Update UI To Use New Model Manager (#3548)

PR for the Model Manager UI work related to 3.0

[DONE]

- Update ModelType Config names to be specific so that the front end can
parse them correctly.
- Rebuild frontend schema to reflect these changes.
- Update Linear UI Text To Image and Image to Image to work with the new
model loader.
- Updated the ModelInput component in the Node Editor to work with the
new changes.

[TODO REMEMBER]

- Add proper types for ModelLoaderType in `ModelSelect.tsx`

[TODO] 

- Everything else.

invokeai/app/api/routers/models.py

@@ -7,8 +7,8 @@ from fastapi.routing import APIRouter, HTTPException
 from pydantic import BaseModel, Field, parse_obj_as
 from ..dependencies import ApiDependencies
 from invokeai.backend import BaseModelType, ModelType
-from invokeai.backend.model_management.models import get_all_model_configs
+from invokeai.backend.model_management.models import OPENAPI_MODEL_CONFIGS
-MODEL_CONFIGS = Union[tuple(get_all_model_configs())]
+MODEL_CONFIGS = Union[tuple(OPENAPI_MODEL_CONFIGS)]
 
 models_router = APIRouter(prefix="/v1/models", tags=["models"])
 
@@ -62,8 +62,7 @@ class ConvertedModelResponse(BaseModel):
     info: DiffusersModelInfo = Field(description="The converted model info")
 
 class ModelsList(BaseModel):
-    models: Dict[BaseModelType, Dict[ModelType, Dict[str, MODEL_CONFIGS]]] # TODO: debug/discuss with frontend
+    models: list[MODEL_CONFIGS]
-    #models: dict[SDModelType, dict[str, Annotated[Union[(DiffusersModelInfo,CkptModelInfo,SafetensorsModelInfo)], Field(discriminator="format")]]]
 
 
 @models_router.get(
@@ -72,10 +71,10 @@ class ModelsList(BaseModel):
     responses={200: {"model": ModelsList }},
 )
 async def list_models(
-    base_model: BaseModelType = Query(
+    base_model: Optional[BaseModelType] = Query(
         default=None, description="Base model"
     ),
-    model_type: ModelType = Query(
+    model_type: Optional[ModelType] = Query(
         default=None, description="The type of model to get"
     ),
 ) -> ModelsList:

invokeai/app/api_app.py

@@ -120,6 +120,22 @@ def custom_openapi():
 
         invoker_schema["output"] = outputs_ref
 
+    from invokeai.backend.model_management.models import get_model_config_enums
+    for model_config_format_enum in set(get_model_config_enums()):
+        name = model_config_format_enum.__qualname__
+
+        if name in openapi_schema["components"]["schemas"]:
+            # print(f"Config with name {name} already defined")
+            continue
+
+        # "BaseModelType":{"title":"BaseModelType","description":"An enumeration.","enum":["sd-1","sd-2"],"type":"string"}
+        openapi_schema["components"]["schemas"][name] = dict(
+            title=name,
+            description="An enumeration.",
+            type="string",
+            enum=list(v.value for v in model_config_format_enum),
+        )
+
     app.openapi_schema = openapi_schema
     return app.openapi_schema
 

invokeai/app/invocations/model.py

@@ -43,12 +43,19 @@ class ModelLoaderOutput(BaseInvocationOutput):
     #fmt: on
 
 
-class SD1ModelLoaderInvocation(BaseInvocation):
+class PipelineModelField(BaseModel):
-    """Loading submodels of selected model."""
+    """Pipeline model field"""
 
-    type: Literal["sd1_model_loader"] = "sd1_model_loader"
+    model_name: str = Field(description="Name of the model")
+    base_model: BaseModelType = Field(description="Base model")
 
-    model_name: str = Field(default="", description="Model to load")
+
+class PipelineModelLoaderInvocation(BaseInvocation):
+    """Loads a pipeline model, outputting its submodels."""
+
+    type: Literal["pipeline_model_loader"] = "pipeline_model_loader"
+
+    model: PipelineModelField = Field(description="The model to load")
     # TODO: precision?
 
     # Schema customisation
@@ -57,22 +64,24 @@ class SD1ModelLoaderInvocation(BaseInvocation):
             "ui": {
                 "tags": ["model", "loader"],
                 "type_hints": {
-                  "model_name": "model" # TODO: rename to model_name?
+                  "model": "model"
                 }
             },
         }
 
     def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
 
-        base_model = BaseModelType.StableDiffusion1 # TODO:
+        base_model = self.model.base_model
+        model_name = self.model.model_name
+        model_type = ModelType.Pipeline
 
         # TODO: not found exceptions
         if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
+            model_name=model_name,
             base_model=base_model,
-            model_type=ModelType.Pipeline,
+            model_type=model_type,
         ):
-            raise Exception(f"Unkown model name: {self.model_name}!")
+            raise Exception(f"Unknown {base_model} {model_type} model: {model_name}")
 
         """
         if not context.services.model_manager.model_exists(
@@ -107,142 +116,39 @@ class SD1ModelLoaderInvocation(BaseInvocation):
         return ModelLoaderOutput(
             unet=UNetField(
                 unet=ModelInfo(
-                    model_name=self.model_name,
+                    model_name=model_name,
                     base_model=base_model,
-                    model_type=ModelType.Pipeline,
+                    model_type=model_type,
                     submodel=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
-                    model_name=self.model_name,
+                    model_name=model_name,
                     base_model=base_model,
-                    model_type=ModelType.Pipeline,
+                    model_type=model_type,
                     submodel=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip=ClipField(
                 tokenizer=ModelInfo(
-                    model_name=self.model_name,
+                    model_name=model_name,
                     base_model=base_model,
-                    model_type=ModelType.Pipeline,
+                    model_type=model_type,
                     submodel=SubModelType.Tokenizer,
                 ),
                 text_encoder=ModelInfo(
-                    model_name=self.model_name,
+                    model_name=model_name,
                     base_model=base_model,
-                    model_type=ModelType.Pipeline,
+                    model_type=model_type,
                     submodel=SubModelType.TextEncoder,
                 ),
                 loras=[],
             ),
             vae=VaeField(
                 vae=ModelInfo(
-                    model_name=self.model_name,
+                    model_name=model_name,
                     base_model=base_model,
-                    model_type=ModelType.Pipeline,
+                    model_type=model_type,
-                    submodel=SubModelType.Vae,
-                ),
-            )
-        )
-
-# TODO: optimize(less code copy)
-class SD2ModelLoaderInvocation(BaseInvocation):
-    """Loading submodels of selected model."""
-
-    type: Literal["sd2_model_loader"] = "sd2_model_loader"
-
-    model_name: str = Field(default="", description="Model to load")
-    # TODO: precision?
-
-    # Schema customisation
-    class Config(InvocationConfig):
-        schema_extra = {
-            "ui": {
-                "tags": ["model", "loader"],
-                "type_hints": {
-                  "model_name": "model" # TODO: rename to model_name?
-                }
-            },
-        }
-
-    def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
-
-        base_model = BaseModelType.StableDiffusion2 # TODO:
-
-        # TODO: not found exceptions
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            base_model=base_model,
-            model_type=ModelType.Pipeline,
-        ):
-            raise Exception(f"Unkown model name: {self.model_name}!")
-
-        """
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.Tokenizer,
-        ):
-            raise Exception(
-                f"Failed to find tokenizer submodel in {self.model_name}! Check if model corrupted"
-            )
-
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.TextEncoder,
-        ):
-            raise Exception(
-                f"Failed to find text_encoder submodel in {self.model_name}! Check if model corrupted"
-            )
-
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.UNet,
-        ):
-            raise Exception(
-                f"Failed to find unet submodel from {self.model_name}! Check if model corrupted"
-            )
-        """
-
-
-        return ModelLoaderOutput(
-            unet=UNetField(
-                unet=ModelInfo(
-                    model_name=self.model_name,
-                    base_model=base_model,
-                    model_type=ModelType.Pipeline,
-                    submodel=SubModelType.UNet,
-                ),
-                scheduler=ModelInfo(
-                    model_name=self.model_name,
-                    base_model=base_model,
-                    model_type=ModelType.Pipeline,
-                    submodel=SubModelType.Scheduler,
-                ),
-                loras=[],
-            ),
-            clip=ClipField(
-                tokenizer=ModelInfo(
-                    model_name=self.model_name,
-                    base_model=base_model,
-                    model_type=ModelType.Pipeline,
-                    submodel=SubModelType.Tokenizer,
-                ),
-                text_encoder=ModelInfo(
-                    model_name=self.model_name,
-                    base_model=base_model,
-                    model_type=ModelType.Pipeline,
-                    submodel=SubModelType.TextEncoder,
-                ),
-                loras=[],
-            ),
-            vae=VaeField(
-                vae=ModelInfo(
-                    model_name=self.model_name,
-                    base_model=base_model,
-                    model_type=ModelType.Pipeline,
                     submodel=SubModelType.Vae,
                 ),
             )

invokeai/app/services/model_manager_service.py

@@ -5,7 +5,7 @@ from __future__ import annotations
 import torch
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Union, Callable, List, Tuple, types, TYPE_CHECKING
+from typing import Optional, Union, Callable, List, Tuple, types, TYPE_CHECKING
 from dataclasses import dataclass
 
 from invokeai.backend.model_management.model_manager import (
@@ -69,19 +69,6 @@ class ModelManagerServiceBase(ABC):
     ) -> bool:
         pass
 
-    @abstractmethod
-    def default_model(self) -> Optional[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Returns the name and typeof the default model, or None
-        if none is defined.
-        """
-        pass
-
-    @abstractmethod
-    def set_default_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType):
-        """Sets the default model to the indicated name."""
-        pass
-
     @abstractmethod
     def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
         """
@@ -270,17 +257,6 @@ class ModelManagerService(ModelManagerServiceBase):
             model_type,
         )
 
-    def default_model(self) -> Optional[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Returns the name of the default model, or None
-        if none is defined.
-        """
-        return self.mgr.default_model()
-
-    def set_default_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType):
-        """Sets the default model to the indicated name."""
-        self.mgr.set_default_model(model_name, base_model, model_type)
-
     def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
         """
         Given a model name returns a dict-like (OmegaConf) object describing it.
@@ -297,21 +273,10 @@ class ModelManagerService(ModelManagerServiceBase):
         self,
         base_model: Optional[BaseModelType] = None,
         model_type: Optional[ModelType] = None
-    ) -> dict:
+    ) -> list[dict]:
+    # ) -> dict:
         """
-        Return a dict of models in the format:
+        Return a list of models.
-        { model_type1:
-          { model_name1: {'status': 'active'|'cached'|'not loaded',
-                         'model_name' : name,
-                         'model_type' : SDModelType,
-                         'description': description,
-                         'format': 'folder'|'safetensors'|'ckpt'
-                         },
-            model_name2: { etc }
-          },
-          model_type2:
-            { model_name_n: etc
-        }
         """
         return self.mgr.list_models(base_model, model_type)
 

invokeai/backend/model_management/model_manager.py

@@ -266,6 +266,8 @@ class ModelManager(object):
         for model_key, model_config in config.items():
             model_name, base_model, model_type = self.parse_key(model_key)
             model_class = MODEL_CLASSES[base_model][model_type]
+            # alias for config file
+            model_config["model_format"] = model_config.pop("format")
             self.models[model_key] = model_class.create_config(**model_config)
 
         # check config version number and update on disk/RAM if necessary
@@ -445,38 +447,6 @@ class ModelManager(object):
             _cache = self.cache,
         )
 
-    def default_model(self) -> Optional[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Returns the name of the default model, or None
-        if none is defined.
-        """
-        for model_key, model_config in self.models.items():
-            if model_config.default:
-                return self.parse_key(model_key)
-
-        for model_key, _ in self.models.items():
-            return self.parse_key(model_key)
-        else:
-            return None # TODO: or redo as (None, None, None)
-
-    def set_default_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> None:
-        """
-        Set the default model. The change will not take
-        effect until you call model_manager.commit()
-        """
-
-        model_key = self.model_key(model_name, base_model, model_type)
-        if model_key not in self.models:
-            raise Exception(f"Unknown model: {model_key}")
-
-        for cur_model_key, config in self.models.items():
-            config.default = cur_model_key == model_key
-
     def model_info(
         self,
         model_name: str,
@@ -503,9 +473,9 @@ class ModelManager(object):
         self,
         base_model: Optional[BaseModelType] = None,
         model_type: Optional[ModelType] = None,
-    ) -> Dict[str, Dict[str, str]]:
+    ) -> list[dict]:
         """
-        Return a dict of models, in format [base_model][model_type][model_name]
+        Return a list of models.
 
         Please use model_manager.models() to get all the model names,
         model_manager.model_info('model-name') to get the stanza for the model
@@ -513,7 +483,7 @@ class ModelManager(object):
         object derived from models.yaml
         """
 
-        models = dict()
+        models = []
         for model_key in sorted(self.models, key=str.casefold):
             model_config = self.models[model_key]
 
@@ -523,18 +493,16 @@ class ModelManager(object):
             if model_type is not None and cur_model_type != model_type:
                 continue
 
-            if cur_base_model not in models:
+            model_dict = dict(
-                models[cur_base_model] = dict()
-            if cur_model_type not in models[cur_base_model]:
-                models[cur_base_model][cur_model_type] = dict()
-
-            models[cur_base_model][cur_model_type][cur_model_name] = dict(
                 **model_config.dict(exclude_defaults=True),
+                # OpenAPIModelInfoBase
                 name=cur_model_name,
                 base_model=cur_base_model,
                 type=cur_model_type,
             )
 
+            models.append(model_dict)
+
         return models
 
     def print_models(self) -> None:
@@ -646,7 +614,9 @@ class ModelManager(object):
             model_class = MODEL_CLASSES[base_model][model_type]
             if model_class.save_to_config:
                 # TODO: or exclude_unset better fits here?
-                data_to_save[model_key] = model_config.dict(exclude_defaults=True)
+                data_to_save[model_key] = model_config.dict(exclude_defaults=True, exclude={"error"})
+                # alias for config file
+                data_to_save[model_key]["format"] = data_to_save[model_key].pop("model_format")
 
         yaml_str = OmegaConf.to_yaml(data_to_save)
         config_file_path = conf_file or self.config_path

invokeai/backend/model_management/models/__init__.py

@@ -1,3 +1,7 @@
+import inspect
+from enum import Enum
+from pydantic import BaseModel
+from typing import Literal, get_origin
 from .base import BaseModelType, ModelType, SubModelType, ModelBase, ModelConfigBase, ModelVariantType, SchedulerPredictionType, ModelError, SilenceWarnings
 from .stable_diffusion import StableDiffusion1Model, StableDiffusion2Model
 from .vae import VaeModel
@@ -29,10 +33,63 @@ MODEL_CLASSES = {
     #},
 }
 
-def get_all_model_configs():
+MODEL_CONFIGS = list()
-    configs = set()
+OPENAPI_MODEL_CONFIGS = list()
-    for models in MODEL_CLASSES.values():
+
-        for _, model in models.items():
+class OpenAPIModelInfoBase(BaseModel):
-            configs.update(model._get_configs().values())
+    name: str
-    configs.discard(None)
+    base_model: BaseModelType
-    return list(configs) # TODO: set, list or tuple
+    type: ModelType
+
+
+for base_model, models in MODEL_CLASSES.items():
+    for model_type, model_class in models.items():
+        model_configs = set(model_class._get_configs().values())
+        model_configs.discard(None)
+        MODEL_CONFIGS.extend(model_configs)
+
+        for cfg in model_configs:
+            model_name, cfg_name = cfg.__qualname__.split('.')[-2:]
+            openapi_cfg_name = model_name + cfg_name
+            if openapi_cfg_name in vars():
+                continue
+
+            api_wrapper = type(openapi_cfg_name, (cfg, OpenAPIModelInfoBase), dict(
+                __annotations__ = dict(
+                    type=Literal[model_type.value],
+                ),
+            ))
+
+            #globals()[openapi_cfg_name] = api_wrapper
+            vars()[openapi_cfg_name] = api_wrapper
+            OPENAPI_MODEL_CONFIGS.append(api_wrapper)
+
+def get_model_config_enums():
+    enums = list()
+
+    for model_config in MODEL_CONFIGS:
+        fields = inspect.get_annotations(model_config)
+        try:
+            field = fields["model_format"]
+        except:
+            raise Exception("format field not found")
+
+        # model_format: None
+        # model_format: SomeModelFormat
+        # model_format: Literal[SomeModelFormat.Diffusers]
+        # model_format: Literal[SomeModelFormat.Diffusers, SomeModelFormat.Checkpoint]
+
+        if isinstance(field, type) and issubclass(field, str) and issubclass(field, Enum):
+            enums.append(field)
+
+        elif get_origin(field) is Literal and all(isinstance(arg, str) and isinstance(arg, Enum) for arg in field.__args__):
+            enums.append(type(field.__args__[0]))
+
+        elif field is None:
+            pass
+
+        else:
+            raise Exception(f"Unsupported format definition in {model_configs.__qualname__}")
+
+    return enums
+

invokeai/backend/model_management/models/base.py

@@ -48,12 +48,10 @@ class ModelError(str, Enum):
 
 class ModelConfigBase(BaseModel):
     path: str # or Path
-    #name: str # not included as present in model key
     description: Optional[str] = Field(None)
-    format: Optional[str] = Field(None)
+    model_format: Optional[str] = Field(None)
-    default: Optional[bool] = Field(False)
     # do not save to config
-    error: Optional[ModelError] = Field(None, exclude=True)
+    error: Optional[ModelError] = Field(None)
 
     class Config:
         use_enum_values = True
@@ -94,6 +92,11 @@ class ModelBase(metaclass=ABCMeta):
     def _hf_definition_to_type(self, subtypes: List[str]) -> Type:
         if len(subtypes) < 2:
             raise Exception("Invalid subfolder definition!")
+        if all(t is None for t in subtypes):
+            return None
+        elif any(t is None for t in subtypes):
+            raise Exception(f"Unsupported definition: {subtypes}")
+        
         if subtypes[0] in ["diffusers", "transformers"]:
             res_type = sys.modules[subtypes[0]]
             subtypes = subtypes[1:]
@@ -122,47 +125,41 @@ class ModelBase(metaclass=ABCMeta):
                 continue
 
             fields = inspect.get_annotations(value)
-            if "format" not in fields:
+            try:
-                raise Exception("Invalid config definition - format field not found")
+                field = fields["model_format"]
+            except:
+                raise Exception(f"Invalid config definition - format field not found({cls.__qualname__})")
 
-            format_type = typing.get_origin(fields["format"])
+            if isinstance(field, type) and issubclass(field, str) and issubclass(field, Enum):
-            if format_type not in {None, Literal, Union}:
+                for model_format in field:
-                raise Exception(f"Invalid config definition - unknown format type: {fields['format']}")
+                    configs[model_format.value] = value
 
-            if format_type is Union and not all(typing.get_origin(v) in {None, Literal} for v in fields["format"].__args__):
+            elif typing.get_origin(field) is Literal and all(isinstance(arg, str) and isinstance(arg, Enum) for arg in field.__args__):
-                raise Exception(f"Invalid config definition - unknown format type: {fields['format']}")
+                for model_format in field.__args__:
+                    configs[model_format.value] = value
+
+            elif field is None:
+                configs[None] = value
 
-            if format_type == Union:
-                f_fields = fields["format"].__args__
             else:
-                f_fields = (fields["format"],)
+                raise Exception(f"Unsupported format definition in {cls.__qualname__}")
-                    
-
-            for field in f_fields:
-                if field is None:
-                    format_name = None
-                else:
-                    format_name = field.__args__[0]
-
-                configs[format_name] = value # TODO: error when override(multiple)?
-
 
         cls.__configs = configs
         return cls.__configs
 
     @classmethod
     def create_config(cls, **kwargs) -> ModelConfigBase:
-        if "format" not in kwargs:
+        if "model_format" not in kwargs:
-            raise Exception("Field 'format' not found in model config")
+            raise Exception("Field 'model_format' not found in model config")
 
         configs = cls._get_configs()
-        return configs[kwargs["format"]](**kwargs)
+        return configs[kwargs["model_format"]](**kwargs)
 
     @classmethod
     def probe_config(cls, path: str, **kwargs) -> ModelConfigBase:
         return cls.create_config(
             path=path,
-            format=cls.detect_format(path),
+            model_format=cls.detect_format(path),
         )
 
     @classmethod

invokeai/backend/model_management/models/controlnet.py

@@ -1,5 +1,6 @@
 import os
 import torch
+from enum import Enum
 from pathlib import Path
 from typing import Optional, Union, Literal
 from .base import (
@@ -14,12 +15,16 @@ from .base import (
     classproperty,
 )
 
+class ControlNetModelFormat(str, Enum):
+    Checkpoint = "checkpoint"
+    Diffusers = "diffusers"
+
 class ControlNetModel(ModelBase):
     #model_class: Type
     #model_size: int
 
     class Config(ModelConfigBase):
-        format: Union[Literal["checkpoint"], Literal["diffusers"]]
+        model_format: ControlNetModelFormat
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
         assert model_type == ModelType.ControlNet
@@ -69,9 +74,9 @@ class ControlNetModel(ModelBase):
     @classmethod
     def detect_format(cls, path: str):
         if os.path.isdir(path):
-            return "diffusers"
+            return ControlNetModelFormat.Diffusers
         else:
-            return "checkpoint"
+            return ControlNetModelFormat.Checkpoint
 
     @classmethod
     def convert_if_required(
@@ -81,7 +86,7 @@ class ControlNetModel(ModelBase):
         config: ModelConfigBase, # empty config or config of parent model
         base_model: BaseModelType,
     ) -> str:
-        if cls.detect_format(model_path) != "diffusers":
+        if cls.detect_format(model_path) != ControlNetModelFormat.Diffusers:
-            raise NotImlemetedError("Checkpoint controlnet models currently unsupported")
+            raise NotImplementedError("Checkpoint controlnet models currently unsupported")
         else:
             return model_path

invokeai/backend/model_management/models/lora.py

@@ -1,5 +1,6 @@
 import os
 import torch
+from enum import Enum
 from typing import Optional, Union, Literal
 from .base import (
     ModelBase,
@@ -12,11 +13,15 @@ from .base import (
 # TODO: naming
 from ..lora import LoRAModel as LoRAModelRaw
 
+class LoRAModelFormat(str, Enum):
+    LyCORIS = "lycoris"
+    Diffusers = "diffusers"
+
 class LoRAModel(ModelBase):
     #model_size: int
 
     class Config(ModelConfigBase):
-        format: Union[Literal["lycoris"], Literal["diffusers"]]
+        model_format: LoRAModelFormat # TODO:
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
         assert model_type == ModelType.Lora
@@ -52,9 +57,9 @@ class LoRAModel(ModelBase):
     @classmethod
     def detect_format(cls, path: str):
         if os.path.isdir(path):
-            return "diffusers"
+            return LoRAModelFormat.Diffusers
         else:
-            return "lycoris"
+            return LoRAModelFormat.LyCORIS
 
     @classmethod
     def convert_if_required(
@@ -64,7 +69,7 @@ class LoRAModel(ModelBase):
         config: ModelConfigBase,
         base_model: BaseModelType,
     ) -> str:
-        if cls.detect_format(model_path) == "diffusers":
+        if cls.detect_format(model_path) == LoRAModelFormat.Diffusers:
             # TODO: add diffusers lora when it stabilizes a bit
             raise NotImplementedError("Diffusers lora not supported")
         else:

invokeai/backend/model_management/models/stable_diffusion.py

@@ -1,5 +1,6 @@
 import os
 import json
+from enum import Enum
 from pydantic import Field
 from pathlib import Path
 from typing import Literal, Optional, Union
@@ -19,16 +20,19 @@ from .base import (
 from invokeai.app.services.config import InvokeAIAppConfig
 from omegaconf import OmegaConf
 
+class StableDiffusion1ModelFormat(str, Enum):
+    Checkpoint = "checkpoint"
+    Diffusers = "diffusers"
 
 class StableDiffusion1Model(DiffusersModel):
 
     class DiffusersConfig(ModelConfigBase):
-        format: Literal["diffusers"]
+        model_format: Literal[StableDiffusion1ModelFormat.Diffusers]
         vae: Optional[str] = Field(None)
         variant: ModelVariantType
 
     class CheckpointConfig(ModelConfigBase):
-        format: Literal["checkpoint"]
+        model_format: Literal[StableDiffusion1ModelFormat.Checkpoint]
         vae: Optional[str] = Field(None)
         config: Optional[str] = Field(None)
         variant: ModelVariantType
@@ -47,7 +51,7 @@ class StableDiffusion1Model(DiffusersModel):
     def probe_config(cls, path: str, **kwargs):
         model_format = cls.detect_format(path)
         ckpt_config_path = kwargs.get("config", None)
-        if model_format == "checkpoint":
+        if model_format == StableDiffusion1ModelFormat.Checkpoint:
             if ckpt_config_path:
                 ckpt_config = OmegaConf.load(ckpt_config_path)
                 ckpt_config["model"]["params"]["unet_config"]["params"]["in_channels"]
@@ -57,7 +61,7 @@ class StableDiffusion1Model(DiffusersModel):
                 checkpoint = checkpoint.get('state_dict', checkpoint)
                 in_channels = checkpoint["model.diffusion_model.input_blocks.0.0.weight"].shape[1]
 
-        elif model_format == "diffusers":
+        elif model_format == StableDiffusion1ModelFormat.Diffusers:
             unet_config_path = os.path.join(path, "unet", "config.json")
             if os.path.exists(unet_config_path):
                 with open(unet_config_path, "r") as f:
@@ -80,7 +84,7 @@ class StableDiffusion1Model(DiffusersModel):
 
         return cls.create_config(
             path=path,
-            format=model_format,
+            model_format=model_format,
 
             config=ckpt_config_path,
             variant=variant,
@@ -93,9 +97,9 @@ class StableDiffusion1Model(DiffusersModel):
     @classmethod
     def detect_format(cls, model_path: str):
         if os.path.isdir(model_path):
-            return "diffusers"
+            return StableDiffusion1ModelFormat.Diffusers
         else:
-            return "checkpoint"
+            return StableDiffusion1ModelFormat.Checkpoint
 
     @classmethod
     def convert_if_required(
@@ -116,19 +120,22 @@ class StableDiffusion1Model(DiffusersModel):
         else:
             return model_path
 
+class StableDiffusion2ModelFormat(str, Enum):
+    Checkpoint = "checkpoint"
+    Diffusers = "diffusers"
 
 class StableDiffusion2Model(DiffusersModel):
 
     # TODO: check that configs overwriten properly
     class DiffusersConfig(ModelConfigBase):
-        format: Literal["diffusers"]
+        model_format: Literal[StableDiffusion2ModelFormat.Diffusers]
         vae: Optional[str] = Field(None)
         variant: ModelVariantType
         prediction_type: SchedulerPredictionType
         upcast_attention: bool
 
     class CheckpointConfig(ModelConfigBase):
-        format: Literal["checkpoint"]
+        model_format: Literal[StableDiffusion2ModelFormat.Checkpoint]
         vae: Optional[str] = Field(None)
         config: Optional[str] = Field(None)
         variant: ModelVariantType
@@ -149,7 +156,7 @@ class StableDiffusion2Model(DiffusersModel):
     def probe_config(cls, path: str, **kwargs):
         model_format = cls.detect_format(path)
         ckpt_config_path = kwargs.get("config", None)
-        if model_format == "checkpoint":
+        if model_format == StableDiffusion2ModelFormat.Checkpoint:
             if ckpt_config_path:
                 ckpt_config = OmegaConf.load(ckpt_config_path)
                 ckpt_config["model"]["params"]["unet_config"]["params"]["in_channels"]
@@ -159,7 +166,7 @@ class StableDiffusion2Model(DiffusersModel):
                 checkpoint = checkpoint.get('state_dict', checkpoint)
                 in_channels = checkpoint["model.diffusion_model.input_blocks.0.0.weight"].shape[1]
 
-        elif model_format == "diffusers":
+        elif model_format == StableDiffusion2ModelFormat.Diffusers:
             unet_config_path = os.path.join(path, "unet", "config.json")
             if os.path.exists(unet_config_path):
                 with open(unet_config_path, "r") as f:
@@ -191,7 +198,7 @@ class StableDiffusion2Model(DiffusersModel):
 
         return cls.create_config(
             path=path,
-            format=model_format,
+            model_format=model_format,
 
             config=ckpt_config_path,
             variant=variant,
@@ -206,9 +213,9 @@ class StableDiffusion2Model(DiffusersModel):
     @classmethod
     def detect_format(cls, model_path: str):
         if os.path.isdir(model_path):
-            return "diffusers"
+            return StableDiffusion2ModelFormat.Diffusers
         else:
-            return "checkpoint"
+            return StableDiffusion2ModelFormat.Checkpoint
 
     @classmethod
     def convert_if_required(
@@ -281,8 +288,8 @@ def _convert_ckpt_and_cache(
         prediction_type = SchedulerPredictionType.Epsilon
 
     elif version == BaseModelType.StableDiffusion2:
-        upcast_attention = config.upcast_attention
+        upcast_attention = model_config.upcast_attention
-        prediction_type = config.prediction_type
+        prediction_type = model_config.prediction_type
 
     else:
         raise Exception(f"Unknown model provided: {version}")

invokeai/backend/model_management/models/textual_inversion.py

@@ -16,7 +16,7 @@ class TextualInversionModel(ModelBase):
     #model_size: int
 
     class Config(ModelConfigBase):
-        format: None
+        model_format: None
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
         assert model_type == ModelType.TextualInversion

invokeai/backend/model_management/models/vae.py

@@ -1,5 +1,7 @@
 import os
 import torch
+import safetensors
+from enum import Enum
 from pathlib import Path
 from typing import Optional, Union, Literal
 from .base import (
@@ -18,12 +20,16 @@ from invokeai.app.services.config import InvokeAIAppConfig
 from diffusers.utils import is_safetensors_available
 from omegaconf import OmegaConf
 
+class VaeModelFormat(str, Enum):
+    Checkpoint = "checkpoint"
+    Diffusers = "diffusers"
+
 class VaeModel(ModelBase):
     #vae_class: Type
     #model_size: int
 
     class Config(ModelConfigBase):
-        format: Union[Literal["checkpoint"], Literal["diffusers"]]
+        model_format: VaeModelFormat
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
         assert model_type == ModelType.Vae
@@ -70,9 +76,9 @@ class VaeModel(ModelBase):
     @classmethod
     def detect_format(cls, path: str):
         if os.path.isdir(path):
-            return "diffusers"
+            return VaeModelFormat.Diffusers
         else:
-            return "checkpoint"
+            return VaeModelFormat.Checkpoint
 
     @classmethod
     def convert_if_required(
@@ -82,7 +88,7 @@ class VaeModel(ModelBase):
         config: ModelConfigBase, # empty config or config of parent model
         base_model: BaseModelType,
     ) -> str:
-        if cls.detect_format(model_path) != "diffusers":
+        if cls.detect_format(model_path) == VaeModelFormat.Checkpoint:
             return _convert_vae_ckpt_and_cache(
                 weights_path=model_path,
                 output_path=output_path,

invokeai/frontend/web/src/app/components/App.tsx

@@ -24,6 +24,7 @@ import Toaster from './Toaster';
 import DeleteImageModal from 'features/gallery/components/DeleteImageModal';
 import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale';
 import UpdateImageBoardModal from '../../features/gallery/components/Boards/UpdateImageBoardModal';
+import { useListModelsQuery } from 'services/apiSlice';
 
 const DEFAULT_CONFIG = {};
 
@@ -46,6 +47,18 @@ const App = ({
 
   const isApplicationReady = useIsApplicationReady();
 
+  const { data: pipelineModels } = useListModelsQuery({
+    model_type: 'pipeline',
+  });
+  const { data: controlnetModels } = useListModelsQuery({
+    model_type: 'controlnet',
+  });
+  const { data: vaeModels } = useListModelsQuery({ model_type: 'vae' });
+  const { data: loraModels } = useListModelsQuery({ model_type: 'lora' });
+  const { data: embeddingModels } = useListModelsQuery({
+    model_type: 'embedding',
+  });
+
   const [loadingOverridden, setLoadingOverridden] = useState(false);
 
   const dispatch = useAppDispatch();

invokeai/frontend/web/src/app/store/enhancers/reduxRemember/serialize.ts

@@ -5,7 +5,6 @@ import { lightboxPersistDenylist } from 'features/lightbox/store/lightboxPersist
 import { nodesPersistDenylist } from 'features/nodes/store/nodesPersistDenylist';
 import { generationPersistDenylist } from 'features/parameters/store/generationPersistDenylist';
 import { postprocessingPersistDenylist } from 'features/parameters/store/postprocessingPersistDenylist';
-import { modelsPersistDenylist } from 'features/system/store/modelsPersistDenylist';
 import { systemPersistDenylist } from 'features/system/store/systemPersistDenylist';
 import { uiPersistDenylist } from 'features/ui/store/uiPersistDenylist';
 import { omit } from 'lodash-es';
@@ -18,7 +17,6 @@ const serializationDenylist: {
   gallery: galleryPersistDenylist,
   generation: generationPersistDenylist,
   lightbox: lightboxPersistDenylist,
-  models: modelsPersistDenylist,
   nodes: nodesPersistDenylist,
   postprocessing: postprocessingPersistDenylist,
   system: systemPersistDenylist,

invokeai/frontend/web/src/app/store/enhancers/reduxRemember/unserialize.ts

@@ -7,7 +7,6 @@ import { initialNodesState } from 'features/nodes/store/nodesSlice';
 import { initialGenerationState } from 'features/parameters/store/generationSlice';
 import { initialPostprocessingState } from 'features/parameters/store/postprocessingSlice';
 import { initialConfigState } from 'features/system/store/configSlice';
-import { initialModelsState } from 'features/system/store/modelSlice';
 import { initialSystemState } from 'features/system/store/systemSlice';
 import { initialHotkeysState } from 'features/ui/store/hotkeysSlice';
 import { initialUIState } from 'features/ui/store/uiSlice';
@@ -21,7 +20,6 @@ const initialStates: {
   gallery: initialGalleryState,
   generation: initialGenerationState,
   lightbox: initialLightboxState,
-  models: initialModelsState,
   nodes: initialNodesState,
   postprocessing: initialPostprocessingState,
   system: initialSystemState,

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected.ts

@@ -1,9 +1,8 @@
-import { startAppListening } from '../..';
 import { log } from 'app/logging/useLogger';
 import { appSocketConnected, socketConnected } from 'services/events/actions';
 import { receivedPageOfImages } from 'services/thunks/image';
-import { receivedModels } from 'services/thunks/model';
 import { receivedOpenAPISchema } from 'services/thunks/schema';
+import { startAppListening } from '../..';
 
 const moduleLog = log.child({ namespace: 'socketio' });
 
@@ -15,7 +14,7 @@ export const addSocketConnectedEventListener = () => {
 
       moduleLog.debug({ timestamp }, 'Connected');
 
-      const { models, nodes, config, images } = getState();
+      const { nodes, config, images } = getState();
 
       const { disabledTabs } = config;
 
@@ -28,10 +27,6 @@ export const addSocketConnectedEventListener = () => {
         );
       }
 
-      if (!models.ids.length) {
-        dispatch(receivedModels());
-      }
-
       if (!nodes.schema && !disabledTabs.includes('nodes')) {
         dispatch(receivedOpenAPISchema());
       }

invokeai/frontend/web/src/app/store/store.ts

@@ -5,34 +5,32 @@ import {
   configureStore,
 } from '@reduxjs/toolkit';
 
-import { rememberReducer, rememberEnhancer } from 'redux-remember';
 import dynamicMiddlewares from 'redux-dynamic-middlewares';
+import { rememberEnhancer, rememberReducer } from 'redux-remember';
 
 import canvasReducer from 'features/canvas/store/canvasSlice';
+import controlNetReducer from 'features/controlNet/store/controlNetSlice';
 import galleryReducer from 'features/gallery/store/gallerySlice';
 import imagesReducer from 'features/gallery/store/imagesSlice';
 import lightboxReducer from 'features/lightbox/store/lightboxSlice';
 import generationReducer from 'features/parameters/store/generationSlice';
-import controlNetReducer from 'features/controlNet/store/controlNetSlice';
 import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
 import systemReducer from 'features/system/store/systemSlice';
 // import sessionReducer from 'features/system/store/sessionSlice';
-import configReducer from 'features/system/store/configSlice';
-import uiReducer from 'features/ui/store/uiSlice';
-import hotkeysReducer from 'features/ui/store/hotkeysSlice';
-import modelsReducer from 'features/system/store/modelSlice';
 import nodesReducer from 'features/nodes/store/nodesSlice';
 import boardsReducer from 'features/gallery/store/boardSlice';
+import configReducer from 'features/system/store/configSlice';
+import hotkeysReducer from 'features/ui/store/hotkeysSlice';
+import uiReducer from 'features/ui/store/uiSlice';
 
 import { listenerMiddleware } from './middleware/listenerMiddleware';
 
 import { actionSanitizer } from './middleware/devtools/actionSanitizer';
-import { stateSanitizer } from './middleware/devtools/stateSanitizer';
 import { actionsDenylist } from './middleware/devtools/actionsDenylist';
-
+import { stateSanitizer } from './middleware/devtools/stateSanitizer';
+import { LOCALSTORAGE_PREFIX } from './constants';
 import { serialize } from './enhancers/reduxRemember/serialize';
 import { unserialize } from './enhancers/reduxRemember/unserialize';
-import { LOCALSTORAGE_PREFIX } from './constants';
 import { api } from 'services/apiSlice';
 
 const allReducers = {
@@ -40,7 +38,6 @@ const allReducers = {
   gallery: galleryReducer,
   generation: generationReducer,
   lightbox: lightboxReducer,
-  models: modelsReducer,
   nodes: nodesReducer,
   postprocessing: postprocessingReducer,
   system: systemReducer,
@@ -50,8 +47,8 @@ const allReducers = {
   images: imagesReducer,
   controlNet: controlNetReducer,
   boards: boardsReducer,
-  [api.reducerPath]: api.reducer,
   // session: sessionReducer,
+  [api.reducerPath]: api.reducer,
 };
 
 const rootReducer = combineReducers(allReducers);
@@ -63,7 +60,6 @@ const rememberedKeys: (keyof typeof allReducers)[] = [
   'gallery',
   'generation',
   'lightbox',
-  // 'models',
   'nodes',
   'postprocessing',
   'system',

invokeai/frontend/web/src/features/nodes/components/fields/ModelInputFieldComponent.tsx

@@ -1,28 +1,18 @@
-import { Select } from '@chakra-ui/react';
+import { SelectItem } from '@mantine/core';
-import { createSelector } from '@reduxjs/toolkit';
+import { useAppDispatch } from 'app/store/storeHooks';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   ModelInputFieldTemplate,
   ModelInputFieldValue,
 } from 'features/nodes/types/types';
-import { selectModelsIds } from 'features/system/store/modelSlice';
-import { isEqual } from 'lodash-es';
-import { ChangeEvent, memo } from 'react';
-import { FieldComponentProps } from './types';
 
-const availableModelsSelector = createSelector(
+import { memo, useCallback, useEffect, useMemo } from 'react';
-  [selectModelsIds],
+import { FieldComponentProps } from './types';
-  (allModelNames) => {
+import { forEach, isString } from 'lodash-es';
-    return { allModelNames };
+import { MODEL_TYPE_MAP as BASE_MODEL_NAME_MAP } from 'features/system/components/ModelSelect';
-    // return map(modelList, (_, name) => name);
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
-  },
+import { useTranslation } from 'react-i18next';
-  {
+import { useListModelsQuery } from 'services/apiSlice';
-    memoizeOptions: {
-      resultEqualityCheck: isEqual,
-    },
-  }
-);
 
 const ModelInputFieldComponent = (
   props: FieldComponentProps<ModelInputFieldValue, ModelInputFieldTemplate>
@@ -30,28 +20,82 @@ const ModelInputFieldComponent = (
   const { nodeId, field } = props;
 
   const dispatch = useAppDispatch();
+  const { t } = useTranslation();
 
-  const { allModelNames } = useAppSelector(availableModelsSelector);
+  const { data: pipelineModels } = useListModelsQuery({
+    model_type: 'pipeline',
+  });
 
-  const handleValueChanged = (e: ChangeEvent<HTMLSelectElement>) => {
+  const data = useMemo(() => {
-    dispatch(
+    if (!pipelineModels) {
-      fieldValueChanged({
+      return [];
-        nodeId,
+    }
-        fieldName: field.name,
+
-        value: e.target.value,
+    const data: SelectItem[] = [];
-      })
+
-    );
+    forEach(pipelineModels.entities, (model, id) => {
-  };
+      if (!model) {
+        return;
+      }
+
+      data.push({
+        value: id,
+        label: model.name,
+        group: BASE_MODEL_NAME_MAP[model.base_model],
+      });
+    });
+
+    return data;
+  }, [pipelineModels]);
+
+  const selectedModel = useMemo(
+    () => pipelineModels?.entities[field.value ?? pipelineModels.ids[0]],
+    [pipelineModels?.entities, pipelineModels?.ids, field.value]
+  );
+
+  const handleValueChanged = useCallback(
+    (v: string | null) => {
+      if (!v) {
+        return;
+      }
+
+      dispatch(
+        fieldValueChanged({
+          nodeId,
+          fieldName: field.name,
+          value: v,
+        })
+      );
+    },
+    [dispatch, field.name, nodeId]
+  );
+
+  useEffect(() => {
+    if (field.value && pipelineModels?.ids.includes(field.value)) {
+      return;
+    }
+
+    const firstModel = pipelineModels?.ids[0];
+
+    if (!isString(firstModel)) {
+      return;
+    }
+
+    handleValueChanged(firstModel);
+  }, [field.value, handleValueChanged, pipelineModels?.ids]);
 
   return (
-    <Select
+    <IAIMantineSelect
+      tooltip={selectedModel?.description}
+      label={
+        selectedModel?.base_model &&
+        BASE_MODEL_NAME_MAP[selectedModel?.base_model]
+      }
+      value={field.value}
+      placeholder="Pick one"
+      data={data}
       onChange={handleValueChanged}
-      value={field.value || allModelNames[0]}
+    />
-    >
-      {allModelNames.map((option) => (
-        <option key={option}>{option}</option>
-      ))}
-    </Select>
   );
 };
 

invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts

@@ -101,21 +101,6 @@ const nodesSlice = createSlice({
     builder.addCase(receivedOpenAPISchema.fulfilled, (state, action) => {
       state.schema = action.payload;
     });
-
-    builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-      const { image_name, image_url, thumbnail_url } = action.payload;
-
-      state.nodes.forEach((node) => {
-        forEach(node.data.inputs, (input) => {
-          if (input.type === 'image') {
-            if (input.value?.image_name === image_name) {
-              input.value.image_url = image_url;
-              input.value.thumbnail_url = thumbnail_url;
-            }
-          }
-        });
-      });
-    });
   },
 });
 

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasImageToImageGraph.ts

@@ -23,6 +23,7 @@ import {
 } from './constants';
 import { set } from 'lodash-es';
 import { addControlNetToLinearGraph } from '../addControlNetToLinearGraph';
+import { modelIdToPipelineModelField } from '../modelIdToPipelineModelField';
 
 const moduleLog = log.child({ namespace: 'nodes' });
 
@@ -36,7 +37,7 @@ export const buildCanvasImageToImageGraph = (
   const {
     positivePrompt,
     negativePrompt,
-    model: model_name,
+    model: modelId,
     cfgScale: cfg_scale,
     scheduler,
     steps,
@@ -49,6 +50,8 @@ export const buildCanvasImageToImageGraph = (
   // The bounding box determines width and height, not the width and height params
   const { width, height } = state.canvas.boundingBoxDimensions;
 
+  const model = modelIdToPipelineModelField(modelId);
+
   /**
    * The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
    * full graph here as a template. Then use the parameters from app state and set friendlier node
@@ -85,9 +88,9 @@ export const buildCanvasImageToImageGraph = (
         id: NOISE,
       },
       [MODEL_LOADER]: {
-        type: 'sd1_model_loader',
+        type: 'pipeline_model_loader',
         id: MODEL_LOADER,
-        model_name,
+        model,
       },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasInpaintGraph.ts

@@ -17,6 +17,7 @@ import {
   INPAINT_GRAPH,
   INPAINT,
 } from './constants';
+import { modelIdToPipelineModelField } from '../modelIdToPipelineModelField';
 
 const moduleLog = log.child({ namespace: 'nodes' });
 
@@ -31,7 +32,7 @@ export const buildCanvasInpaintGraph = (
   const {
     positivePrompt,
     negativePrompt,
-    model: model_name,
+    model: modelId,
     cfgScale: cfg_scale,
     scheduler,
     steps,
@@ -54,6 +55,8 @@ export const buildCanvasInpaintGraph = (
   // We may need to set the inpaint width and height to scale the image
   const { scaledBoundingBoxDimensions, boundingBoxScaleMethod } = state.canvas;
 
+  const model = modelIdToPipelineModelField(modelId);
+
   const graph: NonNullableGraph = {
     id: INPAINT_GRAPH,
     nodes: {
@@ -99,9 +102,9 @@ export const buildCanvasInpaintGraph = (
         prompt: negativePrompt,
       },
       [MODEL_LOADER]: {
-        type: 'sd1_model_loader',
+        type: 'pipeline_model_loader',
         id: MODEL_LOADER,
-        model_name,
+        model,
       },
       [RANGE_OF_SIZE]: {
         type: 'range_of_size',

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasTextToImageGraph.ts

@@ -14,6 +14,7 @@ import {
   TEXT_TO_LATENTS,
 } from './constants';
 import { addControlNetToLinearGraph } from '../addControlNetToLinearGraph';
+import { modelIdToPipelineModelField } from '../modelIdToPipelineModelField';
 
 /**
  * Builds the Canvas tab's Text to Image graph.
@@ -24,7 +25,7 @@ export const buildCanvasTextToImageGraph = (
   const {
     positivePrompt,
     negativePrompt,
-    model: model_name,
+    model: modelId,
     cfgScale: cfg_scale,
     scheduler,
     steps,
@@ -36,6 +37,8 @@ export const buildCanvasTextToImageGraph = (
   // The bounding box determines width and height, not the width and height params
   const { width, height } = state.canvas.boundingBoxDimensions;
 
+  const model = modelIdToPipelineModelField(modelId);
+
   /**
    * The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
    * full graph here as a template. Then use the parameters from app state and set friendlier node
@@ -80,9 +83,9 @@ export const buildCanvasTextToImageGraph = (
         steps,
       },
       [MODEL_LOADER]: {
-        type: 'sd1_model_loader',
+        type: 'pipeline_model_loader',
         id: MODEL_LOADER,
-        model_name,
+        model,
       },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearImageToImageGraph.ts

@@ -22,6 +22,7 @@ import {
 } from './constants';
 import { set } from 'lodash-es';
 import { addControlNetToLinearGraph } from '../addControlNetToLinearGraph';
+import { modelIdToPipelineModelField } from '../modelIdToPipelineModelField';
 
 const moduleLog = log.child({ namespace: 'nodes' });
 
@@ -34,7 +35,7 @@ export const buildLinearImageToImageGraph = (
   const {
     positivePrompt,
     negativePrompt,
-    model: model_name,
+    model: modelId,
     cfgScale: cfg_scale,
     scheduler,
     steps,
@@ -62,6 +63,8 @@ export const buildLinearImageToImageGraph = (
     throw new Error('No initial image found in state');
   }
 
+  const model = modelIdToPipelineModelField(modelId);
+
   // copy-pasted graph from node editor, filled in with state values & friendly node ids
   const graph: NonNullableGraph = {
     id: IMAGE_TO_IMAGE_GRAPH,
@@ -89,9 +92,9 @@ export const buildLinearImageToImageGraph = (
         id: NOISE,
       },
       [MODEL_LOADER]: {
-        type: 'sd1_model_loader',
+        type: 'pipeline_model_loader',
         id: MODEL_LOADER,
-        model_name,
+        model,
       },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearTextToImageGraph.ts

@@ -1,6 +1,10 @@
 import { RootState } from 'app/store/store';
 import { NonNullableGraph } from 'features/nodes/types/types';
-import { RandomIntInvocation, RangeOfSizeInvocation } from 'services/api';
+import {
+  BaseModelType,
+  RandomIntInvocation,
+  RangeOfSizeInvocation,
+} from 'services/api';
 import {
   ITERATE,
   LATENTS_TO_IMAGE,
@@ -14,6 +18,7 @@ import {
   TEXT_TO_LATENTS,
 } from './constants';
 import { addControlNetToLinearGraph } from '../addControlNetToLinearGraph';
+import { modelIdToPipelineModelField } from '../modelIdToPipelineModelField';
 
 type TextToImageGraphOverrides = {
   width: number;
@@ -27,7 +32,7 @@ export const buildLinearTextToImageGraph = (
   const {
     positivePrompt,
     negativePrompt,
-    model: model_name,
+    model: modelId,
     cfgScale: cfg_scale,
     scheduler,
     steps,
@@ -38,6 +43,8 @@ export const buildLinearTextToImageGraph = (
     shouldRandomizeSeed,
   } = state.generation;
 
+  const model = modelIdToPipelineModelField(modelId);
+
   /**
    * The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
    * full graph here as a template. Then use the parameters from app state and set friendlier node
@@ -82,9 +89,9 @@ export const buildLinearTextToImageGraph = (
         steps,
       },
       [MODEL_LOADER]: {
-        type: 'sd1_model_loader',
+        type: 'pipeline_model_loader',
         id: MODEL_LOADER,
-        model_name,
+        model,
       },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildNodesGraph.ts

@@ -1,9 +1,10 @@
 import { Graph } from 'services/api';
 import { v4 as uuidv4 } from 'uuid';
-import { cloneDeep, forEach, omit, reduce, values } from 'lodash-es';
+import { cloneDeep, omit, reduce } from 'lodash-es';
 import { RootState } from 'app/store/store';
 import { InputFieldValue } from 'features/nodes/types/types';
 import { AnyInvocation } from 'services/events/types';
+import { modelIdToPipelineModelField } from '../modelIdToPipelineModelField';
 
 /**
  * We need to do special handling for some fields
@@ -24,6 +25,12 @@ export const parseFieldValue = (field: InputFieldValue) => {
     }
   }
 
+  if (field.type === 'model') {
+    if (field.value) {
+      return modelIdToPipelineModelField(field.value);
+    }
+  }
+
   return field.value;
 };
 

invokeai/frontend/web/src/features/nodes/util/graphBuilders/constants.ts

@@ -7,7 +7,7 @@ export const NOISE = 'noise';
 export const RANDOM_INT = 'rand_int';
 export const RANGE_OF_SIZE = 'range_of_size';
 export const ITERATE = 'iterate';
-export const MODEL_LOADER = 'model_loader';
+export const MODEL_LOADER = 'pipeline_model_loader';
 export const IMAGE_TO_LATENTS = 'image_to_latents';
 export const LATENTS_TO_LATENTS = 'latents_to_latents';
 export const RESIZE = 'resize_image';

invokeai/frontend/web/src/features/nodes/util/modelIdToPipelineModelField.ts

@@ -0,0 +1,18 @@
+import { BaseModelType, PipelineModelField } from 'services/api';
+
+/**
+ * Crudely converts a model id to a pipeline model field
+ * TODO: Make better
+ */
+export const modelIdToPipelineModelField = (
+  modelId: string
+): PipelineModelField => {
+  const [base_model, model_type, model_name] = modelId.split('/');
+
+  const field: PipelineModelField = {
+    base_model: base_model as BaseModelType,
+    model_name,
+  };
+
+  return field;
+};

invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamSchedulerAndModel.tsx

@@ -6,7 +6,7 @@ import ParamScheduler from './ParamScheduler';
 const ParamSchedulerAndModel = () => {
   return (
     <Flex gap={3} w="full">
-      <Box w="20rem">
+      <Box w="25rem">
         <ParamScheduler />
       </Box>
       <Box w="full">

invokeai/frontend/web/src/features/parameters/store/generationSlice.ts

@@ -1,10 +1,9 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
+import { DEFAULT_SCHEDULER_NAME } from 'app/constants';
 import { configChanged } from 'features/system/store/configSlice';
-import { clamp, sortBy } from 'lodash-es';
+import { clamp } from 'lodash-es';
 import { ImageDTO } from 'services/api';
-import { imageUrlsReceived } from 'services/thunks/image';
-import { receivedModels } from 'services/thunks/model';
 import {
   CfgScaleParam,
   HeightParam,
@@ -17,7 +16,6 @@ import {
   StrengthParam,
   WidthParam,
 } from './parameterZodSchemas';
-import { DEFAULT_SCHEDULER_NAME } from 'app/constants';
 
 export interface GenerationState {
   cfgScale: CfgScaleParam;
@@ -220,28 +218,12 @@ export const generationSlice = createSlice({
     },
   },
   extraReducers: (builder) => {
-    builder.addCase(receivedModels.fulfilled, (state, action) => {
-      if (!state.model) {
-        const firstModel = sortBy(action.payload, 'name')[0];
-        state.model = firstModel.name;
-      }
-    });
-
     builder.addCase(configChanged, (state, action) => {
       const defaultModel = action.payload.sd?.defaultModel;
       if (defaultModel && !state.model) {
         state.model = defaultModel;
       }
     });
-
-    // builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
-    //   const { image_name, image_url, thumbnail_url } = action.payload;
-
-    //   if (state.initialImage?.image_name === image_name) {
-    //     state.initialImage.image_url = image_url;
-    //     state.initialImage.thumbnail_url = thumbnail_url;
-    //   }
-    // });
   },
 });
 

invokeai/frontend/web/src/features/parameters/store/parameterZodSchemas.ts

@@ -154,3 +154,17 @@ export type StrengthParam = z.infer<typeof zStrength>;
  */
 export const isValidStrength = (val: unknown): val is StrengthParam =>
   zStrength.safeParse(val).success;
+
+// /**
+//  * Zod schema for BaseModelType
+//  */
+// export const zBaseModelType = z.enum(['sd-1', 'sd-2']);
+// /**
+//  * Type alias for base model type, inferred from its zod schema. Should be identical to the type alias from OpenAPI.
+//  */
+// export type BaseModelType = z.infer<typeof zBaseModelType>;
+// /**
+//  * Validates/type-guards a value as a base model type
+//  */
+// export const isValidBaseModelType = (val: unknown): val is BaseModelType =>
+//   zBaseModelType.safeParse(val).success;

invokeai/frontend/web/src/features/system/components/ModelSelect.tsx

@@ -1,44 +1,59 @@
-import { createSelector } from '@reduxjs/toolkit';
+import { memo, useCallback, useEffect, useMemo } from 'react';
-import { isEqual } from 'lodash-es';
-import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
-import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAIMantineSelect, {
+import IAIMantineSelect from 'common/components/IAIMantineSelect';
-  IAISelectDataType,
-} from 'common/components/IAIMantineSelect';
-import { generationSelector } from 'features/parameters/store/generationSelectors';
 import { modelSelected } from 'features/parameters/store/generationSlice';
-import { selectModelsAll, selectModelsById } from '../store/modelSlice';
 
-const selector = createSelector(
+import { forEach, isString } from 'lodash-es';
-  [(state: RootState) => state, generationSelector],
+import { SelectItem } from '@mantine/core';
-  (state, generation) => {
+import { RootState } from 'app/store/store';
-    const selectedModel = selectModelsById(state, generation.model);
+import { useListModelsQuery } from 'services/apiSlice';
 
-    const modelData = selectModelsAll(state)
+export const MODEL_TYPE_MAP = {
-      .map<IAISelectDataType>((m) => ({
+  'sd-1': 'Stable Diffusion 1.x',
-        value: m.name,
+  'sd-2': 'Stable Diffusion 2.x',
-        label: m.name,
+};
-      }))
-      .sort((a, b) => a.label.localeCompare(b.label));
-    return {
-      selectedModel,
-      modelData,
-    };
-  },
-  {
-    memoizeOptions: {
-      resultEqualityCheck: isEqual,
-    },
-  }
-);
 
 const ModelSelect = () => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
-  const { selectedModel, modelData } = useAppSelector(selector);
+
+  const selectedModelId = useAppSelector(
+    (state: RootState) => state.generation.model
+  );
+
+  const { data: pipelineModels } = useListModelsQuery({
+    model_type: 'pipeline',
+  });
+
+  const data = useMemo(() => {
+    if (!pipelineModels) {
+      return [];
+    }
+
+    const data: SelectItem[] = [];
+
+    forEach(pipelineModels.entities, (model, id) => {
+      if (!model) {
+        return;
+      }
+
+      data.push({
+        value: id,
+        label: model.name,
+        group: MODEL_TYPE_MAP[model.base_model],
+      });
+    });
+
+    return data;
+  }, [pipelineModels]);
+
+  const selectedModel = useMemo(
+    () => pipelineModels?.entities[selectedModelId],
+    [pipelineModels?.entities, selectedModelId]
+  );
+
   const handleChangeModel = useCallback(
     (v: string | null) => {
       if (!v) {
@@ -49,13 +64,27 @@ const ModelSelect = () => {
     [dispatch]
   );
 
+  useEffect(() => {
+    if (selectedModelId && pipelineModels?.ids.includes(selectedModelId)) {
+      return;
+    }
+
+    const firstModel = pipelineModels?.ids[0];
+
+    if (!isString(firstModel)) {
+      return;
+    }
+
+    handleChangeModel(firstModel);
+  }, [handleChangeModel, pipelineModels?.ids, selectedModelId]);
+
   return (
     <IAIMantineSelect
       tooltip={selectedModel?.description}
       label={t('modelManager.model')}
-      value={selectedModel?.name ?? ''}
+      value={selectedModelId}
       placeholder="Pick one"
-      data={modelData}
+      data={data}
       onChange={handleChangeModel}
     />
   );

invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsSchedulers.tsx

@@ -1,6 +1,5 @@
 import { SCHEDULER_LABEL_MAP, SCHEDULER_NAMES } from 'app/constants';
 import { RootState } from 'app/store/store';
-
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIMantineMultiSelect from 'common/components/IAIMantineMultiSelect';
 import { SchedulerParam } from 'features/parameters/store/parameterZodSchemas';
@@ -16,6 +15,7 @@ const data = map(SCHEDULER_NAMES, (s) => ({
 
 export default function SettingsSchedulers() {
   const dispatch = useAppDispatch();
+
   const { t } = useTranslation();
 
   const enabledSchedulers = useAppSelector(

invokeai/frontend/web/src/features/system/hooks/useIsApplicationReady.ts

@@ -7,13 +7,12 @@ import { systemSelector } from '../store/systemSelectors';
 const isApplicationReadySelector = createSelector(
   [systemSelector, configSelector],
   (system, config) => {
-    const { wereModelsReceived, wasSchemaParsed } = system;
+    const { wasSchemaParsed } = system;
 
     const { disabledTabs } = config;
 
     return {
       disabledTabs,
-      wereModelsReceived,
       wasSchemaParsed,
     };
   }
@@ -23,21 +22,17 @@ const isApplicationReadySelector = createSelector(
  * Checks if the application is ready to be used, i.e. if the initial startup process is finished.
  */
 export const useIsApplicationReady = () => {
-  const { disabledTabs, wereModelsReceived, wasSchemaParsed } = useAppSelector(
+  const { disabledTabs, wasSchemaParsed } = useAppSelector(
     isApplicationReadySelector
   );
 
   const isApplicationReady = useMemo(() => {
-    if (!wereModelsReceived) {
-      return false;
-    }
-
     if (!disabledTabs.includes('nodes') && !wasSchemaParsed) {
       return false;
     }
 
     return true;
-  }, [disabledTabs, wereModelsReceived, wasSchemaParsed]);
+  }, [disabledTabs, wasSchemaParsed]);
 
   return isApplicationReady;
 };

invokeai/frontend/web/src/features/system/store/modelSelectors.ts

@@ -1,3 +0,0 @@
-import { RootState } from 'app/store/store';
-
-export const modelSelector = (state: RootState) => state.models;

invokeai/frontend/web/src/features/system/store/modelSlice.ts

@@ -1,47 +0,0 @@
-import { createEntityAdapter } from '@reduxjs/toolkit';
-import { createSlice } from '@reduxjs/toolkit';
-import { RootState } from 'app/store/store';
-import { CkptModelInfo, DiffusersModelInfo } from 'services/api';
-import { receivedModels } from 'services/thunks/model';
-
-export type Model = (CkptModelInfo | DiffusersModelInfo) & {
-  name: string;
-};
-
-export const modelsAdapter = createEntityAdapter<Model>({
-  selectId: (model) => model.name,
-  sortComparer: (a, b) => a.name.localeCompare(b.name),
-});
-
-export const initialModelsState = modelsAdapter.getInitialState();
-
-export type ModelsState = typeof initialModelsState;
-
-export const modelsSlice = createSlice({
-  name: 'models',
-  initialState: initialModelsState,
-  reducers: {
-    modelAdded: modelsAdapter.upsertOne,
-  },
-  extraReducers(builder) {
-    /**
-     * Received Models - FULFILLED
-     */
-    builder.addCase(receivedModels.fulfilled, (state, action) => {
-      const models = action.payload;
-      modelsAdapter.setAll(state, models);
-    });
-  },
-});
-
-export const {
-  selectAll: selectModelsAll,
-  selectById: selectModelsById,
-  selectEntities: selectModelsEntities,
-  selectIds: selectModelsIds,
-  selectTotal: selectModelsTotal,
-} = modelsAdapter.getSelectors<RootState>((state) => state.models);
-
-export const { modelAdded } = modelsSlice.actions;
-
-export default modelsSlice.reducer;

invokeai/frontend/web/src/features/system/store/modelsPersistDenylist.ts

@@ -1,6 +0,0 @@
-import { ModelsState } from './modelSlice';
-
-/**
- * Models slice persist denylist
- */
-export const modelsPersistDenylist: (keyof ModelsState)[] = ['entities', 'ids'];

invokeai/frontend/web/src/features/system/store/systemSlice.ts

@@ -1,20 +1,12 @@
 import { UseToastOptions } from '@chakra-ui/react';
-import { PayloadAction } from '@reduxjs/toolkit';
+import { PayloadAction, createSlice } from '@reduxjs/toolkit';
-import { createSlice } from '@reduxjs/toolkit';
 import * as InvokeAI from 'app/types/invokeai';
 
-import { ProgressImage } from 'services/events/types';
-import { makeToast } from '../../../app/components/Toaster';
-import { isAnySessionRejected, sessionCanceled } from 'services/thunks/session';
-import { receivedModels } from 'services/thunks/model';
-import { parsedOpenAPISchema } from 'features/nodes/store/nodesSlice';
-import { LogLevelName } from 'roarr';
 import { InvokeLogLevel } from 'app/logging/useLogger';
-import { TFuncKey } from 'i18next';
-import { t } from 'i18next';
 import { userInvoked } from 'app/store/actions';
-import { LANGUAGES } from '../components/LanguagePicker';
+import { parsedOpenAPISchema } from 'features/nodes/store/nodesSlice';
-import { imageUploaded } from 'services/thunks/image';
+import { TFuncKey, t } from 'i18next';
+import { LogLevelName } from 'roarr';
 import {
   appSocketConnected,
   appSocketDisconnected,
@@ -26,6 +18,11 @@ import {
   appSocketSubscribed,
   appSocketUnsubscribed,
 } from 'services/events/actions';
+import { ProgressImage } from 'services/events/types';
+import { imageUploaded } from 'services/thunks/image';
+import { isAnySessionRejected, sessionCanceled } from 'services/thunks/session';
+import { makeToast } from '../../../app/components/Toaster';
+import { LANGUAGES } from '../components/LanguagePicker';
 
 export type CancelStrategy = 'immediate' | 'scheduled';
 
@@ -379,13 +376,6 @@ export const systemSlice = createSlice({
       );
     });
 
-    /**
-     * Received available models from the backend
-     */
-    builder.addCase(receivedModels.fulfilled, (state) => {
-      state.wereModelsReceived = true;
-    });
-
     /**
      * OpenAPI schema was parsed
      */

invokeai/frontend/web/src/services/api/index.ts

@@ -25,6 +25,8 @@ export type { ConditioningField } from './models/ConditioningField';
 export type { ContentShuffleImageProcessorInvocation } from './models/ContentShuffleImageProcessorInvocation';
 export type { ControlField } from './models/ControlField';
 export type { ControlNetInvocation } from './models/ControlNetInvocation';
+export type { ControlNetModelConfig } from './models/ControlNetModelConfig';
+export type { ControlNetModelFormat } from './models/ControlNetModelFormat';
 export type { ControlOutput } from './models/ControlOutput';
 export type { CreateModelRequest } from './models/CreateModelRequest';
 export type { CvInpaintInvocation } from './models/CvInpaintInvocation';
@@ -67,14 +69,6 @@ export type { InfillTileInvocation } from './models/InfillTileInvocation';
 export type { InpaintInvocation } from './models/InpaintInvocation';
 export type { IntCollectionOutput } from './models/IntCollectionOutput';
 export type { IntOutput } from './models/IntOutput';
-export type { invokeai__backend__model_management__models__controlnet__ControlNetModel__Config } from './models/invokeai__backend__model_management__models__controlnet__ControlNetModel__Config';
-export type { invokeai__backend__model_management__models__lora__LoRAModel__Config } from './models/invokeai__backend__model_management__models__lora__LoRAModel__Config';
-export type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig } from './models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig';
-export type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig } from './models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig';
-export type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig } from './models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig';
-export type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig } from './models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig';
-export type { invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config } from './models/invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config';
-export type { invokeai__backend__model_management__models__vae__VaeModel__Config } from './models/invokeai__backend__model_management__models__vae__VaeModel__Config';
 export type { IterateInvocation } from './models/IterateInvocation';
 export type { IterateInvocationOutput } from './models/IterateInvocationOutput';
 export type { LatentsField } from './models/LatentsField';
@@ -87,6 +81,8 @@ export type { LoadImageInvocation } from './models/LoadImageInvocation';
 export type { LoraInfo } from './models/LoraInfo';
 export type { LoraLoaderInvocation } from './models/LoraLoaderInvocation';
 export type { LoraLoaderOutput } from './models/LoraLoaderOutput';
+export type { LoRAModelConfig } from './models/LoRAModelConfig';
+export type { LoRAModelFormat } from './models/LoRAModelFormat';
 export type { MaskFromAlphaInvocation } from './models/MaskFromAlphaInvocation';
 export type { MaskOutput } from './models/MaskOutput';
 export type { MediapipeFaceProcessorInvocation } from './models/MediapipeFaceProcessorInvocation';
@@ -109,6 +105,8 @@ export type { PaginatedResults_GraphExecutionState_ } from './models/PaginatedRe
 export type { ParamFloatInvocation } from './models/ParamFloatInvocation';
 export type { ParamIntInvocation } from './models/ParamIntInvocation';
 export type { PidiImageProcessorInvocation } from './models/PidiImageProcessorInvocation';
+export type { PipelineModelField } from './models/PipelineModelField';
+export type { PipelineModelLoaderInvocation } from './models/PipelineModelLoaderInvocation';
 export type { PromptCollectionOutput } from './models/PromptCollectionOutput';
 export type { PromptOutput } from './models/PromptOutput';
 export type { RandomIntInvocation } from './models/RandomIntInvocation';
@@ -120,16 +118,23 @@ export type { ResourceOrigin } from './models/ResourceOrigin';
 export type { RestoreFaceInvocation } from './models/RestoreFaceInvocation';
 export type { ScaleLatentsInvocation } from './models/ScaleLatentsInvocation';
 export type { SchedulerPredictionType } from './models/SchedulerPredictionType';
-export type { SD1ModelLoaderInvocation } from './models/SD1ModelLoaderInvocation';
-export type { SD2ModelLoaderInvocation } from './models/SD2ModelLoaderInvocation';
 export type { ShowImageInvocation } from './models/ShowImageInvocation';
+export type { StableDiffusion1ModelCheckpointConfig } from './models/StableDiffusion1ModelCheckpointConfig';
+export type { StableDiffusion1ModelDiffusersConfig } from './models/StableDiffusion1ModelDiffusersConfig';
+export type { StableDiffusion1ModelFormat } from './models/StableDiffusion1ModelFormat';
+export type { StableDiffusion2ModelCheckpointConfig } from './models/StableDiffusion2ModelCheckpointConfig';
+export type { StableDiffusion2ModelDiffusersConfig } from './models/StableDiffusion2ModelDiffusersConfig';
+export type { StableDiffusion2ModelFormat } from './models/StableDiffusion2ModelFormat';
 export type { StepParamEasingInvocation } from './models/StepParamEasingInvocation';
 export type { SubModelType } from './models/SubModelType';
 export type { SubtractInvocation } from './models/SubtractInvocation';
 export type { TextToLatentsInvocation } from './models/TextToLatentsInvocation';
+export type { TextualInversionModelConfig } from './models/TextualInversionModelConfig';
 export type { UNetField } from './models/UNetField';
 export type { UpscaleInvocation } from './models/UpscaleInvocation';
 export type { VaeField } from './models/VaeField';
+export type { VaeModelConfig } from './models/VaeModelConfig';
+export type { VaeModelFormat } from './models/VaeModelFormat';
 export type { VaeRepo } from './models/VaeRepo';
 export type { ValidationError } from './models/ValidationError';
 export type { ZoeDepthImageProcessorInvocation } from './models/ZoeDepthImageProcessorInvocation';

invokeai/frontend/web/src/services/api/models/ControlNetModelConfig.ts

@@ -0,0 +1,18 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+import type { BaseModelType } from './BaseModelType';
+import type { ControlNetModelFormat } from './ControlNetModelFormat';
+import type { ModelError } from './ModelError';
+
+export type ControlNetModelConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'controlnet';
+  path: string;
+  description?: string;
+  model_format: ControlNetModelFormat;
+  error?: ModelError;
+};
+

invokeai/frontend/web/src/services/api/models/ControlNetModelFormat.ts

@@ -0,0 +1,8 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * An enumeration.
+ */
+export type ControlNetModelFormat = 'checkpoint' | 'diffusers';

invokeai/frontend/web/src/services/api/models/Graph.ts

@@ -49,6 +49,7 @@ import type { OpenposeImageProcessorInvocation } from './OpenposeImageProcessorI
 import type { ParamFloatInvocation } from './ParamFloatInvocation';
 import type { ParamIntInvocation } from './ParamIntInvocation';
 import type { PidiImageProcessorInvocation } from './PidiImageProcessorInvocation';
+import type { PipelineModelLoaderInvocation } from './PipelineModelLoaderInvocation';
 import type { RandomIntInvocation } from './RandomIntInvocation';
 import type { RandomRangeInvocation } from './RandomRangeInvocation';
 import type { RangeInvocation } from './RangeInvocation';
@@ -56,8 +57,6 @@ import type { RangeOfSizeInvocation } from './RangeOfSizeInvocation';
 import type { ResizeLatentsInvocation } from './ResizeLatentsInvocation';
 import type { RestoreFaceInvocation } from './RestoreFaceInvocation';
 import type { ScaleLatentsInvocation } from './ScaleLatentsInvocation';
-import type { SD1ModelLoaderInvocation } from './SD1ModelLoaderInvocation';
-import type { SD2ModelLoaderInvocation } from './SD2ModelLoaderInvocation';
 import type { ShowImageInvocation } from './ShowImageInvocation';
 import type { StepParamEasingInvocation } from './StepParamEasingInvocation';
 import type { SubtractInvocation } from './SubtractInvocation';
@@ -73,7 +72,7 @@ export type Graph = {
   /**
    * The nodes in this graph
    */
-  nodes?: Record<string, (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | SD1ModelLoaderInvocation | SD2ModelLoaderInvocation | LoraLoaderInvocation | DynamicPromptInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | UpscaleInvocation | RestoreFaceInvocation | InpaintInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation)>;
+  nodes?: Record<string, (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | PipelineModelLoaderInvocation | LoraLoaderInvocation | DynamicPromptInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | UpscaleInvocation | RestoreFaceInvocation | InpaintInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation)>;
   /**
    * The connections between nodes and their fields in this graph
    */

invokeai/frontend/web/src/services/api/models/LoRAModelConfig.ts

@@ -0,0 +1,18 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+import type { BaseModelType } from './BaseModelType';
+import type { LoRAModelFormat } from './LoRAModelFormat';
+import type { ModelError } from './ModelError';
+
+export type LoRAModelConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'lora';
+  path: string;
+  description?: string;
+  model_format: LoRAModelFormat;
+  error?: ModelError;
+};
+

invokeai/frontend/web/src/services/api/models/LoRAModelFormat.ts

@@ -0,0 +1,8 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * An enumeration.
+ */
+export type LoRAModelFormat = 'lycoris' | 'diffusers';

invokeai/frontend/web/src/services/api/models/ModelsList.ts

@@ -2,16 +2,16 @@
 /* tslint:disable */
 /* eslint-disable */
 
-import type { invokeai__backend__model_management__models__controlnet__ControlNetModel__Config } from './invokeai__backend__model_management__models__controlnet__ControlNetModel__Config';
+import type { ControlNetModelConfig } from './ControlNetModelConfig';
-import type { invokeai__backend__model_management__models__lora__LoRAModel__Config } from './invokeai__backend__model_management__models__lora__LoRAModel__Config';
+import type { LoRAModelConfig } from './LoRAModelConfig';
-import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig';
+import type { StableDiffusion1ModelCheckpointConfig } from './StableDiffusion1ModelCheckpointConfig';
-import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig';
+import type { StableDiffusion1ModelDiffusersConfig } from './StableDiffusion1ModelDiffusersConfig';
-import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig';
+import type { StableDiffusion2ModelCheckpointConfig } from './StableDiffusion2ModelCheckpointConfig';
-import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig';
+import type { StableDiffusion2ModelDiffusersConfig } from './StableDiffusion2ModelDiffusersConfig';
-import type { invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config } from './invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config';
+import type { TextualInversionModelConfig } from './TextualInversionModelConfig';
-import type { invokeai__backend__model_management__models__vae__VaeModel__Config } from './invokeai__backend__model_management__models__vae__VaeModel__Config';
+import type { VaeModelConfig } from './VaeModelConfig';
 
 export type ModelsList = {
-  models: Record<string, Record<string, Record<string, (invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig | invokeai__backend__model_management__models__controlnet__ControlNetModel__Config | invokeai__backend__model_management__models__lora__LoRAModel__Config | invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig | invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config | invokeai__backend__model_management__models__vae__VaeModel__Config | invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig | invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig)>>>;
+  models: Array<(StableDiffusion1ModelCheckpointConfig | StableDiffusion1ModelDiffusersConfig | VaeModelConfig | LoRAModelConfig | ControlNetModelConfig | TextualInversionModelConfig | StableDiffusion2ModelCheckpointConfig | StableDiffusion2ModelDiffusersConfig)>;
 };
 

invokeai/frontend/web/src/services/api/models/PipelineModelField.ts

@@ -0,0 +1,20 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+import type { BaseModelType } from './BaseModelType';
+
+/**
+ * Pipeline model field
+ */
+export type PipelineModelField = {
+  /**
+   * Name of the model
+   */
+  model_name: string;
+  /**
+   * Base model
+   */
+  base_model: BaseModelType;
+};
+

invokeai/frontend/web/src/services/api/models/PipelineModelLoaderInvocation.ts

@@ -2,10 +2,12 @@
 /* tslint:disable */
 /* eslint-disable */
 
+import type { PipelineModelField } from './PipelineModelField';
+
 /**
- * Loading submodels of selected model.
+ * Loads a pipeline model, outputting its submodels.
  */
-export type SD2ModelLoaderInvocation = {
+export type PipelineModelLoaderInvocation = {
   /**
    * The id of this node. Must be unique among all nodes.
    */
@@ -14,10 +16,10 @@ export type SD2ModelLoaderInvocation = {
    * Whether or not this node is an intermediate node.
    */
   is_intermediate?: boolean;
-  type?: 'sd2_model_loader';
+  type?: 'pipeline_model_loader';
   /**
-   * Model to load
+   * The model to load
    */
-  model_name?: string;
+  model: PipelineModelField;
 };
 

invokeai/frontend/web/src/services/api/models/SD1ModelLoaderInvocation.ts

@@ -1,23 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-
-/**
- * Loading submodels of selected model.
- */
-export type SD1ModelLoaderInvocation = {
-  /**
-   * The id of this node. Must be unique among all nodes.
-   */
-  id: string;
-  /**
-   * Whether or not this node is an intermediate node.
-   */
-  is_intermediate?: boolean;
-  type?: 'sd1_model_loader';
-  /**
-   * Model to load
-   */
-  model_name?: string;
-};
-

invokeai/frontend/web/src/services/api/models/StableDiffusion1ModelCheckpointConfig.ts

@@ -2,14 +2,17 @@
 /* tslint:disable */
 /* eslint-disable */
 
+import type { BaseModelType } from './BaseModelType';
 import type { ModelError } from './ModelError';
 import type { ModelVariantType } from './ModelVariantType';
 
-export type invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig = {
+export type StableDiffusion1ModelCheckpointConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'pipeline';
   path: string;
   description?: string;
-  format: 'checkpoint';
+  model_format: 'checkpoint';
-  default?: boolean;
   error?: ModelError;
   vae?: string;
   config?: string;

invokeai/frontend/web/src/services/api/models/StableDiffusion1ModelDiffusersConfig.ts

@@ -2,14 +2,17 @@
 /* tslint:disable */
 /* eslint-disable */
 
+import type { BaseModelType } from './BaseModelType';
 import type { ModelError } from './ModelError';
 import type { ModelVariantType } from './ModelVariantType';
 
-export type invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig = {
+export type StableDiffusion1ModelDiffusersConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'pipeline';
   path: string;
   description?: string;
-  format: 'diffusers';
+  model_format: 'diffusers';
-  default?: boolean;
   error?: ModelError;
   vae?: string;
   variant: ModelVariantType;

invokeai/frontend/web/src/services/api/models/StableDiffusion1ModelFormat.ts

@@ -0,0 +1,8 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * An enumeration.
+ */
+export type StableDiffusion1ModelFormat = 'checkpoint' | 'diffusers';

invokeai/frontend/web/src/services/api/models/StableDiffusion2ModelCheckpointConfig.ts

@@ -2,15 +2,18 @@
 /* tslint:disable */
 /* eslint-disable */
 
+import type { BaseModelType } from './BaseModelType';
 import type { ModelError } from './ModelError';
 import type { ModelVariantType } from './ModelVariantType';
 import type { SchedulerPredictionType } from './SchedulerPredictionType';
 
-export type invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig = {
+export type StableDiffusion2ModelCheckpointConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'pipeline';
   path: string;
   description?: string;
-  format: 'checkpoint';
+  model_format: 'checkpoint';
-  default?: boolean;
   error?: ModelError;
   vae?: string;
   config?: string;

invokeai/frontend/web/src/services/api/models/StableDiffusion2ModelDiffusersConfig.ts

@@ -2,15 +2,18 @@
 /* tslint:disable */
 /* eslint-disable */
 
+import type { BaseModelType } from './BaseModelType';
 import type { ModelError } from './ModelError';
 import type { ModelVariantType } from './ModelVariantType';
 import type { SchedulerPredictionType } from './SchedulerPredictionType';
 
-export type invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig = {
+export type StableDiffusion2ModelDiffusersConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'pipeline';
   path: string;
   description?: string;
-  format: 'diffusers';
+  model_format: 'diffusers';
-  default?: boolean;
   error?: ModelError;
   vae?: string;
   variant: ModelVariantType;

invokeai/frontend/web/src/services/api/models/StableDiffusion2ModelFormat.ts

@@ -0,0 +1,8 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * An enumeration.
+ */
+export type StableDiffusion2ModelFormat = 'checkpoint' | 'diffusers';

invokeai/frontend/web/src/services/api/models/TextualInversionModelConfig.ts

@@ -0,0 +1,17 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+import type { BaseModelType } from './BaseModelType';
+import type { ModelError } from './ModelError';
+
+export type TextualInversionModelConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'embedding';
+  path: string;
+  description?: string;
+  model_format: null;
+  error?: ModelError;
+};
+

invokeai/frontend/web/src/services/api/models/VaeModelConfig.ts

@@ -0,0 +1,18 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+import type { BaseModelType } from './BaseModelType';
+import type { ModelError } from './ModelError';
+import type { VaeModelFormat } from './VaeModelFormat';
+
+export type VaeModelConfig = {
+  name: string;
+  base_model: BaseModelType;
+  type: 'vae';
+  path: string;
+  description?: string;
+  model_format: VaeModelFormat;
+  error?: ModelError;
+};
+

invokeai/frontend/web/src/services/api/models/VaeModelFormat.ts

@@ -0,0 +1,8 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * An enumeration.
+ */
+export type VaeModelFormat = 'checkpoint' | 'diffusers';

invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__controlnet__ControlNetModel__Config.ts

@@ -1,14 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-
-import type { ModelError } from './ModelError';
-
-export type invokeai__backend__model_management__models__controlnet__ControlNetModel__Config = {
-  path: string;
-  description?: string;
-  format: ('checkpoint' | 'diffusers');
-  default?: boolean;
-  error?: ModelError;
-};
-

invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__lora__LoRAModel__Config.ts

@@ -1,14 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-
-import type { ModelError } from './ModelError';
-
-export type invokeai__backend__model_management__models__lora__LoRAModel__Config = {
-  path: string;
-  description?: string;
-  format: ('lycoris' | 'diffusers');
-  default?: boolean;
-  error?: ModelError;
-};
-

invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config.ts

@@ -1,14 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-
-import type { ModelError } from './ModelError';
-
-export type invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config = {
-  path: string;
-  description?: string;
-  format: null;
-  default?: boolean;
-  error?: ModelError;
-};
-

invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__vae__VaeModel__Config.ts

@@ -1,14 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-
-import type { ModelError } from './ModelError';
-
-export type invokeai__backend__model_management__models__vae__VaeModel__Config = {
-  path: string;
-  description?: string;
-  format: ('checkpoint' | 'diffusers');
-  default?: boolean;
-  error?: ModelError;
-};
-

invokeai/frontend/web/src/services/api/services/SessionsService.ts

@@ -51,6 +51,7 @@ import type { PaginatedResults_GraphExecutionState_ } from '../models/PaginatedR
 import type { ParamFloatInvocation } from '../models/ParamFloatInvocation';
 import type { ParamIntInvocation } from '../models/ParamIntInvocation';
 import type { PidiImageProcessorInvocation } from '../models/PidiImageProcessorInvocation';
+import type { PipelineModelLoaderInvocation } from '../models/PipelineModelLoaderInvocation';
 import type { RandomIntInvocation } from '../models/RandomIntInvocation';
 import type { RandomRangeInvocation } from '../models/RandomRangeInvocation';
 import type { RangeInvocation } from '../models/RangeInvocation';
@@ -58,8 +59,6 @@ import type { RangeOfSizeInvocation } from '../models/RangeOfSizeInvocation';
 import type { ResizeLatentsInvocation } from '../models/ResizeLatentsInvocation';
 import type { RestoreFaceInvocation } from '../models/RestoreFaceInvocation';
 import type { ScaleLatentsInvocation } from '../models/ScaleLatentsInvocation';
-import type { SD1ModelLoaderInvocation } from '../models/SD1ModelLoaderInvocation';
-import type { SD2ModelLoaderInvocation } from '../models/SD2ModelLoaderInvocation';
 import type { ShowImageInvocation } from '../models/ShowImageInvocation';
 import type { StepParamEasingInvocation } from '../models/StepParamEasingInvocation';
 import type { SubtractInvocation } from '../models/SubtractInvocation';
@@ -175,7 +174,7 @@ export class SessionsService {
      * The id of the session
      */
     sessionId: string,
-    requestBody: (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | SD1ModelLoaderInvocation | SD2ModelLoaderInvocation | LoraLoaderInvocation | DynamicPromptInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | UpscaleInvocation | RestoreFaceInvocation | InpaintInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation),
+    requestBody: (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | PipelineModelLoaderInvocation | LoraLoaderInvocation | DynamicPromptInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | UpscaleInvocation | RestoreFaceInvocation | InpaintInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation),
   }): CancelablePromise<string> {
     return __request(OpenAPI, {
       method: 'POST',
@@ -212,7 +211,7 @@ export class SessionsService {
      * The path to the node in the graph
      */
     nodePath: string,
-    requestBody: (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | SD1ModelLoaderInvocation | SD2ModelLoaderInvocation | LoraLoaderInvocation | DynamicPromptInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | UpscaleInvocation | RestoreFaceInvocation | InpaintInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation),
+    requestBody: (LoadImageInvocation | ShowImageInvocation | ImageCropInvocation | ImagePasteInvocation | MaskFromAlphaInvocation | ImageMultiplyInvocation | ImageChannelInvocation | ImageConvertInvocation | ImageBlurInvocation | ImageResizeInvocation | ImageScaleInvocation | ImageLerpInvocation | ImageInverseLerpInvocation | ControlNetInvocation | ImageProcessorInvocation | PipelineModelLoaderInvocation | LoraLoaderInvocation | DynamicPromptInvocation | CompelInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RandomIntInvocation | ParamIntInvocation | ParamFloatInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | ResizeLatentsInvocation | ScaleLatentsInvocation | ImageToLatentsInvocation | CvInpaintInvocation | RangeInvocation | RangeOfSizeInvocation | RandomRangeInvocation | FloatLinearRangeInvocation | StepParamEasingInvocation | UpscaleInvocation | RestoreFaceInvocation | InpaintInvocation | InfillColorInvocation | InfillTileInvocation | InfillPatchMatchInvocation | GraphInvocation | IterateInvocation | CollectInvocation | CannyImageProcessorInvocation | HedImageProcessorInvocation | LineartImageProcessorInvocation | LineartAnimeImageProcessorInvocation | OpenposeImageProcessorInvocation | MidasDepthImageProcessorInvocation | NormalbaeImageProcessorInvocation | MlsdImageProcessorInvocation | PidiImageProcessorInvocation | ContentShuffleImageProcessorInvocation | ZoeDepthImageProcessorInvocation | MediapipeFaceProcessorInvocation | LatentsToLatentsInvocation),
   }): CancelablePromise<GraphExecutionState> {
     return __request(OpenAPI, {
       method: 'PUT',

invokeai/frontend/web/src/services/apiSlice.ts

@@ -13,23 +13,68 @@ import {
   TagTypesFrom,
   TagTypesFromApi,
 } from '@reduxjs/toolkit/dist/query/endpointDefinitions';
+import { EntityState, createEntityAdapter } from '@reduxjs/toolkit';
+import { BaseModelType } from './api/models/BaseModelType';
+import { ModelType } from './api/models/ModelType';
+import { ModelsList } from './api/models/ModelsList';
+import { keyBy } from 'lodash-es';
 
 type ListBoardsArg = { offset: number; limit: number };
 type UpdateBoardArg = { board_id: string; changes: BoardChanges };
 type AddImageToBoardArg = { board_id: string; image_name: string };
 type RemoveImageFromBoardArg = { board_id: string; image_name: string };
 type ListBoardImagesArg = { board_id: string; offset: number; limit: number };
+type ListModelsArg = { base_model?: BaseModelType; model_type?: ModelType };
 
-const tagTypes = ['Board', 'Image'];
+type ModelConfig = ModelsList['models'][number];
+
+const tagTypes = ['Board', 'Image', 'Model'];
 type ApiFullTagDescription = FullTagDescription<(typeof tagTypes)[number]>;
 
 const LIST = 'LIST';
 
+const modelsAdapter = createEntityAdapter<ModelConfig>({
+  selectId: (model) => getModelId(model),
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
+});
+
+const getModelId = ({ base_model, type, name }: ModelConfig) =>
+  `${base_model}/${type}/${name}`;
+
 export const api = createApi({
   baseQuery: fetchBaseQuery({ baseUrl: 'http://localhost:5173/api/v1/' }),
   reducerPath: 'api',
   tagTypes,
   endpoints: (build) => ({
+    /**
+     * Models Queries
+     */
+
+    listModels: build.query<EntityState<ModelConfig>, ListModelsArg>({
+      query: (arg) => ({ url: 'models/', params: arg }),
+      providesTags: (result, error, arg) => {
+        // any list of boards
+        const tags: ApiFullTagDescription[] = [{ id: 'Model', type: LIST }];
+
+        if (result) {
+          // and individual tags for each board
+          tags.push(
+            ...result.ids.map((id) => ({
+              type: 'Model' as const,
+              id,
+            }))
+          );
+        }
+
+        return tags;
+      },
+      transformResponse: (response: ModelsList, meta, arg) => {
+        return modelsAdapter.addMany(
+          modelsAdapter.getInitialState(),
+          keyBy(response.models, getModelId)
+        );
+      },
+    }),
     /**
      * Boards Queries
      */
@@ -174,4 +219,5 @@ export const {
   useRemoveImageFromBoardMutation,
   useListBoardImagesQuery,
   useGetImageDTOQuery,
+  useListModelsQuery,
 } = api;

invokeai/frontend/web/src/services/thunks/model.ts

@@ -1,33 +0,0 @@
-import { log } from 'app/logging/useLogger';
-import { createAppAsyncThunk } from 'app/store/storeUtils';
-import { Model } from 'features/system/store/modelSlice';
-import { reduce, size } from 'lodash-es';
-import { ModelsService } from 'services/api';
-
-const models = log.child({ namespace: 'model' });
-
-export const IMAGES_PER_PAGE = 20;
-
-export const receivedModels = createAppAsyncThunk(
-  'models/receivedModels',
-  async (_) => {
-    const response = await ModelsService.listModels();
-
-    const deserializedModels = reduce(
-      response.models['sd-1']['pipeline'],
-      (modelsAccumulator, model, modelName) => {
-        modelsAccumulator[modelName] = { ...model, name: modelName };
-
-        return modelsAccumulator;
-      },
-      {} as Record<string, Model>
-    );
-
-    models.info(
-      { response },
-      `Received ${size(response.models['sd-1']['pipeline'])} models`
-    );
-
-    return deserializedModels;
-  }
-);

invokeai/frontend/web/src/theme/colors/greenTea.ts

@@ -4,8 +4,8 @@ import { generateColorPalette } from '../util/generateColorPalette';
 export const greenTeaThemeColors: InvokeAIThemeColors = {
   base: generateColorPalette(223, 10),
   baseAlpha: generateColorPalette(223, 10, false, true),
-  accent: generateColorPalette(155, 80),
+  accent: generateColorPalette(160, 60),
-  accentAlpha: generateColorPalette(155, 80, false, true),
+  accentAlpha: generateColorPalette(160, 60, false, true),
   working: generateColorPalette(47, 68),
   workingAlpha: generateColorPalette(47, 68, false, true),
   warning: generateColorPalette(28, 75),
@@ -14,5 +14,5 @@ export const greenTeaThemeColors: InvokeAIThemeColors = {
   okAlpha: generateColorPalette(122, 49, false, true),
   error: generateColorPalette(0, 50),
   errorAlpha: generateColorPalette(0, 50, false, true),
-  gridLineColor: 'rgba(255, 255, 255, 0.2)',
+  gridLineColor: 'rgba(255, 255, 255, 0.15)',
 };

invokeai/frontend/web/src/theme/colors/invokeAI.ts

@@ -2,8 +2,8 @@ import { InvokeAIThemeColors } from 'theme/themeTypes';
 import { generateColorPalette } from 'theme/util/generateColorPalette';
 
 export const invokeAIThemeColors: InvokeAIThemeColors = {
-  base: generateColorPalette(225, 15),
+  base: generateColorPalette(220, 15),
-  baseAlpha: generateColorPalette(225, 15, false, true),
+  baseAlpha: generateColorPalette(220, 15, false, true),
   accent: generateColorPalette(250, 50),
   accentAlpha: generateColorPalette(250, 50, false, true),
   working: generateColorPalette(47, 67),
@@ -14,5 +14,5 @@ export const invokeAIThemeColors: InvokeAIThemeColors = {
   okAlpha: generateColorPalette(113, 70, false, true),
   error: generateColorPalette(0, 76),
   errorAlpha: generateColorPalette(0, 76, false, true),
-  gridLineColor: 'rgba(255, 255, 255, 0.2)',
+  gridLineColor: 'rgba(150, 150, 180, 0.15)',
 };

invokeai/frontend/web/src/theme/colors/lightTheme.ts

@@ -14,5 +14,5 @@ export const lightThemeColors: InvokeAIThemeColors = {
   okAlpha: generateColorPalette(122, 49, true, true),
   error: generateColorPalette(0, 50, true),
   errorAlpha: generateColorPalette(0, 50, true, true),
-  gridLineColor: 'rgba(0, 0, 0, 0.2)',
+  gridLineColor: 'rgba(0, 0, 0, 0.15)',
 };

invokeai/frontend/web/src/theme/colors/oceanBlue.ts

@@ -14,5 +14,5 @@ export const oceanBlueColors: InvokeAIThemeColors = {
   okAlpha: generateColorPalette(122, 49, false, true),
   error: generateColorPalette(0, 100),
   errorAlpha: generateColorPalette(0, 100, false, true),
-  gridLineColor: 'rgba(136, 148, 184, 0.2)',
+  gridLineColor: 'rgba(136, 148, 184, 0.15)',
 };