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Code Issues Packages Projects Releases Wiki Activity

Update UI To Use New Model Manager (#3548)

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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.
This commit is contained in:
blessedcoolant 2023-06-22 22:06:26 +12:00 committed by GitHub
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67 changed files with 710 additions and 668 deletions
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11
invokeai/app/api/routers/models.py
View File

@ -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
MODEL_CONFIGS = Union[tuple(get_all_model_configs())]
from invokeai.backend.model_management.models import OPENAPI_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: dict[SDModelType, dict[str, Annotated[Union[(DiffusersModelInfo,CkptModelInfo,SafetensorsModelInfo)], Field(discriminator="format")]]]
models: list[MODEL_CONFIGS]
@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:

16
invokeai/app/api_app.py
View File

@ -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

150
invokeai/app/invocations/model.py
View File

@ -43,12 +43,19 @@ class ModelLoaderOutput(BaseInvocationOutput):
#fmt: on
class SD1ModelLoaderInvocation(BaseInvocation):
"""Loading submodels of selected model."""
class PipelineModelField(BaseModel):
"""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,
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,
model_type=model_type,
submodel=SubModelType.Vae,
),
)

43
invokeai/app/services/model_manager_service.py
View File

@ -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:
{ 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 a list of models.
"""
return self.mgr.list_models(base_model, model_type)

54
invokeai/backend/model_management/model_manager.py
View File

@ -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:
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_dict = 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

71
invokeai/backend/model_management/models/__init__.py
View File

@ -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():
configs = set()
for models in MODEL_CLASSES.values():
for _, model in models.items():
configs.update(model._get_configs().values())
configs.discard(None)
return list(configs) # TODO: set, list or tuple
MODEL_CONFIGS = list()
OPENAPI_MODEL_CONFIGS = list()
class OpenAPIModelInfoBase(BaseModel):
name: str
base_model: BaseModelType
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

53
invokeai/backend/model_management/models/base.py
View File

@ -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)
default: Optional[bool] = Field(False)
model_format: Optional[str] = Field(None)
# 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:
raise Exception("Invalid config definition - format field not found")
try:
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 format_type not in {None, Literal, Union}:
raise Exception(f"Invalid config definition - unknown format type: {fields['format']}")
if isinstance(field, type) and issubclass(field, str) and issubclass(field, Enum):
for model_format in field:
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__):
raise Exception(f"Invalid config definition - unknown format type: {fields['format']}")
elif typing.get_origin(field) is Literal and all(isinstance(arg, str) and isinstance(arg, Enum) for arg in field.__args__):
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"],)
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)?
raise Exception(f"Unsupported format definition in {cls.__qualname__}")
cls.__configs = configs
return cls.__configs
@classmethod
def create_config(cls, **kwargs) -> ModelConfigBase:
if "format" not in kwargs:
raise Exception("Field 'format' not found in model config")
if "model_format" not in kwargs:
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

15
invokeai/backend/model_management/models/controlnet.py
View File

@ -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":
raise NotImlemetedError("Checkpoint controlnet models currently unsupported")
if cls.detect_format(model_path) != ControlNetModelFormat.Diffusers:
raise NotImplementedError("Checkpoint controlnet models currently unsupported")
else:
return model_path

13
invokeai/backend/model_management/models/lora.py
View File

@ -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:

39
invokeai/backend/model_management/models/stable_diffusion.py
View File

@ -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
prediction_type = config.prediction_type
upcast_attention = model_config.upcast_attention
prediction_type = model_config.prediction_type
else:
raise Exception(f"Unknown model provided: {version}")

2
invokeai/backend/model_management/models/textual_inversion.py
View File

@ -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

14
invokeai/backend/model_management/models/vae.py
View File

@ -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,

13
invokeai/frontend/web/src/app/components/App.tsx
View File

@ -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();

2
invokeai/frontend/web/src/app/store/enhancers/reduxRemember/serialize.ts
View File

@ -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,

2
invokeai/frontend/web/src/app/store/enhancers/reduxRemember/unserialize.ts
View File

@ -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,

9
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected.ts
View File

@ -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());
}

20
invokeai/frontend/web/src/app/store/store.ts
View File

@ -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',

116
invokeai/frontend/web/src/features/nodes/components/fields/ModelInputFieldComponent.tsx
View File

@ -1,28 +1,18 @@
import { Select } from '@chakra-ui/react';
import { createSelector } from '@reduxjs/toolkit';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { SelectItem } from '@mantine/core';
import { useAppDispatch } 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(
[selectModelsIds],
(allModelNames) => {
return { allModelNames };
// return map(modelList, (_, name) => name);
},
{
memoizeOptions: {
resultEqualityCheck: isEqual,
},
}
);
import { memo, useCallback, useEffect, useMemo } from 'react';
import { FieldComponentProps } from './types';
import { forEach, isString } from 'lodash-es';
import { MODEL_TYPE_MAP as BASE_MODEL_NAME_MAP } from 'features/system/components/ModelSelect';
import IAIMantineSelect from 'common/components/IAIMantineSelect';
import { useTranslation } from 'react-i18next';
import { useListModelsQuery } from 'services/apiSlice';
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>) => {
dispatch(
fieldValueChanged({
nodeId,
fieldName: field.name,
value: e.target.value,
})
);
};
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: 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>
/>
);
};

15
invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
View File

@ -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;
}
}
});
});
});
},
});

9
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasImageToImageGraph.ts
View File

@ -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',

9
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasInpaintGraph.ts
View File

@ -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',

9
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasTextToImageGraph.ts
View File

@ -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',

9
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearImageToImageGraph.ts
View File

@ -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',

15
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearTextToImageGraph.ts
View File

@ -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',

9
invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildNodesGraph.ts
View File

@ -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;
};

2
invokeai/frontend/web/src/features/nodes/util/graphBuilders/constants.ts
View File

@ -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';

18
invokeai/frontend/web/src/features/nodes/util/modelIdToPipelineModelField.ts Normal file
View File

@ -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;
};

2
invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamSchedulerAndModel.tsx
View File

@ -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">

22
invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
View File

@ -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;
// }
// });
},
});

14
invokeai/frontend/web/src/features/parameters/store/parameterZodSchemas.ts
View File

@ -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;

95
invokeai/frontend/web/src/features/system/components/ModelSelect.tsx
View File

@ -1,44 +1,59 @@
import { createSelector } from '@reduxjs/toolkit';
import { isEqual } from 'lodash-es';
import { memo, useCallback } from 'react';
import { memo, useCallback, useEffect, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { RootState } from 'app/store/store';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import IAIMantineSelect, {
IAISelectDataType,
} from 'common/components/IAIMantineSelect';
import { generationSelector } from 'features/parameters/store/generationSelectors';
import IAIMantineSelect from 'common/components/IAIMantineSelect';
import { modelSelected } from 'features/parameters/store/generationSlice';
import { selectModelsAll, selectModelsById } from '../store/modelSlice';
const selector = createSelector(
[(state: RootState) => state, generationSelector],
(state, generation) => {
const selectedModel = selectModelsById(state, generation.model);
import { forEach, isString } from 'lodash-es';
import { SelectItem } from '@mantine/core';
import { RootState } from 'app/store/store';
import { useListModelsQuery } from 'services/apiSlice';
const modelData = selectModelsAll(state)
.map<IAISelectDataType>((m) => ({
value: m.name,
label: m.name,
}))
.sort((a, b) => a.label.localeCompare(b.label));
return {
selectedModel,
modelData,
};
},
{
memoizeOptions: {
resultEqualityCheck: isEqual,
},
}
);
export const MODEL_TYPE_MAP = {
'sd-1': 'Stable Diffusion 1.x',
'sd-2': 'Stable Diffusion 2.x',
};
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}
/>
);

2
invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsSchedulers.tsx
View File

@ -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(

11
invokeai/frontend/web/src/features/system/hooks/useIsApplicationReady.ts
View File

@ -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;
};

3
invokeai/frontend/web/src/features/system/store/modelSelectors.ts
View File

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

47
invokeai/frontend/web/src/features/system/store/modelSlice.ts
View File

@ -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;

6
invokeai/frontend/web/src/features/system/store/modelsPersistDenylist.ts
View File

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

28
invokeai/frontend/web/src/features/system/store/systemSlice.ts
View File

@ -1,20 +1,12 @@
import { UseToastOptions } from '@chakra-ui/react';
import { PayloadAction } from '@reduxjs/toolkit';
import { createSlice } from '@reduxjs/toolkit';
import { PayloadAction, 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 { imageUploaded } from 'services/thunks/image';
import { parsedOpenAPISchema } from 'features/nodes/store/nodesSlice';
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
*/

25
invokeai/frontend/web/src/services/api/index.ts
View File

@ -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';

18
invokeai/frontend/web/src/services/api/models/ControlNetModelConfig.ts Normal file
View File

@ -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;
};

8
invokeai/frontend/web/src/services/api/models/ControlNetModelFormat.ts Normal file
View File

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

5
invokeai/frontend/web/src/services/api/models/Graph.ts
View File

@ -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
*/

18
invokeai/frontend/web/src/services/api/models/LoRAModelConfig.ts Normal file
View File

@ -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;
};

8
invokeai/frontend/web/src/services/api/models/LoRAModelFormat.ts Normal file
View File

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

18
invokeai/frontend/web/src/services/api/models/ModelsList.ts
View File

@ -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 { invokeai__backend__model_management__models__lora__LoRAModel__Config } from './invokeai__backend__model_management__models__lora__LoRAModel__Config';
import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig';
import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig';
import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig';
import type { invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig } from './invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig';
import type { invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config } from './invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config';
import type { invokeai__backend__model_management__models__vae__VaeModel__Config } from './invokeai__backend__model_management__models__vae__VaeModel__Config';
import type { ControlNetModelConfig } from './ControlNetModelConfig';
import type { LoRAModelConfig } from './LoRAModelConfig';
import type { StableDiffusion1ModelCheckpointConfig } from './StableDiffusion1ModelCheckpointConfig';
import type { StableDiffusion1ModelDiffusersConfig } from './StableDiffusion1ModelDiffusersConfig';
import type { StableDiffusion2ModelCheckpointConfig } from './StableDiffusion2ModelCheckpointConfig';
import type { StableDiffusion2ModelDiffusersConfig } from './StableDiffusion2ModelDiffusersConfig';
import type { TextualInversionModelConfig } from './TextualInversionModelConfig';
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)>;
};

20
invokeai/frontend/web/src/services/api/models/PipelineModelField.ts Normal file
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@ -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;
};

12
invokeai/frontend/web/src/services/api/models/SD2ModelLoaderInvocation.ts → invokeai/frontend/web/src/services/api/models/PipelineModelLoaderInvocation.ts
View File

@ -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;
};

23
invokeai/frontend/web/src/services/api/models/SD1ModelLoaderInvocation.ts
View File

@ -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;
};

9
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__CheckpointConfig.ts → invokeai/frontend/web/src/services/api/models/StableDiffusion1ModelCheckpointConfig.ts
View File

@ -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';
default?: boolean;
model_format: 'checkpoint';
error?: ModelError;
vae?: string;
config?: string;

9
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion1Model__DiffusersConfig.ts → invokeai/frontend/web/src/services/api/models/StableDiffusion1ModelDiffusersConfig.ts
View File

@ -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';
default?: boolean;
model_format: 'diffusers';
error?: ModelError;
vae?: string;
variant: ModelVariantType;

8
invokeai/frontend/web/src/services/api/models/StableDiffusion1ModelFormat.ts Normal file
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@ -0,0 +1,8 @@
/* istanbul ignore file */
/* tslint:disable */
/* eslint-disable */
/**
* An enumeration.
*/
export type StableDiffusion1ModelFormat = 'checkpoint' | 'diffusers';

9
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__CheckpointConfig.ts → invokeai/frontend/web/src/services/api/models/StableDiffusion2ModelCheckpointConfig.ts
View File

@ -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';
default?: boolean;
model_format: 'checkpoint';
error?: ModelError;
vae?: string;
config?: string;

9
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__stable_diffusion__StableDiffusion2Model__DiffusersConfig.ts → invokeai/frontend/web/src/services/api/models/StableDiffusion2ModelDiffusersConfig.ts
View File

@ -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';
default?: boolean;
model_format: 'diffusers';
error?: ModelError;
vae?: string;
variant: ModelVariantType;

8
invokeai/frontend/web/src/services/api/models/StableDiffusion2ModelFormat.ts Normal file
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@ -0,0 +1,8 @@
/* istanbul ignore file */
/* tslint:disable */
/* eslint-disable */
/**
* An enumeration.
*/
export type StableDiffusion2ModelFormat = 'checkpoint' | 'diffusers';

17
invokeai/frontend/web/src/services/api/models/TextualInversionModelConfig.ts Normal file
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@ -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;
};

18
invokeai/frontend/web/src/services/api/models/VaeModelConfig.ts Normal file
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@ -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;
};

8
invokeai/frontend/web/src/services/api/models/VaeModelFormat.ts Normal file
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@ -0,0 +1,8 @@
/* istanbul ignore file */
/* tslint:disable */
/* eslint-disable */
/**
* An enumeration.
*/
export type VaeModelFormat = 'checkpoint' | 'diffusers';

14
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__controlnet__ControlNetModel__Config.ts
View File

@ -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;
};

14
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__lora__LoRAModel__Config.ts
View File

@ -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;
};

14
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__textual_inversion__TextualInversionModel__Config.ts
View File

@ -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;
};

14
invokeai/frontend/web/src/services/api/models/invokeai__backend__model_management__models__vae__VaeModel__Config.ts
View File

@ -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;
};

7
invokeai/frontend/web/src/services/api/services/SessionsService.ts
View File

@ -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',

48
invokeai/frontend/web/src/services/apiSlice.ts
View File

@ -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;

33
invokeai/frontend/web/src/services/thunks/model.ts
View File

@ -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;
}
);

6
invokeai/frontend/web/src/theme/colors/greenTea.ts
View File

@ -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),
accentAlpha: generateColorPalette(155, 80, false, true),
accent: generateColorPalette(160, 60),
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)',
};

6
invokeai/frontend/web/src/theme/colors/invokeAI.ts
View File

@ -2,8 +2,8 @@ import { InvokeAIThemeColors } from 'theme/themeTypes';
import { generateColorPalette } from 'theme/util/generateColorPalette';
export const invokeAIThemeColors: InvokeAIThemeColors = {
base: generateColorPalette(225, 15),
baseAlpha: generateColorPalette(225, 15, false, true),
base: generateColorPalette(220, 15),
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)',
};

2
invokeai/frontend/web/src/theme/colors/lightTheme.ts
View File

@ -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)',
};

2
invokeai/frontend/web/src/theme/colors/oceanBlue.ts
View File

@ -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)',
};