LLM Label Lab
A single-file training simulator for the Datamaker × International Trade Centre-Kenya data annotation programme (Day 7, Generative AI).
Trainees combine answer pieces in the lab on the left and watch a simulated model change on the right. The model is scripted, not a real AI.
Open index.html in a browser. No build step. Works on GitHub Pages.
Class mode (Supabase)
Trainees join with a name, can tap "Ask the trainer", and the trainer sees everyone live, can pause the class and send everyone to a task.
- Create a Supabase project.
- Open
supabase/setup.sql, replace TRAINER-PIN-HERE with your PIN, and run it in the SQL Editor.
- Put your Project URL and anon key in the
SUPA object in index.html.
- Deploy (Vercel imports this repo directly). The trainer presses Class, then "Trainer? Enter your PIN".
Without Supabase the page still works on its own; the Class button just stays hidden.
Trainee accounts (Trainee-001 to Trainee-040)
Run supabase/setup2.sql after setup.sql. It creates 40 accounts, each with a personal code. The trainer opens Class, enters the PIN, and presses "Login codes" to download or copy the list. Trainees sign in with their account and code; progress is saved per account and survives a refresh or a different device.
Practice hub, points and challenges
Run supabase/setup3.sql after the other two scripts. Trainees get a "Check my answer" button and hints in the lab, a Practice hub (bot growth stages, learning path, badges, streaks) and a leaderboard with teams of ten. The trainer can hide the leaderboard and start a timed challenge (3, 5 or 10 minutes) from the Class panel.
Project Lab (projects.html)
Eight simulation projects, one page: bounding box (safety equipment, grazing, crop pests), polygon (coffee leaf disease), polyline (lane lines), semantic segmentation (skin lesions), keypoints (exercise coaching) and text sentiment/churn (coffee customers). Trainees label generated scenes, a simulated model learns only from those labels, and a system report shows the real-world consequences on new scenes. Progress is kept in the browser only.
GIGO scenes (gigo/)
The GIGO annotation and simulation app (road, warehouse PPE, drone census, maize scout, LLM answers) lives in gigo/ and runs from the same deployment: open gigo/projects.html. Details, file mapping and tests are in MIGRATION.md. Run its tests with node gigo/tests/run.js and node tests/migration.js. Project Lab source is in src/project-lab/ (python3 build.py rebuilds projects.html).
