- Use protocol to define callbacks, this allows them to have kwargs
- Shuffle the profiler around a bit
- Move `thread_limit` and `polling_interval` to `__init__`; `start` is called programmatically and will never get these args in practice
- Add `OnNodeError` and `OnNonFatalProcessorError` callbacks
- Move all session/node callbacks to `SessionRunner` - this ensures we dump perf stats before resetting them and generally makes sense to me
- Remove `complete` event from `SessionRunner`, it's essentially the same as `OnAfterRunSession`
- Remove extraneous `next_invocation` block, which would treat a processor error as a node error
- Simplify loops
- Add some callbacks for testing, to be removed before merge
This query is only subscribed-to in the `QueueItemDetail` component - when is rendered only when the user clicks on a queue item in the queue. Invalidating this tag instead of optimistically updating it won't cause any meaningful change to network traffic.
The session is never updated in the queue after it is first enqueued. As a result, the queue detail view in the frontend never never updates and the session itself doesn't show outputs, execution graph, etc.
We need a new method on the queue service to update a queue item's session, then call it before updating the queue item's status.
Queue item status may be updated via a session-type event _or_ queue-type event. Adding the updated session to all these events is a hairy - simpler to just update the session before we do anything that could trigger a queue item status change event:
- Before calling `emit_session_complete` in the processor (handles session error, completed and cancel events and the corresponding queue events)
- Before calling `cancel_queue_item` in the processor (handles another way queue items can be canceled, outside the session execution loop)
When serializing the session, both in the new service method and the `get_queue_item` endpoint, we need to use `exclude_none=True` to prevent unexpected validation errors.
Currently translated at 98.5% (1210 of 1228 strings)
translationBot(ui): update translation (Italian)
Currently translated at 98.5% (1206 of 1224 strings)
translationBot(ui): update translation (Italian)
Currently translated at 98.5% (1204 of 1222 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
Some asserts were bubbling up in places where they shouldn't have, causing errors when a node has a field without a matching template, or vice-versa.
To resolve this without sacrificing the runtime safety provided by asserts, a `InvocationFieldCheck` component now wraps all field components. This component renders a fallback when a field doesn't exist, so the inner components can safely use the asserts.
At some point, I made a mistake and imported the wrong types to some files for the old v1 and v2 workflow schema migration data.
The relevant zod schemas and inferred types have been restored.
This change doesn't alter runtime behaviour. Only type annotations.
Replace the `isCollection` and `isCollectionOrScalar` flags with a single enum value `cardinality`. Valid values are `SINGLE`, `COLLECTION` and `SINGLE_OR_COLLECTION`.
Why:
- The two flags were mutually exclusive, but this wasn't enforce. You could create a field type that had both `isCollection` and `isCollectionOrScalar` set to true, whuch makes no sense.
- There was no explicit declaration for scalar/single types.
- Checking if a type had only a single flag was tedious.
Thanks to a change a couple months back in which the workflows schema was revised, field types are internal implementation details. Changes to them are non-breaking.
Canvas images are saved by uploading a blob generated from the HTML canvas element. This means the existing metadata handling, inside the graph execution engine, is not available.
To save metadata to canvas images, we need to provide it when uploading that blob.
The upload route now has a `metadata` body param. If this is provided, we use it over any metadata embedded in the image.
Depending on the user behaviour and network conditions, it's possible that we could try to load a workflow before the invocation templates are available.
Fix is simple:
- Use the RTKQ query hook for openAPI schema in App.tsx
- Disable the load workflow buttons until w have templates parsed
Remove our DIY'd reducers, consolidating all node and edge mutations to use `edgesChanged` and `nodesChanged`, which are called by reactflow. This makes the API for manipulating nodes and edges less tangly and error-prone.
