Living with a roommate who has severe food allergies changes how you think about everyday meals. My college friend and roommate Rahul deals with life-threatening tree nut and lactose allergies.
Every grocery trip or cooking session was an exercise in hyper-vigilance: squinting at microscopic warning labels, wondering whether a new recipe contained almond flour, walnut oil, or dairy-derived whey, and second-guessing whether something was genuinely safe.
For the DEV × Hacktoberfest 2026 Weekend Challenge ("Build for a Friend"), I built AllergyPal — a fast, private, open-source AI meal planner and recipe scanner designed specifically to keep Rahul safe and take the anxiety out of dinner.
AllergyPal is an open-source assistive web application with open-source AI at its core.
Instead of forcing users to navigate complex health databases, AllergyPal allows Rahul (or anyone cooking for him) to simply paste a recipe, grocery list, or restaurant dish description. In milliseconds, the open AI engine:
Here is how AllergyPal looks and works in practice:
[ Active Allergen Shield: Rahul (Tree Nuts, Peanuts, Dairy/Lactose) ]
Input:
"Breakfast Smoothie: 1 cup almond milk, 1 banana, 2 tbsp peanut butter, walnuts"
AllergyPal AI Output:
⚠️ High Risk: Unsafe for Rahul!
• ALMOND MILK detected (Tree Nut category) ➡️ Substitute: Fortified Oat Milk
• PEANUT BUTTER detected (Peanut category) ➡️ Substitute: Sunflower Seed Butter (SunButter)
• WALNUTS detected (Tree Nut category) ➡️ Substitute: Toasted Chia & Pumpkin Seeds
When scanning a clean recipe (like a Mediterranean chickpea and roasted sweet potato bowl), AllergyPal gives a bright green "✅ Verified 100% Safe for Rahul" verdict, explaining exactly why no cross-contaminants were found.
AllergyPal is 100% open-source under the permissive MIT License.
At the heart of AllergyPal is an open-weights reasoning pipeline designed to categorize ingredients into allergen ontologies:
Because everything runs directly on the client, the application requires zero external API keys and has zero latency.
This challenge asked us to explain why an open approach worked better than a closed one. For AllergyPal, open-source AI wasn't just a design preference — it was a necessity:
When I showed Rahul the working scanner and generated a safe dinner plan for our apartment, his first reaction was:
"Wait, you built this just for my allergies? Being able to paste a whole recipe and see immediate substitutes without spending 15 minutes googling each ingredient is a game changer."
Knowing that something I built made my friend feel cared for and safe is the best reward of this entire hackathon.
Built with ❤️ for Rahul as part of the Hacktoberfest 2026 Weekend Challenge on DEV.