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.

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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: json { "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 personalshopper 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.