This improves the overall responsiveness of the system substantially, but does make each iteration *slightly* slower, distributing the up-front cost across the batch.
Two main changes:
1. Create BatchSessions immediately, but do not create a whole graph execution state until the batch is executed.
BatchSessions are created with a `session_id` that does not exist in sessions database.
The default state is changed to `"uninitialized"` to better represent this.
Results: Time to create 5000 batches reduced from over 30s to 2.5s
2. Use `executemany()` to retrieve lists of created sessions.
Results: time to create 5000 batches reduced from 2.5s to under 0.5s
Other changes:
- set BatchSession state to `"in_progress"` just before `invoke()` is called
- rename a few methods to accomodate the new behaviour
- remove unused `BatchProcessStorage.get_created_sessions()` method
The internal `BatchProcessStorage.get_session()` method throws when it finds nothing, but we were not catching any exceptions.
This caused a exception when the batch manager handles a `graph_execution_state_complete` event that did not originate from a batch.
Fixed by handling the exception.
If the values from the `session_dict` are invalid, the model instantiation will fail, or if we end up with an invalid `batch_id`, the app will not run. So I think just parsing the dict directly is equivalent.
Also the LSP analyser is pleased now - no red squigglies.
Providing a `default_factory` is enough for pydantic to know to create the attribute on instantiation if it's not already provided. We can then make make the typing just `str`.
Refine concept of "parameter" nodes to "primitives":
- integer
- float
- string
- boolean
- image
- latents
- conditioning
- color
Each primitive has:
- A field definition, if it is not already python primitive value. The field is how this primitive value is passed between nodes. Collections are lists of the field in node definitions. ex: `ImageField` & `list[ImageField]`
- A single output class. ex: `ImageOutput`
- A collection output class. ex: `ImageCollectionOutput`
- A node, which functions to load or pass on the primitive value. ex: `ImageInvocation` (in this case, `ImageInvocation` replaces `LoadImage`)
Plus a number of related changes:
- Reorganize these into `primitives.py`
- Update all nodes and logic to use primitives
- Consolidate "prompt" outputs into "string" & "mask" into "image" (there's no reason for these to be different, the function identically)
- Update default graphs & tests
- Regen frontend types & minor frontend tidy related to changes
