"""Per-serving macro estimator — ingredient lookup, no extra model call needed."""
from __future__ import annotations

# (calories kcal, protein g, carbs g, fat g, fiber g) per 100 g
_MACROS: dict[str, tuple[float, float, float, float, float]] = {
    # proteins
    "chicken": (165, 31, 0, 3.6, 0),
    "beef": (250, 26, 0, 16, 0),
    "pork": (242, 27, 0, 14, 0),
    "fish": (130, 20, 0, 5, 0),
    "salmon": (208, 20, 0, 13, 0),
    "tuna": (130, 29, 0, 0.5, 0),
    "shrimp": (99, 24, 0, 0.3, 0),
    "egg": (155, 13, 1.1, 11, 0),
    "eggs": (155, 13, 1.1, 11, 0),
    "tofu": (76, 8, 1.9, 4.8, 0.3),
    # dairy
    "milk": (61, 3.2, 4.8, 3.3, 0),
    "cheese": (402, 25, 1.3, 33, 0),
    "butter": (717, 0.9, 0.1, 81, 0),
    "yogurt": (59, 3.5, 4.7, 3.3, 0),
    "cream": (340, 2.1, 2.8, 36, 0),
    # starches
    "rice": (130, 2.7, 28, 0.3, 0.4),
    "pasta": (158, 5.8, 31, 0.9, 1.8),
    "bread": (265, 9, 49, 3.2, 2.7),
    "potato": (77, 2, 17, 0.1, 2.2),
    "potatoes": (77, 2, 17, 0.1, 2.2),
    "flour": (364, 10, 76, 1, 2.7),
    "oats": (389, 17, 66, 7, 10.6),
    "quinoa": (120, 4.1, 21, 1.9, 2.8),
    "lentils": (116, 9, 20, 0.4, 7.9),
    "beans": (347, 21, 60, 1.2, 15),
    "chickpeas": (164, 8.9, 27, 2.6, 7.6),
    # vegetables
    "tomato": (18, 0.9, 3.9, 0.2, 1.2),
    "tomatoes": (18, 0.9, 3.9, 0.2, 1.2),
    "onion": (40, 1.1, 9.3, 0.1, 1.7),
    "onions": (40, 1.1, 9.3, 0.1, 1.7),
    "garlic": (149, 6.4, 33, 0.5, 2.1),
    "carrot": (41, 0.9, 10, 0.2, 2.8),
    "carrots": (41, 0.9, 10, 0.2, 2.8),
    "broccoli": (34, 2.8, 7, 0.4, 2.6),
    "spinach": (23, 2.9, 3.6, 0.4, 2.2),
    "pepper": (31, 1, 6, 0.3, 2.1),
    "peppers": (31, 1, 6, 0.3, 2.1),
    "mushroom": (22, 3.1, 3.3, 0.3, 1),
    "mushrooms": (22, 3.1, 3.3, 0.3, 1),
    "zucchini": (17, 1.2, 3.1, 0.3, 1),
    "corn": (86, 3.3, 19, 1.4, 2.7),
    "lettuce": (15, 1.4, 2.9, 0.2, 1.3),
    "cucumber": (16, 0.7, 3.6, 0.1, 0.5),
    "eggplant": (25, 1, 5.9, 0.2, 3),
    "cabbage": (25, 1.3, 5.8, 0.1, 2.5),
    "celery": (16, 0.7, 3, 0.2, 1.6),
    "leek": (61, 1.5, 14, 0.3, 1.8),
    # fruits
    "apple": (52, 0.3, 14, 0.2, 2.4),
    "banana": (89, 1.1, 23, 0.3, 2.6),
    "lemon": (29, 1.1, 9.3, 0.3, 2.8),
    "lime": (30, 0.7, 10.5, 0.2, 2.8),
    "orange": (47, 0.9, 12, 0.1, 2.4),
    # fats & condiments
    "olive oil": (884, 0, 0, 100, 0),
    "oil": (884, 0, 0, 100, 0),
    "soy sauce": (53, 8.1, 4.9, 0.1, 0.8),
    "honey": (304, 0.3, 82, 0, 0.2),
    "sugar": (387, 0, 100, 0, 0),
    "salt": (0, 0, 0, 0, 0),
    "vinegar": (18, 0, 0.9, 0, 0),
}

# Typical portion weight per ingredient (grams)
_GRAMS: dict[str, int] = {
    "egg": 50, "eggs": 100,
    "butter": 15,
    "olive oil": 14, "oil": 14,
    "soy sauce": 15,
    "salt": 3,
    "garlic": 10,
    "honey": 21,
    "sugar": 12,
    "lemon": 30, "lime": 30,
}
_DEFAULT_GRAMS = 80


def compute_nutrition(ingredients: list[str], servings: int = 2) -> dict[str, float]:
    """Return per-serving macro estimates keyed to the NutritionGrid format."""
    cal = prot = carb = fat = fib = 0.0
    for ing in ingredients:
        key = ing.lower().strip()
        row = _MACROS.get(key) or _MACROS.get(key.split()[0]) if key else None
        if row is None:
            continue
        grams = _GRAMS.get(key, _DEFAULT_GRAMS)
        f = grams / 100
        c, p, cb, ft, fb = row
        cal += c * f
        prot += p * f
        carb += cb * f
        fat += ft * f
        fib += fb * f

    sv = max(servings, 1)
    return {
        "calories": round(cal / sv),
        "protein_g": round(prot / sv, 1),
        "carbs_g": round(carb / sv, 1),
        "fat_g": round(fat / sv, 1),
        "fiber_g": round(fib / sv, 1),
    }