Model metadata includes the main model, VAE and refiner model.
These used full model configs, as returned by the server, as their metadata type.
LoRA and control adapter metadata only use the metadata identifier.
This created a difference in handling. After parsing a model/vae/refiner, we have its name and can display it. But for LoRAs and control adapters, we only have the model key and must query for the full model config to get the name.
This change makes main model/vae/refiner metadata only have the model key, like LoRAs and control adapters.
The render function is now async so fetching can occur within it. All metadata fields with models now only contain the identifier, and fetch the model name to render their values.
When we retrieve a list of models, upsert that data into the `getModelConfig` and `getModelConfigByAttrs` query caches.
With this change, calls to those two queries are almost always going to be free, because their caches will already have all models in them. The exception is queries for models that no longer exist.
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
- Rename old "model_management" directory to "model_management_OLD" in order to catch
dangling references to original model manager.
- Caught and fixed most dangling references (still checking)
- Rename lora, textual_inversion and model_patcher modules
- Introduce a RawModel base class to simplfy the Union returned by the
model loaders.
- Tidy up the model manager 2-related tests. Add useful fixtures, and
a finalizer to the queue and installer fixtures that will stop the
services and release threads.
- ModelMetadataStoreService is now injected into ModelRecordStoreService
(these two services are really joined at the hip, and should someday be merged)
- ModelRecordStoreService is now injected into ModelManagerService
- Reduced timeout value for the various installer and download wait*() methods
- Introduced a Mock modelmanager for testing
- Removed bare print() statement with _logger in the install helper backend.
- Removed unused code from model loader init file
- Made `locker` a private variable in the `LoadedModel` object.
- Fixed up model merge frontend (will be deprecated anyway!)
- 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...
- Replace legacy model manager service with the v2 manager.
- Update invocations to use new load interface.
- Fixed many but not all type checking errors in the invocations. Most
were unrelated to model manager
- Updated routes. All the new routes live under the route tag
`model_manager_v2`. To avoid confusion with the old routes,
they have the URL prefix `/api/v2/models`. The old routes
have been de-registered.
- Added a pytest for the loader.
- Updated documentation in contributing/MODEL_MANAGER.md
- Implement new model loader and modify invocations and embeddings
- Finish implementation loaders for all models currently supported by
InvokeAI.
- Move lora, textual_inversion, and model patching support into
backend/embeddings.
- Restore support for model cache statistics collection (a little ugly,
needs work).
- Fixed up invocations that load and patch models.
- Move seamless and silencewarnings utils into better location
- Cache stat collection enabled.
- Implemented ONNX loading.
- Add ability to specify the repo version variant in installer CLI.
- If caller asks for a repo version that doesn't exist, will fall back
to empty version rather than raising an error.
Unfortunately you cannot test for both a specific type of error and match its message. Splitting the error classes makes it easier to test expected error conditions.
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.
Currently translated at 80.4% (1183 of 1470 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
Currently translated at 80.3% (1181 of 1470 strings)
translationBot(ui): update translation (German)
Currently translated at 80.1% (1178 of 1470 strings)
Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
Currently translated at 80.0% (1176 of 1470 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
Currently translated at 95.6% (1406 of 1470 strings)
translationBot(ui): update translation (Italian)
Currently translated at 93.9% (1381 of 1470 strings)
Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
