import torch
import gc

class Iter_ModelSwitch:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "output_index": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
                "input_count": ("INT", {"default": 2, "min": 1, "max": 64, "step": 1}),
                "use_last_input": ("BOOLEAN", {"default": True}),
            },
        }

    RETURN_TYPES = ("MODEL",)
    FUNCTION = "switch_model"
    CATEGORY = "CustomNodes/Iterators"

    def switch_model(self, output_index, input_count, use_last_input, **kwargs):
        # 1. 確定目標索引 (嚴格對應編號)
        target_idx = output_index % input_count
        
        # 2. 往回搜尋有效模型
        res_model = None
        for i in range(target_idx, -1, -1):
            val = kwargs.get(f"model_{i}")
            if val is not None or not use_last_input:
                res_model = val
                break
    

        # 4. VRAM 管理
        #if force_gc == "enable":
        #gc.collect()
        #torch.cuda.empty_cache()

        return (res_model,)