Rolled back the earlier split of the refiner model query.
Now, when you use `useGetMainModelsQuery()`, you must provide it an array of base model types.
They are provided as constants for simplicity:
- ALL_BASE_MODELS
- NON_REFINER_BASE_MODELS
- REFINER_BASE_MODELS
Opted to just use args for the hook instead of wrapping the hook in another hook, we can tidy this up later if desired.
We can derive `isRefinerAvailable` from the query result (eg are there any refiner models installed). This is a piece of server state, so by using the list models response directly, we can avoid needing to manually keep the client in sync with the server.
Created a `useIsRefinerAvailable()` hook to return this boolean wherever it is needed.
Also updated the main models & refiner models endpoints to only return the appropriate models. Now we don't need to filter the data on these endpoints.
At some point I typo'd this and set the max seed to signed int32 max. It should be *un*signed int32 max.
This restored the seed range to what it was in v2.3.
- use the existing logic to determine if generation is txt2img, img2img, inpaint or outpaint
- technically `outpaint` and `inpaint` are the same, just display
"Inpaint" if its either
- debounce this by 1s to prevent jank
When a queue item is popped for processing, we need to retrieve its session from the DB. Pydantic serializes the graph at this stage.
It's possible for a graph to have been made invalid during the graph preparation stage (e.g. an ancestor node executes, and its output is not valid for its successor node's input field).
When this occurs, the session in the DB will fail validation, but we don't have a chance to find out until it is retrieved and parsed by pydantic.
This logic was previously not wrapped in any exception handling.
Just after retrieving a session, we retrieve the specific invocation to execute from the session. It's possible that this could also have some sort of error, though it should be impossible for it to be a pydantic validation error (that would have been caught during session validation). There was also no exception handling here.
When either of these processes fail, the processor gets soft-locked because the processor's cleanup logic is never run. (I didn't dig deeper into exactly what cleanup is not happening, because the fix is to just handle the exceptions.)
This PR adds exception handling to both the session retrieval and node retrieval and events for each: `session_retrieval_error` and `invocation_retrieval_error`.
These events are caught and displayed in the UI as toasts, along with the type of the python exception (e.g. `Validation Error`). The events are also logged to the browser console.
## What type of PR is this? (check all applicable)
- [x] Refactor
- [ ] Feature
- [ ] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [x] Yes
- [ ] No, because:
## Description
Revised boards logic and UI
## Related Tickets & Documents
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## QA Instructions, Screenshots, Recordings
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## Added/updated tests?
- [ ] Yes
- [x] No : n/a
## [optional] Are there any post deployment tasks we need to perform?
