WooCommerce Product Loader

This Python script reads product data from an Excel file, processes it through Google's Gemini LLM to generate WooCommerce-compatible descriptions and attributes, and then adds the products to a WooCommerce store via API.

Features

• Reads product data from Excel files with flexible column naming
• Uses Google Gemini AI to generate product descriptions and attributes
• Converts raw product features into structured WooCommerce attributes
• Adds products to WooCommerce via REST API
• Comprehensive error handling and logging
• Rate limiting to avoid API throttling

Requirements

• Python 3.8+
• WooCommerce store with REST API enabled
• Google Gemini AI API key
• Excel file with product data

Installation

1. Clone or download this repository

2. Install dependencies:

   pip install -r requirements.txt

3. Edit .env file with your actual credentials:

   WOOCOMMERCE_URL=https://yourstore.com
   WOOCOMMERCE_CONSUMER_KEY=ck_your_consumer_key
   WOOCOMMERCE_CONSUMER_SECRET=cs_your_consumer_secret
   GEMINI_API_KEY=your_gemini_api_key
   

Excel File Format

Your Excel file should have these columns (column names are flexible):

• Product Name (or "name", "product_name")
• Raw Features (or "features", "raw_features")
• Price (numeric)
• Regular Price (or "regular_price", numeric)

Usage

1. Place your Excel file in the same directory as the script and name it data/products.xlsx (or modify the script to use a different filename)

2. Run the script:

   python product_loader.py

The script will:

1. Read products from the Excel file
2. Process each product through Gemini AI to generate:
   • Slug
   • Detailed description
   • Short description
   • Structured attributes
3. Add each product to your WooCommerce store

WooCommerce API Setup

1. Go to your WordPress admin panel
2. Navigate to WooCommerce > Settings > Advanced > REST API
3. Click "Add Key"
4. Set permissions to "Read/Write"
5. Copy the Consumer Key and Consumer Secret to your .env file

Gemini AI API Setup

1. Go to Google AI Studio
2. Create a new API key
3. Copy the API key to your .env file

Note: This script uses the new google-genai package with the Gemini 2.5 Flash model for improved performance.

License

This project is open source and available under the MIT License.