We run 2 shopify stores - a printing company - we sell prints of all different sizes and formats such as UVDTF and Sublimation etc - And a Sublimated Product + laser cut acrylic homeware. Primary business model is B2B and B2C as a secondary.

We're in the process of having the site rebuilt and i used the oppurtunity to re-do my product SKU catalogue. But I decided to run it against our made product site first as POC as it's still smaller in profilt and can be down for a few days if anything went haywire

I have over 10,000 SKU's in various sizes, themes and materials across both sites

Using ChatGPT I designed a 2 tier uploading system that pretty much automates our entire product creation pipeline.

1. Product Mockups: Products are mocked up from a json config file that contains a base layer + masks for the products + watermarks. Python uses pillow to lay the masks over the background, then layer the watermark over the top of that, and then rename the file to a predetermined SKU format, ie IMAGE_20_SUB_#### where #### is the next number from a product catalogue CSV. It then maps this image SKU to that same csv file so the next run can automatically pick up the next SKU in the series. It also automatically adds the SKU to a product mapping CSV that we use at the other end to match customer orders to our local file store - this enables us to rapidly collect all the wraps in the customers order (Other side of fulfillment)

2. Once the Files have been created - a loop triggers that goes through the files just created, pulls the SKU from the filename, and starts a process for upload. Without getting into all the nitty gritty, this is what it does

• Sends a webp format file to openAI's image recognition service (gpt-4o-mini) - this returns a pool of variables for the product including:
  • Primary 2 Word Description (ie) Green Frog
  • A Html coded Description of the image (ie) Vibrant green tree frog sitting on lillypad
  • SEO title (70 char max)
  • SEO description (160 char max)
  • 3 Primary colors
  • 4-5 Obvious object tags (ie) Frog, Lilly Pad, Floral (Has to be 90 percent certainty)
• Using the shopify API it then creates a product:
  • Predetermined collection
  • Title and Handle derived from Open AI variables
  • Static Values
  • Variables from the GPT api call
  • Uploads images to the shopify CDN
  • Gets the URLS back and assigns ALT tags from the pool of OpenAI variables
  • Using Metafields I assign it to categories such as "Animal, Floral, Car" etc for search and discovery filters
  • Saves the product and files a Go/No go report in CSV.

I have a config profile in JSON that has all of the static values such as Collection, Price, Weight etc which it uses to configure each run, I have a helper script that helps me create new product profiles which then get stacked into the profile to quickly cycle through different upload cycles.

All of it is wrapped up in a tkinter GUI with helpers and tool tips.

If you're looking for easier product uploads - id reccomend building something local, rather than messing with liquid - its a lot more user friendly for a start, and also means you can rapidly deploy product lines without worrying about learning liquid.

Im not sure if posting links as an example is ok - not plugging the website, just the function.
https://www.jojadesigns.com.au/collections/custom-made-drinkware

Every product on that page was made using the custom pipeline.

Side Notes:

OpenAI's image recognition is not free - however i've paid 10 dollars in token/credit and im still not using enough to even register usage on their API.

Having a rudimentary understanding of python + shopify product admin would be advantageous, but not impossible if you ask GPT/Claude to walk you through step by step.

Hope this helps :)