The provided constraints include some redundancies (e.g., the total iron and cost constraints are repeated).  We've consolidated these in the code below. The code also incorporates the specific variable types (continuous, integer) as requested.

```python
from gurobipy import Model, GRB

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

# Create variables
ravioli = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="ravioli")
peanutbutter_sandwiches = m.addVar(lb=0, vtype=GRB.INTEGER, name="peanutbutter_sandwiches")
chicken_breasts = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="chicken_breasts")

# Set objective function
m.setObjective(5 * ravioli + 6 * peanutbutter_sandwiches + 6 * chicken_breasts, GRB.MINIMIZE)

# Add constraints
m.addConstr(15 * ravioli + 15 * peanutbutter_sandwiches >= 13, "iron_constraint1")
m.addConstr(15 * ravioli + 8 * chicken_breasts >= 33, "iron_constraint2")
m.addConstr(15 * ravioli + 15 * peanutbutter_sandwiches + 8 * chicken_breasts >= 33, "iron_constraint3")
m.addConstr(17 * peanutbutter_sandwiches + 15 * chicken_breasts >= 30, "cost_constraint1")
m.addConstr(13 * ravioli + 17 * peanutbutter_sandwiches + 15 * chicken_breasts >= 68, "cost_constraint2")
m.addConstr(2 * ravioli - 5 * chicken_breasts >= 0, "constraint4")
m.addConstr(-1 * peanutbutter_sandwiches + 1 * chicken_breasts >= 0, "constraint5")
m.addConstr(15 * ravioli + 8 * chicken_breasts <= 38, "iron_constraint6")
m.addConstr(15 * ravioli + 15 * peanutbutter_sandwiches <= 68, "iron_constraint7")
m.addConstr(15 * ravioli <= 112, "iron_ravioli_ub")
m.addConstr(13 * ravioli <= 237, "cost_ravioli_ub")


# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('ravioli:', ravioli.x)
    print('peanutbutter_sandwiches:', peanutbutter_sandwiches.x)
    print('chicken_breasts:', chicken_breasts.x)
elif m.status == GRB.INFEASIBLE:
    print('The model is infeasible.')
else:
    print('Optimization ended with status %d' % m.status)

```
