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 (e.g., 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 (e.g., "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 (e.g., 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 (e.g., "Our store opens at 9 AM").

Set Up 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.