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:

Product Search: Extracts user intent (keywords, price ranges, SKUs) and fetches matching products from WooCommerce.
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.

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