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BuckeyeBites picks a plate from today's Traditions at Scott menu that fits your allergies, diet and goals, then walks you to it.
LifestyleTypeScript · PLpgSQLGitHub @kylafallisOnlineOwner unconfirmed
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The maker's introduction consists of the line above. Read the repository README for more details. Repository README ↗
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Read the full README ↗Live site: https://buckeyebites.vercel.app
BuckeyeBites helps Ohio State students eat well at Traditions at Scott. Tell it your allergies, diets and goals once, and it only ever shows you food that is safe for you. Tap Feed me for a ready-made plate from today's menu, with the stations to visit and how much of each item to take.
Built at HackOHI/O 2026 by team Dominatrices: Kyla (tech lead), Hanna (data), Victoria (testing and AI), Maddie (design).
Every list of food in the app goes through one filter on the server (filterSafe in lib/menu.server.ts) before you see it:
Feed me, the menu, swipes, the meal plan and the recipe dupe all use this same filter. The AI in the recipe dupe only ever sees foods that already passed it, so it can't suggest something unsafe. The data scripts also check the tags, scripts/allergen-audit.sql confirms that no logged or planned plate contains a user's allergen, and the demo data script refuses to write anything if its own audit finds a problem.
BuckeyeBites is a helper, not a medical guarantee. Students with severe allergies should still confirm with dining staff.
Only in the recipe dupe. Gemini (gemini-flash-lite) matches the ingredients in a pasted recipe to foods on Scott's menu. If Gemini is slow or unavailable, a rule-based matcher (lib/dupe.ts) takes over. Feed me uses no AI: the team wrote the plates and the code picks between them.
| Real | Estimated | Simulated |
|---|---|---|
| Scott's menu, stations, nutrition and allergen labels for Oct 24–31, 2026 | Iron, vitamin D and calcium badges, which are tagged from food names. Nutrition for the Salad Bar, Grains and Greens and Mongolian Grill, which are typical values. Sample foods for the coming-soon locations. | Demand on the Insights page, from 150 simulated students marked is_simulated |
@google/genai, for the recipe dupe onlymain deploysnpx tsx scripts/sync-sheet.ts copies it into menu_items, mapping the sheet's tags to allergens and diets.npx tsx scripts/import-recipes.ts loads the ready-made plates from data/recipes.csv.scripts/sample-locations.sql adds sample foods for the coming-soon locations.npx tsx scripts/demo.ts creates the demo personas and simulated students. Use --dry-run to check without writing.npm install
cp .env.example .env.local # then fill in the values below
npm run dev # http://localhost:3000
.env.local needs:
| Variable | Used for |
|---|---|
NEXT_PUBLIC_SUPABASE_URL, NEXT_PUBLIC_SUPABASE_ANON_KEY | the app |
SUPABASE_SERVICE_ROLE_KEY | scripts only, never browser code |
GEMINI_API_KEY | the recipe dupe (optional; without it, the rule-based matcher is used) |
MENU_SHEET_ID | scripts/sync-sheet.ts |
Run the files in supabase/migrations/ in order in the Supabase SQL Editor before the first sync.