On the Canvas tab, when we made the network request to enqueue a batch, we were immediately resetting the request. This effectively disabled RTKQ's tracking of the request - including the loading state.
As a result, when you click the Invoke button on the Canvas tab, it didn't show a spinner, and it was not clear that anything was happening.
The solution is simple - just await the enqueue request before resetting the tracking, same as we already did on the workflows and upscaling tabs.
I also added some extra logging messages for enqueuing, so we get the same JS console logs for each tab on success or failure.
Currently translated at 40.3% (727 of 1801 strings)
translationBot(ui): update translation (Japanese)
Currently translated at 37.7% (680 of 1801 strings)
Co-authored-by: Hiroto N <hironow365@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/ja/
Translation: InvokeAI/Web UI
Previously, custom node loading occurred _during module imports_. A consequence of this is that when a custom node import fails (e.g. its type clobbers an existing node), the app fails to start up.
In fact, any time we import basically anything from the app, we trigger custom node imports! Not good.
This logic is now in its own function, called as the API app starts up.
If a custom node load fails for any reason, it no longer prevents the app from starting up.
One other bonus we get from this is that we can now ensure custom nodes are loaded _after_ core nodes.
Any clobbering that may occur while loading custom nodes is now guaranteed to be a custom node clobbering a core node's type - and not the other way round.
When deleting a board w/ images, the image usage checking logic was not checking image collection fields. This could result in a nonexistent image lingering in a node.
We already handle single image fields correctly, it's only the image collection fields taht were affected.
Found another place where we deepcopy a dict, but it is safe to mutate.
Restructured the prep logic a bit to support this. Updated tests to use the new structure.
- Avoid pydantic models when dict manipulation works
- Avoid extraneous deep copies when we can safely mutate
- Avoid NamedTuple construct and its overhead
- Fix tests to use altered function signatures
- Remove extraneous populate_graph function
