The valid values for this parameter changed when inpainting changed to gradient denoise. The generation slice's redux migration wasn't updated, resulting in a generation error until you change the setting or reset web UI.
With the change to model identifiers from v3 to v4, if a user had persisted redux state with the old format, we could get unexpected runtime errors when rehydrating state if we try to access model attributes that no longer exist.
For example, the CLIP Skip component does this:
```ts
CLIP_SKIP_MAP[model.base].maxClip
```
In v3, models had a `base_type` attribute, but it is renamed to `base` in v4. This code therefore causes a runtime error:
- `model.base` is `undefined`
- `CLIP_SKIP_MAP[undefined]` is also undefined
- `undefined.maxClip` is a runtime error!
Resolved by adding a migration for the redux slices that have model identifiers. The migration simply resets the slice or the part of the slice that is affected, when it's simple to do a partial reset.
Closes#6000
* move defaultModel logic to modelsLoaded and update to work for key instead of name/base/type string
* lint fix
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
* UI in MM to create trigger phrases
* add scheduler and vaePrecision to config
* UI for configuring default settings for models'
* hook MM default model settings up to API
* add button to set default settings in parameters
* pull out trigger phrases
* back-end for default settings
* lint
* remove log;
gi
* ruff
* ruff format
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
- Update most model identifiers to be `{key: string}` instead of name/base/type. Doesn't change the model select components yet.
- Update model _parameters_, stored in redux, to be `{key: string, base: BaseModel}` - we need to store the base model to be able to check model compatibility. May want to store the whole config? Not sure...
There's a challenge to accomplish this due to our slice structure - the model is stored in `generationSlice`, but `canvasSlice` also needs to have awareness of it. For example, when the model changes, the canvas slice doesn't know what the previous model was, so it doesn't know whether or not to optimize the size.
This means we need to lift the "should we optimize size" information up. To do this, the `modelChanged` action creator accepts the previous model as an optional second arg.
Now the canvas has access to both the previous model and new model selection, and can decide whether or not it should optimize its size setting in the same way that the generation slice does.
Closes #5452
* feat(ui): get rid of convoluted socket vs appSocket redux actions
There's no need to have `socket...` and `appSocket...` actions.
I did this initially due to a misunderstanding about the sequence of handling from middleware to reducers.
* feat(ui): bump deps
Mainly bumping to get latest `redux-remember`.
A change to socket.io required a change to the types in `useSocketIO`.
* chore(ui): format
* feat(ui): add error handling to redux persistence layer
- Add an error handler to `redux-remember` config using our logger
- Add custom errors representing storage set and get failures
- Update storage driver to raise these accordingly
- wrap method to clear idbkeyval storage and tidy its logic up
* feat(ui): add debuggingLoggerMiddleware
This simply logs every action and a diff of the state change.
Due to the noise this creates, it's not added by default at all. Add it to the middlewares if you want to use it.
* feat(ui): add $socket to window if in dev mode
* fix(ui): do not enable cancel hotkeys on inputs
* fix(ui): use JSON.stringify for ROARR logger serializer
A recent change to ROARR introduced limits to the size of data that will logged. This ends up making our logs far less useful. Change the serializer back to what it was previously.
* feat(ui): change diff util, update debuggerLoggerMiddleware
The previous diff library would present deleted things as `undefined`. Unfortunately, a JSON.stringify cycle will strip those values out. The ROARR logger does this and so the diffs end up being a lot less useful, not showing removed keys.
The new diff library uses a different format for the delta that serializes nicely.
* feat(ui): add migrations to redux persistence layer
- All persisted slices must now have a slice config, consisting of their initial state and a migrate callback. The migrate callback is very simple for now, with no type safety. It adds missing properties to the state. A future enhancement might be to model the each slice's state with e.g. zod and have proper validation and types.
- Persisted slices now have a `_version` property
- The migrate callback is called inside `redux-remember`'s `unserialize` handler. I couldn't figure out a good way to put this into the reducer and do logging (reducers should have no side effects). Also I ran into a weird race condition that I couldn't figure out. And finally, the typings are tricky. This works for now.
- `generationSlice` and `canvasSlice` both need migrations for the new aspect ratio setup, this has been added
- Stuff related to persistence has been moved in to `store.ts` for simplicity
* feat(ui): clean up StorageError class
* fix(ui): scale method default is now 'auto'
* feat(ui): when changing controlnet model, enable autoconfig
* fix(ui): make embedding popover immediately accessible
Prevents hotkeys from being captured when embeddings are still loading.
Centralize the initial/min/max/etc values for all numerical params. We used this for some but at some point stopped updating it.
All numerical params now use their respective configs. Far fewer hardcoded values throughout the app now.
Also updated the config types a bit to better accommodate slider vs number input constraints.
Ensure workflow editor model selector component gets a value
This introduced some funky type issues related to ONNX models. ONNX doesn't work anyways (unmaintained). Instead of fixing the types to work with a non-working feature, ONNX is now removed entirely from the UI.
- Remove all refs to ONNX (and Olives)
- Fix some type issues
- Add ONNX nodes to the nodes denylist (so they are not visible in UI)
- Update VAE graph helper, which still had some ONNX logic. It's a very simple change and doesn't change any logic. Just removes some conditions that were for ONNX. I tested it and nothing broke.
- Regenerate types
- Fix prettier and eslint ignores for generated types
- Lint
Canvas and non-canvas have separate width and height and need their own separate aspect ratios. In order to not duplicate a lot of aspect ratio logic, the components relating to image size have been modularized.
There are a few breaking changes, which I've addressed.
The vast majority of changes are related to new handling of `reselect`'s `createSelector` options.
For better or worse, we memoize just about all our selectors using lodash `isEqual` for `resultEqualityCheck`. The upgrade requires we explicitly set the `memoize` option to `lruMemoize` to continue using lodash here.
Doing that required changing our `defaultSelectorOptions`.
Instead of changing that and finding dozens of instances where we weren't using that and instead were defining selector options manually, I've created a pre-configured selector: `createMemoizedSelector`.
This is now used everywhere instead of `createSelector`.
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
* working
* added selector for method
* refactoring graph
* added ersgan method
* fixing yarn build
* add tooltips
* a conjuction
* rephrase
* removed manual sliders, set HRF to calculate dimensions automatically to match 512^2 pixels
* working
* working
* working
* fixed tooltip
* add hrf to use all parameters
* adding hrf method to parameters
* working on parameter recall
* working on parameter recall
* cleaning
* fix(ui): fix unnecessary casts in addHrfToGraph
* chore(ui): use camelCase in addHrfToGraph
* fix(ui): do not add HRF metadata unless HRF is added to graph
* fix(ui): remove unused imports in addHrfToGraph
* feat(ui): do not hide HRF params when disabled, only disable them
* fix(ui): remove unused vars in addHrfToGraph
* feat(ui): default HRF str to 0.35, method ESRGAN
* fix(ui): use isValidBoolean to check hrfEnabled param
* fix(nodes): update CoreMetadataInvocation fields for HRF
* feat(ui): set hrf strength default to 0.45
* fix(ui): set default hrf strength in configSlice
* feat(ui): use translations for HRF features
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* added HrfScale type with initial value
* working
* working
* working
* working
* working
* added addHrfToGraph
* continueing to implement this
* working on this
* comments
* working
* made hrf into its own collapse
* working on adding strength slider
* working
* working
* refactoring
* working
* change of this working: 0
* removed onnx support since apparently its not used
* working
* made scale integer
* trying out psycicpebbles idea
* working
* working on this
* working
* added toggle
* comments
* self review
* fixing things
* remove 'any' type
* fixing typing
* changed initial strength value to 3 (large values cause issues)
* set denoising start to be 1 - strength to resemble image to image
* set initial value
* added image to image
* pr1
* pr2
* updating to resolution finding
* working
* working
* working
* working
* working
* working
* working
* working
* working
* use memo
* connect rescale hw to noise
* working
* fixed min bug
* nit
* hides elements conditionally
* style
* feat(ui): add config for HRF, disable if feature disabled or ONNX model in use
* fix(ui): use `useCallback` for HRF toggle
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
