```json
{
  "sym_variables": [
    ("x0", "milligrams of vitamin B6"),
    ("x1", "milligrams of vitamin B12")
  ],
  "objective_function": "9.01 * x0 + 5.56 * x1",
  "constraints": [
    "22 * x0 + 14 * x1 >= 51",
    "10 * x0 + -10 * x1 >= 0",
    "22 * x0 + 14 * x1 <= 85"
  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    x0 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x0") # milligrams of vitamin B6
    x1 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x1") # milligrams of vitamin B12


    # Set objective function
    m.setObjective(9.01 * x0 + 5.56 * x1, gp.GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(22 * x0 + 14 * x1 >= 51, "c0")
    m.addConstr(10 * x0 - 10 * x1 >= 0, "c1")
    m.addConstr(22 * x0 + 14 * x1 <= 85, "c2")


    # Optimize model
    m.optimize()

    # Print results
    if m.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        for v in m.getVars():
            print('%s %g' % (v.varName, v.x))
    elif m.status == gp.GRB.INFEASIBLE:
        print('Optimization problem 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')

```
