I built an offline listing writer for small sellers, and learned that small AI models need guardrails

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

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

I built Local Listing Writer, a small web app that writes product listings for online sellers. It runs entirely on your own laptop, so there's no API key, no cost per listing, and your product details never leave your machine.

You type a product name and a few facts like material, size, colour and price. Then you pick a platform (Etsy, eBay, Amazon, Instagram shop or a WhatsApp catalogue), a tone, and a language: English, Hindi or Hinglish. It gives you back a title, a short description, bullet points and hashtags.

I wanted to see if a small open model on an ordinary laptop could actually be useful for people who sell things online. Writing listings is repetitive, and a lot of small sellers won't pay a monthly subscription for it. The model turned out to be the easy part. Getting it to stop making things up was the hard part, and it gets harder outside English.

So who would pay for this? Small sellers, like home-based resellers and shop owners, who write lots of similar listings and want something free, private and offline.

The app runs locally, so there's no live link, just my test runs. One thing to flag up front: I tested the 4B and 1B models on different inputs, so I can't say how much of the difference comes from model size and how much from the 1B input being shorter.

First, gemma3:4b, with this input: "Jute tote bag, 14x16 inch, natural colour, Rs 200, for shopping and college"

Then gemma3:1b, with a much thinner input: "Handmade jute tote bag" and "Ecofriendly price-200, color red"

Three things stood out from these tests.

Small models fill gaps with confident-sounding claims. The 1B model invented a measurement and a product feature that nobody gave it.

A guardrail can quietly fail in another language. My claim checker caught "durable" in English but missed "टिकाऊ" in Hindi, because my word list was English-only. Even the 4B model slipped.

And a word list can only catch so much. It can't spot an invented measurement or a made-up handle, which is why the app still tells people to read the text before publishing.

https://github.com/Abhinav55849/Local-listing-writer

A small Streamlit app that writes product listings (title, description, bullet points, hashtags) for sellers on Etsy, eBay, Amazon, Instagram and WhatsApp. It supports English, Hindi and Hinglish.

It runs fully on your own laptop with Gemma, an open-weight model, through Ollama. Product details never leave your computer, it costs nothing to run, and it works offline.

ollama pull gemma3:1b ollama pull gemma3:4b Install the Python packages: pip install -r requirements.txt Run the app: streamlit run listing_writer.py Known limits Small models can still invent claims such as "durable" or…