* add base definition of download manager
* basic functionality working
* add unit tests for download queue
* add documentation and FastAPI route
* fix docs
* add missing test dependency; fix import ordering
* fix file path length checking on windows
* fix ruff check error
* move release() into the __del__ method
* disable testing of stderr messages due to issues with pytest capsys fixture
* fix unsorted imports
* harmonized implementation of start() and stop() calls in download and & install modules
* Update invokeai/app/services/download/download_base.py
Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>
* replace test datadir fixture with tmp_path
* replace DownloadJobBase->DownloadJob in download manager documentation
* make source and dest arguments to download_queue.download() an AnyHttpURL and Path respectively
* fix pydantic typecheck errors in the download unit test
* ruff formatting
* add "job cancelled" as an event rather than an exception
* fix ruff errors
* Update invokeai/app/services/download/download_default.py
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* use threading.Event to stop service worker threads; handle unfinished job edge cases
* remove dangling STOP job definition
* fix ruff complaint
* fix ruff check again
* avoid race condition when start() and stop() are called simultaneously from different threads
* avoid race condition in stop() when a job becomes active while shutting down
---------
Co-authored-by: Lincoln Stein <lstein@gmail.com>
Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Co-authored-by: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
The graph library occasionally causes issues when the default graph changes substantially between versions and pydantic validation fails. See #5289 for an example.
We are not currently using the graph library, so we can disable it until we are ready to use it. It's possible that the workflow library will supersede it anyways.
* remove MacOS Sonoma check in devices.py
As of pytorch 2.1.0, float16 works with our MPS fixes on Sonoma, so the check is no longer needed.
* remove unused platform import
* add code to repopulate model config records after schema update
* reformat for ruff
* migrate model records using db cursor rather than the ModelRecordConfigService
* ruff fixes
* tweak exception reporting
* fix: build frontend in pypi-release workflow
This was missing, resulting in the 3.5.0rc1 having no frontend.
* fix: use node 18, set working directory
- Node 20 has a problem with `pnpm`; set it to Node 18
- Set the working directory for the frontend commands
* Don't copy extraneous paths into installer .zip
* feat(installer): delete frontend build after creating installer
This prevents an empty `dist/` from breaking the app on startup.
* feat: add python dist as release artifact, as input to enable publish to pypi
- The release workflow never runs automatically. It must be manually kicked off.
- The release workflow has an input. When running it from the GH actions UI, you will see a "Publish build on PyPi" prompt. If this value is "true", the workflow will upload the build to PyPi, releasing it. If this is anything else (e.g. "false", the default), the workflow will build but not upload to PyPi.
- The `dist/` folder (where the python package is built) is uploaded as a workflow artifact as a zip file. This can be downloaded and inspected. This allows "dry" runs of the workflow.
- The workflow job and some steps have been renamed to clarify what they do
* translationBot(ui): update translation files
Updated by "Cleanup translation files" hook in Weblate.
Co-authored-by: Hosted Weblate <hosted@weblate.org>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/
Translation: InvokeAI/Web UI
* freeze yaml migration logic at upgrade to 3.5
* moved migration code to migration_3
---------
Co-authored-by: Lincoln Stein <lstein@gmail.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Co-authored-by: Hosted Weblate <hosted@weblate.org>
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
This model was a bit too strict, and raised validation errors when workflows we expect to *not* have an ID (eg, an embedded workflow) have one.
Now it strips unknown attributes, allowing those workflows to load.
- Handle an image file not existing despite being in the database.
- Add a simple pydantic model that tests only for the existence of a workflow's version.
- Check against this new model when migrating workflows, skipping if the workflow fails validation. If it succeeds, the frontend should be able to handle the workflow.
Currently translated at 98.1% (1340 of 1365 strings)
translationBot(ui): update translation (Russian)
Currently translated at 84.2% (1150 of 1365 strings)
translationBot(ui): update translation (Russian)
Currently translated at 83.1% (1135 of 1365 strings)
Co-authored-by: Васянатор <ilabulanov339@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/ru/
Translation: InvokeAI/Web UI
- use simpler pattern for migration dependencies
- move SqliteDatabase & migration to utility method `init_db`, use this in both the app and tests, ensuring the same db schema is used in both
This fixes a problem with `Annotated` which prevented us from using pydantic's `Field` to specify a discriminator for a union. We had to use FastAPI's `Body` as a workaround.
* 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
---------
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.
Simplifies a couple things:
- Init is more straightforward
- It's clear in the migrator that the connection we are working with is related to the SqliteDatabase
- Simplify init args to path (None means use memory), logger, and verbose
- Add docstrings to SqliteDatabase (it had almost none)
- Update all usages of the class
- min_overlap removed * restrictions and round_to_8
- min_overlap handles tile size > image size by clipping the num tiles to 1.
- Updated assert test on min_overlap.
In other words, build frontend when creating installer.
Changes to `create_installer.sh`
- If `python` is not in `PATH` but `python3` is, alias them (well, via function). This is needed on some machines to run the installer without symlinking to `python3`.
- Make the messages about pushing tags clearer. The script force-pushes, so it's possible to accidentally take destructive action. I'm not sure how to otherwise prevent damage, so I just added a warning.
- Print out `pwd` when prompting about being in the `installer` dir.
- Rebuild the frontend - if there is already a frontend build, first checks if the user wants to rebuild it.
- Checks for existence of `../build` dir before deleting - if the dir doesn't exist, the script errors and exits at this point.
- Format and spell check.
Other changes:
- Ignore `dist/` folder.
- Delete `dist/`.
**Note: you may need to use `git rm --cached invokeai/app/frontend/web/dist/` if git still wants to track `dist/`.**
Calling `inspect.getmembers()` on a pydantic field results in `getattr` being called on all members of the field. Pydantic has some attrs that are marked deprecated.
In our test suite, we do not filter deprecation warnings, so this is surfaced.
Use a context manager to ignore deprecation warnings when calling the function.
In the latest redux, unknown actions are typed as `unknown`. This forces type-safety upon us, requiring us to be more careful about the shape of actions.
In this case, we don't know if the rejection has a payload or what shape it may be in, so we need to do runtime checks. This is implemented with a simple zod schema, but probably the right way to handle this is to have consistent types in our RTK-Query error logic.
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`.
- update all scripts
- update the frontend GH action
- remove yarn-related files
- update ignores
Yarn classic + storybook has some weird module resolution issue due to how it hoists dependencies.
See https://github.com/storybookjs/storybook/issues/22431#issuecomment-1630086092
When I did the `package.json` solution in this thread, it broke vite. Next option is to upgrade to yarn 3 or pnpm. I chose pnpm.
Using default_factory to autogenerate UUIDs doesn't make sense here, and results awkward typescript types.
Remove the default factory and instead manually create a UUID for workflow id. There are only two places where this needs to happen so it's not a big change.
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
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
* add middleware to handle 403 errors
* remove log
* add logic to warn the user if not all requested images could be deleted
* lint
* fix copy
* feat(ui): simplify batchEnqueuedListener error toast logic
* feat(ui): use translations for error messages
* chore(ui): lint
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Currently translated at 62.9% (830 of 1319 strings)
Co-authored-by: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
* dont set socketURL until socket is initialized
* cleanup
* feat(ui): simplify `socketUrl` memo
no need to mutate the string; just return early if using baseUrl
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Adds logic to `DiskLatentsStorage.start()` to empty the latents folder on startup.
Adds start and stop methods to `ForwardCacheLatentsStorage`. This is required for `DiskLatentsStorage.start()` to be called, due to how this particular service breaks the direct DI pattern, wrapping the underlying storage with a cache.
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)
* add centerpadcrop node
- Allows users to add padding to or crop images from the center
- Also outputs a white mask with the dimensions of the output image for use with outpainting
* add CenterPadCrop to NODES.md
Updates NODES.md with CenterPadCrop entry.
* remove mask & output class
- Remove "ImageMaskOutput" where both image and mask are output
- Remove ability to output mask from node
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Use UTF-8 encoding on reading prompts from files to allow Unicode characters to load correctly.
The following examples currently will not load correctly from a file:
Hello, 世界!
😭🤮💔
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.
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
We used the `RealESRGANer` utility class from the repo. It handled model loading and tiled upscaling logic.
Unfortunately, it hasn't been updated in over a year, had no types, and annoyingly printed to console.
I've adapted the class, cleaning it up a bit and removing the bits that are not relevant for us.
Upscaling functionality is identical.
Currently translated at 64.9% (818 of 1260 strings)
Co-authored-by: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
* working on recall height/width
* working on adding resize
* working on feature
* fix(ui): move added translation from dist/ to public/
* fix(ui): use `metadata` as hotkey cb dependency
Using `imageDTO` may result in stale data being used
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* eslint added and new string added
* strings and translation hook added
* more changes made
* missing translation added
* final errors resolve in progress
* all errors resolved
* fix(ui): fix missing import of `t()`
* fix(ui): use plurals for moving images to board translation
* fix(ui): fix typo in translation key
* fix(ui): do not use translation for "invoke ai"
* chore(ui): lint
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* first string only to test
* more strings changed
* almost half strings added in json file
* more strings added
* more changes
* few strings and t function changed
* resolved
* errors resolved
* chore(ui): fmt en.json
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Currently translated at 64.4% (793 of 1231 strings)
Co-authored-by: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
Resolves two bugs introduced in #5106:
1. Linear UI images sometimes didn't make it to the gallery.
This was a race condition. The VAE decode nodes were handled by the socketInvocationComplete listener. At that moment, the image was marked as intermediate. Immediately after this node was handled, a LinearUIOutputInvocation, introduced in #5106, was handled by socketInvocationComplete. This node internally sets changed the image to not intermediate.
During the handling of that socketInvocationComplete, RTK Query would sometimes use its cache instead of retrieving the image DTO again. The result is that the UI never got the message that the image was not intermediate, so it wasn't added to the gallery.
This is resolved by refactoring the socketInvocationComplete listener. We now skip the gallery processing for linear UI events, except for the LinearUIOutputInvocation. Images now always make it to the gallery, and network requests to get image DTOs are substantially reduced.
2. Canvas temp images always went into the gallery
The LinearUIOutputInvocation was always setting its image's is_intermediate to false. This included all canvas images and resulted in all canvas temp images going to gallery.
This is resolved by making LinearUIOutputInvocation set is_intermediate based on `self.is_intermediate`. The behaviour now more or less mirroring the behaviour of is_intermediate on other image-outputting nodes, except it doesn't save the image again - only changes it.
One extra minor change - LinearUIOutputInvocation only changes is_intermediate if it differs from the image's current setting. Very minor optimisation.
Add a LinearUIOutputInvocation node to be the new terminal node for Linear UI graphs. This node is private and hidden from the Workflow Editor, as it is an implementation detail.
The Linear UI was using the Save Image node for this purpose. It allowed every linear graph to end a single node type, which handled saving metadata and board. This substantially reduced the complexity of the linear graphs.
This caused two related issues:
- Images were saved to disk twice
- Noticeable delay between when an image was decoded and showed up in the UI
To resolve this, the new LinearUIOutputInvocation node will handle adding an image to a board if one is provided.
Metadata is no longer provided in this unified node. Instead, the metadata graph helpers now need to know the node to add metadata to and provide it to the last node that actually outputs an image. This is a `l2i` node for txt2img & img2img graphs, and a different image-outputting node for canvas graphs.
HRF poses another complication, in that it changes the terminal node. To handle this, a new metadata util is added called `setMetadataReceivingNode()`. HRF calls this to change the node that should receive the graph's metadata.
This resolves the duplicate images issue and improves perf without otherwise changing the user experience.
A workflow's nodes may update itself, if its major version matches the template's major version.
If the major versions do not match, the user will need to delete and re-add the node (current behaviour).
The update functionality is not automatic (for now). The logic to update the node is pretty simple, but I want to ensure it works well first before doing it automatically when a workflow is loaded.
- New `Details` tab on Workflow Inspector, displays node title, type, version, and notes
- Button to update the node is displayed on the `Details` tab
- Add hook to determine if a node needs an update, may be updated (i.e. major versions match), and the callback to update the node in state
- Remove the notes modal from the little info icon
- Modularize the node building logic
Do not use `strict=True` when scaling controlnet conditioning.
When using `guess_mode` (e.g. `more_control` or `more_prompt`), `down_block_res_samples` and `scales` are zipped.
These two objects are of different lengths, so using zip's strict mode raises an error.
In testing, `len(scales) === len(down_block_res_samples) + 1`.
It appears this behaviour is intentional, as the final "extra" item in `scales` is used immediately afterwards.
This rule enforces no arrow functions in component props. In practice, it means all functions passed as component props must be wrapped in `useCallback()`.
This is a performance optimization to prevent unnecessary rerenders.
The rule is added and all violations have been fixed, whew!
* adding VAE recall when using all parameters
* adding VAE to the RecallParameters tab in ImageMetadataActions
* checking for nil vae and casting to null if undefined
* adding default VAE to recall actions list if VAE is nullish
* fix(ui): use `lodash-es` for tree-shakeable imports
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Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
