## Step 1: Define the symbolic representation of the problem
The variables are ['chicken drumsticks', 'ravioli', 'strips of bacon'] which can be represented symbolically as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Convert the objective function into symbolic notation
The objective function to maximize is $6x_0^2 + 3x_1^2 + 5x_1 + 7x_2$.

## Step 3: Define the constraints in symbolic notation
The constraints given are:
- $20x_0 + 10x_1 + 9x_2 \geq 34$ (at least 34 grams of fat from chicken drumsticks and strips of bacon, but it seems there was an oversight in directly translating this as it should involve just $x_0$ and $x_2$ for fat: $20x_0 + 9x_2 \geq 34$)
- $19x_0^2 + 12x_1^2 \geq 25$ (at least $25 on chicken drumsticks squared and ravioli squared)
- $12x_1^2 + 12x_2^2 \geq 30$ (at least $30 on ravioli squared plus strips of bacon squared)
- $20x_0 + 9x_2 \leq 70$ (at most 70 grams of fat from chicken drumsticks and strips of bacon)
- $20x_0^2 + 10x_1^2 \leq 101$ (up to 101 grams of fat from chicken drumsticks squared plus ravioli squared)
- $20x_0 + 10x_1 + 9x_2 \leq 101$ (up to 101 grams of fat from chicken drumsticks plus ravioli plus strips of bacon)
- $19x_0 + 12x_2 \leq 95$ (no greater than $95 on chicken drumsticks and strips of bacon)
- $12x_1 + 12x_2 \leq 61$ (no greater than $61 on ravioli plus strips of bacon)
- $19x_0 + 12x_1 + 12x_2 \leq 61$ (no greater than $61 on chicken drumsticks plus ravioli plus strips of bacon)

## 4: Correct and Clarify Constraints
Correcting and clarifying:
- Fat from chicken drumsticks and ravioli and strips of bacon: $20x_0 + 10x_1 + 9x_2$
- The actual constraints should reflect:
  - Minimum fat from chicken drumsticks and strips of bacon: $20x_0 + 9x_2 \geq 34$
  - Maximum fat from chicken drumsticks and strips of bacon: $20x_0 + 9x_2 \leq 70$
  - Total fat: $20x_0 + 10x_1 + 9x_2 \leq 101$

## 5: Symbolic Representation
The symbolic representation is:
```json
{
'sym_variables': [('x0', 'chicken drumsticks'), ('x1', 'ravioli'), ('x2', 'strips of bacon')],
'objective_function': '6*x0^2 + 3*x1^2 + 5*x1 + 7*x2',
'constraints': [
    '20*x0 + 9*x2 >= 34',
    '19*x0^2 + 12*x1^2 >= 25',
    '12*x1^2 + 12*x2^2 >= 30',
    '20*x0 + 9*x2 <= 70',
    '20*x0^2 + 10*x1^2 <= 101',
    '20*x0 + 10*x1 + 9*x2 <= 101',
    '19*x0 + 12*x2 <= 95',
    '12*x1 + 12*x2 <= 61',
    '19*x0 + 12*x1 + 12*x2 <= 61'
  ]
}
```

## 6: Gurobi Code
Now, let's write the Gurobi code for this problem:
```python
import gurobi

def optimization_problem():
    model = gurobi.Model()
    
    # Define variables
    x0 = model.addVar(name="chicken_drumsticks", vtype=gurobi.GRB.INTEGER)  # integer
    x1 = model.addVar(name="ravioli")  # continuous
    x2 = model.addVar(name="strips_of_bacon", vtype=gurobi.GRB.INTEGER)  # integer
    
    # Objective function
    model.setObjective(6*x0**2 + 3*x1**2 + 5*x1 + 7*x2, gurobi.GRB.MAXIMIZE)
    
    # Constraints
    model.addConstr(20*x0 + 9*x2 >= 34, name="min_fat")
    model.addConstr(19*x0**2 + 12*x1**2 >= 25, name="min_cost_cd_ravioli")
    model.addConstr(12*x1**2 + 12*x2**2 >= 30, name="min_cost_ravioli_bacon")
    model.addConstr(20*x0 + 9*x2 <= 70, name="max_fat_cd_bacon")
    model.addConstr(20*x0**2 + 10*x1**2 <= 101, name="max_fat_cd_ravioli")
    model.addConstr(20*x0 + 10*x1 + 9*x2 <= 101, name="max_total_fat")
    model.addConstr(19*x0 + 12*x2 <= 95, name="max_cost_cd_bacon")
    model.addConstr(12*x1 + 12*x2 <= 61, name="max_cost_ravioli_bacon")
    model.addConstr(19*x0 + 12*x1 + 12*x2 <= 61, name="max_total_cost")
    
    # Optimize
    model.optimize()
    
    # Print solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("Chicken drumsticks: ", x0.varValue)
        print("Ravioli: ", x1.varValue)
        print("Strips of bacon: ", x2.varValue)
    else:
        print("No optimal solution found")

optimization_problem()
```