When recalling metadata and/or using control image dimensions, it was possible to set a width or height that was not a multiple of 8, resulting in generation failures.
Added a `clamp` option to the w/h actions to fix this. The option is used for all untrusted sources - everything except for the w/h number inputs, which clamp the values themselves.
These changes were left over from the previous attempt to handle control adapters in control layers with the same logic. Control Layers are now handled totally separately, so these changes may be reverted.
- Revise control adapter config types
- Recreate all control adapter mutations in control layers slice
- Bit of renaming along the way - typing 'RegionalGuidanceLayer' over and over again was getting tedious
Handful of intertwined fixes.
- Create and use helper function to reset staging area.
- Clear staging area when queue items are canceled, failed, cleared, etc. Fixes a bug where the bbox ends up offset and images are put into the wrong spot.
- Fix a number of similar bugs where canvas would "forget" it had pending generations, but they continued to generate. Canvas needs to track batches that should be displayed in it using `state.canvas.batchIds`, and this was getting cleared without actually canceling those batches.
- Disable the `discard current image` button on canvas if there is only one image. Prevents accidentally canceling all canvas batches if you spam the button.
- Add and use more performant `deepClone` method for deep copying throughout the UI.
Benchmarks indicate the Really Fast Deep Clone library (`rfdc`) is the best all-around way to deep-clone large objects.
This is particularly relevant in canvas. When drawing or otherwise manipulating canvas objects, we need to do a lot of deep cloning of the canvas layer state objects.
Previously, we were using lodash's `cloneDeep`.
I did some fairly realistic benchmarks with a handful of deep-cloning algorithms/libraries (including the native `structuredClone`). I used a snapshot of the canvas state as the data to be copied:
On Chromium, `rfdc` is by far the fastest, over an order of magnitude faster than `cloneDeep`.
On FF, `fastest-json-copy` and `recursiveDeepCopy` are even faster, but are rather limited in data types. `rfdc`, while only half as fast as the former 2, is still nearly an order of magnitude faster than `cloneDeep`.
On Safari, `structuredClone` is the fastest, about 2x as fast as `cloneDeep`. `rfdc` is only 30% faster than `cloneDeep`.
`rfdc`'s peak memory usage is about 10% more than `cloneDeep` on Chrome. I couldn't get memory measurements from FF and Safari, but let's just assume the memory usage is similar relative to the other algos.
Overall, `rfdc` is the best choice for a single algo for all browsers. It's definitely the best for Chromium, by far the most popular desktop browser and thus our primary target.
A future enhancement might be to detect the browser and use that to determine which algorithm to use.
- Display a toast on UI launch if the HF token is invalid
- Show form in MM if token is invalid or unable to be verified, let user set the token via this form
When consolidating all the model queries I messed up the query tags. Fixed now, so that when a model is installed, removed, or changed, the list refreshes.
* move defaultModel logic to modelsLoaded and update to work for key instead of name/base/type string
* lint fix
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Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
- Update all queries
- Remove Advanced Add
- Removed un-editable, internal-only model attributes from model edit UI (e.g. format, repo variant, model type)
- Update model tags so the list refreshes when a model installs
- Rename some queries, components, variables, types to match backend
- Fix divide-by-zero in install queue
* 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
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Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Add concepts for metadata handlers. Handlers include parsers, recallers and validators for different metadata types:
- Parsers parse a raw metadata object of any shape to a structured object.
- Recallers load the parsed metadata into state. Recallers are optional, as some metadata types don't need to be loaded into state.
- Validators provide an additional layer of validation before recalling the metadata. This is needed because a metadata object may be valid, but not able to be recalled due to some other requirement, like base model compatibility. Validators are optional.
Sometimes metadata is not a single object but a list of items - like LoRAs. Metadata handlers may implement an optional set of "item" handlers which operate on individual items in the list.
Parsers and validators are async to allow fetching additional data, like a model config. Recallers are synchronous.
The these handlers are composed into a public API, exported as a `handlers` object. Besides the handlers functions, a metadata handler set includes:
- A function to get the label of the metadata type.
- An optional function to render the value of the metadata type.
- An optional function to render the _item_ value of the metadata type.
Refactor of metadata recall handling. This is in preparation for a backwards compatibility layer for models.
- Create helpers to fetch a model outside react (e.g. not in a hook)
- Created helpers to parse model metadata
- Renamed a lot of types that were confusing and/or had naming collisions
Notable updates:
- Minor version of RTK includes customizable selectors for RTK Query, so we can remove the patch that was added to ensure only the LRU memoize function was used for perf reasons. Updated to use the LRU memoize function.
- Major version of react-resizable-panels. No breaking changes, works great, and you can now resize all panels when dragging at the intersection point of panels. Cool!
- Minor (?) version of nanostores. `action` API is removed, we were using it in one spot. Fixed.
- @invoke-ai/eslint-config-react has all deps bumped and now has its dependent plugins/configs listed as normal dependencies (as opposed to peer deps). This means we can remove those packages from explicit dev deps.
- Use a single listener for all of the to keep them in one spot
- Use the bulk download item name as a toast id so we can update the existing toasts
- Update handling to work with other environments
- Move all bulk download handling from components to listener
- 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...
The changes aim to deduplicate data between workflows and node templates, decoupling workflows from internal implementation details. A good amount of data that was needlessly duplicated from the node template to the workflow is removed.
These changes substantially reduce the file size of workflows (and therefore the images with embedded workflows):
- Default T2I SD1.5 workflow JSON is reduced from 23.7kb (798 lines) to 10.9kb (407 lines).
- Default tiled upscale workflow JSON is reduced from 102.7kb (3341 lines) to 51.9kb (1774 lines).
The trade-off is that we need to reference node templates to get things like the field type and other things. In practice, this is a non-issue, because we need a node template to do anything with a node anyways.
- Field types are not included in the workflow. They are always pulled from the node templates.
The field type is now properly an internal implementation detail and we can change it as needed. Previously this would require a migration for the workflow itself. With the v3 schema, the structure of a field type is an internal implementation detail that we are free to change as we see fit.
- Workflow nodes no long have an `outputs` property and there is no longer such a thing as a `FieldOutputInstance`. These are only on the templates.
These were never referenced at a time when we didn't also have the templates available, and there'd be no reason to do so.
- Node width and height are no longer stored in the node.
These weren't used. Also, per https://reactflow.dev/api-reference/types/node, we shouldn't be programmatically changing these properties. A future enhancement can properly add node resizing.
- `nodeTemplates` slice is merged back into `nodesSlice` as `nodes.templates`. Turns out it's just a hassle having these separate in separate slices.
- Workflow migration logic updated to support the new schema. V1 workflows migrate all the way to v3 now.
- Changes throughout the nodes code to accommodate the above changes.
* new workflow tab UI - still using shared state with workflow editor tab
* polish workflow details
* remove workflow tab, add edit/view mode to workflow slice and get that working to switch between within editor tab
* UI updates for view/edit mode
* cleanup
* add warning to view mode
* lint
* start with isTouched false
* working on styling mode toggle
* more UX iteration
* lint
* cleanup
* save original field values to state, add indicator if they have been changed and give user choice to reset
* lint
* fix import and commit translation
* dont switch to view mode when loading a workflow
* warns before clearing editor
* use folder icon
* fix(ui): track do not erase value when resetting field value
- When adding an exposed field, we need to add it to originalExposedFieldValues
- When removing an exposed field, we need to remove it from originalExposedFieldValues
- add `useFieldValue` and `useOriginalFieldValue` hooks to encapsulate related logic
* feat(ui): use IconButton for workflow view/edit button
* feat(ui): change icon for new workflow
It was the same as the workflow tab icon, confusing bc you think it's going to somehow take you to the tab.
* feat(ui): use render props for NewWorkflowConfirmationAlertDialog
There was a lot of potentially sensitive logic shared between the new workflow button and menu items. Also, two instances of ConfirmationAlertDialog.
Using a render prop deduplicates the logic & components
* fix(ui): do not mark workflow touched when loading workflow
This was occurring because the `nodesChanged` action is called by reactflow when loading a workflow. Specifically, it calculates and sets the node dimensions as it loads.
The existing logic set `isTouched` whenever this action was called.
The changes reactflow emits have types, and we can use the change types and data to determine if a change should result in the workflow being marked as touched.
* chore(ui): lint
* chore(ui): lint
* delete empty file
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Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
