Personal Shopper Chatbot for WooCommerce with RAG using Google Drive and openAI

This workflow combines OpenAI , Retrieval-Augmented Generation (RAG) , and WooCommerce to create an intelligent personal shopping assistant. It handles two scenarios:

1. Product Search : Extracts user intent (keywords, price ranges, SKUs) and fetches matching products from WooCommerce.
2. General Inquiries : Answers store-related questions (eg, opening hours, policies) using RAG and documents stored in Google Drive.

How It Works

1. Chat Interaction & Intent Detection

• Chat Trigger :
  • Starts when a user sends a message ( "When chat message received" ).
• Information Extractor :
  • Uses OpenAI to analyze the message and determine if the user is searching for a product or asking a general question .
  • Extracts:
    • search (true/false).
    • keyword , priceRange , SKU , category (if product-related).
  • Example:

     {
     "search": true,
     "keyword": "red handbags",
     "priceRange": { "min": 50, "max": 100 },
     "SKU": "BAG123",
     "category": "women's accessories"
     }
    

2. Product Search (WooCommerce Integration)

• AI Agent :
  • If search: true , routes the request to the personal_shopper tool.
  • WooCommerce Node :
    • Queries the WooCommerce store using extracted parameters ( keyword , priceRange , SKU ).
    • Filters products in stock ( stockStatus: "instock" ).
    • Returns matching products (eg, "red handbags under €100").

3. General Inquiries (RAG System)

• RAG Tool :
  • If search: false , uses the Qdrant Vector Store to retrieve store information from documents.
  • Google Drive Integration :
    • Documents (eg, store policies, FAQs) are stored in Google Drive.
    • Downloaded, split into chunks, and embedded into Qdrant for semantic search.
  • OpenAI Chat Model : Generates answers based on retrieved documents (eg, "Our store opens at 9 AM").

Setup Steps

1. Configure the RAG System

• Google Drive Setup :
  • Upload store documents .
  • Update the Google Drive2 node with your folder ID.
• Qdrant Vector Database :
  • Clean the collection (update Qdrant Vector Store node with your URL).
  • Use Embeddings OpenAI to convert documents into vectors.

2. Configure OpenAI & WooCommerce

• OpenAI Credentials :
  • Add your API key to all OpenAI nodes ( OpenAI Chat Model , Embeddings OpenAI , etc.).
• WooCommerce Integration :
  • Connect your WooCommerce store (credentials in the personal_shopper node).
  • Ensure product data is synced and accessible.

3. Customize the AI ​​Agent

• Intent Detection :
  • Modify the Information Extractor 's system prompt to align with your store's terminology.
• RAG Responses :
  • Update the tool description to reflect your store's documents.

Notes

This template is ideal for e-commerce businesses needing a hybrid assistant for product discovery and customer support.

Need help customizing?

Contact me for consulting and support or add me on Linkedin .