To convert the given natural language description into a symbolic representation and then into Gurobi code, we first need to understand the problem. The goal is to maximize an objective function that involves two variables: 'apple pies' and 'potatoes'. Each of these items contributes differently to the total amount of carbohydrates consumed and has different coefficients in the objective function.

### Symbolic Representation

Given:
- Variables: `x1` for 'apple pies', `x2` for 'potatoes'
- Objective Function: Maximize `5.57*x1 + 6.93*x2`
- Constraints:
  1. `9.23*x1 + 12.35*x2 >= 18` (At least 18 grams of carbohydrates)
  2. `8*x1 - 4*x2 >= 0` (Constraint on the combination of apple pies and potatoes)
  3. `9.23*x1 + 12.35*x2 <= 33` (No more than 33 grams of carbohydrates)
  4. `x1` must be an integer (Non-fractional number of apple pies)
  5. `x2` can be any real number (No restriction to whole numbers for potatoes)

### Symbolic Representation in JSON Format

```json
{
  'sym_variables': [('x1', 'apple pies'), ('x2', 'potatoes')],
  'objective_function': 'Maximize 5.57*x1 + 6.93*x2',
  'constraints': [
    '9.23*x1 + 12.35*x2 >= 18',
    '8*x1 - 4*x2 >= 0',
    '9.23*x1 + 12.35*x2 <= 33',
    'x1 is an integer'
  ]
}
```

### Gurobi Code

To solve this problem using Gurobi, we will write the Python code as follows:

```python
from gurobipy import *

# Create a new model
m = Model("Optimization_Problem")

# Define variables
x1 = m.addVar(vtype=GRB.INTEGER, name="apple_pies")  # Integer variable for apple pies
x2 = m.addVar(vtype=GRB.CONTINUOUS, name="potatoes")  # Continuous variable for potatoes

# Set the objective function
m.setObjective(5.57*x1 + 6.93*x2, GRB.MAXIMIZE)

# Add constraints
m.addConstr(9.23*x1 + 12.35*x2 >= 18, name="carb_min")
m.addConstr(8*x1 - 4*x2 >= 0, name="combination_constraint")
m.addConstr(9.23*x1 + 12.35*x2 <= 33, name="carb_max")

# Optimize the model
m.optimize()

# Print the solution
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Apple Pies: {x1.x}")
    print(f"Potatoes: {x2.x}")
    print(f"Objective Function Value: {m.objVal}")
else:
    print("No optimal solution found")
```