Allow denying and explicitly allowing nodes. When a not-allowed node is used, a pydantic `ValidationError` will be raised.
- When collecting all invocations, check against the allowlist and denylist first. When pydantic constructs any unions related to nodes, the denied nodes will be omitted
- Add `allow_nodes` and `deny_nodes` to `InvokeAIAppConfig`. These are `Union[list[str], None]`, and may be populated with the `type` of invocations.
- When `allow_nodes` is `None`, allow all nodes, else if it is `list[str]`, only allow nodes in the list
- When `deny_nodes` is `None`, deny no nodes, else if it is `list[str]`, deny nodes in the list
- `deny_nodes` overrides `allow_nodes`
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
- move docstrings to ABC
- `start_time: int` -> `start_time: float`
- remove class attribute assignments in `StatsContext`
- add `update_mem_stats()` to ABC
- add class attributes to ABC, because they are referenced in instances of the class. if they should not be on the ABC, then maybe there needs to be some restructuring
When retrieving a graph, it is parsed through pydantic. It is possible that this graph is invalid, and an error is thrown.
Handle this by deleting the failed graph from the stats if this occurs.
- move docstrings to ABC
- `start_time: int` -> `start_time: float`
- remove class attribute assignments in `StatsContext`
- add `update_mem_stats()` to ABC
- add class attributes to ABC, because they are referenced in instances of the class. if they should not be on the ABC, then maybe there needs to be some restructuring
When retrieving a graph, it is parsed through pydantic. It is possible that this graph is invalid, and an error is thrown.
Handle this by deleting the failed graph from the stats if this occurs.
Refine concept of "parameter" nodes to "primitives":
- integer
- float
- string
- boolean
- image
- latents
- conditioning
- color
Each primitive has:
- A field definition, if it is not already python primitive value. The field is how this primitive value is passed between nodes. Collections are lists of the field in node definitions. ex: `ImageField` & `list[ImageField]`
- A single output class. ex: `ImageOutput`
- A collection output class. ex: `ImageCollectionOutput`
- A node, which functions to load or pass on the primitive value. ex: `ImageInvocation` (in this case, `ImageInvocation` replaces `LoadImage`)
Plus a number of related changes:
- Reorganize these into `primitives.py`
- Update all nodes and logic to use primitives
- Consolidate "prompt" outputs into "string" & "mask" into "image" (there's no reason for these to be different, the function identically)
- Update default graphs & tests
- Regen frontend types & minor frontend tidy related to changes
