This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
<!-- What does it do, and how does it get people off the screen and into the world? Who is it for? --> Frostline is a garden planner that runs entirely on my laptop. You give it two dates, your last spring frost and your first fall frost, and it works out which crops are safe to sow this week and which windows open in the next two weeks. A local Gemma model then turns that into a short weekend plan: a few garden tasks, then one 20-minute job to do outside.
The last line of every plan tells you to close the laptop. Most planners keep you scrolling. This one is meant to end its own session. It's for anyone who wants to start a vegetable patch, or keep one going, without hunting through frost-date charts and forum threads.
Demo
Code
How I Built It
<!-- Which open-source AI did you use (open-weight models, agent harnesses, frameworks, local inference), and how is your project built around it? --> The project has two parts with separate jobs:
Plain Python does the calendar math. Each crop has a maturity time, a frost tolerance, and a sowing lead time. From those and your frost dates, the script computes spring and fall sowing windows and checks them against today's date.
A local open-weight model does the writing. Gemma (gemma3:4b, served by Ollama) gets only the verified facts and is told not to add crops or dates. Its job is to phrase a friendly weekend plan, not to decide what's safe to plant.
I split it this way on purpose. A small local model can be confidently wrong about dates, and a wrong sowing date means a lost crop. Keeping the dates in deterministic code means the worst the model can do is write awkwardly. If Ollama isn't running, the script still prints the facts, so the planner works even when the AI part doesn't.
It uses only the Python standard library, so there's nothing to install besides Ollama.
Why Does Open Innovation Matter?
<!-- Why does open innovation matter for what you built? What did it make possible that a closed API wouldn't? --> A garden is often somewhere with weak signal and no reason to ping a server. Because the model runs locally, Frostline needs no connection once the model is downloaded, and no key or account. Where you live and what you grow stay on your machine.
Open weights also let me change the model with one flag (--model) and see how the plan changes. I could add a bigger model for a nicer plan or a smaller one for an old laptop. With a closed API I'd be tied to someone else's pricing and availability.
There are real limits too. A 4B model is a modest writer and the plans can be wordy. The crop table is small and generic, so check your local extension service before trusting a date with a real harvest.
My Agent Session
Prize Categories
<!-- Which partner categories are you entering? List every one that applies, or remove this section. --> Best Use of Gemma
<!-- Team Submissions: Please pick one member to publish the submission and credit teammates by listing their DEV usernames directly in the body of the post. --> NIL
Top comments (1)
it was good