Merge branch 'main' into refactor/model_manager_instantiate

docs/installation/050_INSTALLING_MODELS.md

@@ -124,7 +124,7 @@ installation. Examples:
 invokeai-model-install --list controlnet
 
 # (install the model at the indicated URL)
-invokeai-model-install --add http://civitai.com/2860
+invokeai-model-install --add https://civitai.com/api/download/models/128713
 
 # (delete the named model)
 invokeai-model-install --delete sd-1/main/analog-diffusion
@@ -170,4 +170,4 @@ elsewhere on disk and they will be autoimported. You can also create
 subfolders and organize them as you wish.
 
 The location of the autoimport directories are controlled by settings
-in `invokeai.yaml`. See [Configuration](../features/CONFIGURATION.md).
+in `invokeai.yaml`. See [Configuration](../features/CONFIGURATION.md).

invokeai/app/services/config.py

@@ -414,6 +414,7 @@ class InvokeAIAppConfig(InvokeAISettings):
     outdir              : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
     from_file           : Path = Field(default=None, description='Take command input from the indicated file (command-line client only)', category='Paths')
     use_memory_db       : bool = Field(default=False, description='Use in-memory database for storing image metadata', category='Paths')
+    ignore_missing_core_models : bool = Field(default=False, description='Ignore missing models in models/core/convert')
 
     model               : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
 

invokeai/backend/install/check_root.py

@@ -12,16 +12,17 @@ def check_invokeai_root(config: InvokeAIAppConfig):
         assert config.model_conf_path.exists(), f"{config.model_conf_path} not found"
         assert config.db_path.parent.exists(), f"{config.db_path.parent} not found"
         assert config.models_path.exists(), f"{config.models_path} not found"
-        for model in [
-            "CLIP-ViT-bigG-14-laion2B-39B-b160k",
-            "bert-base-uncased",
-            "clip-vit-large-patch14",
-            "sd-vae-ft-mse",
-            "stable-diffusion-2-clip",
-            "stable-diffusion-safety-checker",
-        ]:
-            path = config.models_path / f"core/convert/{model}"
-            assert path.exists(), f"{path} is missing"
+        if not config.ignore_missing_core_models:
+            for model in [
+                "CLIP-ViT-bigG-14-laion2B-39B-b160k",
+                "bert-base-uncased",
+                "clip-vit-large-patch14",
+                "sd-vae-ft-mse",
+                "stable-diffusion-2-clip",
+                "stable-diffusion-safety-checker",
+            ]:
+                path = config.models_path / f"core/convert/{model}"
+                assert path.exists(), f"{path} is missing"
     except Exception as e:
         print()
         print(f"An exception has occurred: {str(e)}")
@@ -32,5 +33,10 @@ def check_invokeai_root(config: InvokeAIAppConfig):
         print(
             '** From the command line, activate the virtual environment and run "invokeai-configure --yes --skip-sd-weights" **'
         )
+        print(
+            '** (To skip this check completely, add "--ignore_missing_core_models" to your CLI args. Not installing '
+            "these core models will prevent the loading of some or all .safetensors and .ckpt files. However, you can "
+            "always come back and install these core models in the future.)"
+        )
         input("Press any key to continue...")
         sys.exit(0)

invokeai/backend/util/devices.py

@@ -1,6 +1,8 @@
 from __future__ import annotations
 
 from contextlib import nullcontext
+from packaging import version
+import platform
 
 import torch
 from torch import autocast
@@ -30,7 +32,7 @@ def choose_precision(device: torch.device) -> str:
         device_name = torch.cuda.get_device_name(device)
         if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):
             return "float16"
-    elif device.type == "mps":
+    elif device.type == "mps" and version.parse(platform.mac_ver()[0]) < version.parse("14.0.0"):
         return "float16"
     return "float32"