```json
{
  "sym_variables": [
    ("x0", "grams of carbohydrates"),
    ("x1", "milligrams of magnesium"),
    ("x2", "milligrams of calcium"),
    ("x3", "milligrams of vitamin B4")
  ],
  "objective_function": "2*x0 + 3*x1 + 3*x2 + 4*x3",
  "constraints": [
    "1*x0 + 7*x1 >= 10",
    "1*x0 + 2*x3 >= 8",
    "1*x0 + 4*x2 >= 5",
    "1*x0 + 7*x1 + 4*x2 + 2*x3 >= 5",
    "1*x0 + 1*x3 >= 7",
    "1*x0 + 6*x1 >= 11",
    "4*x2 + 1*x3 >= 13",
    "6*x1 + 1*x3 >= 7",
    "6*x1 + 4*x2 + 1*x3 >= 13",
    "1*x0 + 6*x1 + 4*x2 + 1*x3 >= 13",
    "7*x0 - 4*x2 >= 0",
    "-2*x1 + 2*x2 >= 0",
    "1*x0 + 7*x1 + 2*x3 <= 46",
    "1*x0 + 4*x2 + 2*x3 <= 29",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0",
    "1*x0 + 7*x1 + 4*x2 + 2*x3 <= 56",  
    "1*x0 + 6*x1 + 4*x2 + 1*x3 <= 61"
  ]
}
```

```python
import gurobipy as gp

try:
    # Create a new model
    m = gp.Model("nutrition_optimization")

    # Create variables
    carbohydrates = m.addVar(lb=0, name="carbohydrates")
    magnesium = m.addVar(lb=0, name="magnesium")
    calcium = m.addVar(lb=0, name="calcium")
    vitamin_b4 = m.addVar(lb=0, name="vitamin_b4")

    # Set objective function
    m.setObjective(2*carbohydrates + 3*magnesium + 3*calcium + 4*vitamin_b4, gp.GRB.MINIMIZE)

    # Add constraints
    m.addConstr(carbohydrates + 7*magnesium >= 10)
    m.addConstr(carbohydrates + 2*vitamin_b4 >= 8)
    m.addConstr(carbohydrates + 4*calcium >= 5)
    m.addConstr(carbohydrates + 7*magnesium + 4*calcium + 2*vitamin_b4 >= 5)
    m.addConstr(carbohydrates + vitamin_b4 >= 7)
    m.addConstr(carbohydrates + 6*magnesium >= 11)
    m.addConstr(4*calcium + vitamin_b4 >= 13)
    m.addConstr(6*magnesium + vitamin_b4 >= 7)
    m.addConstr(6*magnesium + 4*calcium + vitamin_b4 >= 13)
    m.addConstr(carbohydrates + 6*magnesium + 4*calcium + vitamin_b4 >= 13)
    m.addConstr(7*carbohydrates - 4*calcium >= 0)
    m.addConstr(-2*magnesium + 2*calcium >= 0)
    m.addConstr(carbohydrates + 7*magnesium + 2*vitamin_b4 <= 46)
    m.addConstr(carbohydrates + 4*calcium + 2*vitamin_b4 <= 29)

    # Resource Constraints (upper bounds)
    m.addConstr(carbohydrates + 7*magnesium + 4*calcium + 2*vitamin_b4 <= 56)
    m.addConstr(carbohydrates + 6*magnesium + 4*calcium + vitamin_b4 <= 61)


    # Optimize model
    m.optimize()

    if m.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        print('carbohydrates:', carbohydrates.x)
        print('magnesium:', magnesium.x)
        print('calcium:', calcium.x)
        print('vitamin_b4:', vitamin_b4.x)
    elif m.status == gp.GRB.INFEASIBLE:
        print('The model is infeasible.')
    else:
        print('Optimization ended with status %d' % m.status)


except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ': ' + str(e))

except AttributeError:
    print('Encountered an attribute error')
```