Mealy 🍽️

Smart Meal Optimization for Balanced Nutrition

Mealy is an intelligent meal planning API that uses advanced mathematical optimization to create perfectly balanced meals based on your calorie and macronutrient goals.

What It Does

Mealy solves a complex nutritional puzzle: given a list of available foods, it calculates the exact portions needed to hit your target calories, macronutrients (carbs, protein, fat), and micronutrients—all while ensuring realistic, practical serving sizes.

How It Works

1. Select Your Foods: Choose from a diverse database of whole foods including proteins (chicken, salmon, tofu), carbs (rice, oats, quinoa), healthy fats (avocado, olive oil, almonds), and vegetables
2. Set Your Goals: Specify your target calories and macro percentages (or use smart defaults)
3. Get Optimized Meals: Receive precise portion sizes that balance all your nutritional targets simultaneously

The optimization engine uses weighted least squares with intelligent constraints to find the ideal combination of foods that:

• Hits your calorie target accurately
• Balances macronutrients according to your percentages (e.g., 40% carbs, 30% protein, 30% fat)
• Includes adequate vegetables for micronutrients
• Provides realistic portions (10g–400g per ingredient)
• Considers 13+ essential micronutrients for longevity

Key Benefits

🎯 Precision Nutrition

• Achieve macro targets within 1-2% accuracy
• No more guessing or manual calculations
• Mathematical optimization ensures the best possible balance

🥗 Prevents Extreme Results

• Smart bounds prevent unrealistic portions (no more 878g of carrots!)
• Normalized weighting ensures fair balancing across all nutrients
• Minimum 10g per ingredient prevents trace amounts
• Maximum 400g per ingredient keeps portions realistic

🧮 Science-Based Algorithm

• Uses normalized weights (w/t²) to equalize percentage errors
• Treats a 1% error in fat the same as a 1% error in carbs
• Considers both macronutrients and micronutrients simultaneously
• Decoupled vegetable constraint prevents circular dependencies

🔧 Flexible & Customizable

• Set custom calorie targets (default: 700 kcal per meal)
• Adjust macro percentages to your diet (e.g., 50/25/25 for low-fat)
• Choose from diverse food options including plant-based proteins
• Works with any combination of available foods

⚡ Fast & Reliable

• RESTful API built with FastAPI
• Instant optimization results
• CORS-enabled for easy frontend integration
• Consistent, reproducible results

Technical Highlights

Optimization Approach

The app uses scipy's least squares solver (lsq_linear) with:

• Matrix A: Nutritional content per 100g for each food
• Vector b: Your target nutrient values
• Weight normalization: weight / (target²) for fair percentage-based penalties
• Bounds: 10–400g per ingredient for practical portions

Nutrient Tracking

Each meal is optimized across 17+ nutritional parameters:

• Macros: Calories, carbs, protein, fat, fiber
• Minerals: Magnesium, potassium, selenium, zinc
• Vitamins: D, K2, folate, B12, C, E
• Other: Omega-3 EPA/DHA, choline

Food Database

Curated whole-food database with per-100g nutrition data sourced from USDA:

• Proteins: Chicken, salmon, eggs, beef, tofu
• Carbs: White rice, sweet potato, oats, quinoa
• Fats: Avocado, almonds, olive oil
• Vegetables: Broccoli, spinach, carrots, kale, bell peppers, cauliflower, tomato
• Fruits: Banana, blueberries

API Usage

Endpoint: POST /optimize_meal_prep

Request Body:

{
  "foods": ["chicken", "white_rice", "broccoli", "avocado"],
  "kcalories": 700,
  "carbs_percent": 40,
  "protein_percent": 30,
  "fat_percent": 30
}

Response:

{
  "portions": {
    "chicken": 120.5,
    "white_rice": 85.3,
    "broccoli": 150.0,
    "avocado": 45.2
  },
  "totals": {
    "kcalories": 698.4,
    "carbs_g": 69.8,
    "protein_g": 52.3,
    "fat_g": 23.1,
    "fiber_g": 12.4,
    ...
  }
}

Endpoint: POST /recommend_ingredients

Get food recommendations based on your current selection to improve nutritional balance.

Running Mealy

Local Development

# Install dependencies
pip install -r requirements.txt

# Run the server
./run.sh

The API will be available at http://localhost:8001

Requirements

• Python 3.11+
• FastAPI
• NumPy
• SciPy
• Scikit-learn
• Pydantic

Use Cases

• Meal Prep Planning: Calculate exact portions for weekly meal prep
• Macro Tracking: Hit specific macro targets for fitness goals
• Dietary Balance: Ensure adequate micronutrient intake
• Recipe Development: Create nutritionally optimized meal combinations
• Nutrition Education: Understand how foods combine to meet nutritional needs

Future Enhancements

• Additional food database entries
• Meal planning for multiple meals per day
• Cost optimization alongside nutrition
• Allergen and dietary restriction filtering
• Meal variety scoring to prevent monotony

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Built with ❤️ for optimal nutrition

Mealy - Because balanced nutrition shouldn't require a PhD in mathematics