```json
{
  "sym_variables": [
    ("x1", "batches of donuts"),
    ("x2", "batches of cookies")
  ],
  "objective_function": "Maximize: 20*x1 + 15*x2",
  "constraints": [
    "20*x1 + 5*x2 <= 200 (Jake's time constraint)",
    "10*x1 + 25*x2 <= 300 (Jill's time constraint)",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
donuts = model.addVar(vtype=gp.GRB.CONTINUOUS, name="donuts")  # x1
cookies = model.addVar(vtype=gp.GRB.CONTINUOUS, name="cookies") # x2

# Set objective function
model.setObjective(20 * donuts + 15 * cookies, gp.GRB.MAXIMIZE)

# Add constraints
model.addConstr(20 * donuts + 5 * cookies <= 200, "Jake's Time")
model.addConstr(10 * donuts + 25 * cookies <= 300, "Jill's Time")
model.addConstr(donuts >= 0, "Donuts Non-Negative")
model.addConstr(cookies >= 0, "Cookies Non-Negative")


# Optimize model
model.optimize()

# Print results
if model.status == gp.GRB.OPTIMAL:
    print(f"Optimal Solution Found:")
    print(f"  Donuts: {donuts.x}")
    print(f"  Cookies: {cookies.x}")
    print(f"  Profit: ${model.objVal}")
elif model.status == gp.GRB.INFEASIBLE:
    print("Model is infeasible.")
else:
    print(f"Optimization terminated with status {model.status}")

```
