Function create_optimizer

examples/analysis.py:216–248

Create optimizer instance based on type.

(optimizer_type: str, reward_fn: Optional[Callable[[str, str, str], Any]] = None)

    return "", str(agent_result) if agent_result else ""

def create_optimizer(optimizer_type: str, reward_fn: Optional[Callable[[str, str, str], Any]] = None):
    """Create optimizer instance based on type."""
    base_config = {
        'workdir': config.workdir,
        'model_name': 'openrouter/gemini-3-flash-preview',
        'memory_name': 'optimizer_memory_system',
        'optimize_trainable_variables': False,
        'optimize_solution': True
    }

    if optimizer_type == 'grpo':
        return GrpoOptimizer(
            num_candidates=4,
            clip_ratio=0.2,
            beta=0.01,
            reward_fn=reward_fn,
            prompt_name='grpo_optimizer',
            **base_config
        )
    elif optimizer_type == 'reinforce_pp':
        return ReinforcePlusPlusOptimizer(
            clip_ratio=0.2,
            beta=0.01,
            reward_fn=reward_fn,
            prompt_name='reinforce_plus_plus_optimizer',
            **base_config
        )
    elif optimizer_type == 'reflection':
        return ReflectionOptimizer(prompt_name='reflection_optimizer',
            **base_config
        )
    else:
        raise ValueError(f"Unknown optimizer type: {optimizer_type}")


async def get_all_tasks(benchmark_name: str) -> List[Dict]: