This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle
What I Built
I built ClassKit Kampala to help primary teachers prepare lesson materials faster. A teacher chooses the subject, class, topic, and lesson duration, then gets an editable lesson outline, practice questions, and an answer key. I started with Primary 6 Mathematics and adding fractions.
The potential customer is a teacher, tutor, or small school that needs useful materials without spending extra hours preparing them. I have not yet validated pricing with a customer.
Demo
Try the hosted sample-mode demo. The public demo uses the built-in sample generator. Optional Qwen2.5 3B lesson generation runs locally with Ollama when you follow the setup in the repository.
Code
View the public source code on GitHub.
How I Built It
The interface is built with HTML, CSS, and JavaScript, with a small Node.js server that connects it to Ollama running on the same computer. I used the Qwen2.5 3B open-weight model for local lesson generation and verified that it generated a lesson in ClassKit. The tool also includes a built-in sample draft when local AI is unavailable. All generated materials are drafts for teacher review; the project does not claim official curriculum alignment.
Why Does Open Innovation Matter?
Running an open-weight model locally means the lesson prompt can stay on the teacher's computer instead of being sent to a hosted AI service. It also gives a school the choice to change models and avoids a hosted per-request AI fee. Local inference depends on having Ollama and the model installed, so I am testing how well this setup fits a teacher's everyday computer.
Built by Eliah Festus Wafula.
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