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tidy(nodes): use ModelIdentifierField for model metadata

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Until recently, this had a different shape than the ModelMetadataField. They are now the same, so we can re-use the ModelIdentifierField.
This commit is contained in:
psychedelicious 2024-03-14 10:30:07 +11:00
parent db12ce95a8
commit 4492bedd19
1 changed files with 8 additions and 18 deletions
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26
invokeai/app/invocations/metadata.py
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@ -20,8 +20,8 @@ from invokeai.app.invocations.fields import (
OutputField,
UIType,
)
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.backend.model_manager.config import BaseModelType, ModelType
from ...version import __version__
@ -31,20 +31,10 @@ class MetadataItemField(BaseModel):
value: Any = Field(description=FieldDescriptions.metadata_item_value)
class ModelMetadataField(BaseModel):
"""Model Metadata Field"""
key: str
hash: str
name: str
base: BaseModelType
type: ModelType
class LoRAMetadataField(BaseModel):
"""LoRA Metadata Field"""
model: ModelMetadataField = Field(description=FieldDescriptions.lora_model)
model: ModelIdentifierField = Field(description=FieldDescriptions.lora_model)
weight: float = Field(description=FieldDescriptions.lora_weight)
@ -52,7 +42,7 @@ class IPAdapterMetadataField(BaseModel):
"""IP Adapter Field, minus the CLIP Vision Encoder model"""
image: ImageField = Field(description="The IP-Adapter image prompt.")
ip_adapter_model: ModelMetadataField = Field(
ip_adapter_model: ModelIdentifierField = Field(
description="The IP-Adapter model.",
)
weight: Union[float, list[float]] = Field(
@ -64,7 +54,7 @@ class IPAdapterMetadataField(BaseModel):
class T2IAdapterMetadataField(BaseModel):
image: ImageField = Field(description="The T2I-Adapter image prompt.")
t2i_adapter_model: ModelMetadataField = Field(description="The T2I-Adapter model to use.")
t2i_adapter_model: ModelIdentifierField = Field(description="The T2I-Adapter model to use.")
weight: Union[float, list[float]] = Field(default=1, description="The weight given to the T2I-Adapter")
begin_step_percent: float = Field(
default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
@ -77,7 +67,7 @@ class T2IAdapterMetadataField(BaseModel):
class ControlNetMetadataField(BaseModel):
image: ImageField = Field(description="The control image")
control_model: ModelMetadataField = Field(description="The ControlNet model to use")
control_model: ModelIdentifierField = Field(description="The ControlNet model to use")
control_weight: Union[float, list[float]] = Field(default=1, description="The weight given to the ControlNet")
begin_step_percent: float = Field(
default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
@ -178,7 +168,7 @@ class CoreMetadataInvocation(BaseInvocation):
default=None,
description="The number of skipped CLIP layers",
)
model: Optional[ModelMetadataField] = InputField(default=None, description="The main model used for inference")
model: Optional[ModelIdentifierField] = InputField(default=None, description="The main model used for inference")
controlnets: Optional[list[ControlNetMetadataField]] = InputField(
default=None, description="The ControlNets used for inference"
)
@ -197,7 +187,7 @@ class CoreMetadataInvocation(BaseInvocation):
default=None,
description="The name of the initial image",
)
vae: Optional[ModelMetadataField] = InputField(
vae: Optional[ModelIdentifierField] = InputField(
default=None,
description="The VAE used for decoding, if the main model's default was not used",
)
@ -228,7 +218,7 @@ class CoreMetadataInvocation(BaseInvocation):
)
# SDXL Refiner
refiner_model: Optional[ModelMetadataField] = InputField(
refiner_model: Optional[ModelIdentifierField] = InputField(
default=None,
description="The SDXL Refiner model used",
)