src/utils/download_models.py

import os
from pathlib import Path, PurePosixPath

from huggingface_hub import hf_hub_download


def prepare_base_model():
    base_dir = os.getenv('APP_BASE_DIR', os.path.dirname(os.path.abspath(__file__)))
    local_dir = os.path.join(base_dir, 'pretrained_weights', 'stable-diffusion-v1-5')
    os.makedirs(local_dir, exist_ok=True)
    
    for hub_file in ["unet/config.json", "unet/diffusion_pytorch_model.bin"]:
        # Construct the full path to the file within the local_dir
        saved_path = os.path.join(local_dir, hub_file)
        if os.path.exists(saved_path):
            continue
        
        hf_hub_download(
            repo_id="runwayml/stable-diffusion-v1-5",
            subfolder=PurePosixPath(Path(hub_file).parent),
            filename=PurePosixPath(Path(hub_file).name),
            local_dir=local_dir,
        )


def prepare_image_encoder():
    local_dir = "./pretrained_weights"
    os.makedirs(local_dir, exist_ok=True)
    for hub_file in ["image_encoder/config.json", "image_encoder/pytorch_model.bin"]:
        path = Path(hub_file)
        saved_path = local_dir / path
        if os.path.exists(saved_path):
            continue
        hf_hub_download(
            repo_id="lambdalabs/sd-image-variations-diffusers",
            subfolder=PurePosixPath(path.parent),
            filename=PurePosixPath(path.name),
            local_dir=local_dir,
        )


def prepare_dwpose():
    ...