```json
{
  "sym_variables": [
    ("x1", "hours the university cafe is run"),
    ("x2", "hours the downtown cafe is run")
  ],
  "objective_function": "400*x1 + 700*x2",
  "constraints": [
    "30*x1 + 40*x2 >= 900",
    "40*x1 + 70*x2 >= 700",
    "60*x1 + 110*x2 >= 1400",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
university_hours = m.addVar(lb=0, name="university_hours")
downtown_hours = m.addVar(lb=0, name="downtown_hours")

# Set objective function
m.setObjective(400 * university_hours + 700 * downtown_hours, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(30 * university_hours + 40 * downtown_hours >= 900, "cappuccino_constraint")
m.addConstr(40 * university_hours + 70 * downtown_hours >= 700, "latte_constraint")
m.addConstr(60 * university_hours + 110 * downtown_hours >= 1400, "coffee_constraint")

# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print(f"University Cafe Hours: {university_hours.x}")
    print(f"Downtown Cafe Hours: {downtown_hours.x}")
    print(f"Total Cost: {m.objVal}")
elif m.status == gp.GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization ended with status {m.status}")

```
