## Step 1: Define the symbolic representation of the variables
The variables are 'chicken breasts', 'oreos', 'corn cobs', and 'knishes', which can be represented symbolically as $x_1, x_2, x_3, x_4$ respectively.

## Step 2: Convert the objective function into a symbolic representation
The objective function to maximize is $7x_1 + 9x_2 + 5x_3 + 2x_4$.

## Step 3: Define the constraints in symbolic notation
The constraints given are:
- $14.86x_1 + 9.17x_2 \geq 19$
- $9.17x_2 + 16.5x_3 \geq 15$
- $14.86x_1 + 0.36x_4 \leq 30$
- $9.17x_2 + 0.36x_4 \leq 40$
- $16.5x_3 + 0.36x_4 \leq 64$
- $14.86x_1 + 9.17x_2 \leq 51$
- $14.86x_1 + 9.17x_2 + 16.5x_3 + 0.36x_4 \leq 51$

## 4: Consider the bounds and integrality constraints
- $x_1$ must be an integer
- $x_2$ must be an integer
- $x_3$ must be an integer
- $x_4$ is a continuous variable
- The upper bound for carbohydrates is 88 grams.

## 5: Formulate the problem in Gurobi
We need to maximize $7x_1 + 9x_2 + 5x_3 + 2x_4$ subject to the constraints.

## 6: Write the Gurobi code
```python
import gurobi as gp

# Define the model
m = gp.Model()

# Define the variables
x1 = m.addVar(name="chicken_breasts", vtype=gp.GRB.INTEGER)  # chicken breasts
x2 = m.addVar(name="oreos", vtype=gp.GRB.INTEGER)  # oreos
x3 = m.addVar(name="corn_cobs", vtype=gp.GRB.INTEGER)  # corn cobs
x4 = m.addVar(name="knishes", vtype=gp.GRB.CONTINUOUS)  # knishes

# Objective function
m.setObjective(7*x1 + 9*x2 + 5*x3 + 2*x4, gp.GRB.MAXIMIZE)

# Constraints
m.addConstr(14.86*x1 + 9.17*x2 >= 19)
m.addConstr(9.17*x2 + 16.5*x3 >= 15)
m.addConstr(14.86*x1 + 0.36*x4 <= 30)
m.addConstr(9.17*x2 + 0.36*x4 <= 40)
m.addConstr(16.5*x3 + 0.36*x4 <= 64)
m.addConstr(14.86*x1 + 9.17*x2 <= 51)
m.addConstr(14.86*x1 + 9.17*x2 + 16.5*x3 + 0.36*x4 <= 51)

# Carbohydrates upper bound
m.addConstr(14.86*x1 + 9.17*x2 + 16.5*x3 + 0.36*x4 <= 88)

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("Chicken breasts: ", x1.varValue)
    print("Oreos: ", x2.varValue)
    print("Corn cobs: ", x3.varValue)
    print("Knishes: ", x4.varValue)
else:
    print("The model is infeasible")
```

## 7: Symbolic Representation
```json
{
    'sym_variables': [('x1', 'chicken breasts'), ('x2', 'oreos'), ('x3', 'corn cobs'), ('x4', 'knishes')],
    'objective_function': '7*x1 + 9*x2 + 5*x3 + 2*x4',
    'constraints': [
        '14.86*x1 + 9.17*x2 >= 19',
        '9.17*x2 + 16.5*x3 >= 15',
        '14.86*x1 + 0.36*x4 <= 30',
        '9.17*x2 + 0.36*x4 <= 40',
        '16.5*x3 + 0.36*x4 <= 64',
        '14.86*x1 + 9.17*x2 <= 51',
        '14.86*x1 + 9.17*x2 + 16.5*x3 + 0.36*x4 <= 51',
        '14.86*x1 + 9.17*x2 + 16.5*x3 + 0.36*x4 <= 88'
    ]
}
```