Voice AI customer support for WooCommerce using VAPI, GPT-4o & Gemini with RAG
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Important notice
This workflow is provided as-is. Please review and test before using in production.
Overview
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:
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.
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.
- Retrieve customer orders (
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-miniandEmbeddings OpenAInodes. - Google Gemini API Key: For the
Google Gemini Chat Modelnode. - Qdrant Connection Details: For the
Qdrant Vector Store1node (points to a Hetzner server). - WooCommerce API Keys: For the
get_order,get_orders, andget_usernodes (formagnanigioielli.com). - WordPress HTTP Auth Credentials: For the
Get trackingnode in the sub-workflow.
- OpenAI API Key: For the
- 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) andrag(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
WebhookURL. Configure the request body to send parametersemailandn_orderbased on the conversation with the user. - Tool 2 (RAG): Create another "API Request" tool. Connect it to the n8n
ragwebhook URL. Configure the request body to send asearchparameter containing the user's query.
- Tool 1 (Post-Sales): Create an "API Request" tool. Connect it to the n8n
- 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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