Swap Meal Recommendation

POST /api/ml/swap-recipe

Swap Meal Recommendation

cURL

curl --request POST \
  --url https://api.example.com/api/ml/swap-recipe

import requests

url = "https://api.example.com/api/ml/swap-recipe"

response = requests.post(url)

print(response.text)

const options = {method: 'POST'};

fetch('https://api.example.com/api/ml/swap-recipe', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/api/ml/swap-recipe",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/api/ml/swap-recipe"

	req, _ := http.NewRequest("POST", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/api/ml/swap-recipe")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/ml/swap-recipe")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)

response = http.request(request)
puts response.read_body

200

{
  "id": 123,
  "recipe_id": 123,
  "name": "<string>",
  "calories": 123,
  "protein": 123,
  "carbs": 123,
  "fat": 123,
  "image_url": "<string>",
  "recipe_url": "<string>",
  "ingredients": "<string>",
  "meal_types": [
    {
      "id": 123,
      "name": "<string>"
    }
  ],
  "diet_types": [
    {
      "id": 123,
      "name": "<string>"
    }
  ],
  "assigned_meal_type": "<string>",
  "distance": 123
}

Swap a recipe in your meal plan with a similar alternative that matches your dietary preferences and nutritional goals.

Authentication

This endpoint requires Bearer token authentication. Include your access token in the Authorization header:

Authorization: Bearer <your_access_token>

Request

Query Parameters

recipe_id · integer · required

The external recipe ID of the meal you want to swap. This is the recipe_id field from the recipe object, not the database id.

meal_label · string · required

The meal type for which you want a replacement. Must be one of:

• breakfast
• lunch
• dinner
• snack

n_search · integer · default: "550"

The number of similar recipes to search through before filtering. Higher values increase the likelihood of finding a good match but may slow down the response. Range: 1-1000

Response

Returns a recipe object that is nutritionally similar to the original but matches your dietary requirements.

id · integer

Database ID of the recommended recipe

recipe_id · integer

External recipe ID from the dataset

name · string

Name of the recipe

Example: "Mediterranean Chicken Bowl"

calories · integer

Total calories per serving

Example: 480

protein · integer

Protein content in grams

Example: 35

carbs · integer

Carbohydrate content in grams

Example: 45

fat · integer

Fat content in grams

Example: 18

image_url · string

URL to the recipe image

Example: "https://example.com/recipes/mediterranean-bowl.jpg"

recipe_url · string

URL to the full recipe details and instructions

Example: "https://example.com/recipes/mediterranean-bowl"

ingredients · string

Comma-separated list of ingredients

Example: "chicken breast, quinoa, cherry tomatoes, cucumber, feta cheese, olive oil, lemon"

meal_types · array

Array of meal type objects indicating when this recipe is suitable

Show Meal type object

id · integer

Meal type ID

name · string

Meal type name (breakfast, lunch, dinner, snack)

diet_types · array

Array of diet type objects this recipe belongs to

Show Diet type object

id · integer

Diet type ID

name · string

Diet type name (high_protein, vegan, vegetarian, low_carb, etc.)

assigned_meal_type · string

The meal label that was requested in the swap

Example: "dinner"

distance · number

Similarity score from the ML model. Lower values indicate higher similarity to the original recipe.

Example: 0.234

Example Request

cURL

curl -X POST 'https://api.smarteat.ai/api/ml/swap-recipe?recipe_id=12345&meal_label=dinner&n_search=550' \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."

Python

import requests

url = "https://api.smarteat.ai/api/ml/swap-recipe"
headers = {
    "Authorization": "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
}
params = {
    "recipe_id": 12345,
    "meal_label": "dinner",
    "n_search": 550
}

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

JavaScript

const params = new URLSearchParams({
  recipe_id: '12345',
  meal_label: 'dinner',
  n_search: '550'
});

const response = await fetch(`https://api.smarteat.ai/api/ml/swap-recipe?${params}`, {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...'
  }
});

const data = await response.json();
console.log(data);

Example Response

200 - Success

{
  "id": 847,
  "recipe_id": 67890,
  "name": "Mediterranean Chicken Bowl",
  "calories": 480,
  "protein": 35,
  "carbs": 45,
  "fat": 18,
  "image_url": "https://example.com/recipes/mediterranean-bowl.jpg",
  "recipe_url": "https://example.com/recipes/mediterranean-bowl",
  "ingredients": "chicken breast, quinoa, cherry tomatoes, cucumber, feta cheese, olive oil, lemon, red onion, kalamata olives",
  "meal_types": [
    {
      "id": 2,
      "name": "lunch"
    },
    {
      "id": 3,
      "name": "dinner"
    }
  ],
  "diet_types": [
    {
      "id": 1,
      "name": "high_protein"
    },
    {
      "id": 5,
      "name": "low_calorie"
    }
  ],
  "assigned_meal_type": "dinner",
  "distance": 0.187
}

404 - No Match Found

{
  "detail": "No similar recipe found for this meal type"
}

401 - Unauthorized

{
  "detail": "Invalid token payload"
}

How It Works

1. Load User Profile: Retrieves your dietary preferences and restrictions
2. Get Active Plan: Checks your current meal plan to avoid duplicate recipes
3. Find Similar Recipes: Uses K-Nearest Neighbors ML model to find recipes with similar nutritional profiles
4. Apply Filters:
   • Excludes recipes already in your meal plan
   • Filters by the requested meal type (breakfast, lunch, dinner, snack)
   • Ensures compatibility with your diet types (e.g., vegan, high-protein)
5. Calculate Distance: Measures similarity in scaled nutritional feature space
6. Random Selection: If multiple good matches exist, randomly selects one for variety

Notes

• The algorithm searches through up to n_search neighbors (default 550)
• Recipes already in your active meal plan are automatically excluded
• The swap respects your dietary restrictions from your profile
• Lower distance values indicate closer nutritional similarity
• If no suitable match is found, a 404 error is returned
• The ML model uses standardized scaling for fair comparison across nutritional metrics
• Diet type filtering ensures recommendations align with your preferences (e.g., vegan users only get vegan recipes)

Tips for Best Results

• Use higher n_search values (700-1000) if you have strict dietary restrictions
• Use lower n_search values (300-400) for faster responses when flexibility is acceptable
• Ensure your profile has diet types set for more accurate filtering
• The distance metric helps you understand how similar the swap is nutritionally