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
The setup of `ModelConfigBase` means autogenerated types have critical fields flagged as nullable (like `key` and `base`). Need to manually flag them as required.
- Support extended HF repoid syntax in TUI. This allows
installation of subfolders and safetensors files, as in
`XpucT/Deliberate::Deliberate_v5.safetensors`
- Add `error` and `error_traceback` properties to the install
job objects.
- Rename the `heuristic_import` route to `heuristic_install`.
- Fix the example `config` input in the `heuristic_install` route.
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
Double underscores are used in the app but it doesn't actually do or convey anything that single underscores don't already do. Considered unpythonic except for actual dunder/magic methods.
Consolidate graph processing logic into session processor.
With graphs as the unit of work, and the session queue distributing graphs, we no longer need the invocation queue or processor.
Instead, the session processor dequeues the next session and processes it in a simple loop, greatly simplifying the app.
- Remove `graph_execution_manager` service.
- Remove `queue` (invocation queue) service.
- Remove `processor` (invocation processor) service.
- Remove queue-related logic from `Invoker`. It now only starts and stops the services, providing them with access to other services.
- Remove unused `invocation_retrieval_error` and `session_retrieval_error` events, these are no longer needed.
- Clean up stats service now that it is less coupled to the rest of the app.
- Refactor cancellation logic - cancellations now originate from session queue (i.e. HTTP cancel endpoint) and are emitted as events. Processor gets the events and sets the canceled event. Access to this event is provided to the invocation context for e.g. the step callback.
- Remove `sessions` router; it provided access to `graph_executions` but that no longer exists.
`GraphInvocation` is a node that can contain a whole graph. It is removed for a number of reasons:
1. This feature was unused (the UI doesn't support it) and there is no plan for it to be used.
The use-case it served is known in other node execution engines as "node groups" or "blocks" - a self-contained group of nodes, which has group inputs and outputs. This is a planned feature that will be handled client-side.
2. It adds substantial complexity to the graph processing logic. It's probably not enough to have a measurable performance impact but it does make it harder to work in the graph logic.
3. It allows for graphs to be recursive, and the improved invocations union handling does not play well with it. Actually, it works fine within `graph.py` but not in the tests for some reason. I do not understand why. There's probably a workaround, but I took this as encouragement to remove `GraphInvocation` from the app since we don't use it.
The change to `Graph.nodes` and `GraphExecutionState.results` validation requires some fanagling to get the OpenAPI schema generation to work. See new comments for a details.
We use pydantic to validate a union of valid invocations when instantiating a graph.
Previously, we constructed the union while creating the `Graph` class. This introduces a dependency on the order of imports.
For example, consider a setup where we have 3 invocations in the app:
- Python executes the module where `FirstInvocation` is defined, registering `FirstInvocation`.
- Python executes the module where `SecondInvocation` is defined, registering `SecondInvocation`.
- Python executes the module where `Graph` is defined. A union of invocations is created and used to define the `Graph.nodes` field. The union contains `FirstInvocation` and `SecondInvocation`.
- Python executes the module where `ThirdInvocation` is defined, registering `ThirdInvocation`.
- A graph is created that includes `ThirdInvocation`. Pydantic validates the graph using the union, which does not know about `ThirdInvocation`, raising a `ValidationError` about an unknown invocation type.
This scenario has been particularly problematic in tests, where we may create invocations dynamically. The test files have to be structured in such a way that the imports happen in the right order. It's a major pain.
This PR refactors the validation of graph nodes to resolve this issue:
- `BaseInvocation` gets a new method `get_typeadapter`. This builds a pydantic `TypeAdapter` for the union of all registered invocations, caching it after the first call.
- `Graph.nodes`'s type is widened to `dict[str, BaseInvocation]`. This actually is a nice bonus, because we get better type hints whenever we reference `some_graph.nodes`.
- A "plain" field validator takes over the validation logic for `Graph.nodes`. "Plain" validators totally override pydantic's own validation logic. The validator grabs the `TypeAdapter` from `BaseInvocation`, then validates each node with it. The validation is identical to the previous implementation - we get the same errors.
`BaseInvocationOutput` gets the same treatment.
- Replace AnyModelLoader with ModelLoaderRegistry
- Fix type check errors in multiple files
- Remove apparently unneeded `get_model_config_enum()` method from model manager
- Remove last vestiges of old model manager
- Updated tests and documentation
resolve conflict with seamless.py
- 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.
