To solve the given optimization problem, we first need to clearly define the problem in mathematical terms and then translate it into Gurobi code.

### Problem Definition

**Variables:**
- \(x_0\): cornichons
- \(x_1\): strips of bacon
- \(x_2\): slices of pizza

**Objective Function:**
Maximize \(7x_0 + (1 + 1)x_1 + 1x_2 = 7x_0 + 2x_1 + x_2\)

**Constraints:**
1. \(7x_0 + 6x_1 \leq 22\)
2. \(7x_0 + x_2 \leq 22\)
3. \(7x_0 + 6x_1 + x_2 \leq 23\)
4. \(7x_0 + 6x_1 + x_2 \leq 23\) (Redundant, same as constraint 3)
5. \(x_0\) can be non-integer
6. \(x_1\) can be non-integer
7. \(x_2\) must be an integer

### Gurobi Code

```python
import gurobi

def solve_optimization_problem():
    # Create a new model
    model = gurobi.Model()

    # Define variables
    cornichons = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="cornichons")
    strips_of_bacon = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="strips_of_bacon")
    slices_of_pizza = model.addVar(lb=0, ub=gurobi.GRB.INFINITY, name="slices_of_pizza", vtype=gurobi.GRB.INTEGER)

    # Objective function: Maximize 7*cornichons + 2*strips_of_bacon + slices_of_pizza
    model.setObjective(7 * cornichons + 2 * strips_of_bacon + slices_of_pizza, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(7 * cornichons + 6 * strips_of_bacon <= 22, name="fiber_from_cornichons_and_bacon")
    model.addConstr(7 * cornichons + slices_of_pizza <= 22, name="fiber_from_cornichons_and_pizza")
    model.addConstr(7 * cornichons + 6 * strips_of_bacon + slices_of_pizza <= 23, name="fiber_from_all_sources")

    # Solve the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Cornichons: {cornichons.varValue}")
        print(f"Strips of bacon: {strips_of_bacon.varValue}")
        print(f"Slices of pizza: {slices_of_pizza.varValue}")
        print(f"Objective: {model.objVal}")
    else:
        print("No optimal solution found.")

solve_optimization_problem()
```