A pretrained food allergens classifier that sorts text into one of 10 categories — what food allergens are present. Use the food allergens API immediately, no training required, then adapt it to your own data when you need more.
Drop in some text and get the prediction back. No signup, no setup.
A sample of the 17 labels this pretrained classifier chooses between.
Need a label that isn't here? Clone the classifier into your Nyckel console and edit the label set to fit your data.
Once you've added this classifier to your console, you get your own copy of it behind your own endpoint. Invoke it with any HTTP client:
curl
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer $NYCKEL_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "The text you want to classify"}'Python
import requests
# Get an access token: https://www.nyckel.com/docs/api/overview/authentication/
token = "YOUR_ACCESS_TOKEN"
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer " + token},
json={"data": "The text you want to classify"},
)
print(response.json())Example response
{
"labelName": "Celery",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 food allergens categories, served on Nyckel's own infrastructure — your text snippet stays on Nyckel.
Send raw text to the invoke endpoint; the response is a label with a confidence score.
Clone it, then correct predictions and add your own samples in the console — Nyckel retrains automatically, turning this into a custom model tuned to your data.
Restaurants and food establishments can utilize the food allergens identifier to ensure their menus are compliant with food safety regulations. By accurately labeling dishes that contain allergens, businesses can reduce the risk of allergic reactions among consumers.
Grocery stores can implement this function to classify products based on allergen content. This allows them to create dedicated sections for allergen-free products, enhancing the shopping experience for customers with food allergies.
Food delivery apps can integrate the allergens identifier to provide users with clear information about the allergen content of dishes. This ensures safer choices for customers with dietary restrictions, increasing customer satisfaction and trust.
Cooking apps can leverage the food allergens identifier to filter out recipes that contain allergens specified by the user. This feature helps users with allergies discover safe and enjoyable meal options, encouraging continued use of the app.
Food manufacturers can utilize the allergens identifier during the R&D phase to evaluate new products for allergen content. This helps in designing products that cater specifically to allergen-free markets, increasing potential sales and market reach.
Catering companies can use the food allergens identifier to tailor their offerings to client specifications, ensuring that food served at events is safe for all attendees. Providing allergen-free options can result in a competitive edge in a market that prioritizes health and safety.
Health and nutrition organizations can employ the allergens identifier in educational platforms to raise awareness about food allergens. By informing consumers about potential allergens in commonly consumed foods, these organizations can foster healthier eating habits and prevent allergic reactions.
A zero-shot classifier uses a large foundation model's general knowledge to pick between your labels — no task-specific training, so new or edited labels work immediately. A Nyckel-trained classifier has been trained on labeled examples and runs on Nyckel's own infrastructure, which typically makes it faster, cheaper per call, and more accurate on data that resembles its training set. The "Under the hood" section on this page shows which kind this classifier is, and any classifier can be adapted into a trained one by adding your own examples.
Honestly: we can't know in advance — it depends on your data stream and how closely it resembles what this classifier has seen. The reliable way to find out is to measure it on your own data: start invoking the classifier with real traffic, or upload and annotate a set of text samples in the console — make sure they look like your production data, not idealized examples. Nyckel's evaluation metrics then show you exactly how it performs on that data before you rely on it.
No classifier is perfect, so Nyckel is built around the correction loop: invokes can be captured for review, you confirm or correct predictions in the console, and corrections become training data. Over time the model adapts to your data distribution — accuracy on your traffic improves with use rather than staying fixed.
No. This food allergens classifier works out of the box — clone it into your console and you'll have your own API endpoint in under a minute. Training data only enters the picture when you want to adapt it: your corrected predictions and uploaded samples improve the model, and you can also edit the label set to match your needs.
Trying the classifier on this page is free with no signup. Cloning it requires a free account, and the free tier covers your first API calls each month — see nyckel.com/pricing for current limits and paid tiers.
Add this pretrained classifier to your Nyckel console — you'll get a live API endpoint in under a minute, and a path to a custom model when you need one.