This workflow follows the Google Sheets → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "01 - Main Bot (WhatsApp + Website)",
"nodes": [
{
"parameters": {
"httpMethod": "POST",
"path": "whatsapp",
"responseMode": "responseNode"
},
"id": "webhook-wa",
"name": "WhatsApp Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
240,
300
]
},
{
"parameters": {
"httpMethod": "GET",
"path": "whatsapp",
"responseMode": "responseNode"
},
"id": "webhook-wa-verify",
"name": "WhatsApp Verify",
"type": "n8n-nodes-base.webhook",
"position": [
240,
160
]
},
{
"parameters": {
"respondWith": "text",
"responseBody": "={{ $json['hub.challenge'] }}"
},
"id": "respond-verify",
"name": "Return Challenge",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
460,
160
]
},
{
"parameters": {
"jsCode": "// Extract message from WhatsApp webhook payload\nconst payload = $input.item.json.body || $input.item.json;\nconst entry = payload?.entry?.[0];\nconst change = entry?.changes?.[0]?.value;\nconst messages = change?.messages || [];\nconst contacts = change?.contacts || [];\n\nif (!messages.length) return [];\n\nconst msg = messages[0];\nif (msg.type !== 'text') return [];\n\nconst waId = msg.from;\nconst contact = contacts.find(c => c.wa_id === waId);\n\nreturn [{\n json: {\n phone_number: '+' + waId,\n message_text: msg.text?.body || '',\n student_name: contact?.profile?.name || '',\n source_channel: 'WhatsApp',\n message_id: msg.id,\n timestamp: msg.timestamp\n }\n}];"
},
"id": "extract-message",
"name": "Extract Message",
"type": "n8n-nodes-base.code",
"position": [
460,
300
]
},
{
"parameters": {
"url": "https://api.groq.com/openai/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "=Bearer {{ $env.GROQ_API_KEY }}"
},
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"contentType": "json",
"body": "={\n \"model\": \"llama-3.3-70b-versatile\",\n \"messages\": [{\n \"role\": \"user\",\n \"content\": \"{{ $json.prompt }}\"\n }],\n \"temperature\": 0.7,\n \"max_tokens\": 512\n}"
},
"id": "groq-call",
"name": "Groq AI",
"type": "n8n-nodes-base.httpRequest",
"position": [
900,
300
]
},
{
"parameters": {
"jsCode": "// Build groq prompt with IIST knowledge base\nconst { phone_number, message_text, student_name, source_channel } = $input.item.json;\n\nconst knowledgeBase = `\nIIST Courses: B.Tech CSE (120 seats, \u20b985,000/yr, JEE 85%ile), ECE (60 seats, \u20b982,000/yr, JEE 70%ile), IT (60 seats, \u20b982,000/yr, JEE 75%ile), ME (60 seats, \u20b978,000/yr), CE (60 seats, \u20b975,000/yr), MBA (60 seats, \u20b965,000/yr).\nScholarships: Merit 25% off (95%ile+), SC/ST govt, Girls 10% off, Sports 20% off.\nHostel: Boys \u20b945,000/yr, Girls \u20b948,000/yr.\nDeadline: June 30 2026. Orientation: July 15 2026.\nPlacement: Avg \u20b96.2LPA, Highest \u20b918LPA (Microsoft). 92% CSE placed.\nApply: iist.ac.in/apply | admissions@iist.ac.in | +91-731-XXXXXXX\n`;\n\nconst prompt = `You are AdmitBot, IIST admission assistant. Reply in the SAME language as student (Hindi/Hinglish/English). Max 3-4 lines. 1-2 emojis. Never say 'I don't know' - redirect to counsellor.\n\nKnowledge Base:\n${knowledgeBase}\n\nStudent (${phone_number}) asks: ${message_text}\n\nAfter your reply, add JSON block:\n\\`\\`\\`json\n{\"intent_score\":\"Hot|Warm|Cold\",\"extracted_data\":{\"name\":null,\"city\":null,\"course_interest\":null,\"jee_percentile\":null,\"phone\":null},\"needs_escalation\":false}\n\\`\\`\\``;\n\nreturn [{ json: { ...($input.item.json), prompt } }];"
},
"id": "build-prompt",
"name": "Build Groq Prompt",
"type": "n8n-nodes-base.code",
"position": [
680,
300
]
},
{
"parameters": {
"jsCode": "// Parse Groq response and extract reply + structured data\nconst rawText = $input.item.json.choices?.[0]?.message?.content || '';\n\nconst jsonMatch = rawText.match(/```json\\s*([\\s\\S]*?)\\s*```/);\nlet structured = {};\nlet replyText = rawText.trim();\n\nif (jsonMatch) {\n try { structured = JSON.parse(jsonMatch[1]); } catch(e) {}\n replyText = rawText.substring(0, jsonMatch.index).trim();\n}\n\nconst prev = $node['Extract Message'].json;\n\nreturn [{\n json: {\n phone_number: prev.phone_number,\n student_name: prev.student_name || structured.extracted_data?.name || '',\n source_channel: prev.source_channel,\n message_text: prev.message_text,\n reply_text: replyText,\n intent_score: structured.intent_score || 'Cold',\n extracted_data: structured.extracted_data || {},\n needs_escalation: structured.needs_escalation || false\n }\n}];"
},
"id": "parse-response",
"name": "Parse Groq Response",
"type": "n8n-nodes-base.code",
"position": [
1120,
300
]
},
{
"parameters": {
"url": "=https://graph.facebook.com/v19.0/{{ $env.WHATSAPP_PHONE_NUMBER_ID }}/messages",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "=Bearer {{ $env.WHATSAPP_ACCESS_TOKEN }}"
}
]
},
"sendBody": true,
"contentType": "json",
"body": "={\n \"messaging_product\": \"whatsapp\",\n \"to\": \"{{ $json.phone_number.replace('+','') }}\",\n \"type\": \"text\",\n \"text\": { \"body\": \"{{ $json.reply_text }}\" }\n}"
},
"id": "send-reply",
"name": "Send WhatsApp Reply",
"type": "n8n-nodes-base.httpRequest",
"position": [
1340,
200
]
},
{
"parameters": {
"operation": "appendOrUpdate",
"documentId": {
"value": "={{ $env.GOOGLE_SHEETS_ID }}"
},
"sheetName": {
"value": "Leads"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"Timestamp": "={{ $now.toISO() }}",
"Student Name": "={{ $json.student_name }}",
"Phone Number": "={{ $json.phone_number }}",
"City": "={{ $json.extracted_data.city || '' }}",
"Course Interest": "={{ $json.extracted_data.course_interest || '' }}",
"JEE / 12th Score": "={{ $json.extracted_data.jee_percentile || '' }}",
"Source Channel": "={{ $json.source_channel }}",
"Lead Score": "={{ $json.intent_score }}",
"Assigned To": "",
"Lead Status": "New",
"Notes": "",
"Last Updated": "={{ $now.toISO() }}",
"Conversation History": "=Student: {{ $json.message_text }}\nBot: {{ $json.reply_text }}"
}
},
"matchingColumns": [
"Phone Number"
]
},
"id": "save-lead",
"name": "Save Lead to Sheets",
"type": "n8n-nodes-base.googleSheets",
"position": [
1340,
360
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": false
},
"conditions": [
{
"leftValue": "={{ $json.intent_score }}",
"rightValue": "Hot",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
"id": "if-hot-lead",
"name": "Is Hot Lead?",
"type": "n8n-nodes-base.if",
"position": [
1560,
300
]
},
{
"parameters": {
"respondWith": "json",
"responseBody": "={ \"status\": \"ok\" }"
},
"id": "respond-ok",
"name": "Return OK",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
1340,
500
]
}
],
"connections": {
"WhatsApp Verify": {
"main": [
[
{
"node": "Return Challenge",
"type": "main",
"index": 0
}
]
]
},
"WhatsApp Webhook": {
"main": [
[
{
"node": "Extract Message",
"type": "main",
"index": 0
}
]
]
},
"Extract Message": {
"main": [
[
{
"node": "Build Groq Prompt",
"type": "main",
"index": 0
}
]
]
},
"Build Groq Prompt": {
"main": [
[
{
"node": "Groq AI",
"type": "main",
"index": 0
}
]
]
},
"Groq AI": {
"main": [
[
{
"node": "Parse Groq Response",
"type": "main",
"index": 0
}
]
]
},
"Parse Groq Response": {
"main": [
[
{
"node": "Send WhatsApp Reply",
"type": "main",
"index": 0
},
{
"node": "Save Lead to Sheets",
"type": "main",
"index": 0
},
{
"node": "Is Hot Lead?",
"type": "main",
"index": 0
},
{
"node": "Return OK",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
},
"tags": [
"admitbot",
"phase-1"
]
}
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About this workflow
01 - Main Bot (WhatsApp + Website). Uses httpRequest, googleSheets. Webhook trigger; 11 nodes.
Source: https://github.com/anshika-codes-AI/IIST-AdmitBot/blob/d62fdcdd848b062920b1787d81ac106df7797652/n8n-workflows/01-main-bot.json — original creator credit. Request a take-down →
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