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Voice AI Customer Support for WooCommerce using VAPI, GPT-4o & Gemini with RAG

by Davide•Updated: Last update 20 days ago•Source: n8n.io

Getting Started

This workflow integrates a Retrieval-Augmented Generation (RAG) system with a post-sales AI agent for WooCommerce. It combines vector-based search (Qdrant + OpenAI embeddings) with LLMs (Google Gemini and GPT-4o-mini) to provide accurate and contextual responses.

Both systems are connected to VAPI webhooks , making the workflow usable in a voice AI assistant via Twilio phone numbers.

The workflow receives JSON payloads from VAPI via webhooks, processes the request through the appropriate chain (Agent or RAG), and sends a structured response back to VAPI to be read out to the user.

Advantages

  • ✅ Unified AI Support System : Combines knowledge retrieval (RAG) with transactional support (WooCommerce).
  • ✅ Data Privacy & Security: Enforces strict email/order verification before sharing information.
  • ✅ Multi-Model Power : Leverages both Google Gemini and OpenAI GPT-4o-mini for optimal responses.
  • ✅ Scalable Knowledge Base : Qdrant vector database ensures fast and accurate context retrieval.
  • ✅ Customer Satisfaction : Provides real-time answers about orders, tracking, and store policies.
  • ✅ Flexible Integration : Easily connects with VAPI for voice assistants and phone-based customer support.
  • ✅ Reusable Components : The RAG part can be extended for FAQs, while the post-sales agent can scale with more WooCommerce tools.

How it Works

It has two main components:

  1. RAG System (Knowledge Retrieval & Q&A)

    • Uses OpenAI embeddings to store documents in Qdrant.
    • Retrieves relevant context with a Vector Store Retriever.
    • Sends the information to a Question & Answer Chain powered by Google Gemini.
    • Returns precise, context-based answers to user queries via webhook.

  2. Post-Sales Customer Support Agent

    • Acts as a WooCommerce virtual assistant to:

      • Retrieve customer orders (get_order, get_orders).
      • Get user profiles (get_user).
      • Provide shipment tracking (get_tracking) using YITH WooCommerce Order Tracking plugin.

    • Enforces strict verification rules : customer email must match the order before disclosing details.

    • Communicates professionally, providing clear and secure customer support.

    • Integrates with GPT-4o-mini for natural conversation flow.

Set Up Steps

To implement this workflow, follow these three main steps:

1. Infrastructure & Credentials Setup in n8n:

  • Ensure all required nodes have their credentials configured:
    • OpenAI API Key: For the GPT 4o-mini and Embeddings OpenAI nodes.
    • Google Gemini API Key: For the Google Gemini Chat Model node.
    • Qdrant Connection Details: For the Qdrant Vector Store1 node (points to a Hetzner server).
    • WooCommerce API Keys: For the get_order, get_orders, and get_user nodes (for magnanigioielli.com).
    • WordPress HTTP Auth Credentials: For the Get tracking node in the sub-workflow.
  • Pre-populate the Vector Database: The RAG system requires a pre-filled Qdrant collection with your store's knowledge base (e.g., policy documents, product info). The "Sticky Note2" provides a link to a guide on building this RAG system.

2. Workflow Activation in n8n:

  • Save this JSON workflow in your n8n instance.
  • Activate the workflow. This is crucial, as n8n only listens for webhook triggers when the workflow is active.
  • Note the unique public webhook URLs generated for the Webhook (post-sales agent) and rag (RAG system) nodes. You will need these URLs for the next step.

3. VAPI Configuration:

  • Create Two API Tools in VAPI:
    • Tool 1 (Post-Sales): Create an "API Request" tool. Connect it to the n8n Webhook URL. Configure the request body to send parameters email and n_order based on the conversation with the user.
    • Tool 2 (RAG): Create another "API Request" tool. Connect it to the n8n rag webhook URL. Configure the request body to send a search parameter containing the user's query.
  • Build the Assistant: Create a new assistant in VAPI. Write a system prompt that instructs the AI on when to use each of the two tools you created. In the "Tools" tab, add both tools.
  • Go Live: Add a phone number (e.g., from Twilio) to your VAPI assistant and set it to "Inbound" to receive customer calls.

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