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