Introduction

January AI’s Enterprise API gives you direct access to metabolic health and food intelligence tools, built for seamless B2B integration. Use our RESTful APIs to integrate advanced metabolic health insights and lifestyle intelligence directly into your platform. Our proprietary food database, enhanced with AI/ML, covers 54 million+ verified items across branded foods, groceries, and restaurant menus.
Integrate the most accurate food logging, glucose prediction, and food analysis tools available into your platform.

With January’s APIs, developers can:

🔍 Search millions of food items by name, barcode, or natural language (e.g., “milkshake with banana”).
📸 Scan foods using our market-leading AI vision model for nutrient detection, with industry-best accuracy.
🍽️ Find menu items from local and national restaurants by name and location.
📝 Log food: Create, retrieve, and manage user entries with precision.
🧬 Predict glucose: Enable users to see how food will impact their blood sugar before they eat it, based on their demographics, health condition, and activity—no CGM or sensors required.
🔄 Recommend food swaps: Suggest healthier, semantically-similar foods based on user preferences, health goals, and restrictions.

Authentication

import requests
import json

# Replace YOUR_API_KEY with your actual API key
api_key = 'YOUR_API_KEY'
headers = {
    'Authorization': f'Bearer {api_key}',
    'Content-Type': 'application/json'
}

# With shell, you can just pass the correct header with each request
curl "https://partners.january.ai/v1.1/endpoint" \
  -H "Authorization: Bearer YOUR_API_KEY"

const axios = require('axios');

// Replace YOUR_API_KEY with your actual API key
const apiKey = 'YOUR_API_KEY';
const headers = {
  'Authorization': `Bearer ${apiKey}`,
  'Content-Type': 'application/json'
};

The January AI API uses bearer tokens for authentication. To obtain an API key, please send an email with your request.

The API key must be included in all API requests to the server in a header that looks like the following:

Authorization: Bearer YOUR_API_KEY

You must replace YOUR_API_KEY with your personal API key.

Lifestyle Intelligence APIs

Search, analyze, and interpret food data using these Lifestyle Intelligence APIs.

Food Search (By Name or Barcode)

import requests

url = 'https://partners.january.ai/v1.1/search/foods'
params = {
    'query': 'banana',
    'category': 'branded'
}
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'your-user-id'
}

response = requests.get(url, params=params, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/search/foods?query=banana&category=branded' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: your-user-id'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/search/foods',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'your-user-id'
  },
  params: {
    query: 'banana',
    category: 'branded'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "totalCount": 40,
  "items": [
    {
      "id": 84222716,
      "name": "banana",
      "protein": 2,
      "energy": 160,
      "brand_name": "One",
      "carbs": 15,
      "fat": 10,
      "fat_total_saturated": 5,
      "net_carbs": 13,
      "sodium": 20,
      "sugars": 13,
      "added_sugars": 11,
      "gi": 34.899727,
      "gl": 5.234959,
      "fiber": 2,
      "potassium": 170,
      "cholesterol": 2.5,
      "photo_url": null,
      "servings": [
        {
          "id": 67943292,
          "scaling_factor": 1,
          "quantity": 5,
          "unit": "pieces",
          "weight_grams": 28,
          "is_primary": true
        }
      ]
    }
  ]
}

Search for food items by name or barcode from January’s verified database of 54+ million foods, including branded, grocery, and restaurant items.

HTTP Request

GET https://partners.january.ai/v1.1/search/foods

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
x-partner-user-id	No	Unique user ID from your system

Query Parameters

Parameter	Required	Description
query	Optional	The search term for food items
category	Optional	The category of food items to filter results ('branded' or 'general')
upc	Optional	The UPC representing the barcode of a food item

- Either query or upc must be provided.
- category defaults to 'general'

Response Structure

The response includes:

totalCount: Total number of matching food items
items: Array of food objects, each containing properties such as id, name, brand_name, nutrients, and servings (with detailed nutrients and servings information)

NLP Food Search

import requests

url = 'https://partners.january.ai/v1.1/search/foods/nlp'
params = {
    'query': '1 banana, 1 bowl of oatmeal, glass of orange juice'
}
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'your-user-id'
}

response = requests.get(url, params=params, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/search/foods/nlp?query=1%20banana%2C%201%20bowl%20of%20oatmeal%2C%20glass%20of%20orange%20juice' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: your-user-id'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/search/foods/nlp',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'your-user-id'
  },
  params: {
    query: '1 banana, 1 bowl of oatmeal, glass of orange juice'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "totalNutrients": {
    "calories": {
      "value": 435,
      "unit": "kcal"
    },
    "carbs": {
      "value": 92,
      "unit": "g"
    },
    "protein": {
      "value": 8.5,
      "unit": "g"
    }
  },
  "detections": [
    {
      "food": {
        "name": "Banana",
        "id": 123456,
        "brandName": null,
        "nutrients": {
          "calories": {
            "value": 105,
            "unit": "kcal"
          }
        },
        "servings": [
          {
            "id": 78901,
            "quantity": 1,
            "unit": "medium banana"
          }
        ]
      }
    }
  ]
}

Search for multiple foods at once by describing them in plain English — via voice or text.

HTTP Request

GET https://partners.january.ai/v1.1/search/foods/nlp

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
x-partner-user-id	No	Unique user ID from your system

Query Parameters

Parameter	Required	Description
query	Yes	The search term for food items in natural language

Response Structure

The response includes:

totalNutrients: Summary of total nutritional content
detections: Array of detected food items with detailed information

Restaurant Search

import requests

url = 'https://partners.january.ai/v1.1/search/restaurants'
params = {
    'query': 'mcdonalds',
    'lat': 37.549,
    'lon': -121.989
}
headers = {
    'Authorization': 'Bearer YOUR_API_KEY'
}

response = requests.get(url, params=params, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/search/restaurants?query=mcdonalds&lat=37.549&lon=-121.989' \
--header 'Authorization: Bearer YOUR_API_KEY'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/search/restaurants',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY'
  },
  params: {
    query: 'mcdonalds',
    lat: 37.549,
    lon: -121.989
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "items": [
    {
      "type": "restaurant",
      "id": "53fc3b8a-e6bf-404d-83c8-9f42124d1bee",
      "name": "McDonald's",
      "is_chain": false,
      "distance": 8,
      "city": "San Francisco",
      "address1": "123 Main Street",
      "address2": "Suite 100"
    }
  ]
}

This endpoint allows you to search for restaurants (local and/or chain) by name.

HTTP Request

GET https://partners.january.ai/v1.1/search/restaurants

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication

Query Parameters

Parameter	Required	Description
query	Yes	The search term related to the restaurant. Leave empty to return all nearest restaurants.
lat	Optional	Latitude coordinate for proximity search
lon	Optional	Longitude coordinate for proximity search
distance	Optional	Distance in meters to search for restaurants. Default is 16093 meters (~10 miles)
limit	Optional	Maximum number of results to return. Default is 50

Response Structure

The response includes:

items: Array of restaurant locations with id, name, chain status, distance, and address information

import requests

url = 'https://partners.january.ai/v1.1/search/restaurants/menu'
params = {
    'query': 'burger',
    'lat': 37.549,
    'lon': -121.989
}
headers = {
    'Authorization': 'Bearer YOUR_API_KEY'
}

response = requests.get(url, params=params, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/search/restaurants/menu?query=burger&lat=37.549&lon=-121.989' \
--header 'Authorization: Bearer YOUR_API_KEY'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/search/restaurants/menu',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY'
  },
  params: {
    query: 'burger',
    lat: 37.549,
    lon: -121.989
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "items": [
    {
      "type": "menu_item",
      "id": "228990954",
      "name": "burger",
      "restaurant_name": "morning due cafe",
      "is_chain": false,
      "data_source_id": 12,
      "source_original_id": "ngxZD7tEA1cQGCuOYBF05Ckft2ZP3z3Ja88wVaXYqqr7P7F3QiGFN1BSCl6H0Bt_5iN7y",
      "protein": 48,
      "energy": 800,
      "carbs": 40,
      "net_carbs": 38,
      "sugars": 6,
      "added_sugars": null,
      "fat": 45,
      "gi": 48.507698,
      "gl": 36.67089,
      "fiber": 2,
      "photo_url": "https://cdn-img.ai/23361362e6a706567",
      "servings": [
        {
          "id": 189343592,
          "scaling_factor": 1,
          "quantity": 1,
          "unit": "serving",
          "weight_grams": null,
          "is_primary": true
        }
      ],
      "distance": 124
    }
  ]
}

This endpoint allows you to search for restaurants (local and/or chain) by name.

HTTP Request

GET https://partners.january.ai/v1.1/search/restaurants/menu

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication

Query Parameters

Parameter	Required	Description
query	Yes	The search term related to the menu (food name or restaurant name)
lat	Yes	Latitude coordinate for proximity search
lon	Yes	Longitude coordinate for proximity search
distance	Optional	Distance in meters to search for restaurant menus. Default is 16093 meters (~10 miles)
limit	Optional	Maximum number of results to return. Default is 50

Response Structure

The response includes:

items: Array of menu items with id, name, restaurant name, photo URL, nutrients and primary serving information

Photo Scan

import requests
import json

url = 'https://partners.january.ai/v1.1/vision/foods'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}
data = {
    "photoUrl": "https://i.imgur.com/bTQIGxf.png"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/vision/foods' \
--header 'Content-Type: application/json' \
--header 'x-partner-user-id: your-user-id' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
  "photoUrl": "https://i.imgur.com/bTQIGxf.png"
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/vision/foods',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  },
  data: {
    photoUrl: 'https://i.imgur.com/bTQIGxf.png'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "mealName": "Breakfast Bowl",
  "totalNutrients": {
    "calories": {
      "value": 520,
      "unit": "kcal"
    },
    "carbs": {
      "value": 68,
      "unit": "g"
    },
    "protein": {
      "value": 15,
      "unit": "g"
    }
  },
  "detections": [
    {
      "confidenceScore": "high",
      "food": {
        "name": "Oatmeal",
        "id": 789012,
        "brandName": null,
        "nutrients": {
          "calories": {
            "value": 300,
            "unit": "kcal"
          }
        },
        "servings": [
          {
            "id": 45678,
            "quantity": 1,
            "unit": "cup"
          }
        ]
      }
    }
  ]
}

Scan a photo of a meal to identify and retrieve nutritional data for the foods detected.

HTTP Request

POST https://partners.january.ai/v1.1/vision/foods

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Unique user ID from your system

Request Body

Parameter	Required	Description
photoUrl	No	The URL of the image to be analyzed
photoBase64	No	Base64 encoded image data (if not using photoUrl)

- Either photoUrl or photoBase64 must be provided.

Photo Requirements

Must be at least 512x512 pixels in JPG or JPEG format
Maximum resolution: 1024x1024 pixels
Maximum file size: 4 MB
Must not include location or personal metadata
Must not be blurry or dark

Response Structure

The response includes:

mealName: Name of the meal identified in the image
totalNutrients: Summary of total nutritional content
detections: Array of detected food items with confidence scores

Edit Photo Scan Results

import requests
import json

url = 'https://partners.january.ai/v1.1/vision/fix-ai'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}
data = {
  "mealName": "Breakfast Bowl",
  "detections": [
    {
      "confidenceScore": "high",
      "food": {
        "name": "Oatmeal",
        "id": 789012,
        "brandName": null,
        "nutrients": {
          "calories": {
            "value": 300,
            "unit": "kcal"
          }
        },
        "servings": [
          {
            "id": 45678,
            "quantity": 1,
            "unit": "cup"
          }
        ]
      }
    }
  ],
  "userInput": "change oatmeal to steel-cut oats"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/vision/fix-ai' \
--header 'Content-Type: application/json' \
--header 'x-partner-user-id: your-user-id' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
  "mealName": "Breakfast Bowl",
  "detections": [
    {
      "confidenceScore": "high",
      "food": {
        "name": "Oatmeal",
        "id": 789012,
        "brandName": null,
        "nutrients": {
          "calories": {
            "value": 300,
            "unit": "kcal"
          }
        },
        "servings": [
          {
            "id": 45678,
            "quantity": 1,
            "unit": "cup"
          }
        ]
      }
    }
  ],
  "userInput": "change oatmeal to steel-cut oats"
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/vision/fix-ai',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  },
  data: {
    "mealName": "Breakfast Bowl",
    "detections": [
      {
        "confidenceScore": "high",
        "food": {
          "name": "Oatmeal",
          "id": 789012,
          "brandName": null,
          "nutrients": {
            "calories": {
              "value": 300,
              "unit": "kcal"
            }
          },
          "servings": [
            {
              "id": 45678,
              "quantity": 1,
              "unit": "cup"
            }
          ]
        }
      }
    ],
    "userInput": "change oatmeal to steel-cut oats"
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "mealName": "Breakfast Bowl",
  "totalNutrients": {
    "calories": {
      "value": 520,
      "unit": "kcal"
    },
    "carbs": {
      "value": 68,
      "unit": "g"
    },
    "protein": {
      "value": 15,
      "unit": "g"
    }
  },
  "detections": [
    {
      "confidenceScore": "high",
      "food": {
        "name": "Oatmeal",
        "id": 789012,
        "brandName": null,
        "nutrients": {
          "calories": {
            "value": 300,
            "unit": "kcal"
          }
        },
        "servings": [
          {
            "id": 45678,
            "quantity": 1,
            "unit": "cup"
          }
        ]
      }
    }
  ]
}

This API lets users update food types and quantities from a photo scan using natural language, either by voice or text. For example, after scanning a photo of a Mexican chicken and rice bowl and noticing a couple of inaccuracies, a user might say:

"It was actually 1 cup of chicken. It was also white rice, not brown rice."

The API parses this input and updates the scan results accordingly.

HTTP Request

POST https://partners.january.ai/v1.1/vision/fix-ai

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Unique user ID from your system

Request Body

Parameter	Required	Description
mealName	Yes	Name of the meal to edit
detections	Yes	Array of detected food items to edit
userInput	Yes	Text representation of changes to make

Response Structure

The response includes:

mealName: Modified name of the meal
totalNutrients: Summary of total nutritional content
detections: Array of modified food items with confidence scores

Healthy Alternatives

import requests
import json

url = 'https://partners.january.ai/v1.1/food-alternatives/5467772'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}
data = {
    "dietRestrictions": ["Gluten"],
    "dietPreferences": ["Vegan"]
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/food-alternatives/5467772' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
  "dietRestrictions": ["Gluten"],
  "dietPreferences": ["Vegan"]
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/food-alternatives/5467772',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  data: {
    dietRestrictions: ["Gluten"],
    dietPreferences: ["Vegan"]
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "alternatives": [
    {
      "food": {
        "name": "Gluten-Free Oat Bread",
        "id": 9876543,
        "brandName": "Nature's Path",
        "nutrients": {
          "calories": {
            "value": 80,
            "unit": "kcal"
          },
          "carbs": {
            "value": 15,
            "unit": "g"
          }
        },
        "servings": [
          {
            "id": 12345,
            "quantity": 1,
            "unit": "slice"
          }
        ]
      }
    }
  ]
}

Get healthier alternatives for individual foods based on nutrition, context, and user preferences.

HTTP Request

POST https://partners.january.ai/v1.1/food-alternatives/{foodId}

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`

URL Parameters

Parameter	Description
foodId	The unique identifier of the food item to find alternatives for

Request Body

Parameter	Required	Description
dietRestrictions	Yes	Array of dietary restrictions/allergies
dietPreferences	Yes	Array of dietary preferences

Dietary Restrictions

Valid dietary restrictions include:

Gluten
Lactose
Yeast
Tree nuts
Peanuts
Dairy
Eggs
Sulfites
Soy
Wheat
Shellfish
Fish
Mushrooms
Sesame
MSG
Caffeine
FODMAPs

Dietary Preferences

Valid dietary preferences include:

Vegetarian
Vegan
Keto
Paleo
Pescatarian
Low carbohydrate
High protein
Kosher

Response Structure

The response includes:

alternatives: Array of alternative food items with name, id, brandName, nutrients, and servings information

Food Logging APIs

Create, retrieve, and manage food logs with these Food Logging APIs.

Create Food Logs

import requests
import json

url = 'https://partners.january.ai/v1.1/logs/foods'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}
data = {
    "foods": [
        {
            "id": 101963552,
            "serving": {
                "id": 68051535,
                "quantity": 1.4
            }
        }
    ],
    "timestampUtc": "2024-09-13T11:34:56Z"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/logs/foods' \
--header 'Content-Type: application/json' \
--header 'x-partner-user-id: your-user-id' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
  "foods": [
    {
      "id": 101963552,
      "serving": {
        "id": 68051535,
        "quantity": 1.4
      }
    }
  ],
  "timestampUtc": "2024-09-13T11:34:56Z"
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/logs/foods',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  },
  data: {
    foods: [
      {
        id: 101963552,
        serving: {
          id: 68051535,
          quantity: 1.4
        }
      }
    ],
    timestampUtc: "2024-09-13T11:34:56Z"
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

Associate logged foods with a specific user.

HTTP Request

POST https://partners.january.ai/v1.1/logs/foods

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Unique user ID from your system

Request Body

Parameter	Required	Description
foods	Yes	Array of food items to be logged
foods[].id	Yes	Unique identifier of the food item
foods[].serving	Yes	Serving details of the food item
foods[].serving.id	Yes	Serving size identifier
foods[].serving.quantity	Yes	Amount of the serving consumed
timestampUtc	Yes	UTC timestamp when food was consumed (YYYY-MM-DDTHH:MM:SSZ)
name	Optional	Name of the meal

Retrieve Food Logs

import requests

url = 'https://partners.january.ai/v1.1/logs/foods'
params = {
    'start': '2023-09-12',
    'end': '2024-09-15'
}
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'your-user-id'
}

response = requests.get(url, params=params, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/logs/foods?start=2023-09-12&end=2024-09-15' \
--header 'x-partner-user-id: your-user-id' \
--header 'Authorization: Bearer YOUR_API_KEY'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/logs/foods',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'your-user-id'
  },
  params: {
    start: '2023-09-12',
    end: '2024-09-15'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

Retrieve food logs for a specific user over a defined date range.

HTTP Request

GET https://partners.january.ai/v1.1/logs/foods

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
x-partner-user-id	Yes	Unique user ID from your system

Query Parameters

Parameter	Required	Description
start	Yes	Start date (YYYY-MM-DD format)
end	Yes	End date (YYYY-MM-DD format)

Delete Food Log

import requests

url = 'https://partners.january.ai/v1.1/logs/foods/78129823-8ba2-4183-b13b-71f0e963c606'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'user123'
}

response = requests.delete(url, headers=headers)
print(response.status_code)

curl --location --request DELETE 'https://partners.january.ai/v1.1/logs/foods/78129823-8ba2-4183-b13b-71f0e963c606' \
--header 'x-partner-user-id: user123' \
--header 'Authorization: Bearer YOUR_API_KEY'

const axios = require('axios');

const config = {
  method: 'delete',
  url: 'https://partners.january.ai/v1.1/logs/foods/78129823-8ba2-4183-b13b-71f0e963c606',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'x-partner-user-id': 'user123'
  }
};

axios(config)
  .then(response => {
    console.log(response.status);
  })
  .catch(error => {
    console.log(error);
  });

Delete food logs associated with a specific user.

HTTP Request

DELETE https://partners.january.ai/v1.1/logs/foods/{logId}

URL Parameters

Parameter	Description
logId	The unique identifier of the food log to delete

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
x-partner-user-id	Yes	Unique user ID from your system

Glucose Insights APIs

Predict post-meal glucose responses with these Glucose Insights APIs.

Glucose Prediction

import requests
import json

url = 'https://partners.january.ai/v1.1/cgm/glucose-predict'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-timezone': 'America/Los_Angeles'
}
data = {
    "userProfile": {
        "age": 25,
        "gender": "male",
        "height": 65,
        "weight": 165,
        "activityLevel": "very_active",
        "healthConditions": ["Type 2 diabetes"]
    },
    "startTime": "2025-04-09T19:06:12Z",
    "foods": [
        {
            "id": 70380652,
            "serving": {
                "id": 34176931,
                "quantity": 1
            }
        }
    ],
    "cgmData": [
        # Optional CGM data array
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "value": 92
        },
        {
            "timestamp": "2025-04-03T14:59:40Z",
            "value": 95
        }
    ],
    "consumedFoods": [
        # Optional historical user foods
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "id": 70380652,
            "serving": {
                "id": 34176931,
                "quantity": 1
            }
        }
    ]
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/cgm/glucose-predict' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-timezone: America/Los_Angeles' \
--data '{
  "userProfile": {
    "age": 25,
    "gender": "male",
    "height": 65,
    "weight": 165,
    "activityLevel": "very_active",
    "healthConditions": ["Type 2 diabetes"]
  },
  "startTime": "2025-04-09T19:06:12Z",
  "foods": [
    {
      "id": 70380652,
      "serving": {
        "id": 34176931,
        "quantity": 1
      }
    }
  ],
  "cgmData": [
    {
      "timestamp": "2025-04-03T14:56:03Z",
      "value": 92
    },
    {
      "timestamp": "2025-04-03T14:59:40Z",
      "value": 95
    }
  ],
  "consumedFoods": [
    {
      "timestamp": "2025-04-03T14:56:03Z",
      "id": 70380652,
      "serving": {
          "id": 34176931,
          "quantity": 1
      }
    }
  ]
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/cgm/glucose-predict',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-timezone': 'America/Los_Angeles'
  },
  data: {
    userProfile: {
      age: 25,
      gender: "male",
      height: 65,
      weight: 165,
      activityLevel: "very_active",
      healthConditions: ["Type 2 diabetes"]
    },
    startTime: "2025-04-09T19:06:12Z",
    foods: [
      {
        id: 70380652,
        serving: {
          id: 34176931,
          quantity: 1
        }
      }
    ],
    cgmData: [
        // Optional CGM data array
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "value": 92
        }
    ],
    consumedFoods: [
        // Optional historical user foods
        {
            timestamp: "2025-04-03T14:56:03Z",
            id: 70380652,
            serving: {
                id: 34176931,
                quantity: 1
            }
        }
    ]
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "cgp": [
    [0, 95],
    [15, 110],
    [30, 140],
    [45, 155],
    [60, 145],
    [75, 125],
    [90, 110],
    [105, 100],
    [120, 95],
    [135, 92]
  ],
  "scoring": "medium_impact",
  "cgp_min": 70,
  "cgp_max": 140
}

This endpoint returns two-hour glucose predictions for a user based on individual food or meal lookups.

You can optionally provide cgmData and consumedFoods to enable hyper-personalized glucose predictions. To complete training, the data must include at least five “complete” training days.

A training day is considered complete if it meets both of the following criteria: - At least 12 hours of CGM data - At least 2 logged meals at different times of the day

HTTP Request

POST https://partners.january.ai/v1.1/cgm/glucose-predict

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-timezone	Yes	User local timezone (e.g. `America/New_York` or `US/Pacific`)

Request Body

Parameter	Required	Description
userProfile	Yes	User's profile data
userProfile.age	Yes	User's age
userProfile.gender	Yes	User's gender ('male' or 'female')
userProfile.height	Yes	User's height in inches
userProfile.weight	Yes	User's weight in pounds
userProfile.activityLevel	Yes	Activity level ('sedentary', 'lightly_active', 'moderately_active', 'very_active')
userProfile.healthConditions	Yes	Array of health conditions
foods	Yes	Array of foods and servings for prediction
foods[].id	Yes	Unique identifier of the food item
foods[].serving	Yes	Serving details
foods[].serving.id	Yes	Serving size identifier
foods[].serving.quantity	Yes	Amount of serving consumed
startTime	Yes	ISO 8601 timestamp for when foods are consumed
cgmData	No	CGM data array for AI training. Please provide at least one data point per 15 minutes. If `cgmData` is provided, `consumedFoods` must be provided also.
cgmData[].timestamp	Yes	ISO 8601 timestamp for the CGM data point
cgmData[].value	Yes	Blood sugar level (in mg/dL)
consumedFoods	No	Array of historical user foods and servings for AI training.
consumedFoods[].timestamp	Yes	ISO 8601 timestamp for when the food is consumed
consumedFoods[].id	Yes	Unique identifier of the food item
consumedFoods[].serving	Yes	Serving details
consumedFoods[].serving.id	Yes	Serving size identifier
consumedFoods[].serving.quantity	Yes	Amount of serving consumed

Health Conditions

Valid health conditions include:

Type 1 diabetes
Type 2 diabetes
Prediabetes
Gestational diabetes (prior pregnancy)
Latent autoimmune diabetes in adults (LADA)
Cystic-fibrosis related diabetes
Diabetes, but not sure which type
None of the above
Other

Response Structure

The response includes:

cgp: Array of data points representing glucose response curve [minute, glucose_value]
scoring: Qualitative impact scoring ('low_impact', 'medium_impact', 'high_impact')
cgp_min: User's minimum glucose level (in mg/dL), based on the input user profile.
cgp_max: User's maximum glucose level (in mg/dL), based on the input user profile.

AI-Trained Glucose Prediction

import requests
import json

url = 'https://partners.january.ai/v1.1/cgm/user-glucose-predict'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'YOUR_PARTNER_USER_ID',
    'x-partner-timezone': 'America/Los_Angeles'
}
data = {
    "startTime": "2025-04-09T19:06:12Z",
    "foods": [
        {
            "id": 70380652,
            "serving": {
                "id": 34176931,
                "quantity": 1
            }
        }
    ]
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/cgm/user-glucose-predict' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: YOUR_PARTNER_USER_ID' \
--header 'x-partner-timezone: America/Los_Angeles' \
--data '{
  "startTime": "2025-04-09T19:06:12Z",
  "foods": [
    {
      "id": 70380652,
      "serving": {
        "id": 34176931,
        "quantity": 1
      }
    }
  ]
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/cgm/user-glucose-predict',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'YOUR_PARTNER_USER_ID',
    'x-partner-timezone': 'America/Los_Angeles'
  },
  data: {
    startTime: "2025-04-09T19:06:12Z",
    foods: [
      {
        id: 70380652,
        serving: {
          id: 34176931,
          quantity: 1
        }
      }
    ]
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
  "cgp": [
    [0, 95],
    [15, 110],
    [30, 140],
    [45, 155],
    [60, 145],
    [75, 125],
    [90, 110],
    [105, 100],
    [120, 95],
    [135, 92]
  ],
  "scoring": "medium_impact",
  "cgp_min": 70,
  "cgp_max": 140
}

Returns a two-hour glucose prediction using a personalized AI model trained on a specific user's CGM and meal history.

To use this endpoint, pass the user’s ID in the x-partner-user-id header. The user must already exist and have completed AI training (see User Management APIs).

Accepts either the foods or nutrients parameter as input. Unlike the standard glucose prediction endpoint, this version does not require passing CGM data in the request — improving performance by using previously stored training data.

HTTP Request

POST https://partners.january.ai/v1.1/cgm/user-glucose-predict

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Partner User ID (UUID format)
x-partner-timezone	Yes	User local timezone (e.g. `America/New_York` or `US/Pacific`)

Request Body

Parameter	Required	Description
startTime	No	ISO 8601 timestamp for when foods are consumed (default is current time)
foods	No	Array of foods and servings for prediction. If not specified, then `nutrients` parameter is applied.
foods[].id	Yes	Unique identifier of the food item
foods[].serving	Yes	Serving details
foods[].serving.id	Yes	Serving size identifier
foods[].serving.quantity	Yes	Amount of serving consumed
nutrients	No	Object with nutrients quantities (applied only when `foods` parameter is not specified)
nutrients.water	No	Quantity of water (g)
nutrients.energy	No	Quantity of energy (calories)
nutrients.protein	No	Quantity of protein (g)
nutrients.fat_total_lipid	No	Quantity of total fat (g)
nutrients.carbohydrate	No	Quantity of carbohydrates (g)
nutrients.fiber	No	Quantity of fiber (g)
nutrients.sugars	No	Quantity of sugars (g)
nutrients.calcium	No	Quantity of calcium (g)
nutrients.iron	No	Quantity of iron (g)
nutrients.potassium	No	Quantity of potassium (g)
nutrients.sodium	No	Quantity of sodium (mg)
nutrients.vit_c	No	Quantity of vit C (g)
nutrients.vit_a_iu	No	Quantity of vit A iu (g)
nutrients.fat_total_saturated	No	Quantity of saturated fat (g)
nutrients.fat_total_monounsaturated	No	Quantity of monounsaturated fat (g)
nutrients.fat_total_polyunsaturated	No	Quantity of polyunsaturated fat (g)
nutrients.fat_total_trans	No	Quantity of trans fat (g)
nutrients.cholesterol	No	Quantity of cholesterol (g)
nutrients.caffeine	No	Quantity of caffeine (g)

Response Structure

The response includes:

cgp: Array of data points representing glucose response curve [minute, glucose_value]
scoring: Qualitative impact scoring ('low_impact', 'medium_impact', 'high_impact')
cgp_min: User's minimum glucose level (in mg/dL), based on the input user profile.
cgp_max: User's maximum glucose level (in mg/dL), based on the input user profile.

User Management APIs

Create, update, and delete users, and check whether they meet the criteria for AI training to enable personalized glucose predictions.

Create User

import requests
import json

url = 'https://partners.january.ai/v1.1/user'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}
data = {
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/user' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--data '{
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/user',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  data: {
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
    "user_id": "a88888ef-cc9c-5882-ba2c-9cbee8a4b73c",
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}

Creates a user and returns the user ID. Requires a user profile in the request.

HTTP Request

POST https://partners.january.ai/v1.1/user

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`

Request Body

Parameter	Required	Description
profile	Yes	User profile object
profile.age	Yes	User's age
profile.gender	Yes	User's gender ('male' or 'female')
profile.height	Yes	User's height in inches
profile.weight	Yes	User's weight in pounds
profile.activityLevel	No	Activity level ('sedentary', 'lightly_active', 'moderately_active', 'very_active')
profile.healthConditions	No	Array of health conditions

Health Conditions

Valid health conditions include:

Type 1 diabetes
Type 2 diabetes
Prediabetes
Gestational diabetes (prior pregnancy)
Latent autoimmune diabetes in adults (LADA)
Cystic-fibrosis related diabetes
Diabetes, but not sure which type
None of the above
Other

Response Structure

The response includes:

user_id: Created user ID
profile: User profile object

Get User Profile

import requests
import json

url = 'https://partners.january.ai/v1.1/user'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}

response = requests.get(url, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/user' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: your-user-id'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/user',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
    "user_id": "a88888ef-cc9c-5882-ba2c-9cbee8a4b73c",
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}

Returns the partner user's ID and profile. Returns a 404 Not Found error if the specified user ID does not exist.

HTTP Request

GET https://partners.january.ai/v1.1/user

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Your user ID

Response Structure

The response includes:

user_id: Partner user ID
profile: User profile object

Update User Profile

import requests
import json

url = 'https://partners.january.ai/v1.1/user'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}
data = {
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}

response = requests.patch(url, headers=headers, json=data)
print(response.json())

curl --location --request PATCH 'https://partners.january.ai/v1.1/user' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: your-user-id'
--data '{
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}'

const axios = require('axios');

const config = {
  method: 'patch',
  url: 'https://partners.january.ai/v1.1/user',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  },
  data: {
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
    "user_id": "a88888ef-cc9c-5882-ba2c-9cbee8a4b73c",
    "profile": {
        "age": 20,
        "gender": "male",
        "weight": 80,
        "height": 36,
        "activity_level": "sedentary",
        "medical_conditions": []
    }
}

Updates the user's profile and returns their user information. Requires a user profile in the request body.

HTTP Request

PATCH https://partners.january.ai/v1.1/user

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Your user ID

Request Body

Parameter	Required	Description
profile	Yes	User profile object
profile.age	Yes	User's age
profile.gender	Yes	User's gender ('male' or 'female')
profile.height	Yes	User's height in inches
profile.weight	Yes	User's weight in pounds
profile.activityLevel	No	Activity level ('sedentary', 'lightly_active', 'moderately_active', 'very_active')
profile.healthConditions	No	Array of health conditions

Health Conditions

Valid health conditions include:

Type 1 diabetes
Type 2 diabetes
Prediabetes
Gestational diabetes (prior pregnancy)
Latent autoimmune diabetes in adults (LADA)
Cystic-fibrosis related diabetes
Diabetes, but not sure which type
None of the above
Other

Response Structure

The response includes:

user_id: Partner user ID
profile: User profile object

Delete User

import requests
import json

url = 'https://partners.january.ai/v1.1/user'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}

response = requests.delete(url, headers=headers)
print(response.json())

curl --location --request DELETE 'https://partners.january.ai/v1.1/user' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: your-user-id'

const axios = require('axios');

const config = {
  method: 'delete',
  url: 'https://partners.january.ai/v1.1/user',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

Deletes the user. If the specified user ID does not exist, the request still returns a success status.

HTTP Request

DELETE https://partners.january.ai/v1.1/user

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Your user ID to delete

Get All Users

import requests
import json

url = 'https://partners.january.ai/v1.1/users'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}

response = requests.get(url, headers=headers)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/users' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY'

const axios = require('axios');

const config = {
  method: 'get',
  url: 'https://partners.january.ai/v1.1/users',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

[
  {
    "user_id": "a88888ef-cc9c-5882-ba2c-9cbee8a4b73c",
    "profile": {
      "age": 20,
      "gender": "male",
      "weight": 80,
      "height": 36,
      "activity_level": "sedentary",
      "medical_conditions": []
    }
  },
  ....
]

This endpoint returns all partner user IDs and profiles.

HTTP Request

GET https://partners.january.ai/v1.1/users

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`

Response Structure

The response includes array of:

user_id: Partner user ID
profile: User profile object

Mark User as AI-Trained

import requests
import json

url = 'https://partners.january.ai/v1.1/user/training'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
}
data = {
    "cgm_data": [
        # CGM data array
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "value": 92
        },
        {
            "timestamp": "2025-04-03T14:59:40Z",
            "value": 95
        }
    ],
    "consumed_foods": [
        # Historical user foods
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "id": 70380652,
            "serving": {
                "id": 34176931,
                "quantity": 1
            }
        }
    ]
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl --location 'https://partners.january.ai/v1.1/user/training' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'x-partner-user-id: your-user-id' \
--data '{
    "cgm_data": [
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "value": 92
        },
        {
            "timestamp": "2025-04-03T14:59:40Z",
            "value": 95
        }
    ],
    "consumed_foods": [
        {
            "timestamp": "2025-04-03T14:56:03Z",
            "id": 70380652,
            "serving": {
                "id": 34176931,
                "quantity": 1
            }
        }
    ]
}'

const axios = require('axios');

const config = {
  method: 'post',
  url: 'https://partners.january.ai/v1.1/user/training',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
    'x-partner-user-id': 'your-user-id'
  },
  data: {
    "cgm_data": [
      // CGM data array
      {
        "timestamp": "2025-04-03T14:56:03Z",
        "value": 92
      },
      {
        "timestamp": "2025-04-03T14:59:40Z",
        "value": 95
      }
    ],
    "consumed_foods": [
      // Historical user foods
      {
        "timestamp": "2025-04-03T14:56:03Z",
        "id": 70380652,
        "serving": {
          "id": 34176931,
          "quantity": 1
        }
      }
    ]
  }
};

axios(config)
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.log(error);
  });

{
    "good_days": [
        "2025-09-01",
        "2025-09-02",
        "2025-09-03",
        "2025-09-04",
        "2025-09-05"
    ]
}

Sets user AI training data for personalized glucose predictions.

Requires cgm_data and consumed_foods parameters with sufficient data to complete training. Training is considered complete if the input includes five or more valid training days.

A valid training day must include:

At least 12 hours of CGM data
At least 2 logged meals at different times of the day

If the data does not meet these requirements, the endpoint returns a 400 Bad Request error.

HTTP Request

POST https://partners.january.ai/v1.1/user/training

Headers

Header	Required	Description
Authorization	Yes	Bearer token for authentication
Content-Type	Yes	Must be `application/json`
x-partner-user-id	Yes	Your user ID

Request Body

Parameter	Required	Description
cgm_data	Yes	CGM data array for AI training. Please provide at least one data point per 15 minutes.
cgm_data[].timestamp	Yes	ISO 8601 timestamp for the CGM data point
cgm_data[].value	Yes	Blood sugar level (in mg/dL)
consumed_foods	Yes	Array of historical user foods and servings for AI training.
consumed_foods[].timestamp	Yes	ISO 8601 timestamp for when the food is consumed
consumed_foods[].id	Yes	Unique identifier of the food item
consumed_foods[].serving	Yes	Serving details
consumed_foods[].serving.id	Yes	Serving size identifier
consumed_foods[].serving.quantity	Yes	Amount of serving consumed

Response Structure

The response includes:

good_days: Array of good days (ISO 8601 date format)

Errors

The January AI API uses the following error codes:

Error Code	Meaning
400	Bad Request -- Your request is invalid or malformed.
401	Unauthorized -- Your API key is invalid or missing.
403	Forbidden -- You don't have permission to access this resource.
404	Not Found -- The specified resource could not be found.
405	Method Not Allowed -- You tried to access a resource with an invalid HTTP method.
406	Not Acceptable -- You requested a format that isn't supported.
422	Unprocessable Entity -- The request was well-formed but contains semantic errors.
429	Too Many Requests -- You're making too many requests! Please slow down.
500	Internal Server Error -- We had a problem with our server. Try again later.
503	Service Unavailable -- We're temporarily offline for maintenance. Please try again later.

Error Response Format

{
  "error": {
    "code": 400,
    "message": "Bad Request",
    "details": "The 'query' parameter is required for this endpoint."
  }
}

All error responses follow a consistent format with an error object containing:

code: HTTP status code
message: Human-readable error message
details: Additional information about the error (when available)

Common Error Scenarios

Authentication Errors

401 Unauthorized: Missing or invalid API key
403 Forbidden: Valid API key but insufficient permissions

Request Errors

400 Bad Request: Missing required parameters or invalid parameter values
422 Unprocessable Entity: Valid request format but business logic errors
429 Too Many Requests: Rate limiting exceeded

Server Errors

500 Internal Server Error: Unexpected server-side error
503 Service Unavailable: Temporary service outage

Introduction

Authentication

Lifestyle Intelligence APIs

Food Search (By Name or Barcode)

HTTP Request

Headers

Query Parameters

Response Structure

NLP Food Search

HTTP Request

Headers

Query Parameters

Response Structure

Restaurant Search

HTTP Request

Headers

Query Parameters

Response Structure

Menu within a Restaurant Search

HTTP Request

Headers

Query Parameters

Response Structure

Photo Scan

HTTP Request

Headers

Request Body

Photo Requirements

Response Structure

Edit Photo Scan Results

HTTP Request

Headers

Request Body

Response Structure

Healthy Alternatives

HTTP Request

Headers

URL Parameters

Request Body

Dietary Restrictions

Dietary Preferences

Response Structure

Food Logging APIs

Create Food Logs

HTTP Request

Headers

Request Body

Retrieve Food Logs

HTTP Request

Headers

Query Parameters

Delete Food Log

HTTP Request

URL Parameters

Headers

Glucose Insights APIs

Glucose Prediction

HTTP Request

Headers

Request Body

Health Conditions

Response Structure

AI-Trained Glucose Prediction

HTTP Request

Headers

Request Body

Response Structure

User Management APIs

Create User

HTTP Request

Headers

Request Body

Health Conditions

Response Structure

Get User Profile

HTTP Request

Headers

Response Structure

Update User Profile

HTTP Request