## Problem Description and Formulation

The problem described is a classic example of a linear programming problem. Theta Electronics produces two types of phone models: regular and premium. Each model requires a certain amount of time for assembly and software verification. The goal is to maximize profit given the constraints on assembly and software verification time.

Let's define the decision variables:
- \(R\): The number of regular models to be produced.
- \(P\): The number of premium models to be produced.

The objective function to maximize profit (\(Z\)) is:
\[ Z = 200R + 500P \]

Subject to the constraints:
1. Assembly time constraint: \(70R + 100P \leq 6000\)
2. Software verification time constraint: \(25R + 30P \leq 4000\)
3. Non-negativity constraints: \(R \geq 0, P \geq 0\)

## Gurobi Code

To solve this problem using Gurobi in Python, we will use the Gurobi Python API. First, ensure you have Gurobi installed in your Python environment. You can install it via pip if you have the Gurobi license and the appropriate installation files or channels configured.

```python
import gurobi as gp
from gurobi import GRB

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

# Define the decision variables
R = model.addVar(lb=0, vtype=GRB.CONTINUOUS, name="Regular_Models")
P = model.addVar(lb=0, vtype=GRB.CONTINUOUS, name="Premium_Models")

# Objective function: Maximize profit
model.setObjective(200*R + 500*P, GRB.MAXIMIZE)

# Assembly time constraint
model.addConstr(70*R + 100*P <= 6000, name="Assembly_Time_Constraint")

# Software verification time constraint
model.addConstr(25*R + 30*P <= 4000, name="Software_Verification_Time_Constraint")

# Optimize the model
model.optimize()

# Print the status of the optimization
print("Optimization Status: ", model.status)

# Print the solution
if model.status == GRB.OPTIMAL:
    print("Optimal Solution:")
    print("Regular Models: ", R.varValue)
    print("Premium Models: ", P.varValue)
    print("Max Profit: ", model.objVal)
else:
    print("The model is infeasible or unbounded.")
```