{
  "workflow": {
    "id": 10826,
    "name": "Analyze social media sentiment & trends from Twitter & Facebook using GPT-4o",
    "views": 135,
    "recentViews": 0,
    "totalViews": 135,
    "createdAt": "2025-11-14T12:15:00.429Z",
    "description": "## Description\n Gain real-time audience intelligence with this cross-platform AI Sentiment Analyzer for Twitter (X) and Facebook. 📊🧠\n This workflow consolidates mentions and comments, performs GPT-4o-powered sentiment and keyword analysis, summarizes audience mood, highlights dominant trends, and sends a polished HTML report via email — all automatically. Ideal for marketing and insights teams tracking brand conversations across social platforms. 🚀💬\n\n## What This Template Does\n 1️⃣ Starts manually to fetch the latest Twitter mentions and Facebook post comments. 🕹️\n 2️⃣ Merges both datasets into a unified JSON structure for seamless cross-platform analysis. 🧩\n 3️⃣ Validates incoming API data to ensure completeness before processing. ✅\n 4️⃣ Runs a custom JavaScript transformation to normalize all messages and add sentiment placeholders. 🧠\n 5️⃣ Uses GPT-4o to perform sentiment and keyword trend analysis, returning structured JSON insights. 📈\n 6️⃣ Parses AI output to extract overall sentiment ratios and detailed post-level analysis. 🔍\n 7️⃣ Generates a human-readable HTML summary using GPT-4o — featuring emojis, bullet insights, and trend sections. 🎨\n 8️⃣ Emails the formatted sentiment report directly to the marketing team. ✉️\n 9️⃣ Logs API or runtime errors automatically into Google Sheets for transparent monitoring. 🧾\n\n## Key Benefits\n ✅ Provides an automated end-to-end pipeline for sentiment intelligence.\n ✅ Centralizes Twitter and Facebook audience data in one workflow.\n ✅ Delivers structured insights ready for dashboards or client reporting.\n ✅ Generates branded HTML summaries that are ready for emailing.\n ✅ Improves reliability with built-in error tracking and validation layers.\n\n## Features\n- Dual-platform integration (Twitter X API + Facebook Graph API).\n- JavaScript logic for merging and normalizing social datasets.\n- GPT-4o-based sentiment classification and keyword extraction.\n- Structured JSON parsing and visualization pipeline.\n- AI-generated HTML summary reports for presentation and sharing.\n- Automated email dispatch via Gmail.\n- Google Sheets logging for audit and debugging.\n- Modular configuration — easily extendable to other social networks.\n\n#3 Requirements\n- Twitter OAuth2 credentials for fetching mentions.\n- Facebook Graph API credentials for reading posts and comments.\n- Azure OpenAI (GPT-4o) credentials for sentiment and summary generation.\n- Gmail OAuth2 credentials for automated email delivery.\n- Google Sheets OAuth2 credentials for error logging and tracking.\n\n## Environment Variables\n- TWITTER_API_KEY\n- FACEBOOK_GRAPH_TOKEN\n- AZURE_OPENAI_API_KEY\n- GMAIL_REPORT_RECIPIENTS\n- GOOGLE_SHEET_ERROR_LOG_ID\n\n## Target Audience\n 📈 Marketing and insights teams monitoring audience engagement.\n 💬 Social media managers analyzing public sentiment.\n 🧠 Data analysts exploring brand perception trends.\n 💡 PR and communications teams managing online reputation.\n 🧾 Operations or automation teams integrating AI analytics into dashboards.\n\n## Step-by-Step Setup Instructions\n 1️⃣ Connect all API credentials — Twitter, Facebook Graph, Azure OpenAI, Gmail, and Google Sheets.\n 2️⃣ Update your Twitter user ID and Facebook Page ID in the respective nodes.\n 3️⃣ Confirm the merge and validation logic in the Merge Platform Datasets and Validate API Response nodes.\n 4️⃣ Check that your Azure OpenAI account has GPT-4o access enabled.\n 5️⃣ Verify the Gmail recipient and test the “Send Email Summary” node for delivery.\n 6️⃣ Link your Google Sheet with a tab named error log sheet to capture workflow exceptions.\n 7️⃣ Run the workflow once manually to validate each layer — data, AI response, email delivery.\n 8️⃣ Optionally, schedule it to run daily or weekly for automated sentiment insights. ✅\n",
    "workflow": {
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      "meta": {
        "instanceId": "8443f10082278c46aa5cf3acf8ff0f70061a2c58bce76efac814b16290845177"
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      "name": "AI-Powered Cross-Platform Audience Sentiment & Trend Analyzer",
      "tags": [],
      "nodes": [
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          "name": "Configure GPT-4o Model",
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            "azureOpenAiApi": {
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          "name": "Fetch Recent Mentions (X API)",
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            "url": "https://api.x.YOUR_AWS_SECRET_KEY_HERE?tweet.fields=created_at,text,public_metrics,author_id",
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            "nodeCredentialType": "twitterOAuth2Api"
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          "name": " Fetch Recent Facebook Comments ",
          "type": "n8n-nodes-base.facebookGraphApi",
          "position": [
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            "edge": "posts",
            "node": "230476031170639",
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              "fields": {
                "field": [
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                    "name": "id,message,story,created_time,permalink_url,full_picture,attachments{media_type,media,url,description},shares,likes.limit(100).summary(true){id,name},comments.limit(100).summary(true){id,from,message,created_time,like_count,comment_count,reactions.summary(true)},reactions.limit(100).summary(true){type,id,name},from{id,name,category}"
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            "graphApiVersion": "v23.0"
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          "name": "Consolidate Mentions & Comments ",
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            "jsCode": "// Input: Combined JSON from X and Facebook (like in your example)\nconst allData = $input.all();\n\n// Helper: normalize date safely\nfunction normalizeDate(dateString) {\n  if (!dateString) return null;\n  try {\n    return new Date(dateString).toISOString();\n  } catch {\n    return dateString;\n  }\n}\n\nconst unified = [];\n\n// Iterate over each input item\nfor (const item of allData) {\n  const dataArray = item.json.data || [];\n\n  // --- Case 1: X (Twitter) Mentions ---\n  if (dataArray[0]?.text && dataArray[0]?.public_metrics) {\n    for (const tweet of dataArray) {\n      unified.push({\n        platform: \"Twitter\",\n        post_id: tweet.id,\n        author_id: tweet.author_id,\n        message: tweet.text,\n        created_at: normalizeDate(tweet.created_at),\n        likes: tweet.public_metrics.like_count,\n        replies: tweet.public_metrics.reply_count,\n        impressions: tweet.public_metrics.impression_count,\n        retweets: tweet.public_metrics.retweet_count,\n        link: `https://x.com/i/web/status/${tweet.id}`,\n        sentiment_status: \"\", // can be filled later by AI\n      });\n    }\n  }\n\n  // --- Case 2: Facebook Posts + Comments ---\n  if (dataArray[0]?.message && dataArray[0]?.comments) {\n    for (const post of dataArray) {\n      const comments = post.comments?.data || [];\n      for (const c of comments) {\n        unified.push({\n          platform: \"Facebook\",\n          post_id: post.id,\n          comment_id: c.id,\n          commenter: c.from?.name || \"Unknown\",\n          message: c.message,\n          created_at: normalizeDate(c.created_time),\n          likes: c.like_count || 0,\n          reactions: c.reactions?.summary?.total_count || 0,\n          post_link: post.permalink_url,\n          sentiment_status: \"\", // for AI analysis later\n        });\n      }\n    }\n  }\n}\n\n// --- Output ---\nreturn [\n  {\n    json: {\n      total_items: unified.length,\n      unified_comments: unified,\n      summary: {\n        twitter_mentions: unified.filter(i => i.platform === \"Twitter\").length,\n        facebook_comments: unified.filter(i => i.platform === \"Facebook\").length,\n      },\n    },\n  },\n];\n"
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          "name": "Perform Sentiment & Keyword Analysis ",
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            "text": "=Analyze the following social media dataset for sentiment and keyword trends.\n\nInput Data:\n{{ JSON.stringify($json.unified_comments) }}\n\nReturn structured JSON in this format:\n{\n  \"overall_summary\": {\n    \"positive\": 0,\n    \"negative\": 0,\n    \"neutral\": 0,\n    \"dominant_trends\": [\"example\", \"keywords\"]\n  },\n  \"detailed_analysis\": [\n    {\n      \"platform\": \"\",\n      \"message\": \"\",\n      \"sentiment\": \"\",\n      \"keywords\": [],\n      \"reasoning\": \"\"\n    }\n  ]\n}\n",
            "options": {
              "systemMessage": "=You are a social media analytics assistant.\n\nYour job is to analyze combined social media mentions, comments, and posts across platforms such as Twitter (X) and Facebook.\n\nGiven an input dataset of social posts and comments, you must:\n1. Perform **sentiment analysis** on each item (positive / negative / neutral).\n2. Extract **key topics, themes, or keywords** mentioned.\n3. Identify **top recurring trends** across all items.\n4. Calculate **overall sentiment distribution** (e.g., 60% positive, 20% negative, 20% neutral).\n5. Return the output as clean, structured JSON.\n\nEnsure your analysis is concise, data-driven, and easy to visualize later.\nAvoid repeating text or adding unnecessary narrative.\n"
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          "id": "e146a4e0-ef7a-4ec0-9da5-1e28b2ab67e9",
          "name": " Parse AI Output to Structured JSON",
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          "position": [
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          ],
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            "jsCode": "// Get raw AI output (string)\nconst raw = $json.output;\n\n// Remove markdown wrappers (```json ... ```)\nconst cleaned = raw.replace(/```json|```/g, '').trim();\n\nlet parsed;\ntry {\n  parsed = JSON.parse(cleaned);\n} catch (error) {\n  parsed = { error: \"Failed to parse JSON\", raw: cleaned };\n}\n\n// Extract the main sections for clarity\nconst overall = parsed.overall_summary || {};\nconst details = parsed.detailed_analysis || [];\n\n// Return structured data\nreturn [\n  {\n    json: {\n      overall_summary: overall,\n      detailed_analysis: details,\n      total_posts: details.length\n    }\n  }\n];\n"
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            "text": "=You are a professional marketing insights writer who transforms structured analytical data into clean, visually engaging reports. \n\nYour task is to summarize social media sentiment data and engagement trends in a polished and human-readable tone.  \n\nFocus on:\n1. Highlighting positive, negative, and neutral sentiment proportions with short insights.\n2. Extracting top recurring topics or keywords and summarizing what they indicate about audience mood.\n3. Giving 3–5 bullet-point insights about the overall tone of discussion (what people liked, disliked, and discussed the most).\n4. Mentioning key examples from the dataset when useful (e.g., “Users praised the movie excitement and visuals.”)\n5. Keeping formatting clean with short paragraphs, emojis, and clear section titles (use Markdown headings like **Overall Summary**, **Top Trends**, **Insights**, etc.)\n\nReturn your response in **HTML format**, suitable for an email body, with light styling (headers, bold text, lists, and emojis).\nAvoid adding JSON or code blocks — just return clean HTML.\n",
            "options": {
              "systemMessage": "=You are a professional marketing insights writer who transforms structured analytical data into clean, visually engaging reports. \n\nYour task is to summarize social media sentiment data and engagement trends in a polished and human-readable tone.  \n\nFocus on:\n1. Highlighting positive, negative, and neutral sentiment proportions with short insights.\n2. Extracting top recurring topics or keywords and summarizing what they indicate about audience mood.\n3. Giving 3–5 bullet-point insights about the overall tone of discussion (what people liked, disliked, and discussed the most).\n4. Mentioning key examples from the dataset when useful (e.g., “Users praised the movie excitement and visuals.”)\n5. Keeping formatting clean with short paragraphs, emojis, and clear section titles (use Markdown headings like **Overall Summary**, **Top Trends**, **Insights**, etc.)\n\nReturn your response in **HTML format**, suitable for an email body, with light styling (headers, bold text, lists, and emojis).\nAvoid adding JSON or code blocks — just return clean HTML.\n"
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          "typeVersion": 2.1
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          "id": "53905e4c-1b06-4e80-a767-ae5d82b858fb",
          "name": "Send Email Summary to Marketing Team",
          "type": "n8n-nodes-base.gmail",
          "position": [
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          ],
          "webhookId": "0c82c299-6938-42ed-bda6-5007d79af34f",
          "parameters": {
            "sendTo": "=newscctv22@gmail.com",
            "message": "={{ $json.output }}",
            "options": {},
            "subject": "=Audience Sentiment and Keyword Trend Monitoring"
          },
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            "gmailOAuth2": {
              "id": "credential-id",
              "name": "gmailOAuth2 Credential"
            }
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          "id": "58e719fc-aff0-42c7-8bd0-547997c55bfa",
          "name": "Log Errors in Google Sheets",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
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              "cachedResultName": "Interviewer Brief Pack "
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            "conditions": {
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                "caseSensitive": true,
                "typeValidation": "strict"
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            "height": 480,
            "content": "## Cross-Platform Audience Sentiment Analyzer 🎯\nThis workflow unifies data from Twitter (X) and Facebook, performs AI-driven sentiment and keyword analysis, and delivers structured marketing summaries by email.  \nIt provides real-time insight into audience tone, trending topics, and engagement behavior across both platforms.\n\n### Key Steps:\n1️⃣ Fetch mentions from Twitter and comments from Facebook.  \n2️⃣ Merge both datasets into a unified comment structure.  \n3️⃣ Run sentiment and keyword extraction using GPT-4o.  \n4️⃣ Summarize audience mood and top trends in HTML format.  \n5️⃣ Email the final report to the marketing team automatically.  \n6️⃣ Log API or runtime errors into Google Sheets for monitoring.\n\n### Setup Checklist:\n- Connect credentials: Twitter, Facebook Graph, Azure OpenAI, Gmail, Google Sheets.  \n- Verify Gmail and Google Sheet IDs.  \n- Adjust API endpoints to your preferred handles or pages.  \n- Optionally schedule a weekly run for automated social insights.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "6178296d-3b96-4c7d-8621-0c8a4531bb87",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -688,
            -192
          ],
          "parameters": {
            "color": 7,
            "width": 384,
            "height": 800,
            "content": "## Data Collection Layer\nFetches recent mentions from Twitter (X) and recent post comments from Facebook.  \nProvides raw input data for sentiment and trend analysis across both platforms.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "99a214c5-5d48-4aa1-958f-7e4e28fb90d9",
          "name": "Sticky Note2",
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          "parameters": {
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            "height": 672,
            "content": "## Dataset Merging\nCombines results from both APIs into a unified dataset.  \nEnsures consistent structure for message text, timestamps, reactions, and likes.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "9c70b6a7-973a-4b59-a9b4-5717c3e58c91",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
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            -80
          ],
          "parameters": {
            "color": 7,
            "height": 560,
            "content": "## Data Validation\nChecks API responses to confirm essential fields exist before analysis.  \nInvalid or empty responses are sent to Google Sheets for error tracking.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "43bb63ef-a9ee-4511-8b92-69626ce1a50b",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
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            -32
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          "parameters": {
            "color": 7,
            "height": 512,
            "content": "## Data Consolidation\nStandardizes and merges Facebook comments and Twitter mentions into a clean JSON array.  \nAdds key attributes like platform, author, sentiment placeholder, and post URLs.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "1d86c84c-e101-4eb8-b4ca-f1fde1a461e9",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
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          ],
          "parameters": {
            "color": 7,
            "width": 320,
            "height": 608,
            "content": "## AI Sentiment & Keyword Analysis\nUses GPT-4o to classify each post/comment as Positive, Negative, or Neutral.  \nExtracts recurring themes and dominant keywords to detect engagement trends.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "11a4865e-1a8d-47eb-ab54-50537084250c",
          "name": "Sticky Note6",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1056,
            -16
          ],
          "parameters": {
            "color": 7,
            "height": 384,
            "content": "## AI Output Parsing\nCleans and parses the AI output JSON.  \nExtracts sentiment distribution, topic keywords, and detailed message-level analysis for downstream summarization.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "d6eef13f-ebaa-446a-b61f-542ee194a4ed",
          "name": "Sticky Note7",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1360,
            -32
          ],
          "parameters": {
            "color": 7,
            "width": 336,
            "height": 608,
            "content": "## AI Summary Generation\nGPT-4o converts structured data into a visually rich HTML summary.  \nIncludes sentiment ratios, trending topics, and top insights formatted for email readability.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "df66fc74-e5e8-42e0-a9e6-5ec8f26c203c",
          "name": "Sticky Note8",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1760,
            -16
          ],
          "parameters": {
            "color": 7,
            "height": 576,
            "content": "## Email Delivery\nSends the final HTML summary via Gmail to marketing stakeholders.  \nIncludes formatted sections with emojis and highlights for quick readability.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "f352a4d1-542e-425b-b900-08aabe024b16",
          "name": "Sticky Note9",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
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            624
          ],
          "parameters": {
            "color": 7,
            "height": 448,
            "content": "## Error Logging\nCaptures workflow or API-level errors and logs them in Google Sheets.  \nProvides an audit trail for debugging and workflow reliability.\n"
          },
          "typeVersion": 1
        }
      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
      },
      "versionId": "11fd2dec-9841-45df-a7cb-d553064c9cce",
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        "displayName": "HTTP Request",
        "typeVersion": 4,
        "nodeCategories": [
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            "id": 5,
            "name": "Development"
          },
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
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        "id": 20,
        "icon": "fa:map-signs",
        "name": "n8n-nodes-base.if",
        "codex": {
          "data": {
            "alias": [
              "Router",
              "Filter",
              "Condition",
              "Logic",
              "Boolean",
              "Branch"
            ],
            "details": "The IF node can be used to implement binary conditional logic in your workflow. You can set up one-to-many conditions to evaluate each item of data being inputted into the node. That data will either evaluate to TRUE or FALSE and route out of the node accordingly.\n\nThis node has multiple types of conditions: Bool, String, Number, and Date & Time.",
            "resources": {
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                  "url": "https://n8n.io/blog/learn-to-automate-your-factorys-incident-reporting-a-step-by-step-guide/",
                  "icon": "🏭",
                  "label": "Learn to Automate Your Factory's Incident Reporting: A Step by Step Guide"
                },
                {
                  "url": "https://n8n.io/blog/2021-the-year-to-automate-the-new-you-with-n8n/",
                  "icon": "☀️",
                  "label": "2021: The Year to Automate the New You with n8n"
                },
                {
                  "url": "https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/",
                  "icon": "🧬",
                  "label": "Why business process automation with n8n can change your daily life"
                },
                {
                  "url": "https://n8n.io/blog/create-a-toxic-language-detector-for-telegram/",
                  "icon": "🤬",
                  "label": "Create a toxic language detector for Telegram in 4 step"
                },
                {
                  "url": "https://n8n.io/blog/no-code-ecommerce-workflow-automations/",
                  "icon": "store",
                  "label": "6 e-commerce workflows to power up your Shopify s"
                },
                {
                  "url": "https://n8n.io/blog/how-to-build-a-low-code-self-hosted-url-shortener/",
                  "icon": "🔗",
                  "label": "How to build a low-code, self-hosted URL shortener in 3 steps"
                },
                {
                  "url": "https://n8n.io/blog/automate-your-data-processing-pipeline-in-9-steps-with-n8n/",
                  "icon": "⚙️",
                  "label": "Automate your data processing pipeline in 9 steps"
                },
                {
                  "url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
                  "icon": "👥",
                  "label": "How to get started with CRM automation (with 3 no-code workflow ideas"
                },
                {
                  "url": "https://n8n.io/blog/5-tasks-you-can-automate-with-notion-api/",
                  "icon": "⚡️",
                  "label": "5 tasks you can automate with the new Notion API "
                },
                {
                  "url": "https://n8n.io/blog/automate-google-apps-for-productivity/",
                  "icon": "💡",
                  "label": "15 Google apps you can combine and automate to increase productivity"
                },
                {
                  "url": "https://n8n.io/blog/automation-for-maintainers-of-open-source-projects/",
                  "icon": "🏷️",
                  "label": "How to automatically manage contributions to open-source projects"
                },
                {
                  "url": "https://n8n.io/blog/how-uproc-scraped-a-multi-page-website-with-a-low-code-workflow/",
                  "icon": " 🕸️",
                  "label": "How uProc scraped a multi-page website with a low-code workflow"
                },
                {
                  "url": "https://n8n.io/blog/5-workflow-automations-for-mattermost-that-we-love-at-n8n/",
                  "icon": "🤖",
                  "label": "5 workflow automations for Mattermost that we love at n8n"
                },
                {
                  "url": "https://n8n.io/blog/why-this-product-manager-loves-workflow-automation-with-n8n/",
                  "icon": "🧠",
                  "label": "Why this Product Manager loves workflow automation with n8n"
                },
                {
                  "url": "https://n8n.io/blog/sending-automated-congratulations-with-google-sheets-twilio-and-n8n/",
                  "icon": "🙌",
                  "label": "Sending Automated Congratulations with Google Sheets, Twilio, and n8n "
                },
                {
                  "url": "https://n8n.io/blog/how-to-set-up-a-ci-cd-pipeline-with-no-code/",
                  "icon": "🎡",
                  "label": "How to set up a no-code CI/CD pipeline with GitHub and TravisCI"
                },
                {
                  "url": "https://n8n.io/blog/benefits-of-automation-and-n8n-an-interview-with-hubspots-hugh-durkin/",
                  "icon": "🎖",
                  "label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin"
                },
                {
                  "url": "https://n8n.io/blog/aws-workflow-automation/",
                  "label": "7 no-code workflow automations for Amazon Web Services"
                }
              ],
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                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.if/"
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
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            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "If",
          "color": "#408000"
        },
        "iconData": {
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          "type": "icon"
        },
        "displayName": "If",
        "typeVersion": 2,
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            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 24,
        "icon": "file:merge.svg",
        "name": "n8n-nodes-base.merge",
        "codex": {
          "data": {
            "alias": [
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              "Concatenate",
              "Wait"
            ],
            "resources": {
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                  "url": "https://n8n.io/blog/how-to-sync-data-between-two-systems/",
                  "icon": "🏬",
                  "label": "How to synchronize data between two systems (one-way vs. two-way sync"
                },
                {
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                {
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                  "icon": "📈",
                  "label": "Migrating Community Metrics to Orbit using n8n"
                },
                {
                  "url": "https://n8n.io/blog/build-your-own-virtual-assistant-with-n8n-a-step-by-step-guide/",
                  "icon": "👦",
                  "label": "Build your own virtual assistant with n8n: A step by step guide"
                },
                {
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            "subcategories": {
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            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
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            "id": 9,
            "name": "Core Nodes"
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        ]
      },
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        "id": 314,
        "icon": "file:facebook.svg",
        "name": "n8n-nodes-base.facebookGraphApi",
        "codex": {
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                  "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.facebookgraphapi/"
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              ],
              "credentialDocumentation": [
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                  "url": "https://docs.n8n.io/integrations/builtin/credentials/facebookgraph/"
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            "categories": [
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            "nodeVersion": "1.0",
            "codexVersion": "1.0"
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        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Facebook Graph API"
        },
        "iconData": {
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        ]
      },
      {
        "id": 356,
        "icon": "file:gmail.svg",
        "name": "n8n-nodes-base.gmail",
        "codex": {
          "data": {
            "alias": [
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              "human",
              "form",
              "wait",
              "hitl",
              "approval"
            ],
            "resources": {
              "generic": [
                {
                  "url": "https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/",
                  "icon": "🧬",
                  "label": "Why business process automation with n8n can change your daily life"
                },
                {
                  "url": "https://n8n.io/blog/supercharging-your-conference-registration-process-with-n8n/",
                  "icon": "🎫",
                  "label": "Supercharging your conference registration process with n8n"
                },
                {
                  "url": "https://n8n.io/blog/no-code-ecommerce-workflow-automations/",
                  "icon": "store",
                  "label": "6 e-commerce workflows to power up your Shopify s"
                },
                {
                  "url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
                  "icon": "👥",
                  "label": "How to get started with CRM automation (with 3 no-code workflow ideas"
                },
                {
                  "url": "https://n8n.io/blog/automate-google-apps-for-productivity/",
                  "icon": "💡",
                  "label": "15 Google apps you can combine and automate to increase productivity"
                },
                {
                  "url": "https://n8n.io/blog/your-business-doesnt-need-you-to-operate/",
                  "icon": " 🖥️",
                  "label": "Hey founders! Your business doesn't need you to operate"
                },
                {
                  "url": "https://n8n.io/blog/using-automation-to-boost-productivity-in-the-workplace/",
                  "icon": "💪",
                  "label": "Using Automation to Boost Productivity in the Workplace"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.gmail/"
                }
              ],
              "credentialDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/"
                }
              ]
            },
            "categories": [
              "Communication",
              "HITL"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "HITL": [
                "Human in the Loop"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Gmail"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNTYiIGhlaWdodD0iMTkzIiBwcmVzZXJ2ZUFzcGVjdFJhdGlvPSJ4TWlkWU1pZCI+PHBhdGggZmlsbD0iIzQyODVGNCIgZD0iTTU4LjE4MiAxOTIuMDVWOTMuMTRMMjcuNTA3IDY1LjA3NyAwIDQ5LjUwNHYxMjUuMDkxYzAgOS42NTggNy44MjUgMTcuNDU1IDE3LjQ1NSAxNy40NTV6Ii8+PHBhdGggZmlsbD0iIzM0QTg1MyIgZD0iTTE5Ny44MTggMTkyLjA1aDQwLjcyN2M5LjY1OSAwIDE3LjQ1NS03LjgyNiAxNy40NTUtMTcuNDU1VjQ5LjUwNWwtMzEuMTU2IDE3LjgzNy0yNy4wMjYgMjUuNzk4eiIvPjxwYXRoIGZpbGw9IiNFQTQzMzUiIGQ9Im01OC4xODIgOTMuMTQtNC4xNzQtMzguNjQ3IDQuMTc0LTM2Ljk4OUwxMjggNjkuODY4bDY5LjgxOC01Mi4zNjQgNC42NyAzNC45OTItNC42NyA0MC42NDRMMTI4IDE0NS41MDR6Ii8+PHBhdGggZmlsbD0iI0ZCQkMwNCIgZD0iTTE5Ny44MTggMTcuNTA0VjkzLjE0TDI1NiA0OS41MDRWMjYuMjMxYzAtMjEuNTg1LTI0LjY0LTMzLjg5LTQxLjg5LTIwLjk0NXoiLz48cGF0aCBmaWxsPSIjQzUyMjFGIiBkPSJtMCA0OS41MDQgMjYuNzU5IDIwLjA3TDU4LjE4MiA5My4xNFYxNy41MDRMNDEuODkgNS4yODZDMjQuNjEtNy42NiAwIDQuNjQ2IDAgMjYuMjN6Ii8+PC9zdmc+"
        },
        "displayName": "Gmail",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 6,
            "name": "Communication"
          },
          {
            "id": 28,
            "name": "HITL"
          }
        ]
      },
      {
        "id": 565,
        "icon": "fa:sticky-note",
        "name": "n8n-nodes-base.stickyNote",
        "codex": {
          "data": {
            "alias": [
              "Comments",
              "Notes",
              "Sticky"
            ],
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Sticky Note",
          "color": "#FFD233"
        },
        "iconData": {
          "icon": "sticky-note",
          "type": "icon"
        },
        "displayName": "Sticky Note",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 834,
        "icon": "file:code.svg",
        "name": "n8n-nodes-base.code",
        "codex": {
          "data": {
            "alias": [
              "cpde",
              "Javascript",
              "JS",
              "Python",
              "Script",
              "Custom Code",
              "Function"
            ],
            "details": "The Code node allows you to execute JavaScript in your workflow.",
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.code/"
                }
              ]
            },
            "categories": [
              "Development",
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers",
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Code"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Code",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 5,
            "name": "Development"
          },
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 838,
        "icon": "fa:mouse-pointer",
        "name": "n8n-nodes-base.manualTrigger",
        "codex": {
          "data": {
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.manualworkflowtrigger/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "When clicking ‘Execute workflow’",
          "color": "#909298"
        },
        "iconData": {
          "icon": "mouse-pointer",
          "type": "icon"
        },
        "displayName": "Manual Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 1119,
        "icon": "fa:robot",
        "name": "@n8n/n8n-nodes-langchain.agent",
        "codex": {
          "data": {
            "alias": [
              "LangChain",
              "Chat",
              "Conversational",
              "Plan and Execute",
              "ReAct",
              "Tools"
            ],
            "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": 1253,
        "icon": "file:azure.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatAzureOpenAi",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatazureopenai/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Language Models",
                "Root Nodes"
              ],
              "Language Models": [
                "Chat Models (Recommended)"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Azure OpenAI Chat Model"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Azure OpenAI Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 32,
        "name": "Market Research"
      },
      {
        "id": 49,
        "name": "AI Summarization"
      }
    ],
    "image": []
  }
}