```json
{
  "sym_variables": [
    ("x0", "grams of carbohydrates"),
    ("x1", "grams of protein"),
    ("x2", "milligrams of potassium")
  ],
  "objective_function": "2.87 * x0 + 8.97 * x1 + 2.78 * x2",
  "constraints": [
    "3 * x0 + 7 * x1 >= 10",
    "3 * x0 + 10 * x2 >= 17",
    "3 * x0 + 7 * x1 + 10 * x2 >= 17",
    "10 * x1 - 5 * x2 >= 0",
    "1 * x0 - 9 * x1 >= 0"
  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    carbs = m.addVar(lb=0, name="carbs")
    protein = m.addVar(lb=0, name="protein")
    potassium = m.addVar(lb=0, name="potassium")


    # Set objective function
    m.setObjective(2.87 * carbs + 8.97 * protein + 2.78 * potassium, gp.GRB.MINIMIZE)

    # Add constraints
    m.addConstr(3 * carbs + 7 * protein >= 10, "c0")
    m.addConstr(3 * carbs + 10 * potassium >= 17, "c1")
    m.addConstr(3 * carbs + 7 * protein + 10 * potassium >= 17, "c2")
    m.addConstr(10 * protein - 5 * potassium >= 0, "c3")
    m.addConstr(1 * carbs - 9 * protein >= 0, "c4")


    # Optimize model
    m.optimize()

    if m.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        print('carbs:', carbs.x)
        print('protein:', protein.x)
        print('potassium:', potassium.x)
    elif m.status == gp.GRB.INFEASIBLE:
        print('The model is infeasible.')
    elif m.status == gp.GRB.UNBOUNDED:
        print('The model is unbounded.')
    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')

```