* add support for flux-kontext models in nodes
* flux kontext in canvas
* add aspect ratio support
* lint
* restore aspect ratio logic
* more linting
* typegen
* fix typegen
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-Air.lan>
For example:
```py
my_field: Literal["foo", "bar"] | None = InputField(default=None)
```
Previously, this would cause a field parsing error and prevent the app from loading.
Two fixes:
- This type annotation and resultant schema are now parsed correctly
- Error handling added to template building logic to prevent the hang at startup when an error does occur
Board fields in the workflow editor now default to using the auto-add board by default.
**This is a change in behaviour - previously, we defaulted to no board (i.e. Uncategorized).**
There is some translation needed between the UI field values for a board and what the graph expects.
A "BoardField" is an object in the shape of `{board_id: string}`.
Valid board field values in the graph:
- undefined
- a BoardField
Value UI values and their mapping to the graph values:
- 'none' -> undefined
- 'auto' -> BoardField for the auto-add board, or if the auto-add board is Uncategorized, undefined
- undefined -> undefined (this is a fallback case with the new logic)
- a BoardField -> the same BoardField
There's a technical challenge with outputting these values directly. `ImageField` does not store them, so the batch's `ImageField` collection does not have width and height for each image.
In order to set up the batch and pass along width and height for each image, we'd need to make a network request for each image when the user clicks Invoke. It would often be cached, but this will eventually create a scaling issue and poor user experience.
As a very simple workaround, users can output the batch image output into an `Image Primitive` node to access the width and height.
This change is implemented by adding some simple special handling when parsing the output fields for the `image_batch` node.
I'll keep this situation in mind when extending the batching system to other field types.
We now keep track of the original field type, derived from the python type annotation in addition to the override type provided by `ui_type`.
This makes `ui_type` work more like it sound like it should work - change the UI input component only.
Connection validation is extend to also check the original types. If there is any match between two fields' "final" or original types, we consider the connection valid.This change is backwards-compatible; there is no workflow migration needed.
