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healthy-fit/backend/scripts/nutrition_data.py
Carlos Escalante 184c8330a7 Add AI-powered nutrition and plan modules 
Introduces DSPy-based nutrition and plan generation modules, including image analysis for nutritional info and personalized diet/exercise plans. Adds new API endpoints for health metrics/goals, nutrition image analysis, and plan management. Updates models, schemas, and backend structure to support these features, and includes initial training data and configuration for prompt optimization.
2026-01-18 17:14:56 -06:00

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import dspy
from app.ai.nutrition import NutritionalInfo
# A diverse set of 50 validated examples covering:
# - Home cooked meals
# - Restaurant items
# - Snacks
# - Complex dishes with hidden calories
train_examples = [
# --- Breakfast ---
dspy.Example(
description="Oatmeal with almonds, blueberries, and honey",
nutritional_info=NutritionalInfo(
reasoning="1 cup cooked oats (150 cal). 1 oz almonds (160 cal). "
"1/2 cup blueberries (40 cal). 1 tbsp honey (60 cal). Total ~410 cal.",
name="Oatmeal Bowl",
calories=410,
protein=10,
carbs=65,
fats=16,
),
).with_inputs("description"),
dspy.Example(
description="Two eggs over easy with two slices of bacon and buttered toast",
nutritional_info=NutritionalInfo(
reasoning="2 eggs (140 cal) cooked in fat (+20 cal). 2 slices bacon (90 cal). "
"1 slice huge toast (100 cal) + 1 tsp butter (35 cal). Total ~385 cal.",
name="Eggs & Bacon Breakfast",
calories=385,
protein=20,
carbs=15,
fats=26,
),
).with_inputs("description"),
dspy.Example(
description="Greek yogurt parfait with granola and strawberries",
nutritional_info=NutritionalInfo(
reasoning="1 cup non-fat greek yogurt (130 cal). 1/2 cup granola (200 cal). "
"1 cup sliced strawberries (50 cal). Total ~380 cal.",
name="Yogurt Parfait",
calories=380,
protein=24,
carbs=55,
fats=8,
),
).with_inputs("description"),
dspy.Example(
description="Avocado toast with a poached egg",
nutritional_info=NutritionalInfo(
reasoning="1 slice artisan bread (110 cal). 1/2 avocado (120 cal). "
"1 poached egg (70 cal). Drizzle of oil/seasoning (20 cal). Total ~320 cal.",
name="Avocado Toast",
calories=320,
protein=10,
carbs=20,
fats=22,
),
).with_inputs("description"),
dspy.Example(
description="Spinach and feta omelette containing 3 eggs",
nutritional_info=NutritionalInfo(
reasoning="3 eggs (210 cal). 1 tsp oil/butter (40 cal). "
"1 cup spinach (10 cal). 1 oz feta (75 cal). Total ~335 cal.",
name="Spinach Feta Omelette",
calories=335,
protein=22,
carbs=4,
fats=25,
),
).with_inputs("description"),
# --- Lunch ---
dspy.Example(
description="Grilled chicken breast sandwich with mayo, lettuce, tomato",
nutritional_info=NutritionalInfo(
reasoning="Bun (180 cal). Chicken breast 4oz (160 cal). "
"1 tbsp mayo (90 cal). Veggies (10 cal). Total ~440 cal.",
name="Grilled Chicken Sandwich",
calories=440,
protein=30,
carbs=35,
fats=18,
),
).with_inputs("description"),
dspy.Example(
description="Caesar salad with grilled chicken",
nutritional_info=NutritionalInfo(
reasoning="Romaine lettuce (20 cal). 4oz chicken (160 cal). 2 tbsp dressing (170 cal). "
"Croutons (100 cal). Parmesan (60 cal). Total ~510 cal.",
name="Chicken Caesar Salad",
calories=510,
protein=35,
carbs=15,
fats=35,
),
).with_inputs("description"),
dspy.Example(
description="Turkey club sandwich with bacon and cheese",
nutritional_info=NutritionalInfo(
reasoning="3 slices bread (240 cal). Turkey (60 cal). Bacon (90 cal). "
"Cheese (110 cal). Mayo (90 cal). Lettuce / Tomato. Total ~590 cal.",
name="Turkey Club",
calories=590,
protein=30,
carbs=45,
fats=32,
),
).with_inputs("description"),
dspy.Example(
description="Quinoa bowl with black beans, corn, and avocado",
nutritional_info=NutritionalInfo(
reasoning="1 cup cooked quinoa (220 cal). 1/2 cup black beans (110 cal). "
"1/2 cup corn (70 cal). 1/4 avocado (60 cal). Lime dressing (50 cal). Total ~510 cal.",
name="Veggie Quinoa Bowl",
calories=510,
protein=18,
carbs=85,
fats=12,
),
).with_inputs("description"),
dspy.Example(
description="Tuna salad sushi roll (6 pieces) and miso soup",
nutritional_info=NutritionalInfo(
reasoning="Sushi roll (rice, tuna, mayo) ~300 cal. Miso soup ~40 cal. Total ~340 cal.",
name="Sushi Lunch",
calories=340,
protein=15,
carbs=45,
fats=8,
),
).with_inputs("description"),
# --- Dinner (Complex) ---
dspy.Example(
description="Spaghetti bolognaise with parmesan cheese",
nutritional_info=NutritionalInfo(
reasoning="2 cups pasta cooked (400 cal). 1 cup meat sauce/beef (300 cal). "
"1 tbsp oil in cooking (120 cal). 2 tbsp parmesan (40 cal). Total ~860 cal.",
name="Spaghetti Bolognese",
calories=860,
protein=35,
carbs=100,
fats=35,
),
).with_inputs("description"),
dspy.Example(
description="Grilled salmon with asparagus and roasted potatoes",
nutritional_info=NutritionalInfo(
reasoning="6oz Salmon fillet (350 cal). Oil for cooking (60 cal). "
"Asparagus (30 cal) + oil (30 cal). 1 cup roasted potatoes (150 cal) + oil (60 cal). Total ~680 cal.",
name="Salmon Dinner",
calories=680,
protein=40,
carbs=25,
fats=45,
),
).with_inputs("description"),
dspy.Example(
description="Beef stir fry with rice",
nutritional_info=NutritionalInfo(
reasoning="1 cup rice (200 cal). 4oz Beef strips (250 cal). "
"Oil for frying 2 tbsp (240 cal). Veggies (50 cal). Sauce (50 cal). Total ~790 cal.",
name="Beef Stir Fry",
calories=790,
protein=30,
carbs=50,
fats=50,
),
).with_inputs("description"),
dspy.Example(
description="Cheeseburger with fries",
nutritional_info=NutritionalInfo(
reasoning="Bun (200 cal). 4oz Patty 80/20 (280 cal). Cheese (100 cal). "
"Condiments (50 cal). Small fries (300 cal). Total ~930 cal.",
name="Burger and Fries",
calories=930,
protein=35,
carbs=90,
fats=45,
),
).with_inputs("description"),
dspy.Example(
description="Chicken Tikka Masala with Naan and Rice",
nutritional_info=NutritionalInfo(
reasoning="Curry with cream/butter/chicken (600 cal). "
"1 cup Rice (200 cal). 1 piece Naan (250 cal). Total ~1050 cal.",
name="Chicken Tikka Meal",
calories=1050,
protein=45,
carbs=120,
fats=45,
),
).with_inputs("description"),
dspy.Example(
description="2 slices of pepperoni pizza",
nutritional_info=NutritionalInfo(
reasoning="2 slices (300 cal each). Total ~600 cal. High fat/carbs.",
name="2 Pizza Slices",
calories=600,
protein=24,
carbs=70,
fats=26,
),
).with_inputs("description"),
dspy.Example(
description="Tacos - 3 beef tacos with cheese and sour cream",
nutritional_info=NutritionalInfo(
reasoning="3 corn tortillas (150 cal). Ground beef filling (250 cal - cooked with fat). "
"Cheese (110 cal). Sour cream (60 cal). Total ~570 cal.",
name="Beef Tacos",
calories=570,
protein=25,
carbs=45,
fats=30,
),
).with_inputs("description"),
dspy.Example(
description="Ribeye steak (10oz) with mashed potatoes",
nutritional_info=NutritionalInfo(
reasoning="10oz Ribeye (fatty cut) ~750 cal. "
"Mashed potatoes with butter/cream (1 cup) ~300 cal. Total ~1050 cal.",
name="Ribeye Steak Dinner",
calories=1050,
protein=60,
carbs=35,
fats=75,
),
).with_inputs("description"),
# --- Snacks/Others ---
dspy.Example(
description="Medium Banana",
nutritional_info=NutritionalInfo(
reasoning="Standard fruit size.", name="Banana", calories=105, protein=1.3, carbs=27, fats=0.3
),
).with_inputs("description"),
dspy.Example(
description="Protein Shake (Whey)",
nutritional_info=NutritionalInfo(
reasoning="1 scoop whey (120 cal). Water (0 cal).",
name="Whey Protein Shake",
calories=120,
protein=24,
carbs=3,
fats=1,
),
).with_inputs("description"),
dspy.Example(
description="Apple with peanut butter",
nutritional_info=NutritionalInfo(
reasoning="1 apple (95 cal). 2 tbsp peanut butter (190 cal). Total ~285 cal.",
name="Apple & PB",
calories=285,
protein=8,
carbs=30,
fats=16,
),
).with_inputs("description"),
dspy.Example(
description="Bag of potato chips (small)",
nutritional_info=NutritionalInfo(
reasoning="Standard vending machine size (1.5 oz/42g). Fried.",
name="Potato Chips",
calories=220,
protein=3,
carbs=22,
fats=14,
),
).with_inputs("description"),
dspy.Example(
description="Hummus and carrot sticks",
nutritional_info=NutritionalInfo(
reasoning="1/4 cup hummus (150 cal). 2 carrots (50 cal). Total ~200 cal.",
name="Hummus Snack",
calories=200,
protein=5,
carbs=25,
fats=9,
),
).with_inputs("description"),
dspy.Example(
description="Chocolate chip cookie (Subway style)",
nutritional_info=NutritionalInfo(
reasoning="1 large cookie, heavy on sugar/butter.",
name="Large Cookie",
calories=220,
protein=2,
carbs=30,
fats=10,
),
).with_inputs("description"),
dspy.Example(
description="Blueberry Muffin (Bakery size)",
nutritional_info=NutritionalInfo(
reasoning="Large bakery muffin is notoriously high cal. Flour, sugar, oil.",
name="Bakery Muffin",
calories=450,
protein=6,
carbs=65,
fats=18,
),
).with_inputs("description"),
# --- Add 25 more diverse items to reach 50 ---
dspy.Example(
description="Hard boiled egg",
nutritional_info=NutritionalInfo(
reasoning="One large egg.", name="Egg", calories=78, protein=6, carbs=0.6, fats=5
),
).with_inputs("description"),
dspy.Example(
description="Slice of cheddar cheese",
nutritional_info=NutritionalInfo(
reasoning="1 oz slice.", name="Cheddar", calories=110, protein=7, carbs=0.4, fats=9
),
).with_inputs("description"),
dspy.Example(
description="Glass of whole milk (8oz)",
nutritional_info=NutritionalInfo(
reasoning="Full fat dairy.", name="Whole Milk", calories=150, protein=8, carbs=12, fats=8
),
).with_inputs("description"),
dspy.Example(
description="Coca Cola (12oz can)",
nutritional_info=NutritionalInfo(
reasoning="High sugar soda.", name="Coke", calories=140, protein=0, carbs=39, fats=0
),
).with_inputs("description"),
dspy.Example(
description="Orange Juice (8oz)",
nutritional_info=NutritionalInfo(
reasoning="Natural sugars.", name="OJ", calories=110, protein=2, carbs=26, fats=0
),
).with_inputs("description"),
dspy.Example(
description="Kind Bar (Dark Chocolate Nuts)",
nutritional_info=NutritionalInfo(
reasoning="Nut based bar.", name="Nut Bar", calories=200, protein=6, carbs=16, fats=13
),
).with_inputs("description"),
dspy.Example(
description="Bowl of Beef Chili (1 cup)",
nutritional_info=NutritionalInfo(
reasoning="Ground beef, beans, tomato base.", name="Chili", calories=300, protein=20, carbs=25, fats=15
),
).with_inputs("description"),
dspy.Example(
description="Pork Chop (baked) with green beans",
nutritional_info=NutritionalInfo(
reasoning="6oz pork chop (250 cal). Steam beans (30 cal). Total ~280.",
name="Pork Chop Meal",
calories=280,
protein=35,
carbs=10,
fats=12,
),
).with_inputs("description"),
dspy.Example(
description="Clam Chowder Bowl",
nutritional_info=NutritionalInfo(
reasoning="Cream based soup (heavy cream). 1.5 cups.",
name="Clam Chowder",
calories=450,
protein=12,
carbs=40,
fats=28,
),
).with_inputs("description"),
dspy.Example(
description="Philly Cheesesteak",
nutritional_info=NutritionalInfo(
reasoning="Roll (250 cal). Fatty steak (400 cal). Cheese whiz/provolone (150 cal). Oil (100 cal).",
name="Cheesesteak",
calories=900,
protein=40,
carbs=50,
fats=55,
),
).with_inputs("description"),
dspy.Example(
description="Fish and Chips (3 pieces)",
nutritional_info=NutritionalInfo(
reasoning="Deep fried batter fits + fried chips. Very high oil absorption.",
name="Fish and Chips",
calories=950,
protein=30,
carbs=90,
fats=55,
),
).with_inputs("description"),
dspy.Example(
description="Cobb Salad with ranch",
nutritional_info=NutritionalInfo(
reasoning="Greens, bacon, egg, avocado, blue cheese, ranch dressing. Salad is low cal, toppings are high.",
name="Cobb Salad",
calories=750,
protein=35,
carbs=15,
fats=60,
),
).with_inputs("description"),
dspy.Example(
description="Hot Dog with bun, mustard, ketchup",
nutritional_info=NutritionalInfo(
reasoning="Processed meat link (150 cal). Bun (120 cal). Condiments (20 cal).",
name="Hot Dog",
calories=290,
protein=10,
carbs=25,
fats=16,
),
).with_inputs("description"),
dspy.Example(
description="Pad Thai with Shrimp",
nutritional_info=NutritionalInfo(
reasoning="Rice noodles stir fried in oil and sugar based sauce. Peanuts.",
name="Pad Thai",
calories=800,
protein=25,
carbs=110,
fats=30,
),
).with_inputs("description"),
dspy.Example(
description="Burrito (Chipotle style - Chicken, Rice, Beans, Cheese, Guac)",
nutritional_info=NutritionalInfo(
reasoning="Tortilla (300). Rice (200). Beans (150). Chicken (180). Cheese (100). Guac (230!).",
name="Burrito",
calories=1160,
protein=55,
carbs=110,
fats=55,
),
).with_inputs("description"),
dspy.Example(
description="Smoothie (Berry, Banana, Yogurt)",
nutritional_info=NutritionalInfo(
reasoning="Healthy but sugar dense fruits + yogurt.",
name="Fruit Smoothie",
calories=300,
protein=8,
carbs=60,
fats=2,
),
).with_inputs("description"),
dspy.Example(
description="Falafel Wrap",
nutritional_info=NutritionalInfo(
reasoning="Fried chickpea balls (250), pita (150), tahini sauce (100).",
name="Falafel Wrap",
calories=550,
protein=15,
carbs=70,
fats=25,
),
).with_inputs("description"),
dspy.Example(
description="Macaroni and Cheese (1 cup homemade)",
nutritional_info=NutritionalInfo(
reasoning="Pasta + Roux + Milk + lots of Cheese.",
name="Mac & Cheese",
calories=500,
protein=18,
carbs=45,
fats=28,
),
).with_inputs("description"),
dspy.Example(
description="Ice Cream (2 scoops vanilla)",
nutritional_info=NutritionalInfo(
reasoning="Sugar and Cream.", name="Ice Cream", calories=350, protein=6, carbs=40, fats=20
),
).with_inputs("description"),
dspy.Example(
description="Cottage Cheese (1 cup)",
nutritional_info=NutritionalInfo(
reasoning="Low fat high protein dairy.", name="Cottage Cheese", calories=180, protein=25, carbs=10, fats=5
),
).with_inputs("description"),
dspy.Example(
description="Beef Jerky (1 bag / 3oz)",
nutritional_info=NutritionalInfo(
reasoning="Dried meat, lean protein.", name="Beef Jerky", calories=240, protein=35, carbs=15, fats=4
),
).with_inputs("description"),
dspy.Example(
description="Edamame (1 cup in pod)",
nutritional_info=NutritionalInfo(
reasoning="Soybeans.", name="Edamame", calories=190, protein=17, carbs=15, fats=8
),
).with_inputs("description"),
dspy.Example(
description="Popcorn (movie theater small, buttered)",
nutritional_info=NutritionalInfo(
reasoning="Corn + oil popping + butter topping.",
name="Movie Popcorn",
calories=600,
protein=6,
carbs=60,
fats=40,
),
).with_inputs("description"),
dspy.Example(
description="Veggie Pizza Slice",
nutritional_info=NutritionalInfo(
reasoning="Cheese + Dough + Veggies.", name="Veggie Pizza", calories=260, protein=10, carbs=32, fats=10
),
).with_inputs("description"),
dspy.Example(
description="Salmon Nigiri (2 pcs)",
nutritional_info=NutritionalInfo(
reasoning="Rice ball + Slice of raw fish.", name="Salmon Nigiri", calories=120, protein=10, carbs=15, fats=3
),
).with_inputs("description"),
]
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