```json
{
  "sym_variables": [
    ("x1", "bottles of chocolate milk"),
    ("x2", "bottles of vegetable juice")
  ],
  "objective_function": "3.5 * x1 + 6 * x2",
  "constraints": [
    "6 * x1 + 9 * x2 >= 20",
    "4 * x1 + 5 * x2 >= 8",
    "5 * x1 + 7 * x2 >= 12",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

```python
import gurobipy as gp

# Create a new model
m = gp.Model("Andy's Drink Optimization")

# Create variables
chocolate_milk = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="chocolate_milk")
vegetable_juice = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="vegetable_juice")


# Set objective function
m.setObjective(3.5 * chocolate_milk + 6 * vegetable_juice, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(6 * chocolate_milk + 9 * vegetable_juice >= 20, "potassium")
m.addConstr(4 * chocolate_milk + 5 * vegetable_juice >= 8, "magnesium")
m.addConstr(5 * chocolate_milk + 7 * vegetable_juice >= 12, "calcium")


# Optimize model
m.optimize()

# Check for infeasibility
if m.status == gp.GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    # Print results
    print(f"Optimal Chocolate Milk Bottles: {chocolate_milk.x}")
    print(f"Optimal Vegetable Juice Bottles: {vegetable_juice.x}")
    print(f"Minimum Cost: ${m.objVal}")

```
