The VAE decode on linear graphs was getting cached. This caused some unexpected behaviour around image outputs.
For example, say you ran the exact same graph twice. The first time, you get an image written to disk and added to gallery. The second time, the VAE decode is cached and no image file is created. But, the UI still gets the graph complete event and selects the first image in the gallery. The second run does not add an image to the gallery.
There are probbably edge cases related to this - the UI does not expect this to happen. I'm not sure how to handle it any better in the UI.
The solution is to not cache VAE decode on the linear graphs, ever. If you run a graph twice in linear, you expect two images.
This simple change disables the node cache for terminal VAE decode nodes in all linear graphs, ensuring you always get images. If they graph was fully cached, all images after the first will be created very quickly of course.
- "Reset Workflow Editor" -> "New Workflow"
- "New Workflow" gets nodes icon & is no longer danger coloured
- When creating a new workflow, if the current workflow has unsaved changes, you get a dialog asking for confirmation. If the current workflow is saved, it immediately creates a new workflow.
- "Download Workflow" -> "Save to File"
- "Upload Workflow" -> "Load from File"
- Moved "Load from File" up 1 in the menu
* selector added
* ref and useeffect added
* scrolling done using useeffect
* fixed scroll and changed the ref name
* fixed scroll again
* created hook for scroll logic
* feat(ui): debounce metadata fetch by 300ms
This vastly reduces the network requests when using the arrow keys to quickly skim through images.
* feat(ui): extract logic to determine virtuoso scrollToIndex align
This needs to be used in `useNextPrevImage()` to ensure the scrolling puts the image at the top or bottom appropriately
* feat(ui): add debounce to image workflow hook
This was spamming network requests like the metadata query
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Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Invocations now have a classification:
- Stable: LTS
- Beta: LTS planned, API may change
- Prototype: No LTS planned, API may change, may be removed entirely
The `@invocation` decorator has a new arg `classification`, and an enum `Classification` is added to `baseinvocation.py`.
The default is Stable; this is a non-breaking change.
The classification is presented in the node header as a hammer icon (Beta) or flask icon (prototype).
The icon has a tooltip briefly describing the classification.
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`.
This addresses an edge case where:
1. the workflow references fields that are present on the workflow's nodes, but not on the invocation templates for those nodes and
2. The invocation template for that type does exist
This should be a fairly obscure edge case, but could happen if a user fiddled around with the workflow manually.
I ran into it as a result of two nodes having accidentally mixed up their invocation types, a problem introduced with a wonky merge commit.
This logic is moved into a hook.
This is needed for our context menus to close when the user clicks something in reactflow. It needed to be extended to support menus also.
Disabling these introduces an issue where, if you were on an image with a workflow/metadata, then switch to one without, you can end up on a disabled tab. This could potentially cause a runtime error.
* chore: bump pydantic to 2.5.2
This release fixespydantic/pydantic#8175 and allows us to use `JsonValue`
* fix(ui): exclude public/en.json from prettier config
* fix(workflow_records): fix SQLite workflow insertion to ignore duplicates
* feat(backend): update workflows handling
Update workflows handling for Workflow Library.
**Updated Workflow Storage**
"Embedded Workflows" are workflows associated with images, and are now only stored in the image files. "Library Workflows" are not associated with images, and are stored only in DB.
This works out nicely. We have always saved workflows to files, but recently began saving them to the DB in addition to in image files. When that happened, we stopped reading workflows from files, so all the workflows that only existed in images were inaccessible. With this change, access to those workflows is restored, and no workflows are lost.
**Updated Workflow Handling in Nodes**
Prior to this change, workflows were embedded in images by passing the whole workflow JSON to a special workflow field on a node. In the node's `invoke()` function, the node was able to access this workflow and save it with the image. This (inaccurately) models workflows as a property of an image and is rather awkward technically.
A workflow is now a property of a batch/session queue item. It is available in the InvocationContext and therefore available to all nodes during `invoke()`.
**Database Migrations**
Added a `SQLiteMigrator` class to handle database migrations. Migrations were needed to accomodate the DB-related changes in this PR. See the code for details.
The `images`, `workflows` and `session_queue` tables required migrations for this PR, and are using the new migrator. Other tables/services are still creating tables themselves. A followup PR will adapt them to use the migrator.
**Other/Support Changes**
- Add a `has_workflow` column to `images` table to indicate that the image has an embedded workflow.
- Add handling for retrieving the workflow from an image in python. The image file must be fetched, the workflow extracted, and then sent to client, avoiding needing the browser to parse the image file. With the `has_workflow` column, the UI knows if there is a workflow to be fetched, and only fetches when the user requests to load the workflow.
- Add route to get the workflow from an image
- Add CRUD service/routes for the library workflows
- `workflow_images` table and services removed (no longer needed now that embedded workflows are not in the DB)
* feat(ui): updated workflow handling (WIP)
Clientside updates for the backend workflow changes.
Includes roughed-out workflow library UI.
* feat: revert SQLiteMigrator class
Will pursue this in a separate PR.
* feat(nodes): do not overwrite custom node module names
Use a different, simpler method to detect if a node is custom.
* feat(nodes): restore WithWorkflow as no-op class
This class is deprecated and no longer needed. Set its workflow attr value to None (meaning it is now a no-op), and issue a warning when an invocation subclasses it.
* fix(nodes): fix get_workflow from queue item dict func
* feat(backend): add WorkflowRecordListItemDTO
This is the id, name, description, created at and updated at workflow columns/attrs. Used to display lists of workflowsl
* chore(ui): typegen
* feat(ui): add workflow loading, deleting to workflow library UI
* feat(ui): workflow library pagination button styles
* wip
* feat: workflow library WIP
- Save to library
- Duplicate
- Filter/sort
- UI/queries
* feat: workflow library - system graphs - wip
* feat(backend): sync system workflows to db
* fix: merge conflicts
* feat: simplify default workflows
- Rename "system" -> "default"
- Simplify syncing logic
- Update UI to match
* feat(workflows): update default workflows
- Update TextToImage_SD15
- Add TextToImage_SDXL
- Add README
* feat(ui): refine workflow list UI
* fix(workflow_records): typo
* fix(tests): fix tests
* feat(ui): clean up workflow library hooks
* fix(db): fix mis-ordered db cleanup step
It was happening before pruning queue items - should happen afterwards, else you have to restart the app again to free disk space made available by the pruning.
* feat(ui): tweak reset workflow editor translations
* feat(ui): split out workflow redux state
The `nodes` slice is a rather complicated slice. Removing `workflow` makes it a bit more reasonable.
Also helps to flatten state out a bit.
* docs: update default workflows README
* fix: tidy up unused files, unrelated changes
* fix(backend): revert unrelated service organisational changes
* feat(backend): workflow_records.get_many arg "filter_text" -> "query"
* feat(ui): use custom hook in current image buttons
Already in use elsewhere, forgot to use it here.
* fix(ui): remove commented out property
* fix(ui): fix workflow loading
- Different handling for loading from library vs external
- Fix bug where only nodes and edges loaded
* fix(ui): fix save/save-as workflow naming
* fix(ui): fix circular dependency
* fix(db): fix bug with releasing without lock in db.clean()
* fix(db): remove extraneous lock
* chore: bump ruff
* fix(workflow_records): default `category` to `WorkflowCategory.User`
This allows old workflows to validate when reading them from the db or image files.
* hide workflow library buttons if feature is disabled
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Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
IndexedDB has a much larger storage limit than LocalStorage, and is widely supported.
Implemented as a custom storage driver for `redux-remember` via `idb-keyval`. `idb-keyval` is a simple wrapper for IndexedDB that allows it to be used easily as a key-value store.
The logic to clear persisted storage has been updated throughout the app.
- Reset init image, control adapter images, and node image fields when their selected image fails to load
- Only do this if the app is connected via socket (this indicates that the image is "really" gone, and there isn't just a transient network issue)
It's possible for image parameters/nodes/states to have reference a deleted image. For example, a resize image node might have an image set on it, and the workflow saved. The workflow contains a hard reference to that image.
The image is deleted and the workflow loaded again later. The deleted image is still in that workflow, but the app doesn't detect that. The result is that the workflow/graph appears to be valid, but will fail on invoke.
This creates a really confusing user experience, where when somebody shares a workflow with an image baked into it, and another person opens it, everything *looks* ok, but the workflow fails with a mysterious error about a missing image.
The problem affects node images, control adapter images and the img2img init image. Resetting the image when it fails to load *and* socket is connected resolves this in a simple way.
The problem also affects canvas images, but we have handle that by displaying an error fallback image, so no change is made there.
Closes#5121
- Parse `anyOf` for enums (present when they are optional)
- Consolidate `FieldTypeParseError` and `UnsupportedFieldTypeError` into `FieldParseError` (there was no difference in handling and it simplifies things a bit)
This new name more accurately represents that these are fields with a type of `T | T[]`, where the "base" type must be the same on both sides of the union.
Custom nodes have a new attribute `node_pack` indicating the node pack they came from.
- This is displayed in the UI in the icon icon tooltip.
- If a workflow is loaded and a node is unavailable, its node pack will be displayed (if it is known).
- If a workflow is migrated from v1 to v2, and the node is unknown, it falls back to "Unknown". If the missing node pack is installed and the node is updated, the node pack will be updated as expected.
