- fix "bounding box region only" not being respected when saving
- add toasts for each action
- improve workflow `take()` predicates to use the requestId
- responsive changes were causing a lot of weird layout issues, had to remove the rest of them
- canvas (non-beta) toolbar now wraps
- reduces minH for prompt boxes a bit
1. Model installer works correctly under Windows 11 Terminal
2. Fixed crash when configure script hands control off to installer
3. Kill install subprocess on keyboard interrupt
4. Command-line functionality for --yes configuration and model installation
restored.
5. New command-line features:
- install/delete lists of diffusers, LoRAS, controlnets and textual inversions
using repo ids, paths or URLs.
Help:
```
usage: invokeai-model-install [-h] [--diffusers [DIFFUSERS ...]] [--loras [LORAS ...]] [--controlnets [CONTROLNETS ...]] [--textual-inversions [TEXTUAL_INVERSIONS ...]] [--delete] [--full-precision | --no-full-precision]
[--yes] [--default_only] [--list-models {diffusers,loras,controlnets,tis}] [--config_file CONFIG_FILE] [--root_dir ROOT]
InvokeAI model downloader
options:
-h, --help show this help message and exit
--diffusers [DIFFUSERS ...]
List of URLs or repo_ids of diffusers to install/delete
--loras [LORAS ...] List of URLs or repo_ids of LoRA/LyCORIS models to install/delete
--controlnets [CONTROLNETS ...]
List of URLs or repo_ids of controlnet models to install/delete
--textual-inversions [TEXTUAL_INVERSIONS ...]
List of URLs or repo_ids of textual inversion embeddings to install/delete
--delete Delete models listed on command line rather than installing them
--full-precision, --no-full-precision
use 32-bit weights instead of faster 16-bit weights (default: False)
--yes, -y answer "yes" to all prompts
--default_only only install the default model
--list-models {diffusers,loras,controlnets,tis}
list installed models
--config_file CONFIG_FILE, -c CONFIG_FILE
path to configuration file to create
--root_dir ROOT path to root of install directory
```
Implement `dnd-kit` for image drag and drop
- vastly simplifies logic bc we can drag and drop non-serializable data (like an `ImageDTO`)
- also much prettier
- also will fix conflicts with file upload via OS drag and drop, bc `dnd-kit` does not use native HTML drag and drop API
- Implemented for Init image, controlnet, and node editor so far
More progress on the ControlNet UI
- The invokeai.db database file has now been moved into
`INVOKEAIROOT/databases`. Using plural here for possible
future with more than one database file.
- Removed a few dangling debug messages that appeared during
testing.
- Rebuilt frontend to test web.
1. Separated the "starter models" and "more models" sections. This
gives us room to list all installed diffuserse models, not just
those that are on the starter list.
2. Support mouse-based paste into the textboxes with either middle
or right mouse buttons.
3. Support terminal-style cursor movement:
^A to move to beginning of line
^E to move to end of line
^K kill text to right and put in killring
^Y yank text back
4. Internal code cleanup.
The gallery could get in a state where it thought it had just reached the end of the list and endlessly fetches more images, if there are no more images to fetch (weird I know).
Add some logic to remove the `end reached` handler when there are no more images to load.
it doesn't work for the img2img pipelines, but the implemented conditional display could break the scheduler selection dropdown.
simple fix until diffusers merges the fix - never use this scheduler.
Inputs with explicit values are validated by pydantic even if they also
have a connection (which is the actual value that is used).
Fix this by omitting explicit values for inputs that have a connection.
This may cause minor gallery jumpiness at the very end of processing, but is necessary to prevent the progress image from sticking around if the last node in a session did not have an image output.
Some socket events should not be handled by the slice reducers. For example generation progress should not be handled for a canceled session.
Added another layer of socket actions.
Example:
- `socketGeneratorProgress` is dispatched when the actual socket event is received
- Listener middleware exclusively handles this event and determines if the application should also handle it
- If so, it dispatches `appSocketGeneratorProgress`, which the slices can handle
Needed to fix issues related to canceling invocations.
Now that images are in a database and we can make filtered queries, we can do away with the cumbersome `resultsSlice` and `uploadsSlice`.
- Remove `resultsSlice` and `uploadsSlice` entirely
- Add `imagesSlice` fills the same role
- Convert the application to use `imagesSlice`, reducing a lot of messy logic where we had to check which category was selected
- Add a simple filter popover to the gallery, which lets you select any number of image categories
- Update all thunks & network related things
- Update gallery
What I have not done yet is rename the gallery tabs and the relevant slices, but I believe the functionality is all there.
Also I fixed several bugs along the way but couldn't really commit them separately bc I was refactoring. Can't remember what they were, but related to the gallery image switching.
- Update the canvas graph generation to flag its uploaded init and mask images as `intermediate`.
- During canvas setup, hit the update route to associate the uploaded images with the session id.
- Organize the socketio and RTK listener middlware better. Needed to facilitate the updated canvas logic.
- Add a new action `sessionReadyToInvoke`. The `sessionInvoked` action is *only* ever run in response to this event. This lets us do whatever complicated setup (eg canvas) and explicitly invoking. Previously, invoking was tied to the socket subscribe events.
- Some minor tidying.
feat(nodes): add ResultsServiceABC & SqliteResultsService
**Doesn't actually work bc of circular imports. Can't even test it.**
- add a base class for ResultsService and SQLite implementation
- use `graph_execution_manager` `on_changed` callback to keep `results` table in sync
fix(nodes): fix results service bugs
chore(ui): regen api
fix(ui): fix type guards
feat(nodes): add `result_type` to results table, fix types
fix(nodes): do not shadow `list` builtin
feat(nodes): add results router
It doesn't work due to circular imports still
fix(nodes): Result class should use outputs classes, not fields
feat(ui): crude results router
fix(ui): send to canvas in currentimagebuttons not working
feat(nodes): add core metadata builder
feat(nodes): add design doc
feat(nodes): wip latents db stuff
feat(nodes): images_db_service and resources router
feat(nodes): wip images db & router
feat(nodes): update image related names
feat(nodes): update urlservice
feat(nodes): add high-level images service
This commit makes InvokeAI 3.0 to be installable via PyPi.org and the
installer script.
Main changes.
1. Move static web pages into `invokeai/frontend/web` and modify the
API to look for them there. This allows pip to copy the files into the
distribution directory so that user no longer has to be in repo root
to launch.
2. Update invoke.sh and invoke.bat to launch the new web application
properly. This also changes the wording for launching the CLI from
"generate images" to "explore the InvokeAI node system," since I would
not recommend using the CLI to generate images routinely.
3. Fix a bug in the checkpoint converter script that was identified
during testing.
4. Better error reporting when checkpoint converter fails.
5. Rebuild front end.
* added optional middleware prop and new actions needed
* accidental import
* make middleware an array
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
- Make environment variable settings case InSenSiTive:
INVOKEAI_MAX_LOADED_MODELS and InvokeAI_Max_Loaded_Models
environment variables will both set `max_loaded_models`
- Updated realesrgan to use new config system.
- Updated textual_inversion_training to use new config system.
- Discovered a race condition when InvokeAIAppConfig is created
at module load time, which makes it impossible to customize
or replace the help message produced with --help on the command
line. To fix this, moved all instances of get_invokeai_config()
from module load time to object initialization time. Makes code
cleaner, too.
- Added `--from_file` argument to `invokeai-node-cli` and changed
github action to match. CI tests will hopefully work now.
* refetch images list if error loading
* tell user to refresh instead of refetching
* unused import
* feat(ui): use `useAppToaster` to make toast
* fix(ui): clear selected/initial image on error
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
1. If an external VAE is specified in config file, then
get_model(submodel=vae) will return the external VAE, not the one
burnt into the parent diffusers pipeline.
2. The mechanism in (1) is generalized such that you can now have
"unet:", "text_encoder:" and similar stanzas in the config file.
Valid formats of these subsections:
unet:
repo_id: foo/bar
unet:
path: /path/to/local/folder
unet:
repo_id: foo/bar
subfolder: unet
In the near future, these will also be used to attach external
parts to the pipeline, generalizing VAE behavior.
3. Accommodate callers (i.e. the WebUI) that are passing the
model key ("diffusers/stable-diffusion-1.5") to get_model()
instead of the tuple of model_name and model_type.
4. Fixed bug in VAE model attaching code.
5. Rebuilt web front end.
