Listing Studio: Private Marketplace Copy with Local AI for Independent Sellers

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle*

What I Built

I built Listing Studio, a privacy-first product listing writer for independent sellers.

Small sellers often spend a lot of time writing product titles, descriptions, tags, and promotional copy for every item they list. Listing Studio helps sellers turn simple product notes into polished marketplace content for platforms such as Etsy, eBay, Depop, Shopify, and Instagram.

The seller enters:

• Product name
• Category
• Condition
• Materials and product details
• Price
• Target marketplace
• Writing voice

Listing Studio then generates:

• A marketplace-ready title
• A product description
• Searchable tags
• Basic price positioning guidance

The result can be edited and copied directly into a marketplace listing.

This could be useful for Etsy sellers, handmade product creators, vintage sellers, jewelry makers, ceramic artists, digital product creators, and other small businesses that need to create many listings quickly.

Demo

Try the live demo here:

Listing Studio Demo

The application works directly in the browser. No account or installation is required for the default experience.

Code

The project is open source on GitHub:

Listing Studio Repository

My GitHub profile:

SandipSAM2025 on GitHub

The project uses a simple structure:

• index.html for the application interface
• style.css for responsive styling, themes, colors, and animations
• script.js for the listing generator and interactions
• README.md for project documentation

How I Built It

I built Listing Studio with plain HTML, CSS, and JavaScript so that it is lightweight, easy to understand, and easy to run.

The interface includes:

• Responsive desktop and mobile layouts
• Light mode and dark mode
• Product image upload and drag-and-drop preview
• Warm, Playful, and Minimal writing voices
• Editable generated content
• Copy-to-clipboard actions
• Animated buttons and result transitions
• Browser-based local storage for theme preferences

The project also includes an optional local AI integration through Ollama. When Ollama is installed, the application can send the product prompt to a locally running open-weight model such as Llama 3.2.

The default browser writer works without Ollama, so the application is still usable offline and without an API key. The local AI path allows sellers to use an open-weight model on their own computer instead of depending on a hosted AI provider.

Why Does Open Innovation Matter?

Open innovation matters because independent sellers may enter private product information, business ideas, pricing details, customer-related information, and unreleased designs into a writing tool.

A local-first approach gives sellers more control:

• Product details do not need to be sent to a hosted AI company.
• Sellers can run an open-weight model on their own computer.
• They can change the model or prompt without being locked into one provider.
• They can avoid usage-based AI API costs.
• The project can continue working without an internet connection.
• The code is simple enough for sellers and developers to inspect and customize.

A closed AI API could generate similar text, but it would require sending the prompt to an external service and could introduce API costs, privacy concerns, rate limits, and vendor lock-in.

Listing Studio demonstrates how open tools can make a small, practical business workflow more private, flexible, and affordable.

Prize Categories

• Open-source AI
• Local-first AI
• Privacy-focused AI
• Side Hustle*This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle*