I built an offline AI that knows your last frost date, no internet, no API

Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Submission 🌿

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

The most useful number in a vegetable garden is the last spring frost date. Get it wrong by a week and one cold night turns your tomato seedlings to mush.

Every tool that gives you that number has the same flaw. It lives on a server. You look it up on your phone, standing in the one corner of the allotment that gets a bar of signal, hoping the page loads before the rain starts.

So I built FrostWise: it predicts your last frost and tells you what to plant, and it does the whole thing on your laptop with the Wi-Fi off. Two open-weight models, no API key, no account, nothing leaves the machine.

I built it for a specific person: my friend who keeps a plot at a community garden on a hill where the signal drops to nothing. Every spring she texts me "is it safe to plant yet" because she cannot load a frost-date site from the plot itself. FrostWise is the answer she can keep on her own phone and open with no bars.

FrostWise answers one question honestly: when does the cold let go where you are, and what should you do about it.

You pick a location (or type your own climate numbers), choose a crop, and it returns three things:

It gets people off the screen in the most literal way. The screen is the ten seconds you spend before you walk outside and put a seed in the ground. The whole point is to make that part short.

Who it is for: anyone with a patch of soil and a spotty signal. Community plots, hillside allotments, a herb bed at a trail-head cabin. The places where a cloud API is useless are exactly where people garden.

Try it now: d2damz5gbd2rbh.cloudfront.net

That hosted link is a static site (S3 plus CloudFront, near zero cost) that serves real, pre-computed TabPFN-v2 and Gemma results for the preset cities, so you can click through actual model output. The live models themselves run on your own machine. For custom climate input, fully offline, clone the repo and run python run.py.

Here is the full flow across three very different climates: Miami (effectively frost-free), Chicago (a real May frost), and Fargo (frost that lingers into summer). Same code, three honest answers.

Here is what one answer looks like: a predicted last frost, the honest range around it, and planting advice written locally by Gemma for the exact crop.

The frost date animates in, then a local Gemma model writes the planting advice live. Nothing in that video calls out to the internet.

Hacktoberfest Open-Source AI Challenge · Week 1: Touch Grass

🔗 Live demo: d2damz5gbd2rbh.cloudfront.net · 💻 Run it live: Getting Started (the full offline models run locally) · 🎬 YouTube demo: coming soon

About the live demo. The hosted preview is a static site (S3 + CloudFront) that serves real, pre-computed TabPFN-v2 + Gemma results for the preset cities, so you can click through actual model output. The live models themselves run on your machine with no server and no internet. For custom…