },
    "lastUpdatedBy": 29,
    "workflowInfo": {
      "nodeCount": 14,
      "nodeTypes": {
        "n8n-nodes-base.stickyNote": {
          "count": 6
        },
        "n8n-nodes-base.httpRequest": {
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        },
        "n8n-nodes-base.googleSheets": {
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        },
        "@n8n/n8n-nodes-langchain.agent": {
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        },
        "n8n-nodes-base.scheduleTrigger": {
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        },
        "@n8n/n8n-nodes-langchain.lmChatOpenAi": {
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        }
      }
    },
    "status": "published",
    "user": {
      "name": "Yaron Been",
      "username": "yaron-nofluff",
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            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Agents",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "AI Agent",
          "color": "#404040"
        },
        "iconData": {
          "icon": "robot",
          "type": "icon"
        },
        "displayName": "AI Agent",
        "typeVersion": 3,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1153,
        "icon": "file:openAiLight.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Language Models",
                "Root Nodes"
              ],
              "Language Models": [
                "Chat Models (Recommended)"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "OpenAI Chat Model"
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        "iconData": {
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        "displayName": "OpenAI Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 33,
        "name": "Social Media"
      },
      {
        "id": 51,
        "name": "Multimodal AI"
      }
    ],
    "image": []
  }
}