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Personal shopper chatbot for WooCommerce with RAG using Google Drive and openAI

DavideDavide
13378 views
2/3/2026
data-extractionemailautomationinbox-processingimap
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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.

n8n Personal Shopper Chatbot for WooCommerce with RAG using Google Drive and OpenAI

This n8n workflow creates an AI-powered personal shopper chatbot for a WooCommerce store. It leverages Retrieval Augmented Generation (RAG) by connecting to product information stored in Google Drive and utilizes OpenAI for conversational AI. The chatbot can answer questions about products, provide recommendations, and potentially extract information from user queries.

What it does

This workflow automates the following steps:

  1. Listens for Chat Messages: It triggers whenever a new chat message is received, acting as the entry point for user interactions with the chatbot.
  2. Initializes AI Agent: Sets up an AI agent configured with a chat model, memory, and various tools.
  3. Configures OpenAI Chat Model: Defines the OpenAI chat model (likely GPT-3.5 or GPT-4) to be used for generating conversational responses.
  4. Establishes Simple Memory: Implements a basic memory buffer to maintain context within a conversation, allowing the chatbot to remember previous turns.
  5. Sets up OpenAI Embeddings: Configures OpenAI embeddings for converting text into numerical representations, crucial for vector store operations.
  6. Integrates Google Drive for Data Loading: Connects to Google Drive to load product information or other relevant documents.
  7. Splits Text for Vector Storage: Uses a token splitter to break down the loaded documents into manageable chunks for efficient storage and retrieval from the vector database.
  8. Connects to Qdrant Vector Store: Utilizes Qdrant as a vector database to store and retrieve document embeddings, enabling the RAG capabilities.
  9. Provides a Calculator Tool: Equips the AI agent with a calculator tool, allowing it to perform mathematical operations if needed during a conversation.
  10. Enables Vector Store Question Answering Tool: Integrates a tool that allows the AI agent to answer questions by searching and retrieving relevant information from the Qdrant vector store.
  11. Includes an Information Extractor: Provides a tool for the AI agent to extract structured information (e.g., product names, quantities, user preferences) from user queries.
  12. Performs HTTP Requests: Includes an HTTP Request node, which could be used for interacting with the WooCommerce API (e.g., fetching product details, adding items to a cart, or updating order information) based on the AI agent's decisions.
  13. Edits Fields (Set): A Set node is included, likely for data transformation or preparing data before or after interactions with other services.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • OpenAI API Key: An API key for OpenAI to use their chat models and embeddings.
  • Google Drive Account: A Google Drive account with relevant product information or documents structured for retrieval.
  • Qdrant Instance: Access to a Qdrant vector database instance (self-hosted or cloud-based).
  • WooCommerce Store: A WooCommerce store (the workflow is designed to interact with it, though direct WooCommerce nodes are not explicitly shown, the HTTP Request node would handle this).

Setup/Usage

  1. Import the Workflow: Download the JSON provided and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key credentials for the "OpenAI Chat Model" and "Embeddings OpenAI" nodes.
    • Configure Google Drive credentials for the "Google Drive" node.
    • Configure Qdrant credentials for the "Qdrant Vector Store" node.
  3. Populate Google Drive: Ensure your Google Drive contains the product information or documents that the chatbot should use for RAG. These documents will be loaded, split, and embedded into Qdrant.
  4. Customize HTTP Request Node: Configure the "HTTP Request" node (ID 19) to interact with your WooCommerce API as needed. This might involve fetching product details, handling user requests, or updating order information.
  5. Activate the Workflow: Once all credentials are set and configurations are done, activate the workflow.
  6. Interact with the Chatbot: The "When chat message received" trigger will listen for incoming messages, allowing you to interact with your personal shopper chatbot.

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