```json
{
  "sym_variables": [
    ("x0", "steaks"),
    ("x1", "milkshakes"),
    ("x2", "black beans"),
    ("x3", "chicken thighs")
  ],
  "objective_function": "2.74 * x0 + 5.05 * x1 + 4.98 * x2 + 6.54 * x3",
  "constraints": [
    "5 * x0 + 4 * x1 >= 24",
    "5 * x0 + 2 * x3 >= 11",
    "1 * x2 + 9 * x3 >= 14",
    "3 * x1 + 9 * x3 >= 16",
    "4 * x0 + 9 * x3 >= 15",
    "3 * x1 + 1 * x2 >= 12",
    "4 * x0 + 3 * x1 + 1 * x2 >= 16",
    "4 * x0 + 3 * x1 + 9 * x3 >= 16",
    "3 * x1 + 1 * x2 + 9 * x3 >= 16",
    "4 * x0 + 3 * x1 + 1 * x2 >= 10",
    "4 * x0 + 3 * x1 + 9 * x3 >= 10",
    "3 * x1 + 1 * x2 + 9 * x3 >= 10",
    "4 * x0 + 3 * x1 + 1 * x2 >= 10",
    "4 * x0 + 3 * x1 + 9 * x3 >= 10",
    "3 * x1 + 1 * x2 + 9 * x3 >= 10",
    "5 * x0 + 5 * x2 <= 69",
    "4 * x1 + 5 * x2 <= 66",
    "5 * x0 + 2 * x3 <= 64",
    "5 * x0 + 4 * x1 <= 87",
    "5 * x0 + 4 * x1 + 2 * x3 <= 34",
    "5 * x0 + 4 * x1 + 5 * x2 <= 68",
    "5 * x0 + 5 * x2 + 2 * x3 <= 58",
    "5 * x0 + 4 * x1 + 5 * x2 + 2 * x3 <= 58",
    "3 * x1 + 9 * x3 <= 67",
    "4 * x0 + 9 * x3 <= 20",
    "4 * x0 + 3 * x1 <= 62",
    "3 * x1 + 1 * x2 <= 70",
    "4 * x0 + 3 * x1 + 1 * x2 + 9 * x3 <= 70",
    "5 * x0 + 4 * x1 + 5 * x2 + 2 * x3 <= 114",  // Iron upper bound
    "4 * x0 + 3 * x1 + 1 * x2 + 9 * x3 <= 71" // Carbohydrates upper bound

  ]
}
```

```python
import gurobipy as gp

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

# Create variables
steaks = m.addVar(vtype=gp.GRB.INTEGER, name="steaks")
milkshakes = m.addVar(vtype=gp.GRB.INTEGER, name="milkshakes")
black_beans = m.addVar(vtype=gp.GRB.INTEGER, name="black_beans")
chicken_thighs = m.addVar(vtype=gp.GRB.INTEGER, name="chicken_thighs")

# Set objective function
m.setObjective(2.74 * steaks + 5.05 * milkshakes + 4.98 * black_beans + 6.54 * chicken_thighs, gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(5 * steaks + 4 * milkshakes >= 24)
m.addConstr(5 * steaks + 2 * chicken_thighs >= 11)
m.addConstr(black_beans + 9 * chicken_thighs >= 14)
m.addConstr(3 * milkshakes + 9 * chicken_thighs >= 16)
m.addConstr(4 * steaks + 9 * chicken_thighs >= 15)
m.addConstr(3 * milkshakes + black_beans >= 12)
m.addConstr(4 * steaks + 3 * milkshakes + black_beans >= 16)
m.addConstr(4 * steaks + 3 * milkshakes + 9 * chicken_thighs >= 16)
m.addConstr(3 * milkshakes + black_beans + 9 * chicken_thighs >= 16)
m.addConstr(4 * steaks + 3 * milkshakes + black_beans >= 10)
m.addConstr(4 * steaks + 3 * milkshakes + 9 * chicken_thighs >= 10)
m.addConstr(3 * milkshakes + black_beans + 9 * chicken_thighs >= 10)
m.addConstr(4 * steaks + 3 * milkshakes + black_beans >= 10)
m.addConstr(4 * steaks + 3 * milkshakes + 9 * chicken_thighs >= 10)
m.addConstr(3 * milkshakes + black_beans + 9 * chicken_thighs >= 10)


m.addConstr(5 * steaks + 5 * black_beans <= 69)
m.addConstr(4 * milkshakes + 5 * black_beans <= 66)
m.addConstr(5 * steaks + 2 * chicken_thighs <= 64)
m.addConstr(5 * steaks + 4 * milkshakes <= 87)
m.addConstr(5 * steaks + 4 * milkshakes + 2 * chicken_thighs <= 34)
m.addConstr(5 * steaks + 4 * milkshakes + 5 * black_beans <= 68)
m.addConstr(5 * steaks + 5 * black_beans + 2 * chicken_thighs <= 58)
m.addConstr(5 * steaks + 4 * milkshakes + 5 * black_beans + 2 * chicken_thighs <= 58)
m.addConstr(3 * milkshakes + 9 * chicken_thighs <= 67)
m.addConstr(4 * steaks + 9 * chicken_thighs <= 20)
m.addConstr(4 * steaks + 3 * milkshakes <= 62)
m.addConstr(3 * milkshakes + black_beans <= 70)
m.addConstr(4 * steaks + 3 * milkshakes + black_beans + 9 * chicken_thighs <= 70)

# Resource constraints from the provided dictionary
m.addConstr(5 * steaks + 4 * milkshakes + 5 * black_beans + 2 * chicken_thighs <= 114) # Iron
m.addConstr(4 * steaks + 3 * milkshakes + black_beans + 9 * chicken_thighs <= 71) # Carbs


# 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)

```
