feat(mm): make config_path optional

Author: psychedelicious

invokeai/app/invocations/flux_denoise.py

@@ -48,7 +48,7 @@
     unpack,
 )
 from invokeai.backend.flux.text_conditioning import FluxReduxConditioning, FluxTextConditioning
-from invokeai.backend.model_manager.taxonomy import ModelFormat, ModelVariantType
+from invokeai.backend.model_manager.taxonomy import FluxVariantType, ModelFormat
 from invokeai.backend.patches.layer_patcher import LayerPatcher
 from invokeai.backend.patches.lora_conversions.flux_lora_constants import FLUX_LORA_TRANSFORMER_PREFIX
 from invokeai.backend.patches.model_patch_raw import ModelPatchRaw
@@ -232,7 +232,7 @@ def _run_diffusion(
         )
 
         transformer_config = context.models.get_config(self.transformer.transformer)
-        is_schnell = "schnell" in getattr(transformer_config, "config_path", "")
+        is_schnell = transformer_config.variant is FluxVariantType.Schnell
 
         # Calculate the timestep schedule.
         timesteps = get_schedule(
@@ -277,7 +277,7 @@ def _run_diffusion(
 
         # Prepare the extra image conditioning tensor (img_cond) for either FLUX structural control or FLUX Fill.
         img_cond: torch.Tensor | None = None
-        is_flux_fill = transformer_config.variant == ModelVariantType.Inpaint  # type: ignore
+        is_flux_fill = transformer_config.variant is FluxVariantType.DevFill
         if is_flux_fill:
             img_cond = self._prep_flux_fill_img_cond(
                 context, device=TorchDevice.choose_torch_device(), dtype=inference_dtype

invokeai/backend/model_manager/config.py

@@ -198,7 +198,6 @@ def __init_subclass__(cls, **kwargs):
         super().__init_subclass__(**kwargs)
         if issubclass(cls, LegacyProbeMixin):
             ModelConfigBase.USING_LEGACY_PROBE.add(cls)
-        # Cannot use `elif isinstance(cls, UnknownModelConfig)` because UnknownModelConfig is not defined yet
         else:
             ModelConfigBase.USING_CLASSIFY_API.add(cls)
 
@@ -346,11 +345,16 @@ class CheckpointConfigBase(ABC, BaseModel):
     """Base class for checkpoint-style models."""
 
     format: Literal[ModelFormat.Checkpoint, ModelFormat.BnbQuantizednf4b, ModelFormat.GGUFQuantized] = Field(
-        description="Format of the provided checkpoint model", default=ModelFormat.Checkpoint
+        description="Format of the provided checkpoint model",
+        default=ModelFormat.Checkpoint,
     )
-    config_path: str = Field(description="path to the checkpoint model config file")
-    converted_at: Optional[float] = Field(
-        description="When this model was last converted to diffusers", default_factory=time.time
+    config_path: str | None = Field(
+        description="path to the checkpoint model config file",
+        default=None,
+    )
+    converted_at: float | None = Field(
+        description="When this model was last converted to diffusers",
+        default_factory=time.time,
     )
 
 

invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/MainModelPicker.tsx

@@ -27,7 +27,7 @@ export const MainModelPicker = memo(() => {
     () =>
       selectedModelConfig &&
       isCheckpointMainModelConfig(selectedModelConfig) &&
-      selectedModelConfig.config_path === 'flux-dev',
+      selectedModelConfig.variant === 'flux_dev',
     [selectedModelConfig]
   );
 

invokeai/frontend/web/src/features/ui/layouts/InitialStateMainModelPicker.tsx

@@ -26,7 +26,7 @@ export const InitialStateMainModelPicker = memo(() => {
     () =>
       selectedModelConfig &&
       isCheckpointMainModelConfig(selectedModelConfig) &&
-      selectedModelConfig.config_path === 'flux-dev',
+      selectedModelConfig.variant === 'flux_dev',
     [selectedModelConfig]
   );