feat(nodes): update all invocations to use new invocation context

Update all invocations to use the new context. The changes are all fairly simple, but there are a lot of them.

Supporting minor changes:
- Patch bump for all nodes that use the context
- Update invocation processor to provide new context
- Minor change to `EventServiceBase` to accept a node's ID instead of the dict version of a node
- Minor change to `ModelManagerService` to support the new wrapped context
- Fanagling of imports to avoid circular dependencies

invokeai/app/invocations/model.py

@@ -10,7 +10,6 @@ from ...backend.model_management import BaseModelType, ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -102,7 +101,7 @@ class LoRAModelField(BaseModel):
     title="Main Model",
     tags=["model"],
     category="model",
-    version="1.0.0",
+    version="1.0.1",
 )
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
@@ -110,13 +109,13 @@ class MainModelLoaderInvocation(BaseInvocation):
     model: MainModelField = InputField(description=FieldDescriptions.main_model, input=Input.Direct)
     # TODO: precision?
 
-    def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
+    def invoke(self, context) -> ModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
 
         # TODO: not found exceptions
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             model_name=model_name,
             base_model=base_model,
             model_type=model_type,
@@ -203,7 +202,7 @@ class LoraLoaderOutput(BaseInvocationOutput):
     clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.0")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.1")
 class LoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
@@ -222,14 +221,14 @@ class LoraLoaderInvocation(BaseInvocation):
         title="CLIP",
     )
 
-    def invoke(self, context: InvocationContext) -> LoraLoaderOutput:
+    def invoke(self, context) -> LoraLoaderOutput:
         if self.lora is None:
             raise Exception("No LoRA provided")
 
         base_model = self.lora.base_model
         lora_name = self.lora.model_name
 
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             base_model=base_model,
             model_name=lora_name,
             model_type=ModelType.Lora,
@@ -285,7 +284,7 @@ class SDXLLoraLoaderOutput(BaseInvocationOutput):
     title="SDXL LoRA",
     tags=["lora", "model"],
     category="model",
-    version="1.0.0",
+    version="1.0.1",
 )
 class SDXLLoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
@@ -311,14 +310,14 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
         title="CLIP 2",
     )
 
-    def invoke(self, context: InvocationContext) -> SDXLLoraLoaderOutput:
+    def invoke(self, context) -> SDXLLoraLoaderOutput:
         if self.lora is None:
             raise Exception("No LoRA provided")
 
         base_model = self.lora.base_model
         lora_name = self.lora.model_name
 
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             base_model=base_model,
             model_name=lora_name,
             model_type=ModelType.Lora,
@@ -384,7 +383,7 @@ class VAEModelField(BaseModel):
     model_config = ConfigDict(protected_namespaces=())
 
 
-@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.0")
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.1")
 class VaeLoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
@@ -394,12 +393,12 @@ class VaeLoaderInvocation(BaseInvocation):
         title="VAE",
     )
 
-    def invoke(self, context: InvocationContext) -> VAEOutput:
+    def invoke(self, context) -> VAEOutput:
         base_model = self.vae_model.base_model
         model_name = self.vae_model.model_name
         model_type = ModelType.Vae
 
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             base_model=base_model,
             model_name=model_name,
             model_type=model_type,
@@ -449,7 +448,7 @@ class SeamlessModeInvocation(BaseInvocation):
     seamless_y: bool = InputField(default=True, input=Input.Any, description="Specify whether Y axis is seamless")
     seamless_x: bool = InputField(default=True, input=Input.Any, description="Specify whether X axis is seamless")
 
-    def invoke(self, context: InvocationContext) -> SeamlessModeOutput:
+    def invoke(self, context) -> SeamlessModeOutput:
         # Conditionally append 'x' and 'y' based on seamless_x and seamless_y
         unet = copy.deepcopy(self.unet)
         vae = copy.deepcopy(self.vae)
@@ -485,6 +484,6 @@ class FreeUInvocation(BaseInvocation):
     s1: float = InputField(default=0.9, ge=-1, le=3, description=FieldDescriptions.freeu_s1)
     s2: float = InputField(default=0.2, ge=-1, le=3, description=FieldDescriptions.freeu_s2)
 
-    def invoke(self, context: InvocationContext) -> UNetOutput:
+    def invoke(self, context) -> UNetOutput:
         self.unet.freeu_config = FreeUConfig(s1=self.s1, s2=self.s2, b1=self.b1, b2=self.b2)
         return UNetOutput(unet=self.unet)