Salia_Load_Lora_Wan.py

import logging
import os
import shutil
import subprocess
import urllib.parse
import urllib.request

import comfy.sd
import comfy.utils
import folder_paths


HF_REPO_BASE = "https://huggingface.co/saliacoel/x/resolve/main"


class salia_Load_Lora_Wan:
    """
    Downloads paired *_HI / *_LO LoRAs from the public Hugging Face repo
    `saliacoel/x` when missing, then applies them model-only to two separate
    MODEL inputs.

    Input examples that all resolve to the same pair:
      - Fade_to_Black
      - Fade_to_Black_HI
      - Fade_to_Black_LO
      - Fade_to_Black_HI.safetensors
    """

    CATEGORY = "loaders/saliacoel"
    FUNCTION = "load_dual_loras"
    RETURN_TYPES = ("MODEL", "MODEL")
    RETURN_NAMES = ("loaded_out_HI", "loaded_out_LO")
    DESCRIPTION = (
        "Downloads missing *_HI/*_LO LoRAs from saliacoel/x and applies them "
        "with model-only LoRA loading to separate HI and LO model inputs."
    )
    OUTPUT_TOOLTIPS = (
        "model_in_HI with the *_HI LoRA applied.",
        "model_in_LO with the *_LO LoRA applied.",
    )

    def __init__(self):
        self.loaded_lora_hi = None
        self.loaded_lora_lo = None

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {
                "filename": (
                    "STRING",
                    {
                        "default": "",
                        "multiline": False,
                        "placeholder": "Fade_to_Black or Fade_to_Black_HI",
                        "tooltip": (
                            "Base LoRA name. A trailing _HI, _LO, or .safetensors "
                            "is accepted and normalized automatically."
                        ),
                    },
                ),
                "model_in_HI": (
                    "MODEL",
                    {"tooltip": "The MODEL input that will receive the *_HI LoRA."},
                ),
                "model_in_LO": (
                    "MODEL",
                    {"tooltip": "The MODEL input that will receive the *_LO LoRA."},
                ),
                "strength_HI": (
                    "FLOAT",
                    {
                        "default": 1.0,
                        "min": -100.0,
                        "max": 100.0,
                        "step": 0.01,
                        "tooltip": "Strength used when applying the *_HI LoRA.",
                    },
                ),
                "strength_LO": (
                    "FLOAT",
                    {
                        "default": 1.0,
                        "min": -100.0,
                        "max": 100.0,
                        "step": 0.01,
                        "tooltip": "Strength used when applying the *_LO LoRA.",
                    },
                ),
            }
        }

    @staticmethod
    def _normalize_base_name(name: str) -> str:
        base = (name or "").strip()
        if not base:
            raise ValueError("filename cannot be empty.")

        # Drop any directory component to avoid path traversal or accidental nesting.
        base = os.path.basename(base)

        if base.lower().endswith(".safetensors"):
            base = base[: -len(".safetensors")]

        if base.endswith("_HI"):
            base = base[: -len("_HI")]
        elif base.endswith("_LO"):
            base = base[: -len("_LO")]

        if not base:
            raise ValueError("filename resolves to an empty base name.")

        return base

    @classmethod
    def _build_pair_names(cls, name: str) -> tuple[str, str]:
        base = cls._normalize_base_name(name)
        return f"{base}_HI.safetensors", f"{base}_LO.safetensors"

    @staticmethod
    def _download_file(url: str, target_path: str) -> None:
        os.makedirs(os.path.dirname(target_path), exist_ok=True)
        tmp_path = target_path + ".download"

        if os.path.exists(tmp_path):
            os.remove(tmp_path)

        wget_path = shutil.which("wget")

        try:
            if wget_path:
                subprocess.run(
                    [wget_path, "-O", tmp_path, url],
                    check=True,
                    cwd=os.path.dirname(target_path),
                )
            else:
                request = urllib.request.Request(
                    url,
                    headers={"User-Agent": "ComfyUI-SaliacoelDualRepoLoraModelOnly/1.0"},
                )
                with urllib.request.urlopen(request) as response, open(tmp_path, "wb") as out_file:
                    shutil.copyfileobj(response, out_file)

            os.replace(tmp_path, target_path)
        except Exception:
            if os.path.exists(tmp_path):
                os.remove(tmp_path)
            raise

    @classmethod
    def _ensure_lora_available(cls, lora_name: str) -> str:
        existing_path = folder_paths.get_full_path("loras", lora_name)
        if existing_path is not None:
            return existing_path

        lora_dirs = folder_paths.get_folder_paths("loras")
        if not lora_dirs:
            raise RuntimeError("No ComfyUI 'loras' folder is configured.")

        target_dir = lora_dirs[0]
        target_path = os.path.join(target_dir, lora_name)
        url = f"{HF_REPO_BASE}/{urllib.parse.quote(lora_name)}"

        logging.info("[SaliacoelDualRepoLoraModelOnly] Downloading missing LoRA: %s", url)
        cls._download_file(url, target_path)

        # Re-resolve through ComfyUI's folder lookup so the returned path matches
        # normal Comfy conventions if multiple LoRA directories are configured.
        resolved_path = folder_paths.get_full_path("loras", lora_name)
        return resolved_path if resolved_path is not None else target_path

    def _get_or_load_lora(self, cache_attr: str, lora_path: str):
        cached = getattr(self, cache_attr)
        if cached is not None and cached[0] == lora_path:
            return cached[1]

        lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
        setattr(self, cache_attr, (lora_path, lora))
        return lora

    def _apply_lora_model_only(self, model, lora_path: str, strength: float, cache_attr: str):
        if strength == 0:
            return model

        lora = self._get_or_load_lora(cache_attr, lora_path)
        model_lora, _ = comfy.sd.load_lora_for_models(model, None, lora, strength, 0)
        return model_lora

    def load_dual_loras(self, filename, model_in_HI, model_in_LO, strength_HI, strength_LO):
        hi_name, lo_name = self._build_pair_names(filename)

        hi_path = self._ensure_lora_available(hi_name)
        lo_path = self._ensure_lora_available(lo_name)

        loaded_out_HI = self._apply_lora_model_only(
            model=model_in_HI,
            lora_path=hi_path,
            strength=strength_HI,
            cache_attr="loaded_lora_hi",
        )
        loaded_out_LO = self._apply_lora_model_only(
            model=model_in_LO,
            lora_path=lo_path,
            strength=strength_LO,
            cache_attr="loaded_lora_lo",
        )

        return (loaded_out_HI, loaded_out_LO)


NODE_CLASS_MAPPINGS = {
    "salia_Load_Lora_Wan": salia_Load_Lora_Wan,
}

NODE_DISPLAY_NAME_MAPPINGS = {
    "salia_Load_Lora_Wan": "Salia Load Dual LoRA Loader (Model Only)",
}