{ "nodes": [ { "id": "a3d70ad2-5e07-41b2-8e09-420ab377f17d", "name": "Trigger: Scheduled Run", "type": "n8n-nodes-base.scheduleTrigger", "position": [ -1600, 192 ], "parameters": { "rule": { "interval": [ { "field": "minutes", "minutesInterval": 30 } ] } }, "typeVersion": 1.3 }, { "id": "50268d00-75f4-4117-9784-f5c7e2fec03a", "name": "Load Global Constants", "type": "n8n-nodes-globals.globalConstants", "position": [ -1360, 192 ], "parameters": {}, "typeVersion": 1 }, { "id": "0877929f-5fe2-46ed-82cb-888763ffb239", "name": "Fetch Unreplied Threads (Udemy API)", "type": "n8n-nodes-base.httpRequest", "position": [ -1136, 192 ], "parameters": { "url": "https://www.udemy.com/instructor-api/v1/message-threads/", "options": {}, "sendQuery": true, "authentication": "genericCredentialType", "genericAuthType": "httpHeaderAuth", "queryParameters": { "parameters": [ { "name": "status", "value": "unreplied" } ] } }, "typeVersion": 4.3 }, { "id": "0d7940d4-0fd3-45f1-b052-fe78d280d5e8", "name": "Split Threads Array", "type": "n8n-nodes-base.splitOut", "position": [ -896, 192 ], "parameters": { "options": {}, "fieldToSplitOut": "results" }, "typeVersion": 1 }, { "id": "03c62900-d0a6-451c-abfd-3e19d0ebd72c", "name": "Loop Through Each Thread", "type": "n8n-nodes-base.splitInBatches", "position": [ -624, 192 ], "parameters": { "options": {} }, "typeVersion": 3 }, { "id": "b5d82906-5567-4a12-b25e-3e7279e838c8", "name": "Fetch Full Thread History", "type": "n8n-nodes-base.httpRequest", "position": [ -336, 208 ], "parameters": { "url": "=https://www.udemy.com/instructor-api/v1/message-threads/{{ $json.id }}/messages/", "options": {}, "sendQuery": true, "authentication": "genericCredentialType", "genericAuthType": "httpHeaderAuth", "queryParameters": { "parameters": [ { "name": "message_thread_id", "value": "={{ $json.id }}" } ] } }, "typeVersion": 4.3 }, { "id": "383df8ad-9ff2-4e22-a699-0741e9770fca", "name": "Log New Message to Sheet", "type": "n8n-nodes-base.googleSheets", "position": [ 384, 432 ], "parameters": { "columns": { "value": { "ID": "={{ $json.results[0].id }}", "DATE": "={{ $json.results[0].created }}", "User": "={{ $json.results[0].user.title }}", "STATUS": "={{ $('Load Global Constants').first().json.constants.status6 }}", "Message Content": "={{ $json.results[0].content.replace(/<[^>]*>/g, '') }}", "Responded (Y/N)": "N", "Previous Interactions (Aggregated)": "={{ $json.results.slice(1).map((r, i) => `[${i + 1}] ${r.user.name}: ${r.content.replace(/<[^>]*>/g, '')}`).join('\\n\\n') }}" }, "schema": [ { "id": "ID", "type": "string", "display": true, "required": false, "displayName": "ID", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "STATUS", "type": "string", "display": true, "required": false, "displayName": "STATUS", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "DATE", "type": "string", "display": true, "required": false, "displayName": "DATE", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "User", "type": "string", "display": true, "required": false, "displayName": "User", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Message Content", "type": "string", "display": true, "required": false, "displayName": "Message Content", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Previous Interactions (Aggregated)", "type": "string", "display": true, "required": false, "displayName": "Previous Interactions (Aggregated)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Response", "type": "string", "display": true, "removed": true, "required": false, "displayName": "Response", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Vetting", "type": "string", "display": true, "removed": true, "required": false, "displayName": "Vetting", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Pass/Fail", "type": "string", "display": true, "removed": true, "required": false, "displayName": "Pass/Fail", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Responded (Y/N)", "type": "string", "display": true, "required": false, "displayName": "Responded (Y/N)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Further Action (Y/N)", "type": "string", "display": true, "removed": true, "required": false, "displayName": "Further Action (Y/N)", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "name", "value": "={{ $('Load Global Constants').first().json.constants.sheet_name }}" }, "documentId": { "__rl": true, "mode": "id", "value": "={{ $('Load Global Constants').first().json.constants.sheetid }}" } }, "typeVersion": 4.7 }, { "id": "28f0665e-7c04-41bd-b93f-82abfd2b2658", "name": "Skip if Instructor Sent Last Message", "type": "n8n-nodes-base.if", "position": [ -64, 208 ], "parameters": { "options": {}, "conditions": { "options": { "version": 3, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "1f150c14-4eaf-4c1f-b71e-583ae59ebe7b", "operator": { "type": "string", "operation": "equals" }, "leftValue": "={{ $json.results[0].user.title }}", "rightValue": "={{ $('Load Global Constants').first().json.constants.instructor_name }}" } ] } }, "typeVersion": 2.3 }, { "id": "99a5e07d-419b-4b3a-8fee-46b3882139e9", "name": "Generate Redis Session Key", "type": "n8n-nodes-base.code", "position": [ 624, 432 ], "parameters": { "mode": "runOnceForEachItem", "jsCode": "let characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789';\nlet result = '';\nlet length = 48; // Desired length of the random string\nfor (let i = 0; i < length; i++) {\n result += characters.charAt(Math.floor(Math.random() * characters.length));\n}\nreturn { randomString: result };" }, "typeVersion": 2 }, { "id": "f1e0d0f4-92e0-4740-9364-4a5c2136646e", "name": "AI Agent: Reply or Escalate", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 800, 432 ], "parameters": { "text": "=## Latest Message\n\n{{ $('Log New Message to Sheet').item.json['Message Content'] }}\n\n## Message Context\n\n{{ $('Log New Message to Sheet').item.json['Previous Interactions (Aggregated)'] }}\n\nOutput Format: Format your response in Markdown. Use \\n\\n to separate paragraphs. Use standard Markdown syntax for emphasis (**bold**, *italic*) or links ([text](url)) where appropriate. Do not use any HTML tags whatsoever (no

,
, , , etc.). The response must be pure Markdown.", "options": { "systemMessage": "=You are an AI assistant responding on behalf of a Udemy instructor. Your role is to handle student Q&A messages professionally and efficiently.\n\n## Instructor Information\n- **Name:** {{ $('Load Global Constants').first().json.constants.instructor_name }}\n- **Bio:** {{ $('Load Global Constants').first().json.constants.instructor_bio }}\n\n## Your Task\nYou will receive:\n1. The latest student message requiring a response\n2. Previous message context (if available)\n\nYou must decide whether to respond directly OR escalate to the instructor.\n\n## Escalation Rules (Instructor Required ~20% of messages)\n\n### PRIORITY: Sales Opportunities\nALWAYS escalate when you detect a potential sales opportunity, including:\n- Student expresses interest in related topics not covered in the current course\n- Student asks about other courses the instructor offers\n- Student mentions wanting to go deeper or advance their skills\n- Student asks for recommendations on \"what to learn next\"\n- Student praises the course and expresses enthusiasm for more content\n- Student mentions career goals that could align with other offerings\n- Student asks about certifications, career paths, or comprehensive learning plans\n- Any opening where the instructor could naturally recommend their other courses or services\n\nThese are high-value interactions. The instructor's personal touch converts interest into enrollments.\n\n### Other Escalation Triggers\nESCALATE to the instructor when the message:\n- Asks personal questions about the instructor's background, experience, or life beyond the bio\n- Requests private coaching, consulting, or 1-on-1 mentorship\n- Asks about pricing, refunds, or payment issues\n- Requests course content changes, additions, or custom materials\n- Involves complaints or disputes requiring human judgment\n- Asks for contact information, social media, or communication outside Udemy\n- References information about the instructor's other services/offerings you don't have access to\n- Contains sensitive personal disclosures requiring empathetic human response\n- Is genuinely ambiguous AFTER the student has provided details\u2014meaning you cannot determine what they're asking even with full context (note: vague openers like \"I have a question\" are NOT ambiguous; just ask for clarification)\n\n## Auto-Response Rules (AI Handles ~80% of messages)\nRESPOND directly when the message:\n- Asks technical questions related to course content (use Jina Search to verify/supplement)\n- Seeks clarification on concepts taught in the course\n- Is a general greeting, thank you, or positive feedback WITHOUT expressed interest in more content\n- Asks about general best practices in the subject domain\n- Requests resource recommendations for FREE documentation, tools, or further reading\n- Reports minor technical issues with videos/quizzes (provide standard troubleshooting)\n- Asks \"how to\" questions within the course's subject matter\n- Is a simple follow-up to a previous exchange you can contextually address\n\n### Conversation Openers & Incomplete Messages\nRESPOND directly (do not escalate) when the message:\n- Is a greeting with a vague or unspecified question (\"Hi, I had a question about...\")\n- Says they have a question but doesn't actually ask it yet\n- Is an introduction without specific content\n\nFor these, respond warmly and invite them to share their question. Keep it brief and friendly, e.g.:\n\"Hey! Happy to help\u2014what's your question?\"\n\nDo NOT escalate these as \"ambiguous.\" They're just incomplete\u2014prompt for details.\n\n## Response Guidelines\nWhen you respond:\n1. **Length:** 10-100 words. Match complexity to the question\u2014simple questions get concise answers; detailed technical questions get fuller explanations. Never pad responses unnecessarily.\n2. **Tone:** Professional yet warm and approachable. You represent a friendly expert instructor.\n3. **Style Matching:** Mirror the formality level of the student and previous context, but always maintain professionalism. If the student is overly casual or uses slang, elevate slightly while remaining friendly.\n4. **Technical Accuracy:** Use Jina Search to verify technical information. Never guess on technical details.\n5. **No Fluff:** Avoid generic filler phrases like \"Great question!\" or \"I'm happy to help!\" unless the context genuinely calls for warmth.\n6. **Sign-off:** Do not include a sign-off or signature. The platform handles that.\n7. **Output Format:** Format your response in Markdown. Use \\n\\n to separate paragraphs. Use standard Markdown syntax (**bold**, *italic*, [text](url)) where appropriate. Never include HTML tags of any kind (no

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