feat(nodes): remove siglip from flux_redux, dl it jit when needed if we cannot find it

This follows the same pattern for IP Adapter w/ its CLIP Vision model. The SigLIP model is unlikely to ever change and we don't want to force the user to select it anywhere. Hardcoding it is safe and makes the UX much nicer.

The alternative is a model dropdown that will likely only ever have one valid choice in it.

Author: psychedelicious

invokeai/app/invocations/flux_redux.py

@@ -20,8 +20,11 @@
 )
 from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.primitives import ImageField
+from invokeai.app.services.model_records.model_records_base import ModelRecordChanges
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.flux.redux.flux_redux_model import FluxReduxModel
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelType
+from invokeai.backend.model_manager.starter_models import siglip
 from invokeai.backend.sig_lip.sig_lip_pipeline import SigLipPipeline
 from invokeai.backend.util.devices import TorchDevice
 
@@ -35,16 +38,12 @@ class FluxReduxOutput(BaseInvocationOutput):
     )
 
 
-SIGLIP_STARTER_MODEL_NAME = "SigLIP - google/siglip-so400m-patch14-384"
-FLUX_REDUX_STARTER_MODEL_NAME = "FLUX Redux"
-
-
 @invocation(
     "flux_redux",
     title="FLUX Redux",
     tags=["ip_adapter", "control"],
     category="ip_adapter",
-    version="1.0.0",
+    version="2.0.0",
     classification=Classification.Prototype,
 )
 class FluxReduxInvocation(BaseInvocation):
@@ -61,11 +60,6 @@ class FluxReduxInvocation(BaseInvocation):
         title="FLUX Redux Model",
         ui_type=UIType.FluxReduxModel,
     )
-    siglip_model: ModelIdentifierField = InputField(
-        description="The SigLIP model to use.",
-        title="SigLIP Model",
-        ui_type=UIType.SigLipModel,
-    )
 
     def invoke(self, context: InvocationContext) -> FluxReduxOutput:
         image = context.images.get_pil(self.image.image_name, "RGB")
@@ -80,7 +74,8 @@ def invoke(self, context: InvocationContext) -> FluxReduxOutput:
 
     @torch.no_grad()
     def _siglip_encode(self, context: InvocationContext, image: Image.Image) -> torch.Tensor:
-        with context.models.load(self.siglip_model).model_on_device() as (_, siglip_pipeline):
+        siglip_model_config = self._get_siglip_model(context)
+        with context.models.load(siglip_model_config.key).model_on_device() as (_, siglip_pipeline):
             assert isinstance(siglip_pipeline, SigLipPipeline)
             return siglip_pipeline.encode_image(
                 x=image, device=TorchDevice.choose_torch_device(), dtype=TorchDevice.choose_torch_dtype()
@@ -93,3 +88,32 @@ def _flux_redux_encode(self, context: InvocationContext, encoded_x: torch.Tensor
             dtype = next(flux_redux.parameters()).dtype
             encoded_x = encoded_x.to(dtype=dtype)
             return flux_redux(encoded_x)
+
+    def _get_siglip_model(self, context: InvocationContext) -> AnyModelConfig:
+        siglip_models = context.models.search_by_attrs(name=siglip.name, base=BaseModelType.Any, type=ModelType.SigLIP)
+
+        if not len(siglip_models) > 0:
+            context.logger.warning(
+                f"The SigLIP model required by FLUX Redux ({siglip.name}) is not installed. Downloading and installing now. This may take a while."
+            )
+
+            # TODO(psyche): Can the probe reliably determine the type of the model? Just hardcoding it bc I don't want to experiment now
+            config_overrides = ModelRecordChanges(name=siglip.name, type=ModelType.SigLIP)
+
+            # Queue the job
+            job = context._services.model_manager.install.heuristic_import(siglip.source, config=config_overrides)
+
+            # Wait for up to 10 minutes - model is ~3.5GB
+            context._services.model_manager.install.wait_for_job(job, timeout=600)
+
+            siglip_models = context.models.search_by_attrs(
+                name=siglip.name,
+                base=BaseModelType.Any,
+                type=ModelType.SigLIP,
+            )
+
+            if len(siglip_models) == 0:
+                context.logger.error("Error while fetching SigLIP for FLUX Redux")
+                assert len(siglip_models) == 1
+
+        return siglip_models[0]