feat(nodes): move all invocation metadata (type, title, tags, category) to decorator

All invocation metadata (type, title, tags and category) are now defined in decorators.

The decorators add the `type: Literal["invocation_type"]: "invocation_type"` field to the invocation.

Category is a new invocation metadata, but it is not used by the frontend just yet.

- `@invocation()` decorator for invocations

```py
@invocation(
    "sdxl_compel_prompt",
    title="SDXL Prompt",
    tags=["sdxl", "compel", "prompt"],
    category="conditioning",
)
class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
    ...
```

- `@invocation_output()` decorator for invocation outputs

```py
@invocation_output("clip_skip_output")
class ClipSkipInvocationOutput(BaseInvocationOutput):
    ...
```

- update invocation docs
- add category to decorator
- regen frontend types

invokeai/app/invocations/model.py

@@ -1,5 +1,5 @@
 import copy
-from typing import List, Literal, Optional
+from typing import List, Optional
 
 from pydantic import BaseModel, Field
 
@@ -13,8 +13,8 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIType,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 
 
@@ -49,11 +49,10 @@ class VaeField(BaseModel):
     seamless_axes: List[str] = Field(default_factory=list, description='Axes("x" and "y") to which apply seamless')
 
 
+@invocation_output("model_loader_output")
 class ModelLoaderOutput(BaseInvocationOutput):
     """Model loader output"""
 
-    type: Literal["model_loader_output"] = "model_loader_output"
-
     unet: UNetField = OutputField(description=FieldDescriptions.unet, title="UNet")
     clip: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP")
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
@@ -74,14 +73,10 @@ class LoRAModelField(BaseModel):
     base_model: BaseModelType = Field(description="Base model")
 
 
-@title("Main Model")
-@tags("model")
+@invocation("main_model_loader", title="Main Model", tags=["model"], category="model")
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
 
-    type: Literal["main_model_loader"] = "main_model_loader"
-
-    # Inputs
     model: MainModelField = InputField(description=FieldDescriptions.main_model, input=Input.Direct)
     # TODO: precision?
 
@@ -170,25 +165,18 @@ class MainModelLoaderInvocation(BaseInvocation):
         )
 
 
+@invocation_output("lora_loader_output")
 class LoraLoaderOutput(BaseInvocationOutput):
     """Model loader output"""
 
-    # fmt: off
-    type: Literal["lora_loader_output"] = "lora_loader_output"
-
     unet: Optional[UNetField] = OutputField(default=None, description=FieldDescriptions.unet, title="UNet")
     clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
-    # fmt: on
 
 
-@title("LoRA")
-@tags("lora", "model")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model")
 class LoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
-    type: Literal["lora_loader"] = "lora_loader"
-
-    # Inputs
     lora: LoRAModelField = InputField(description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA")
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -247,25 +235,19 @@ class LoraLoaderInvocation(BaseInvocation):
         return output
 
 
+@invocation_output("sdxl_lora_loader_output")
 class SDXLLoraLoaderOutput(BaseInvocationOutput):
     """SDXL LoRA Loader Output"""
 
-    # fmt: off
-    type: Literal["sdxl_lora_loader_output"] = "sdxl_lora_loader_output"
-
     unet: Optional[UNetField] = OutputField(default=None, description=FieldDescriptions.unet, title="UNet")
     clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP 1")
     clip2: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP 2")
-    # fmt: on
 
 
-@title("SDXL LoRA")
-@tags("sdxl", "lora", "model")
+@invocation("sdxl_lora_loader", title="SDXL LoRA", tags=["lora", "model"], category="model")
 class SDXLLoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
-    type: Literal["sdxl_lora_loader"] = "sdxl_lora_loader"
-
     lora: LoRAModelField = InputField(description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA")
     weight: float = Field(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = Field(
@@ -349,23 +331,17 @@ class VAEModelField(BaseModel):
     base_model: BaseModelType = Field(description="Base model")
 
 
+@invocation_output("vae_loader_output")
 class VaeLoaderOutput(BaseInvocationOutput):
-    """Model loader output"""
+    """VAE output"""
 
-    type: Literal["vae_loader_output"] = "vae_loader_output"
-
-    # Outputs
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@title("VAE")
-@tags("vae", "model")
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model")
 class VaeLoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
-    type: Literal["vae_loader"] = "vae_loader"
-
-    # Inputs
     vae_model: VAEModelField = InputField(
         description=FieldDescriptions.vae_model, input=Input.Direct, ui_type=UIType.VaeModel, title="VAE"
     )
@@ -392,24 +368,18 @@ class VaeLoaderInvocation(BaseInvocation):
         )
 
 
+@invocation_output("seamless_output")
 class SeamlessModeOutput(BaseInvocationOutput):
     """Modified Seamless Model output"""
 
-    type: Literal["seamless_output"] = "seamless_output"
-
-    # Outputs
     unet: Optional[UNetField] = OutputField(description=FieldDescriptions.unet, title="UNet")
     vae: Optional[VaeField] = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@title("Seamless")
-@tags("seamless", "model")
+@invocation("seamless", title="Seamless", tags=["seamless", "model"], category="model")
 class SeamlessModeInvocation(BaseInvocation):
     """Applies the seamless transformation to the Model UNet and VAE."""
 
-    type: Literal["seamless"] = "seamless"
-
-    # Inputs
     unet: Optional[UNetField] = InputField(
         default=None, description=FieldDescriptions.unet, input=Input.Connection, title="UNet"
     )