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Reply to grouped WhatsApp messages with Wafly and OpenAI

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Created by: Iago || iagovelasco
Iago

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Last update 17 hours ago

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Quick overview

This workflow receives WhatsApp webhooks from Wafly, groups rapid-fire messages into a single question (and optionally transcribes voice notes), then uses an OpenAI-powered agent with per-contact memory to generate a short reply and sends it back to the user on WhatsApp.

How it works

  1. Receives an incoming WhatsApp event via a webhook endpoint exposed by n8n.
  2. Normalizes the payload so either typed text or a voice-note transcription becomes a single question field.
  3. Filters out non-customer events such as echoes from your own number, group messages, and empty messages.
  4. Sends the customer’s question to an AI agent backed by an OpenAI chat model and a per-phone-number memory window.
  5. Sends the agent’s reply back to the customer as a WhatsApp text message using Wafly.

Setup

  1. Self-host n8n and install the community node n8n-nodes-wafly (this template does not work on n8n Cloud).
  2. Create Wafly API credentials in n8n and replace the placeholder Wafly credential references in the Wafly nodes.
  3. Create an OpenAI API credential in n8n and select it in the OpenAI Chat Model node.
  4. Run the manual setup sequence to enable Wafly message buffering (and optionally voice-note transcription by pasting your OpenAI key into Wafly’s transcription settings).
  5. Copy the webhook Production URL from the webhook trigger and register it as the Wafly “received” webhook URL for your instance (using the provided curl request and your instance/token values).

Requirements

  • Self-hosted n8n. This template uses a community node and does not run on n8n Cloud.

Customization

  • Edit the AI Agent system message, tune the 8s silence window and 30s ceiling in the buffer setup node, or swap the memory node for a database.