adjust non-app modules to use new config system

invokeai/app/api_app.py

@@ -17,7 +17,7 @@ from .api.dependencies import ApiDependencies
 from .api.routers import images, sessions, models
 from .api.sockets import SocketIO
 from .invocations.baseinvocation import BaseInvocation
-from .services.config import InvokeAIWebConfig
+from .services.config import InvokeAIWebConfig, get_invokeai_config
 
 # Create the app
 # TODO: create this all in a method so configuration/etc. can be passed in?
@@ -133,7 +133,7 @@ def invoke_api():
     # parse command-line settings, environment and the init file
     # (this is a module global)
     global web_config
-    web_config = InvokeAIWebConfig()
+    web_config = get_invokeai_config(InvokeAIWebConfig)
     app.add_middleware(
         CORSMiddleware,
         allow_origins=web_config.allow_origins,

invokeai/app/cli_app.py

@@ -33,7 +33,7 @@ from .services.invocation_services import InvocationServices
 from .services.invoker import Invoker
 from .services.processor import DefaultInvocationProcessor
 from .services.sqlite import SqliteItemStorage
-from .services.config import InvokeAIAppConfig
+from .services.config import get_invokeai_config
 
 class CliCommand(BaseModel):
     command: Union[BaseCommand.get_commands() + BaseInvocation.get_invocations()] = Field(discriminator="type")  # type: ignore
@@ -188,7 +188,7 @@ def invoke_all(context: CliContext):
 
 
 def invoke_cli():
-    config = InvokeAIAppConfig()
+    config = get_invokeai_config()
     model_manager = get_model_manager(config,logger=logger)
     
     events = EventServiceBase()

invokeai/backend/config/invokeai_configure.py

@@ -44,28 +44,29 @@ from ...frontend.install.widgets import (
     IntTitleSlider,
     set_min_terminal_size,
 )
-from ..args import PRECISION_CHOICES, Args
-from ..globals import Globals, global_cache_dir, global_config_dir, global_config_file
 from .model_install_backend import (
     default_dataset,
     download_from_hf,
     hf_download_with_resume,
     recommended_datasets,
 )
+from invokeai.app.services.config import get_invokeai_config()
 
 warnings.filterwarnings("ignore")
 
 transformers.logging.set_verbosity_error()
 
 # --------------------------globals-----------------------
+config = get_invokeai_config()
+
 Model_dir = "models"
 Weights_dir = "ldm/stable-diffusion-v1/"
 
 # the initial "configs" dir is now bundled in the `invokeai.configs` package
 Dataset_path = Path(configs.__path__[0]) / "INITIAL_MODELS.yaml"
 
-Default_config_file = Path(global_config_dir()) / "models.yaml"
+Default_config_file = config.model_conf_path
-SD_Configs = Path(global_config_dir()) / "stable-diffusion"
+SD_Configs = config.legacy_conf_path
 
 Datasets = OmegaConf.load(Dataset_path)
 
@@ -73,6 +74,8 @@ Datasets = OmegaConf.load(Dataset_path)
 MIN_COLS = 135
 MIN_LINES = 45
 
+PRECISION_CHOICES = ['auto','float16','float32','autocast']
+
 INIT_FILE_PREAMBLE = """# InvokeAI initialization file
 # This is the InvokeAI initialization file, which contains command-line default values.
 # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
@@ -103,7 +106,7 @@ Command-line interface:
    invokeai
 
 If you installed using an installation script, run:
-  {Globals.root}/invoke.{"bat" if sys.platform == "win32" else "sh"}
+  {config.root}/invoke.{"bat" if sys.platform == "win32" else "sh"}
 
 Add the '--help' argument to see all of the command-line switches available for use.
 """
@@ -216,11 +219,11 @@ def download_realesrgan():
     wdn_model_url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth"
 
     model_dest = os.path.join(
-        Globals.root, "models/realesrgan/realesr-general-x4v3.pth"
+        config.root, "models/realesrgan/realesr-general-x4v3.pth"
     )
 
     wdn_model_dest = os.path.join(
-        Globals.root, "models/realesrgan/realesr-general-wdn-x4v3.pth"
+        config.root, "models/realesrgan/realesr-general-wdn-x4v3.pth"
     )
 
     download_with_progress_bar(model_url, model_dest, "RealESRGAN")
@@ -243,7 +246,7 @@ def download_gfpgan():
             "./models/gfpgan/weights/parsing_parsenet.pth",
         ],
     ):
-        model_url, model_dest = model[0], os.path.join(Globals.root, model[1])
+        model_url, model_dest = model[0], os.path.join(config.root, model[1])
         download_with_progress_bar(model_url, model_dest, "GFPGAN weights")
 
 
@@ -253,7 +256,7 @@ def download_codeformer():
     model_url = (
         "https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth"
     )
-    model_dest = os.path.join(Globals.root, "models/codeformer/codeformer.pth")
+    model_dest = os.path.join(config.root, "models/codeformer/codeformer.pth")
     download_with_progress_bar(model_url, model_dest, "CodeFormer")
 
 
@@ -306,7 +309,7 @@ def download_vaes():
         if not hf_download_with_resume(
             repo_id=repo_id,
             model_name=model_name,
-            model_dir=str(Globals.root / Model_dir / Weights_dir),
+            model_dir=str(config.root / Model_dir / Weights_dir),
         ):
             raise Exception(f"download of {model_name} failed")
     except Exception as e:
@@ -321,8 +324,7 @@ def get_root(root: str = None) -> str:
     elif os.environ.get("INVOKEAI_ROOT"):
         return os.environ.get("INVOKEAI_ROOT")
     else:
-        return Globals.root
+        return config.root
-
 
 # -------------------------------------
 class editOptsForm(npyscreen.FormMultiPage):
@@ -332,7 +334,7 @@ class editOptsForm(npyscreen.FormMultiPage):
     def create(self):
         program_opts = self.parentApp.program_opts
         old_opts = self.parentApp.invokeai_opts
-        first_time = not (Globals.root / Globals.initfile).exists()
+        first_time = not (config.root / 'invokeai.init').exists()
         access_token = HfFolder.get_token()
         window_width, window_height = get_terminal_size()
         for i in [
@@ -384,7 +386,7 @@ class editOptsForm(npyscreen.FormMultiPage):
         self.safety_checker = self.add_widget_intelligent(
             npyscreen.Checkbox,
             name="NSFW checker",
-            value=old_opts.safety_checker,
+            value=old_opts.nsfw_checker,
             relx=5,
             scroll_exit=True,
         )
@@ -438,14 +440,7 @@ class editOptsForm(npyscreen.FormMultiPage):
         self.xformers = self.add_widget_intelligent(
             npyscreen.Checkbox,
             name="Enable xformers support if available",
-            value=old_opts.xformers,
+            value=old_opts.xformers_enabled,
-            relx=5,
-            scroll_exit=True,
-        )
-        self.ckpt_convert = self.add_widget_intelligent(
-            npyscreen.Checkbox,
-            name="Load legacy checkpoint models into memory as diffusers models",
-            value=old_opts.ckpt_convert,
             relx=5,
             scroll_exit=True,
         )
@@ -583,7 +578,6 @@ class editOptsForm(npyscreen.FormMultiPage):
             "xformers",
             "always_use_cpu",
             "embedding_path",
-            "ckpt_convert",
         ]:
             setattr(new_opts, attr, getattr(self, attr).value)
 
@@ -628,15 +622,14 @@ def edit_opts(program_opts: Namespace, invokeai_opts: Namespace) -> argparse.Nam
 
 
 def default_startup_options(init_file: Path) -> Namespace:
-    opts = Args().parse_args([])
+    opts = InvokeAIAppConfig(argv=[])
     outdir = Path(opts.outdir)
     if not outdir.is_absolute():
-        opts.outdir = str(Globals.root / opts.outdir)
+        opts.outdir = str(config.root / opts.outdir)
     if not init_file.exists():
-        opts.safety_checker = True
+        opts.nsfw_checker = True
     return opts
 
-
 def default_user_selections(program_opts: Namespace) -> Namespace:
     return Namespace(
         starter_models=default_dataset()
@@ -724,7 +717,6 @@ def write_opts(opts: Namespace, init_file: Path):
 --max_loaded_models={int(opts.max_loaded_models)}
 --{'no-' if not opts.safety_checker else ''}nsfw_checker
 --{'no-' if not opts.xformers else ''}xformers
---{'no-' if not opts.ckpt_convert else ''}ckpt_convert
 {'--free_gpu_mem' if opts.free_gpu_mem else ''}
 {'--always_use_cpu' if opts.always_use_cpu else ''}
 """
@@ -740,13 +732,11 @@ def write_opts(opts: Namespace, init_file: Path):
 
 # -------------------------------------
 def default_output_dir() -> Path:
-    return Globals.root / "outputs"
+    return config.root / "outputs"
-
 
 # -------------------------------------
 def default_embedding_dir() -> Path:
-    return Globals.root / "embeddings"
+    return config.root / "embeddings"
-
 
 # -------------------------------------
 def write_default_options(program_opts: Namespace, initfile: Path):
@@ -810,7 +800,7 @@ def main():
     opt = parser.parse_args()
 
     # setting a global here
-    Globals.root = Path(os.path.expanduser(get_root(opt.root) or ""))
+    config.root = Path(os.path.expanduser(get_root(opt.root) or ""))
 
     errors = set()
 
@@ -818,9 +808,10 @@ def main():
         models_to_download = default_user_selections(opt)
 
         # We check for to see if the runtime directory is correctly initialized.
-        init_file = Path(Globals.root, Globals.initfile)
+        print('** invokeai.init init file is no longer supported. Migrate this code to invokeai.yaml **')
-        if not init_file.exists() or not global_config_file().exists():
+        init_file = Path(config.root, 'invokeai.init')
-            initialize_rootdir(Globals.root, opt.yes_to_all)
+        if not init_file.exists() or not config.model_conf_path.exists():
+            initialize_rootdir(config.root, opt.yes_to_all)
 
         if opt.yes_to_all:
             write_default_options(opt, init_file)

invokeai/backend/config/model_install_backend.py

@@ -19,13 +19,15 @@ from tqdm import tqdm
 
 import invokeai.configs as configs
 
-from ..globals import Globals, global_cache_dir, global_config_dir
+from invokeai.app.services.config import get_invokeai_config()
 from ..model_management import ModelManager
 from ..stable_diffusion import StableDiffusionGeneratorPipeline
 
+
 warnings.filterwarnings("ignore")
 
 # --------------------------globals-----------------------
+config = get_invokeai_config()
 Model_dir = "models"
 Weights_dir = "ldm/stable-diffusion-v1/"
 
@@ -47,12 +49,11 @@ Config_preamble = """
 
 
 def default_config_file():
-    return Path(global_config_dir()) / "models.yaml"
+    return config.model_conf_path
 
 
 def sd_configs():
-    return Path(global_config_dir()) / "stable-diffusion"
+    return config.legacy_conf_path
-
 
 def initial_models():
     global Datasets
@@ -121,8 +122,9 @@ def install_requested_models(
 
     if scan_at_startup and scan_directory.is_dir():
         argument = "--autoconvert"
-        initfile = Path(Globals.root, Globals.initfile)
+        print('** The global initfile is no longer supported; rewrite to support new yaml format **')
-        replacement = Path(Globals.root, f"{Globals.initfile}.new")
+        initfile = Path(config.root, 'invokeai.init')
+        replacement = Path(config.root, f"invokeai.init.new")
         directory = str(scan_directory).replace("\\", "/")
         with open(initfile, "r") as input:
             with open(replacement, "w") as output:
@@ -150,7 +152,7 @@ def get_root(root: str = None) -> str:
     elif os.environ.get("INVOKEAI_ROOT"):
         return os.environ.get("INVOKEAI_ROOT")
     else:
-        return Globals.root
+        return config.root
 
 
 # ---------------------------------------------
@@ -183,7 +185,7 @@ def all_datasets() -> dict:
 # look for legacy model.ckpt in models directory and offer to
 # normalize its name
 def migrate_models_ckpt():
-    model_path = os.path.join(Globals.root, Model_dir, Weights_dir)
+    model_path = os.path.join(config.root, Model_dir, Weights_dir)
     if not os.path.exists(os.path.join(model_path, "model.ckpt")):
         return
     new_name = initial_models()["stable-diffusion-1.4"]["file"]
@@ -228,7 +230,7 @@ def _download_repo_or_file(
 def _download_ckpt_weights(mconfig: DictConfig, access_token: str) -> Path:
     repo_id = mconfig["repo_id"]
     filename = mconfig["file"]
-    cache_dir = os.path.join(Globals.root, Model_dir, Weights_dir)
+    cache_dir = os.path.join(config.root, Model_dir, Weights_dir)
     return hf_download_with_resume(
         repo_id=repo_id,
         model_dir=cache_dir,
@@ -239,9 +241,9 @@ def _download_ckpt_weights(mconfig: DictConfig, access_token: str) -> Path:
 
 # ---------------------------------------------
 def download_from_hf(
-    model_class: object, model_name: str, cache_subdir: Path = Path("hub"), **kwargs
+    model_class: object, model_name: str, **kwargs
 ):
-    path = global_cache_dir(cache_subdir)
+    path = config.cache_dir
     model = model_class.from_pretrained(
         model_name,
         cache_dir=path,
@@ -417,7 +419,7 @@ def new_config_file_contents(
             stanza["height"] = mod["height"]
         if "file" in mod:
             stanza["weights"] = os.path.relpath(
-                successfully_downloaded[model], start=Globals.root
+                successfully_downloaded[model], start=config.root
             )
             stanza["config"] = os.path.normpath(
                 os.path.join(sd_configs(), mod["config"])
@@ -456,7 +458,7 @@ def delete_weights(model_name: str, conf_stanza: dict):
 
     weights = Path(weights)
     if not weights.is_absolute():
-        weights = Path(Globals.root) / weights
+        weights = Path(config.root) / weights
         try:
             weights.unlink()
         except OSError as e:

invokeai/backend/image_util/patchmatch.py

@@ -6,9 +6,9 @@ be suppressed or deferred
 """
 import numpy as np
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 class PatchMatch:
     """

invokeai/backend/image_util/txt2mask.py

@@ -33,11 +33,11 @@ from PIL import Image, ImageOps
 from transformers import AutoProcessor, CLIPSegForImageSegmentation
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 
 CLIPSEG_MODEL = "CIDAS/clipseg-rd64-refined"
 CLIPSEG_SIZE = 352
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 class SegmentedGrayscale(object):
     def __init__(self, image: Image, heatmap: torch.Tensor):

invokeai/backend/model_management/convert_ckpt_to_diffusers.py

@@ -26,7 +26,7 @@ import torch
 from safetensors.torch import load_file
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 
 from .model_manager import ModelManager, SDLegacyType
 
@@ -73,7 +73,7 @@ from transformers import (
 
 from ..stable_diffusion import StableDiffusionGeneratorPipeline
 
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 def shave_segments(path, n_shave_prefix_segments=1):
     """

invokeai/backend/model_management/model_manager.py

@@ -47,7 +47,7 @@ from diffusers.pipelines.stable_diffusion.safety_checker import (
 from ..stable_diffusion import (
     StableDiffusionGeneratorPipeline,
 )
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 from ..util import CUDA_DEVICE, ask_user, download_with_resume
 
 class SDLegacyType(Enum):
@@ -68,7 +68,7 @@ class SDModelComponent(Enum):
     feature_extractor="feature_extractor"
     
 DEFAULT_MAX_MODELS = 2
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 class ModelManager(object):
     """

invokeai/backend/prompting/conditioning.py

@@ -20,11 +20,11 @@ from compel.prompt_parser import (
 
 import invokeai.backend.util.logging as logger
 
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 from ..stable_diffusion import InvokeAIDiffuserComponent
 from ..util import torch_dtype
 
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 def get_uc_and_c_and_ec(
     prompt_string, model, log_tokens=False, skip_normalize_legacy_blend=False

invokeai/backend/restoration/codeformer.py

@@ -6,8 +6,8 @@ import numpy as np
 import torch
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 pretrained_model_url = (
     "https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth"

invokeai/backend/restoration/gfpgan.py

@@ -7,8 +7,8 @@ import torch
 from PIL import Image
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 class GFPGAN:
     def __init__(self, gfpgan_model_path="models/gfpgan/GFPGANv1.4.pth") -> None:

invokeai/backend/safety_checker.py

@@ -15,10 +15,10 @@ from transformers import AutoFeatureExtractor
 
 import invokeai.assets.web as web_assets
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 from .util import CPU_DEVICE
 
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 class SafetyChecker(object):
     CAUTION_IMG = "caution.png"

invokeai/backend/stable_diffusion/concepts_lib.py

@@ -18,8 +18,8 @@ from huggingface_hub import (
 )
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 class HuggingFaceConceptsLibrary(object):
     def __init__(self, root=None):

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -33,7 +33,7 @@ from torchvision.transforms.functional import resize as tv_resize
 from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 from typing_extensions import ParamSpec
 
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 from ..util import CPU_DEVICE, normalize_device
 from .diffusion import (
     AttentionMapSaver,
@@ -43,7 +43,7 @@ from .diffusion import (
 from .offloading import FullyLoadedModelGroup, LazilyLoadedModelGroup, ModelGroup
 from .textual_inversion_manager import TextualInversionManager
 
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 @dataclass
 class PipelineIntermediateState:

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -9,7 +9,7 @@ from diffusers.models.attention_processor import AttentionProcessor
 from typing_extensions import TypeAlias
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 
 from .cross_attention_control import (
     Arguments,
@@ -31,7 +31,7 @@ ModelForwardCallback: TypeAlias = Union[
     Callable[[torch.Tensor, torch.Tensor, torch.Tensor], torch.Tensor],
 ]
 
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 @dataclass(frozen=True)
 class PostprocessingSettings:

invokeai/backend/util/devices.py

@@ -4,12 +4,12 @@ from contextlib import nullcontext
 
 import torch
 from torch import autocast
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import get_invokeai_config
 
 CPU_DEVICE = torch.device("cpu")
 CUDA_DEVICE = torch.device("cuda")
 MPS_DEVICE = torch.device("mps")
-config = InvokeAIAppConfig()
+config = get_invokeai_config()
 
 def choose_torch_device() -> torch.device:
     """Convenience routine for guessing which GPU device to run model on"""

invokeai/frontend/install/model_install.py

@@ -23,7 +23,6 @@ from npyscreen import widget
 from omegaconf import OmegaConf
 
 import invokeai.backend.util.logging as logger
-from invokeai.backend.globals import Globals, global_config_dir
 
 from ...backend.config.model_install_backend import (
     Dataset_path,
@@ -41,11 +40,13 @@ from .widgets import (
     TextBox,
     set_min_terminal_size,
 )
+from invokeai.app.services.config import get_invokeai_config
 
 # minimum size for the UI
 MIN_COLS = 120
 MIN_LINES = 45
 
+config = get_invokeai_config()
 
 class addModelsForm(npyscreen.FormMultiPage):
     # for responsive resizing - disabled
@@ -453,9 +454,9 @@ def main():
     opt = parser.parse_args()
 
     # setting a global here
-    Globals.root = os.path.expanduser(get_root(opt.root) or "")
+    config.root = os.path.expanduser(get_root(opt.root) or "")
 
-    if not global_config_dir().exists():
+    if not (config.conf_path / '..' ).exists():
         logger.info(
             "Your InvokeAI root directory is not set up. Calling invokeai-configure."
         )

invokeai/frontend/merge/merge_diffusers.py

@@ -8,7 +8,6 @@ import argparse
 import curses
 import os
 import sys
-import traceback
 import warnings
 from argparse import Namespace
 from pathlib import Path
@@ -20,20 +19,13 @@ from diffusers import logging as dlogging
 from npyscreen import widget
 from omegaconf import OmegaConf
 
-from ...backend.globals import (
-    Globals,
-    global_cache_dir,
-    global_config_file,
-    global_models_dir,
-    global_set_root,
-)
-
 import invokeai.backend.util.logging as logger
+from invokeai.services.config import get_invokeai_config
 from ...backend.model_management import ModelManager
 from ...frontend.install.widgets import FloatTitleSlider
 
 DEST_MERGED_MODEL_DIR = "merged_models"
-
+config = get_invokeai_config()
 
 def merge_diffusion_models(
     model_ids_or_paths: List[Union[str, Path]],
@@ -60,7 +52,7 @@ def merge_diffusion_models(
 
         pipe = DiffusionPipeline.from_pretrained(
             model_ids_or_paths[0],
-            cache_dir=kwargs.get("cache_dir", global_cache_dir()),
+            cache_dir=kwargs.get("cache_dir", config.cache_dir),
             custom_pipeline="checkpoint_merger",
         )
         merged_pipe = pipe.merge(
@@ -94,7 +86,7 @@ def merge_diffusion_models_and_commit(
     **kwargs - the default DiffusionPipeline.get_config_dict kwargs:
          cache_dir, resume_download, force_download, proxies, local_files_only, use_auth_token, revision, torch_dtype, device_map
     """
-    config_file = global_config_file()
+    config_file = config.model_conf_path
     model_manager = ModelManager(OmegaConf.load(config_file))
     for mod in models:
         assert mod in model_manager.model_names(), f'** Unknown model "{mod}"'
@@ -106,7 +98,7 @@ def merge_diffusion_models_and_commit(
     merged_pipe = merge_diffusion_models(
         model_ids_or_paths, alpha, interp, force, **kwargs
     )
-    dump_path = global_models_dir() / DEST_MERGED_MODEL_DIR
+    dump_path = config.models_dir / DEST_MERGED_MODEL_DIR
 
     os.makedirs(dump_path, exist_ok=True)
     dump_path = dump_path / merged_model_name
@@ -126,7 +118,7 @@ def _parse_args() -> Namespace:
     parser.add_argument(
         "--root_dir",
         type=Path,
-        default=Globals.root,
+        default=config.root,
         help="Path to the invokeai runtime directory",
     )
     parser.add_argument(
@@ -398,7 +390,7 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
 class Mergeapp(npyscreen.NPSAppManaged):
     def __init__(self):
         super().__init__()
-        conf = OmegaConf.load(global_config_file())
+        conf = OmegaConf.load(config.model_conf_path)
         self.model_manager = ModelManager(
             conf, "cpu", "float16"
         )  # precision doesn't really matter here
@@ -429,7 +421,7 @@ def run_cli(args: Namespace):
             f'No --merged_model_name provided. Defaulting to "{args.merged_model_name}"'
         )
 
-        model_manager = ModelManager(OmegaConf.load(global_config_file()))
+        model_manager = ModelManager(OmegaConf.load(config.model_conf_path))
         assert (
             args.clobber or args.merged_model_name not in model_manager.model_names()
         ), f'A model named "{args.merged_model_name}" already exists. Use --clobber to overwrite.'
@@ -440,9 +432,9 @@ def run_cli(args: Namespace):
 
 def main():
     args = _parse_args()
-    global_set_root(args.root_dir)
+    config.root = args.root_dir
 
-    cache_dir = str(global_cache_dir("hub"))
+    cache_dir = config.cache_dir
     os.environ[
         "HF_HOME"
     ] = cache_dir  # because not clear the merge pipeline is honoring cache_dir