```json
{
  "sym_variables": [
    ("x1", "chicken servings"),
    ("x2", "pork servings")
  ],
  "objective_function": "10*x1 + 15*x2",
  "constraints": [
    "20*x1 + 15*x2 >= 100",
    "5*x1 + 3*x2 >= 50",
    "6*x1 + 8*x2 >= 30",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
chicken = m.addVar(lb=0, name="chicken")
pork = m.addVar(lb=0, name="pork")

# Set objective function
m.setObjective(10 * chicken + 15 * pork, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(20 * chicken + 15 * pork >= 100, "protein_req")
m.addConstr(5 * chicken + 3 * pork >= 50, "carb_req")
m.addConstr(6 * chicken + 8 * pork >= 30, "fat_req")


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print(f"Optimal cost: {m.objVal}")
    print(f"Chicken servings: {chicken.x}")
    print(f"Pork servings: {pork.x}")
elif m.status == gp.GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization ended with status {m.status}")

```
