🤖 Automating WhatsApp replies using Go High Level with Redis and Anthropic

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Description

Automating WhatsApp replies in Go High Level with Redis and Anthropic

Description


Who’s it for


How it works / What it does

  1. Receive message in n8n via Webhook from GHL (Customer Replied (SMS) automation). WhatsApp messages arrive the same way using the Wazzap plugin.
  2. Filter message type:
    • If audio → skip processing and send fallback asking for text.
    • If text → sanitize by fixing escaped quotes, escaping line breaks/carriage returns/tabs, and removing invalid fields.
  3. Buffer messages in Redis to group multiple messages sent in a short window.
  4. Run AI Agent using the ClientInfo tool to answer only with accurate service/branch data.
  5. Sanitize AI output before sending back.
  6. Update GHL contact custom field (IA_answer) with the AI’s response.
  7. Send SMS reply automatically via GHL’s outbound automation triggered by the updated custom field.

How to set up

  1. In GHL, create:
    • Inbound automation: Trigger on Customer Replied (SMS) → Send to your n8n Webhook.
    • Outbound automation: Trigger when IA_answer is updated → Send SMS to the contact.
    • Create a custom field named IA_answer.
  2. Connect Wazzap in GHL to handle WhatsApp messages.
  3. Configure Redis in n8n (host, port, DB index, password).
  4. Add your AI model credentials (Anthropic, OpenAI, etc.) in n8n.
  5. (Optional) Set up the Google Drive Excel Merge sub-workflow to enrich ClientInfo with external data.

Requirements


How to customize the workflow

🔗 Nodes Used

HTTP Request, Redis, Webhook, Google Drive, Execute Workflow Trigger, AI Agent

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup