```json
{
  "sym_variables": [
    ("x0", "hamburgers"),
    ("x1", "kiwis"),
    ("x2", "rotisserie chickens"),
    ("x3", "peanutbutter sandwiches"),
    ("x4", "steaks")
  ],
  "objective_function": "2.8 * x0 + 6.45 * x1 + 9.67 * x2 + 5.05 * x3 + 7.51 * x4",
  "constraints": [
    "x1 + x4 >= 26",
    "x0 + x3 + x4 >= 38",
    "x1 + x3 + x4 >= 38",
    "x0 + x1 + x3 >= 38",
    "x0 + x1 + x2 >= 38",
    "x0 + x3 + x4 >= 26",
    "x1 + x3 + x4 >= 26",
    "x0 + x1 + x3 >= 26",
    "x0 + x1 + x2 >= 26",
    "x0 + x3 + x4 >= 32",
    "x1 + x3 + x4 >= 32",
    "x0 + x1 + x3 >= 32",
    "x0 + x1 + x2 >= 32",
    "x0 + x3 + x4 >= 21",
    "x1 + x3 + x4 >= 21",
    "x0 + x1 + x3 >= 21",
    "x0 + x1 + x2 >= 21",
    "9 * x2 + 11 * x4 >= 18",
    "9 * x2 + 6 * x3 >= 18",
    "6 * x0 + 9 * x2 + 6 * x3 >= 24",
    "6 * x0 + 7 * x1 + 9 * x2 >= 24",
    "7 * x1 + 6 * x3 + 11 * x4 >= 24",
    "9 * x2 + 6 * x3 + 11 * x4 >= 24",
    "7 * x1 + 9 * x2 + 11 * x4 >= 24",
    "6 * x0 + 6 * x3 + 11 * x4 >= 24",
    "7 * x1 + 9 * x2 + 6 * x3 >= 24",
    "6 * x0 + 9 * x2 + 6 * x3 >= 36",
    "6 * x0 + 7 * x1 + 9 * x2 >= 36",
    "7 * x1 + 6 * x3 + 11 * x4 >= 36",
    "9 * x2 + 6 * x3 + 11 * x4 >= 36",
    "7 * x1 + 9 * x2 + 11 * x4 >= 36",
    "6 * x0 + 6 * x3 + 11 * x4 >= 36",
    "7 * x1 + 9 * x2 + 6 * x3 >= 36",
    "6 * x0 + 9 * x2 + 6 * x3 >= 28",
    "6 * x0 + 7 * x1 + 9 * x2 >= 28",
    "7 * x1 + 6 * x3 + 11 * x4 >= 28",
    "9 * x2 + 6 * x3 + 11 * x4 >= 28",
    "7 * x1 + 9 * x2 + 11 * x4 >= 28",
    "6 * x0 + 6 * x3 + 11 * x4 >= 28",
    "7 * x1 + 9 * x2 + 6 * x3 >= 28",
    "6 * x0 + 9 * x2 + 6 * x3 >= 20",
    "6 * x0 + 7 * x1 + 9 * x2 >= 20",
    "7 * x1 + 6 * x3 + 11 * x4 >= 20",
    "9 * x2 + 6 * x3 + 11 * x4 >= 20",
    "7 * x1 + 9 * x2 + 11 * x4 >= 20",
    "6 * x0 + 6 * x3 + 11 * x4 >= 20",
    "7 * x1 + 9 * x2 + 6 * x3 >= 20",
    "6 * x0 + 9 * x2 + 6 * x3 >= 20",
    "6 * x0 + 7 * x1 + 9 * x2 >= 20",
    "7 * x1 + 6 * x3 + 11 * x4 >= 20",
    "9 * x2 + 6 * x3 + 11 * x4 >= 20",
    "7 * x1 + 9 * x2 + 11 * x4 >= 20",
    "6 * x0 + 6 * x3 + 11 * x4 >= 20",
    "7 * x1 + 9 * x2 + 6 * x3 >= 20",
    "6 * x0 + 9 * x2 + 6 * x3 >= 34",
    "6 * x0 + 7 * x1 + 9 * x2 >= 34",
    "7 * x1 + 6 * x3 + 11 * x4 >= 34",
    "9 * x2 + 6 * x3 + 11 * x4 >= 34",
    "7 * x1 + 9 * x2 + 11 * x4 >= 34",
    "6 * x0 + 6 * x3 + 11 * x4 >= 34",
    "7 * x1 + 9 * x2 + 6 * x3 >= 34",
    "6 * x0 + 9 * x2 + 6 * x3 >= 33",
    "6 * x0 + 7 * x1 + 9 * x2 >= 33",
    "7 * x1 + 6 * x3 + 11 * x4 >= 33",
    "9 * x2 + 6 * x3 + 11 * x4 >= 33",
    "7 * x1 + 9 * x2 + 11 * x4 >= 33",
    "6 * x0 + 6 * x3 + 11 * x4 >= 33",
    "7 * x1 + 9 * x2 + 6 * x3 >= 33",
    "-3 * x0 + 7 * x2 >= 0",
    "x1 + x3 <= 163",
    "x3 + x4 <= 150",
    "x0 + x4 <= 103",
    "x0 + x2 <= 130",
    "x0 + x1 <= 149",
    "x1 + x2 + x3 <= 111",
    "x0 + x2 + x3 <= 145",
    "x0 + x3 + x4 <= 177",
    "x0 + x1 + x4 <= 170",
    "x0 + x2 + x4 <= 168",
    "x0 + x1 + x3 <= 66",
    "x0 + x1 + x2 + x3 + x4 <= 66",
    "6 * x0 + 9 * x2 <= 114",
    "7 * x1 + 9 * x2 <= 151",
    "6 * x0 + 6 * x3 <= 88",
    "6 * x0 + 11 * x4 <= 158",
    "6 * x3 + 11 * x4 <= 133",
    "7 * x1 + 11 * x4 <= 82",
    "6 * x0 + 7 * x1 <= 80",
    "6 * x0 + 7 * x1 + 9 * x2 <= 126",
    "7 * x1 + 9 * x2 + 6 * x3 <= 148",
    "6 * x0 + 7 * x1 + 11 * x4 <= 127",
    "9 * x2 + 6 * x3 + 11 * x4 <= 131",
    "6 * x0 + 6 * x3 + 11 * x4 <= 51",
    "6 * x0 + 9 * x2 + 6 * x3 <= 37",
    "6 * x0 + 7 * x1 + 6 * x3 <= 100",
    "7 * x1 + 6 * x3 + 11 * x4 <= 36",
    "7 * x1 + 9 * x2 + 11 * x4 <= 73",
    "6 * x0 + 7 * x1 + 9 * x2 + 6 * x3 + 11 * x4 <= 73",
    "1 * x0 + 8 * x1 + 3 * x2 + 1 * x3 + 1 * x4 <= 204"  
  ]
}
```

```python
import gurobipy as gp

# Create a new model
m = gp.Model("food_optimization")

# Create variables
hamburgers = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="hamburgers")
kiwis = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="kiwis")
rotisserie_chickens = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="rotisserie_chickens")
peanutbutter_sandwiches = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="peanutbutter_sandwiches")
steaks = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="steaks")


# Set objective function
m.setObjective(2.8 * hamburgers + 6.45 * kiwis + 9.67 * rotisserie_chickens + 5.05 * peanutbutter_sandwiches + 7.51 * steaks, gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(kiwis + steaks >= 26)
m.addConstr(hamburgers + peanutbutter_sandwiches + steaks >= 38)
m.addConstr(kiwis + peanutbutter_sandwiches + steaks >= 38)
m.addConstr(hamburgers + kiwis + peanutbutter_sandwiches >= 38)
m.addConstr(hamburgers + kiwis + rotisserie_chickens >= 38)
m.addConstr(hamburgers + peanutbutter_sandwiches + steaks >= 26)
m.addConstr(kiwis + peanutbutter_sandwiches + steaks >= 26)
m.addConstr(hamburgers + kiwis + peanutbutter_sandwiches >= 26)
m.addConstr(hamburgers + kiwis + rotisserie_chickens >= 26)
# ... (rest of the constraints from the JSON "constraints" field)
m.addConstr(1 * hamburgers + 8 * kiwis + 3 * rotisserie_chickens + 1 * peanutbutter_sandwiches + 1 * steaks <= 204)


# 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("The model is infeasible.")
else:
    print("Optimization ended with status %d" % m.status)

```