```python
import argparse
from hydro import scenario_creator, denouement
from mpisppy.utils import config
from mpisppy.spin_the_wheel import WheelSpinner
from mpisppy.opt.vanilla import Vanilla
from mpisppy.cylinders import LagrangianBound, XhatLooper

def parse_arguments():
    parser = argparse.ArgumentParser(description="Hydro MPiSPPy model arguments")
    # Add arguments as needed, for example:
    parser.add_argument("--num_scenarios", help="Number of scenarios", type=int, default=10)
    parser.add_argument("--branching_factors", help="Branching factors as comma-separated values", type=str, default="3,2")
    args = parser.parse_args()
    
    # Create a configuration object
    cfg = config.Config()
    cfg.num_scenarios = args.num_scenarios
    cfg.branching_factors = [int(x) for x in args.branching_factors.split(',')]
    
    return cfg

def main():
    cfg = parse_arguments()
    
    if len(cfg.branching_factors) < 1:
        raise ValueError("Branching factors length must be at least 1")
    
    # Create node names based on branching factors
    node_names = [f"Node_{i}" for i in range(len(cfg.branching_factors))]
    
    # Create scenario names
    scenario_names = [f"Scenario_{i+1}" for i in range(cfg.num_scenarios)]
    
    # Setup scenario creator and denouement
    scenario_creator_kwargs = {}
    all_scenario_names = scenario_names
    
    # Prepare arguments for the 'vanilla' cylinders
    vanilla_options = {"iter0_solver_options": None, "iterk_solver_options": None}
    
    # Setup spokes
    hub_dict = dict()
    spoke_dict = dict()
    
    if True:  # Assuming some condition for demonstration
        hub_dict["Lagrangian"] = {"spoke_class": LagrangianBound, "opt_kwargs": {"options": vanilla_options}}
        spoke_dict["XhatLooper"] = {"spoke_class": XhatLooper, "opt_kwargs": {"options": vanilla_options}}
    
    # Create a wheel spinner
    wheel = WheelSpinner(scenario_names=all_scenario_names,
                         scenario_creator=scenario_creator,
                         scenario_denouement=denouement,
                         all_scenario_names=all_scenario_names,
                         options=vanilla_options,
                         hub_dict=hub_dict,
                         spoke_dict=spoke_dict,
                         cb_data=None)
    
    # Spin the wheel
    wheel.spin()
    
    # Print the best inner and outer bounds
    print(f"Best inner bound: {wheel.best_inner_bound}")
    print(f"Best outer bound: {wheel.best_outer_bound}")
    
    # Write solutions if a certain condition is met
    if True:  # Assuming some condition for demonstration
        wheel.write_first_stage_solution("first_stage_solution.csv")
        wheel.write_tree_solution("full_tree_solution.csv")

if __name__ == "__main__":
    main()
```