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"),
]