This workflow follows the Emailsend → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"nodes": [
{
"parameters": {
"jsCode": "const webhookData = $input.first().json;\nconst messages = webhookData.body?.messages || [];\nconst lastUserMsg = messages.filter(m => m.role === 'user').pop()?.content || '';\nconst text = lastUserMsg.toLowerCase();\n\n// Heur\u00edstica para decidir si buscar en la base de conocimientos\nconst isShort = text.length < 60;\nconst hasQuestion = text.includes('?');\nconst isJustEmail = /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}/.test(text) && text.length < 80;\n\nlet requires_rag = true;\nif ((isShort && !hasQuestion && isJustEmail) || ['hola', 'hi', 'hello', 'buenos d\u00edas', 'gracias', 'thanks'].includes(text.trim())) {\n requires_rag = false;\n}\n\nreturn [{\n json: {\n ...webhookData,\n requires_rag\n }\n}];"
},
"id": "[NODE_ID_1]",
"name": "Analyze Intent",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-2272,
1104
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 1
},
"conditions": [
{
"id": "cond1",
"leftValue": "={{ $json.requires_rag }}",
"rightValue": "={{ true }}",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "[NODE_ID_2]",
"name": "Needs Knowledge Base?",
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
-2048,
1104
]
},
{
"parameters": {
"httpMethod": "POST",
"path": "mga-ai-agent",
"responseMode": "responseNode",
"options": {
"allowedOrigins": "https://www.mgatc.com,https://mgatc.pages.dev,http://localhost:3000,http://localhost:3001,https://mgatc.com"
}
},
"id": "[NODE_ID_3]",
"name": "Webhook Trigger1",
"type": "n8n-nodes-base.webhook",
"typeVersion": 2,
"position": [
-2496,
1104
]
},
{
"parameters": {
"jsCode": "const response = $input.first().json;\nconst error = response.error;\nconst assistantMessage = error ? '' : (response.choices?.[0]?.message?.content || '');\n\nconst webhookBody = $('Webhook Trigger1').first().json.body;\nconst allMessages = webhookBody.messages || []; // Aseguramos que sea un array\nconst conversationStr = JSON.stringify(allMessages);\n\n// PRIORIDAD: Datos directos del nuevo formulario de identidad\nlet email = webhookBody.user_info?.email || null;\nlet name = webhookBody.user_info?.name || null;\n\n// FALLBACK: Regex\nif (!email) {\n const emailRegex = /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}/g;\n const emails = conversationStr.match(emailRegex) || [];\n email = emails[0] || null;\n}\n\nif (!name) {\n const nameRegex = /(?:me llamo|soy|my name is|i am|i\\'m)\\s+([A-Z][a-z\u00e1\u00e9\u00ed\u00f3\u00fa\u00c1\u00c9\u00cd\u00d3\u00daa-z]+(?:\\s+[A-Z][a-z\u00e1\u00e9\u00ed\u00f3\u00fa\u00c1\u00c9\u00cd\u00d3\u00daa-z]+)?)/gi;\n const nameMatch = nameRegex.exec(conversationStr);\n name = nameMatch ? nameMatch[1] : null;\n}\n\nconst systemMsg = allMessages.find(m => m.role === 'system');\nconst sourceLang = systemMsg?.content?.includes('currently set to English') ? 'en' : 'es';\n\n// --- GENERACI\u00d3N DE HTML SEGURO ---\nlet chatHtml = \"\";\n\ntry {\n // Tomamos los \u00faltimos mensajes y quitamos el de sistema\n const chatMessages = allMessages.filter(m => m.role !== 'system').slice(-6);\n \n if (chatMessages.length > 0) {\n chatHtml = chatMessages.map(msg => {\n const isUser = msg.role === 'user';\n const label = isUser ? 'Usuario' : 'Asistente';\n const bgColor = isUser ? '#f8fafc' : '#ffffff';\n const borderColor = isUser ? '#2563eb' : '#10b981';\n \n return `\n <div style=\"margin-bottom: 12px; padding: 12px; border-radius: 8px; background-color: ${bgColor}; border-left: 4px solid ${borderColor}; font-family: sans-serif;\">\n <strong style=\"display: block; font-size: 11px; color: #64748b; text-transform: uppercase; margin-bottom: 4px;\">${label}</strong>\n <div style=\"font-size: 14px; color: #1e293b; line-height: 1.5;\">${msg.content}</div>\n </div>`;\n }).join('');\n } else {\n chatHtml = \"<p>No hay mensajes recientes en la conversaci\u00f3n.</p>\";\n }\n} catch (e) {\n chatHtml = \"<p>Error al formatear la conversaci\u00f3n.</p>\";\n}\n\nreturn [{\n json: {\n error,\n assistantMessage,\n email,\n name,\n sourceLang,\n hasLead: !!(email || name),\n chatHtml, // Ahora s\u00ed o s\u00ed estar\u00e1 presente\n conversation: allMessages.slice(-6) // Lo mantenemos por si lo necesitas\n }\n}];"
},
"id": "[NODE_ID_4]",
"name": "Extract Lead Data1",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-1152,
1104
]
},
{
"parameters": {
"respondWith": "json",
"responseBody": "={{ { content: $json.assistantMessage || ($json.error ? 'Error: ' + $json.error.message : 'No se pudo obtener respuesta de la IA.') } }}",
"options": {}
},
"id": "[NODE_ID_5]",
"name": "Respond to Frontend2",
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1,
"position": [
-928,
1008
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 1
},
"conditions": [
{
"id": "e5fda4e4-0e70-4b06-a9d7-5664090c13ea",
"leftValue": "={{ $json.hasLead }}",
"rightValue": "={{ true }}",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "[NODE_ID_6]",
"name": "Has Lead Info?1",
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
-928,
1200
]
},
{
"parameters": {
"tableId": "leads",
"fieldsUi": {
"fieldValues": [
{
"fieldId": "name",
"fieldValue": "={{ $json.name || null }}"
},
{
"fieldId": "email",
"fieldValue": "={{ $json.email || null }}"
},
{
"fieldId": "interest",
"fieldValue": "={{ $json.assistantMessage.substring(0, 300) }}"
},
{
"fieldId": "source_lang",
"fieldValue": "={{ $json.sourceLang }}"
},
{
"fieldId": "source_page",
"fieldValue": "={{ $('Webhook Trigger1').first().json.body.source_page || 'unknown' }}"
},
{
"fieldId": "conversation",
"fieldValue": "={{ JSON.stringify($json.conversation) }}"
},
{
"fieldId": "status",
"fieldValue": "new"
}
]
}
},
"id": "[NODE_ID_7]",
"name": "Save Lead to Supabase1",
"type": "n8n-nodes-base.supabase",
"typeVersion": 1,
"position": [
-704,
1104
],
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"html": "<!DOCTYPE html>\n<html>\n<head>\n <meta charset=\"UTF-8\">\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n <style>\n body { font-family: Arial, sans-serif; line-height: 1.6; color: #333; margin: 0; padding: 0; background-color: #f4f4f4; }\n .container { max-width: 600px; margin: 20px auto; background: #ffffff; border-radius: 8px; overflow: hidden; box-shadow: 0 2px 4px rgba(0,0,0,0.1); }\n .header { background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); padding: 40px 20px; text-align: center; }\n .logo { max-width: 200px; height: auto; margin-bottom: 20px; }\n .header h1 { color: #ffffff; margin: 0; font-size: 24px; }\n .content { padding: 40px 30px; }\n .content h2 { color: #667eea; margin-top: 0; font-size: 20px; }\n .content p { margin: 15px 0; }\n .highlight { background-color: #f8f9ff; padding: 20px; border-left: 4px solid #667eea; margin: 20px 0; }\n .chat-box { background-color: #f8f9fa; border: 1px solid #e9ecef; border-radius: 4px; padding: 15px; margin-top: 15px; font-size: 14px; color: #555; white-space: pre-line; }\n .footer { background-color: #f8f9fa; padding: 20px; text-align: center; font-size: 12px; color: #666; }\n </style>\n</head>\n<body>\n <div class=\"container\">\n <div class=\"header\">\n <img src=\"https://raw.githubusercontent.com/Mgobeaalcoba/Mgobeaalcoba.github.io/6e7c26232117f9e2d85828b6477192e1e89f34b4/assets/images/logo_claro.png\" alt=\"MGA Tech\" class=\"logo\">\n <h1>\u00a1Nuevo Lead Detectado!</h1>\n </div>\n <div class=\"content\">\n <h2>Alerta del Agente IA</h2>\n <p>Se ha detectado un nuevo lead interactuando con el chat del Agente IA. A continuaci\u00f3n tienes los detalles:</p>\n \n <div class=\"highlight\">\n <p style=\"margin: 5px 0;\"><strong>Nombre:</strong> {{ $json.name || 'No detectado' }}</p>\n <p style=\"margin: 5px 0;\"><strong>Email:</strong> {{ $json.email || 'No detectado' }}</p>\n <p style=\"margin: 5px 0;\"><strong>Idioma:</strong> {{ $json.sourceLang === 'en' ? 'Ingl\u00e9s' : 'Espa\u00f1ol' }}</p>\n </div>\n\n <h2 style=\"margin-top: 30px; font-size: 18px;\">\u00daltimos mensajes de la conversaci\u00f3n:</h2>\n <div class=\"chat-box\">\n {{ $('Extract Lead Data1').item.json.chatHtml }}\n </div>\n \n </div>\n <div class=\"footer\">\n <p>Esta es una notificaci\u00f3n autom\u00e1tica interna del sistema.</p>\n <p>© 2026 MGA Tech Consulting. Todos los derechos reservados.</p>\n </div>\n </div>\n</body>\n</html>"
},
"type": "n8n-nodes-base.html",
"typeVersion": 1.2,
"position": [
-480,
1104
],
"id": "[NODE_ID_8]",
"name": "HTML1"
},
{
"parameters": {},
"type": "n8n-nodes-base.noOp",
"typeVersion": 1,
"position": [
-704,
1296
],
"id": "[NODE_ID_9]",
"name": "No Operation, do nothing1"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ \n JSON.stringify({ \n messages: (function() { \n const webhookData = $('Webhook Trigger1').first().json; \n const history = (webhookData.body && webhookData.body.messages) ? webhookData.body.messages : []; \n const knowledgeData = $('Search Knowledge Supabase').first().json; \n const contextChunks = Array.isArray(knowledgeData) ? knowledgeData.map(r => r.content).join('\\n---\\n') : (knowledgeData.content || ''); \n const systemMsg = history.find(m => m.role === 'system'); \n const otherMsgs = history.filter(m => m.role !== 'system'); \n return [ \n { \n role: 'system', \n content: (systemMsg?.content || 'You are a helpful assistant.') + '\\n\\nKNOWLEDGE BASE CONTEXT (Usa esto para responder solo si es relevante):\\n' + contextChunks \n }, \n ...otherMsgs \n ]; \n })(), \n model: 'zai-org/GLM-4.7-Flash:novita', \n stream: false \n }) \n}}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
-1376,
1008
],
"id": "[NODE_ID_10]",
"name": "Call Hugging Face RAG",
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"onError": "continueRegularOutput"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/ v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "=={{ \n JSON.stringify({ \n messages: $('Webhook Trigger1').first().json.body.messages, \n model: 'zai-org/GLM-4.7-Flash:novita', \n stream: false \n }) \n}}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
-1376,
1200
],
"id": "[NODE_ID_11]",
"name": "Call Hugging Face General",
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"onError": "continueRegularOutput"
},
{
"parameters": {
"method": "POST",
"url": "https://router.huggingface.co/hf-inference/models/intfloat/multilingual-e5-small/pipeline/feature-extraction",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "inputs",
"value": "={{ $json.body.messages[0].content }}"
}
]
},
"options": {
"response": {
"response": {
"fullResponse": true
}
}
}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
-1824,
1008
],
"id": "[NODE_ID_12]",
"name": "Hugging Face Embedding Model",
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"method": "POST",
"url": "={{ $vars.NEXT_PUBLIC_SUPABASE_URL }}/rest/v1/rpc/match_knowledge",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "apikey",
"value": "={{ $vars.NEXT_PUBLIC_SUPABASE_ANON_KEY }}"
},
{
"name": "Authorization",
"value": "=Bearer {{ $vars.NEXT_PUBLIC_SUPABASE_ANON_KEY }}"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"query_embedding\": {{ JSON.stringify($json.body) }},\n \"match_threshold\": 0.5,\n \"match_count\": 3\n}",
"options": {}
},
"id": "[NODE_ID_13]",
"name": "Search Knowledge Supabase",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.1,
"position": [
-1600,
1008
]
},
{
"parameters": {
"fromEmail": "mariano@mgatc.com",
"toEmail": "gobeamariano@gmail.com",
"subject": "Nuevo Lead Detectado",
"html": "={{ $json.html }}",
"options": {}
},
"type": "n8n-nodes-base.emailSend",
"typeVersion": 2.1,
"position": [
-256,
1104
],
"id": "[NODE_ID_14]",
"name": "Send an Email",
"credentials": {
"smtp": {
"name": "<your credential>"
}
}
}
],
"connections": {
"Analyze Intent": {
"main": [
[
{
"node": "Needs Knowledge Base?",
"type": "main",
"index": 0
}
]
]
},
"Needs Knowledge Base?": {
"main": [
[
{
"node": "Hugging Face Embedding Model",
"type": "main",
"index": 0
}
],
[
{
"node": "Call Hugging Face General",
"type": "main",
"index": 0
}
]
]
},
"Webhook Trigger1": {
"main": [
[
{
"node": "Analyze Intent",
"type": "main",
"index": 0
}
]
]
},
"Extract Lead Data1": {
"main": [
[
{
"node": "Respond to Frontend2",
"type": "main",
"index": 0
},
{
"node": "Has Lead Info?1",
"type": "main",
"index": 0
}
]
]
},
"Has Lead Info?1": {
"main": [
[
{
"node": "Save Lead to Supabase1",
"type": "main",
"index": 0
}
],
[
{
"node": "No Operation, do nothing1",
"type": "main",
"index": 0
}
]
]
},
"Save Lead to Supabase1": {
"main": [
[
{
"node": "HTML1",
"type": "main",
"index": 0
}
]
]
},
"HTML1": {
"main": [
[
{
"node": "Send an Email",
"type": "main",
"index": 0
}
]
]
},
"Call Hugging Face RAG": {
"main": [
[
{
"node": "Extract Lead Data1",
"type": "main",
"index": 0
}
]
]
},
"Call Hugging Face General": {
"main": [
[
{
"node": "Extract Lead Data1",
"type": "main",
"index": 0
}
]
]
},
"Hugging Face Embedding Model": {
"main": [
[
{
"node": "Search Knowledge Supabase",
"type": "main",
"index": 0
}
]
]
},
"Search Knowledge Supabase": {
"main": [
[
{
"node": "Call Hugging Face RAG",
"type": "main",
"index": 0
}
]
]
}
},
"meta": {
"templateCredsSetupCompleted": true
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
httpHeaderAuthsmtpsupabaseApi
Pro
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How this works
This workflow transforms incoming webhook requests into intelligent responses by analysing user intent and extracting key details like lead information, making it ideal for developers building AI-assisted chat interfaces or lead capture forms without deep AI expertise. It delivers quick value by automating personalised replies and data storage, ensuring no leads slip through the cracks while keeping interactions smooth and engaging. The core step involves a code node that dissects the request to determine intent, followed by conditional checks that route to either a knowledge base query via HTTP requests or direct lead saving in Supabase, with email notifications for follow-ups.
Use this workflow when integrating real-time AI-like assistance into web apps or customer support tools that receive webhook data, particularly for lead generation where quick analysis and storage are crucial. Avoid it for high-volume traffic without scaling Supabase, or if you need advanced AI nodes beyond basic intent detection. Common variations include adding Slack notifications instead of email for team alerts, or swapping Supabase for Airtable to match your database preferences.
About this workflow
Ai Assistant Workflow. Uses supabase, httpRequest, emailSend. Webhook trigger; 14 nodes.
Source: https://github.com/Mgobeaalcoba/Mgobeaalcoba.github.io/blob/main/docs/automations/ai_assistant_workflow.json — original creator credit. Request a take-down →
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