2023-08-14 09:41:29 +00:00
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# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
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2024-01-13 12:23:16 +00:00
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from typing import Optional
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2023-08-14 09:41:29 +00:00
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import torch
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2024-02-10 21:54:01 +00:00
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from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
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2024-01-13 12:23:16 +00:00
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from invokeai.app.invocations.fields import (
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ColorField,
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ConditioningField,
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DenoiseMaskField,
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FieldDescriptions,
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ImageField,
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Input,
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InputField,
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LatentsField,
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OutputField,
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UIComponent,
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)
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from invokeai.app.services.images.images_common import ImageDTO
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2024-02-05 06:16:35 +00:00
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from invokeai.app.services.shared.invocation_context import InvocationContext
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2023-11-08 23:43:38 +00:00
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2023-08-14 09:41:29 +00:00
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from .baseinvocation import (
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BaseInvocation,
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BaseInvocationOutput,
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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
2023-08-30 08:35:12 +00:00
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invocation,
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invocation_output,
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2023-08-14 09:41:29 +00:00
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)
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"""
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Primitives: Boolean, Integer, Float, String, Image, Latents, Conditioning, Color
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- primitive nodes
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- primitive outputs
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- primitive collection outputs
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"""
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# region Boolean
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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
2023-08-30 08:35:12 +00:00
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@invocation_output("boolean_output")
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2023-08-14 09:41:29 +00:00
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class BooleanOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single boolean"""
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value: bool = OutputField(description="The output boolean")
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2023-08-14 09:41:29 +00:00
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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
2023-08-30 08:35:12 +00:00
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@invocation_output("boolean_collection_output")
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2023-08-14 09:41:29 +00:00
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class BooleanCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of booleans"""
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feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
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collection: list[bool] = OutputField(
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description="The output boolean collection",
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)
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2023-08-14 09:41:29 +00:00
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2023-09-04 08:11:56 +00:00
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@invocation(
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"boolean", title="Boolean Primitive", tags=["primitives", "boolean"], category="primitives", version="1.0.0"
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)
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2023-08-14 09:41:29 +00:00
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class BooleanInvocation(BaseInvocation):
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"""A boolean primitive value"""
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value: bool = InputField(default=False, description="The boolean value")
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2023-08-14 09:41:29 +00:00
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2024-02-05 06:16:35 +00:00
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def invoke(self, context: InvocationContext) -> BooleanOutput:
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2023-08-18 10:17:21 +00:00
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return BooleanOutput(value=self.value)
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2023-08-14 09:41:29 +00:00
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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
2023-08-30 08:35:12 +00:00
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@invocation(
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"boolean_collection",
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title="Boolean Collection Primitive",
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tags=["primitives", "boolean", "collection"],
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category="primitives",
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feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
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version="1.0.1",
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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
2023-08-30 08:35:12 +00:00
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)
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2023-08-15 12:18:37 +00:00
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class BooleanCollectionInvocation(BaseInvocation):
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"""A collection of boolean primitive values"""
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feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
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collection: list[bool] = InputField(default=[], description="The collection of boolean values")
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2023-08-15 12:18:37 +00:00
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2024-02-05 06:16:35 +00:00
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def invoke(self, context: InvocationContext) -> BooleanCollectionOutput:
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2023-08-15 12:18:37 +00:00
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return BooleanCollectionOutput(collection=self.collection)
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2023-08-14 09:41:29 +00:00
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# endregion
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# region Integer
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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
2023-08-30 08:35:12 +00:00
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@invocation_output("integer_output")
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2023-08-14 09:41:29 +00:00
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class IntegerOutput(BaseInvocationOutput):
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"""Base class for nodes that output a single integer"""
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2023-08-18 10:17:21 +00:00
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value: int = OutputField(description="The output integer")
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2023-08-14 09:41:29 +00:00
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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
2023-08-30 08:35:12 +00:00
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@invocation_output("integer_collection_output")
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2023-08-14 09:41:29 +00:00
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class IntegerCollectionOutput(BaseInvocationOutput):
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"""Base class for nodes that output a collection of integers"""
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feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
|
|
|
collection: list[int] = OutputField(
|
|
|
|
description="The int collection",
|
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
2023-09-04 08:11:56 +00:00
|
|
|
@invocation(
|
|
|
|
"integer", title="Integer Primitive", tags=["primitives", "integer"], category="primitives", version="1.0.0"
|
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
class IntegerInvocation(BaseInvocation):
|
|
|
|
"""An integer primitive value"""
|
|
|
|
|
2023-08-18 10:17:21 +00:00
|
|
|
value: int = InputField(default=0, description="The integer value")
|
2023-08-14 09:41:29 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> IntegerOutput:
|
2023-08-18 10:17:21 +00:00
|
|
|
return IntegerOutput(value=self.value)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"integer_collection",
|
|
|
|
title="Integer Collection Primitive",
|
|
|
|
tags=["primitives", "integer", "collection"],
|
|
|
|
category="primitives",
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
version="1.0.1",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-15 12:18:37 +00:00
|
|
|
class IntegerCollectionInvocation(BaseInvocation):
|
|
|
|
"""A collection of integer primitive values"""
|
|
|
|
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
collection: list[int] = InputField(default=[], description="The collection of integer values")
|
2023-08-15 12:18:37 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
|
2023-08-15 12:18:37 +00:00
|
|
|
return IntegerCollectionOutput(collection=self.collection)
|
|
|
|
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
# endregion
|
|
|
|
|
|
|
|
# region Float
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("float_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class FloatOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a single float"""
|
|
|
|
|
2023-08-18 10:17:21 +00:00
|
|
|
value: float = OutputField(description="The output float")
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("float_collection_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class FloatCollectionOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a collection of floats"""
|
|
|
|
|
feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
|
|
|
collection: list[float] = OutputField(
|
|
|
|
description="The float collection",
|
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
2023-09-04 08:11:56 +00:00
|
|
|
@invocation("float", title="Float Primitive", tags=["primitives", "float"], category="primitives", version="1.0.0")
|
2023-08-14 09:41:29 +00:00
|
|
|
class FloatInvocation(BaseInvocation):
|
|
|
|
"""A float primitive value"""
|
|
|
|
|
2023-08-18 10:17:21 +00:00
|
|
|
value: float = InputField(default=0.0, description="The float value")
|
2023-08-14 09:41:29 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> FloatOutput:
|
2023-08-18 10:17:21 +00:00
|
|
|
return FloatOutput(value=self.value)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"float_collection",
|
|
|
|
title="Float Collection Primitive",
|
|
|
|
tags=["primitives", "float", "collection"],
|
|
|
|
category="primitives",
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
version="1.0.1",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-15 12:18:37 +00:00
|
|
|
class FloatCollectionInvocation(BaseInvocation):
|
|
|
|
"""A collection of float primitive values"""
|
|
|
|
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
collection: list[float] = InputField(default=[], description="The collection of float values")
|
2023-08-15 12:18:37 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
|
2023-08-15 12:18:37 +00:00
|
|
|
return FloatCollectionOutput(collection=self.collection)
|
|
|
|
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
# endregion
|
|
|
|
|
|
|
|
# region String
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("string_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class StringOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a single string"""
|
|
|
|
|
2023-08-18 10:17:21 +00:00
|
|
|
value: str = OutputField(description="The output string")
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("string_collection_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class StringCollectionOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a collection of strings"""
|
|
|
|
|
feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
|
|
|
collection: list[str] = OutputField(
|
|
|
|
description="The output strings",
|
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
2023-09-04 08:11:56 +00:00
|
|
|
@invocation("string", title="String Primitive", tags=["primitives", "string"], category="primitives", version="1.0.0")
|
2023-08-14 09:41:29 +00:00
|
|
|
class StringInvocation(BaseInvocation):
|
|
|
|
"""A string primitive value"""
|
|
|
|
|
2023-08-18 10:17:21 +00:00
|
|
|
value: str = InputField(default="", description="The string value", ui_component=UIComponent.Textarea)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> StringOutput:
|
2023-08-18 10:17:21 +00:00
|
|
|
return StringOutput(value=self.value)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"string_collection",
|
|
|
|
title="String Collection Primitive",
|
|
|
|
tags=["primitives", "string", "collection"],
|
|
|
|
category="primitives",
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
version="1.0.1",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-15 12:18:37 +00:00
|
|
|
class StringCollectionInvocation(BaseInvocation):
|
|
|
|
"""A collection of string primitive values"""
|
|
|
|
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
collection: list[str] = InputField(default=[], description="The collection of string values")
|
2023-08-15 12:18:37 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> StringCollectionOutput:
|
2023-08-15 12:18:37 +00:00
|
|
|
return StringCollectionOutput(collection=self.collection)
|
|
|
|
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
# endregion
|
|
|
|
|
|
|
|
# region Image
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("image_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ImageOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a single image"""
|
|
|
|
|
|
|
|
image: ImageField = OutputField(description="The output image")
|
|
|
|
width: int = OutputField(description="The width of the image in pixels")
|
|
|
|
height: int = OutputField(description="The height of the image in pixels")
|
|
|
|
|
2024-01-13 12:23:16 +00:00
|
|
|
@classmethod
|
|
|
|
def build(cls, image_dto: ImageDTO) -> "ImageOutput":
|
|
|
|
return cls(
|
|
|
|
image=ImageField(image_name=image_dto.image_name),
|
|
|
|
width=image_dto.width,
|
|
|
|
height=image_dto.height,
|
|
|
|
)
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("image_collection_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ImageCollectionOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a collection of images"""
|
|
|
|
|
feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
|
|
|
collection: list[ImageField] = OutputField(
|
|
|
|
description="The output images",
|
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
2024-01-13 12:23:16 +00:00
|
|
|
@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives", version="1.0.1")
|
2024-02-07 05:33:55 +00:00
|
|
|
class ImageInvocation(BaseInvocation):
|
2023-08-14 09:41:29 +00:00
|
|
|
"""An image primitive value"""
|
|
|
|
|
|
|
|
image: ImageField = InputField(description="The image to load")
|
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> ImageOutput:
|
2024-01-13 12:23:16 +00:00
|
|
|
image = context.images.get_pil(self.image.image_name)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
return ImageOutput(
|
|
|
|
image=ImageField(image_name=self.image.image_name),
|
|
|
|
width=image.width,
|
|
|
|
height=image.height,
|
|
|
|
)
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"image_collection",
|
|
|
|
title="Image Collection Primitive",
|
|
|
|
tags=["primitives", "image", "collection"],
|
|
|
|
category="primitives",
|
2023-09-04 08:11:56 +00:00
|
|
|
version="1.0.0",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-15 12:18:37 +00:00
|
|
|
class ImageCollectionInvocation(BaseInvocation):
|
|
|
|
"""A collection of image primitive values"""
|
|
|
|
|
2023-09-04 05:24:44 +00:00
|
|
|
collection: list[ImageField] = InputField(description="The collection of image values")
|
2023-08-15 12:18:37 +00:00
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> ImageCollectionOutput:
|
2023-08-15 12:18:37 +00:00
|
|
|
return ImageCollectionOutput(collection=self.collection)
|
|
|
|
|
|
|
|
|
2023-08-17 16:19:07 +00:00
|
|
|
# endregion
|
|
|
|
|
2023-08-26 17:50:13 +00:00
|
|
|
# region DenoiseMask
|
2023-08-17 16:19:07 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("denoise_mask_output")
|
2023-08-26 17:50:13 +00:00
|
|
|
class DenoiseMaskOutput(BaseInvocationOutput):
|
2023-08-18 01:07:40 +00:00
|
|
|
"""Base class for nodes that output a single image"""
|
|
|
|
|
2023-08-26 17:50:13 +00:00
|
|
|
denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run")
|
2023-08-17 16:19:07 +00:00
|
|
|
|
2024-01-13 12:23:16 +00:00
|
|
|
@classmethod
|
2024-02-21 02:13:19 +00:00
|
|
|
def build(
|
2024-02-21 03:13:01 +00:00
|
|
|
cls, mask_name: str, masked_latents_name: Optional[str] = None, gradient: bool = False
|
2024-02-21 02:13:19 +00:00
|
|
|
) -> "DenoiseMaskOutput":
|
2024-01-13 12:23:16 +00:00
|
|
|
return cls(
|
2024-02-21 02:13:19 +00:00
|
|
|
denoise_mask=DenoiseMaskField(
|
|
|
|
mask_name=mask_name, masked_latents_name=masked_latents_name, gradient=gradient
|
|
|
|
),
|
2024-01-13 12:23:16 +00:00
|
|
|
)
|
|
|
|
|
2023-08-17 16:19:07 +00:00
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
# endregion
|
|
|
|
|
|
|
|
# region Latents
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("latents_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class LatentsOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a single latents tensor"""
|
|
|
|
|
2024-02-07 06:41:23 +00:00
|
|
|
latents: LatentsField = OutputField(description=FieldDescriptions.latents)
|
2023-08-14 09:41:29 +00:00
|
|
|
width: int = OutputField(description=FieldDescriptions.width)
|
|
|
|
height: int = OutputField(description=FieldDescriptions.height)
|
|
|
|
|
2024-01-13 12:23:16 +00:00
|
|
|
@classmethod
|
|
|
|
def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
|
|
|
|
return cls(
|
|
|
|
latents=LatentsField(latents_name=latents_name, seed=seed),
|
2024-02-10 21:54:01 +00:00
|
|
|
width=latents.size()[3] * LATENT_SCALE_FACTOR,
|
|
|
|
height=latents.size()[2] * LATENT_SCALE_FACTOR,
|
2024-01-13 12:23:16 +00:00
|
|
|
)
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("latents_collection_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class LatentsCollectionOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a collection of latents tensors"""
|
|
|
|
|
2023-08-15 12:18:37 +00:00
|
|
|
collection: list[LatentsField] = OutputField(
|
2023-08-14 09:41:29 +00:00
|
|
|
description=FieldDescriptions.latents,
|
|
|
|
)
|
|
|
|
|
|
|
|
|
2023-09-04 08:11:56 +00:00
|
|
|
@invocation(
|
2024-01-13 12:23:16 +00:00
|
|
|
"latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives", version="1.0.1"
|
2023-09-04 08:11:56 +00:00
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
class LatentsInvocation(BaseInvocation):
|
|
|
|
"""A latents tensor primitive value"""
|
|
|
|
|
|
|
|
latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
|
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> LatentsOutput:
|
2024-02-07 12:30:46 +00:00
|
|
|
latents = context.tensors.load(self.latents.latents_name)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
2024-01-13 12:23:16 +00:00
|
|
|
return LatentsOutput.build(self.latents.latents_name, latents)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"latents_collection",
|
|
|
|
title="Latents Collection Primitive",
|
|
|
|
tags=["primitives", "latents", "collection"],
|
|
|
|
category="primitives",
|
2023-09-04 08:11:56 +00:00
|
|
|
version="1.0.0",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-15 12:18:37 +00:00
|
|
|
class LatentsCollectionInvocation(BaseInvocation):
|
|
|
|
"""A collection of latents tensor primitive values"""
|
|
|
|
|
|
|
|
collection: list[LatentsField] = InputField(
|
feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
|
|
|
description="The collection of latents tensors",
|
2023-08-15 12:18:37 +00:00
|
|
|
)
|
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> LatentsCollectionOutput:
|
2023-08-15 12:18:37 +00:00
|
|
|
return LatentsCollectionOutput(collection=self.collection)
|
|
|
|
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
# endregion
|
|
|
|
|
|
|
|
# region Color
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("color_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ColorOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a single color"""
|
|
|
|
|
|
|
|
color: ColorField = OutputField(description="The output color")
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("color_collection_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ColorCollectionOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a collection of colors"""
|
|
|
|
|
feat: polymorphic fields
Initial support for polymorphic field types. Polymorphic types are a single of or list of a specific type. For example, `Union[str, list[str]]`.
Polymorphics do not yet have support for direct input in the UI (will come in the future). They will be forcibly set as Connection-only fields, in which case users will not be able to provide direct input to the field.
If a polymorphic should present as a singleton type - which would allow direct input - the node must provide an explicit type hint.
For example, `DenoiseLatents`' `CFG Scale` is polymorphic, but in the node editor, we want to present this as a number input. In the node definition, the field is given `ui_type=UIType.Float`, which tells the UI to treat this as a `float` field.
The connection validation logic will prevent connecting a collection to `CFG Scale` in this situation, because it is typed as `float`. The workaround is to disable validation from the settings to make this specific connection. A future improvement will resolve this.
This also introduces better support for collection field types. Like polymorphics, collection types are parsed automatically by the client and do not need any specific type hints.
Also like polymorphics, there is no support yet for direct input of collection types in the UI.
- Disabling validation in workflow editor now displays the visual hints for valid connections, but lets you connect to anything.
- Added `ui_order: int` to `InputField` and `OutputField`. The UI will use this, if present, to order fields in a node UI. See usage in `DenoiseLatents` for an example.
- Updated the field colors - duplicate colors have just been lightened a bit. It's not perfect but it was a quick fix.
- Field handles for collections are the same color as their single counterparts, but have a dark dot in the center of them.
- Field handles for polymorphics are a rounded square with dot in the middle.
- Removed all fields that just render `null` from `InputFieldRenderer`, replaced with a single fallback
- Removed logic in `zValidatedWorkflow`, which checked for existence of node templates for each node in a workflow. This logic introduced a circular dependency, due to importing the global redux `store` in order to get the node templates within a zod schema. It's actually fine to just leave this out entirely; The case of a missing node template is handled by the UI. Fixing it otherwise would introduce a substantial headache.
- Fixed the `ControlNetInvocation.control_model` field default, which was a string when it shouldn't have one.
2023-09-01 09:40:27 +00:00
|
|
|
collection: list[ColorField] = OutputField(
|
|
|
|
description="The output colors",
|
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
|
|
|
|
|
2023-09-04 08:11:56 +00:00
|
|
|
@invocation("color", title="Color Primitive", tags=["primitives", "color"], category="primitives", version="1.0.0")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ColorInvocation(BaseInvocation):
|
|
|
|
"""A color primitive value"""
|
|
|
|
|
|
|
|
color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color value")
|
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> ColorOutput:
|
2023-08-14 09:41:29 +00:00
|
|
|
return ColorOutput(color=self.color)
|
|
|
|
|
|
|
|
|
|
|
|
# endregion
|
|
|
|
|
|
|
|
# region Conditioning
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("conditioning_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ConditioningOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a single conditioning tensor"""
|
|
|
|
|
|
|
|
conditioning: ConditioningField = OutputField(description=FieldDescriptions.cond)
|
|
|
|
|
2024-01-13 12:23:16 +00:00
|
|
|
@classmethod
|
|
|
|
def build(cls, conditioning_name: str) -> "ConditioningOutput":
|
|
|
|
return cls(conditioning=ConditioningField(conditioning_name=conditioning_name))
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation_output("conditioning_collection_output")
|
2023-08-14 09:41:29 +00:00
|
|
|
class ConditioningCollectionOutput(BaseInvocationOutput):
|
|
|
|
"""Base class for nodes that output a collection of conditioning tensors"""
|
|
|
|
|
|
|
|
collection: list[ConditioningField] = OutputField(
|
|
|
|
description="The output conditioning tensors",
|
|
|
|
)
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"conditioning",
|
|
|
|
title="Conditioning Primitive",
|
|
|
|
tags=["primitives", "conditioning"],
|
|
|
|
category="primitives",
|
2023-09-04 08:11:56 +00:00
|
|
|
version="1.0.0",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-14 09:41:29 +00:00
|
|
|
class ConditioningInvocation(BaseInvocation):
|
|
|
|
"""A conditioning tensor primitive value"""
|
|
|
|
|
|
|
|
conditioning: ConditioningField = InputField(description=FieldDescriptions.cond, input=Input.Connection)
|
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> ConditioningOutput:
|
2023-08-14 09:41:29 +00:00
|
|
|
return ConditioningOutput(conditioning=self.conditioning)
|
|
|
|
|
|
|
|
|
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
2023-08-30 08:35:12 +00:00
|
|
|
@invocation(
|
|
|
|
"conditioning_collection",
|
|
|
|
title="Conditioning Collection Primitive",
|
|
|
|
tags=["primitives", "conditioning", "collection"],
|
|
|
|
category="primitives",
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
version="1.0.1",
|
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
2023-08-30 08:35:12 +00:00
|
|
|
)
|
2023-08-15 12:18:37 +00:00
|
|
|
class ConditioningCollectionInvocation(BaseInvocation):
|
|
|
|
"""A collection of conditioning tensor primitive values"""
|
|
|
|
|
|
|
|
collection: list[ConditioningField] = InputField(
|
feat(ui): add support for custom field types
Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported.
Two notes:
1. Your field type's class name must be unique.
Suggest prefixing fields with something related to the node pack as a kind of namespace.
2. Custom field types function as connection-only fields.
For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type.
This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection.
feat(ui): fix tooltips for custom types
We need to hold onto the original type of the field so they don't all just show up as "Unknown".
fix(ui): fix ts error with custom fields
feat(ui): custom field types connection validation
In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic.
*Actually, it was `"Unknown"`, but I changed it to custom for clarity.
Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields.
To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`.
This ended up needing a bit of fanagling:
- If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property.
While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer.
(Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.)
- Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future.
- We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`.
Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`.
This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent.
fix(ui): typo
feat(ui): add CustomCollection and CustomPolymorphic field types
feat(ui): add validation for CustomCollection & CustomPolymorphic types
- Update connection validation for custom types
- Use simple string parsing to determine if a field is a collection or polymorphic type.
- No longer need to keep a list of collection and polymorphic types.
- Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing
chore(ui): remove errant console.log
fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType'
This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type.
fix(ui): fix ts error
feat(nodes): add runtime check for custom field names
"Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names.
chore(ui): add TODO for revising field type names
wip refactor fieldtype structured
wip refactor field types
wip refactor types
wip refactor types
fix node layout
refactor field types
chore: mypy
organisation
organisation
organisation
fix(nodes): fix field orig_required, field_kind and input statuses
feat(nodes): remove broken implementation of default_factory on InputField
Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args.
Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used.
Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`.
fix(nodes): fix InputField name validation
workflow validation
validation
chore: ruff
feat(nodes): fix up baseinvocation comments
fix(ui): improve typing & logic of buildFieldInputTemplate
improved error handling in parseFieldType
fix: back compat for deprecated default_factory and UIType
feat(nodes): do not show node packs loaded log if none loaded
chore(ui): typegen
2023-11-17 00:32:35 +00:00
|
|
|
default=[],
|
2023-08-31 03:22:31 +00:00
|
|
|
description="The collection of conditioning tensors",
|
2023-08-15 12:18:37 +00:00
|
|
|
)
|
|
|
|
|
2024-02-05 06:16:35 +00:00
|
|
|
def invoke(self, context: InvocationContext) -> ConditioningCollectionOutput:
|
2023-08-15 12:18:37 +00:00
|
|
|
return ConditioningCollectionOutput(collection=self.collection)
|
|
|
|
|
|
|
|
|
2023-08-14 09:41:29 +00:00
|
|
|
# endregion
|