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Author SHA1 Message Date
2af511c98a release 2.3.4 2023-04-09 13:31:45 -04:00
f0039cc70a [Bugfix] truncate filenames in invokeai batch that exceed max filename length (#3143)
- This prevents `invokeai-batch` from trying to create image files whose
names would exceed PC_NAME_MAX.
- Closes #3115
2023-04-09 12:36:10 -04:00
8fa7d5ca64 Merge branch 'v2.3' into bugfix/truncate-filenames-in-invokeai-batch 2023-04-09 12:16:06 -04:00
d90aa42799 [WebUI] 2.3.4 UI Bug Fixes (#3139)
Some quick bug fixes related to the UI for the 2.3.4. release.

**Features:**

- Added the ability to now add Textual Inversions to the Negative Prompt
using the UI.
- Added the ability to clear Textual Inversions and Loras from Prompt
and Negative Prompt with a single click.
- Textual Inversions now have status pips - indicating whether they are
used in the Main Prompt, Negative Prompt or both.

**Fixes**

- Fixes #3138
- Fixes #3144
- Fixed `usePrompt` not updating the Lora and TI count in prompt /
negative prompt.
- Fixed the TI regex not respecting names in substrings.
- Fixed trailing spaces when adding and removing loras and TI's.
- Fixed an issue with the TI regex not respecting the `<` and `>` used
by HuggingFace concepts.
- Some other minor bug fixes.
2023-04-09 12:07:41 -04:00
c5b34d21e5 Merge branch 'v2.3' into bugfix/truncate-filenames-in-invokeai-batch 2023-04-09 11:29:32 -04:00
40a4867143 Merge branch 'v2.3' into 234-ui-bugfixes 2023-04-09 15:56:44 +12:00
4b25f80427 [Bugfix] Pass extra_conditioning_info in inpaint, so lora can be initialized (#3151) 2023-04-08 21:17:53 -04:00
894e2e643d Pass extra_conditioning_info in inpaint 2023-04-09 00:50:30 +03:00
a38ff1a16b build(ui): Test Build (2.3.4 Feat Updates) 2023-04-09 07:37:41 +12:00
41f268b475 feat(ui): Improve TI & Lora UI 2023-04-09 07:35:19 +12:00
b3ae3f595f fix(ui): Fixed Use Prompt not detecting Loras / TI Count 2023-04-09 03:44:17 +12:00
29962613d8 chore(ui): Move Lora & TI Managers to Prompt Extras 2023-04-08 22:47:30 +12:00
1170cee1d8 fix(ui): Options panel sliding because of long Lora or TI names 2023-04-08 16:48:28 +12:00
5983e65b22 invokeai-batch: truncate image filenames that exceed filesystem's max filename size
- Closes #3115
2023-04-07 18:20:32 -04:00
bc724fcdc3 fix(ui): Fix Main Width Slider being read only. 2023-04-08 04:15:55 +12:00
1faf9c5cdd bump version 2023-04-07 09:52:32 -04:00
6d1f8e6997 [FEATURE] Lora support in 2.3 (#3072)
NOTE: This PR works with `diffusers` models **only**. As a result
InvokeAI is now converting all legacy checkpoint/safetensors files into
diffusers models on the fly. This introduces a bit of extra delay when
loading legacy models. You can avoid this by converting the files to
diffusers either at import time, or after the fact.

# Instructions:

1. Download LoRA .safetensors files of your choice and place in
`INVOKEAIROOT/loras`. Unlike the draft version of this PR, the file
names can now contain underscores and hyphens. Names with arbitrary
unicode characters are not supported.

2. Add `withLora(lora-file-basename,weight)` to your prompt. The weight
is optional and will default to 1.0. A few examples, assuming that a
LoRA file named `loras/sushi.safetensors` is present:

```
family sitting at dinner table eating sushi withLora(sushi,0.9)
family sitting at dinner table eating sushi withLora(sushi, 0.75)
family sitting at dinner table eating sushi withLora(sushi)
```

Multiple `withLora()` prompt fragments are allowed. The weight can be
arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher
weights make the LoRA's influence stronger. The last version of the
syntax, which uses the default weight of 1.0, is waiting on the next
version of the Compel library to be released and may not work at this
time.

In my limited testing, I found it useful to reduce the CFG to avoid
oversharpening. Also I got better results when running the LoRA on top
of the model on which it was based during training.

Don't try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice
versa. You will get a nasty stack trace. This needs to be cleaned up.

3. You can change the location of the `loras` directory by passing the
`--lora_directory` option to `invokeai.

Documentation can be found in docs/features/LORAS.md.

Note that this PR incorporates the unmerged 2.3.3 PR code (#3058) and
bumps the version number up to 2.3.4a0.

A zillion thanks to @felorhik, @neecapp and many others for this
implementation. @blessedcoolant and I just did a little tidying up.
2023-04-07 09:37:28 -04:00
b141ab42d3 bump compel version to fix lora + blend 2023-04-07 14:12:22 +02:00
0590bd6626 Merge branch 'v2.3' into feat/lora-support-2.3 2023-04-06 22:30:08 -04:00
35c4ff8ab0 prevent crash when prompt blend requested 2023-04-06 21:22:47 -04:00
0784e49d92 code cleanup and change default LoRA weight
- Remove unused (and probably dangerous) `unload_applied_loras()` method
- Remove unused `LoraManager.loras_to_load` attribute
- Change default LoRA weight to 0.75 when using WebUI to add a LoRA to prompt.
2023-04-06 16:34:22 -04:00
09fe21116b Update shared_invokeai_diffusion.py
add line to docs
2023-04-06 11:01:00 +02:00
b185931f84 [Bugfix] Pip - Access is denied durring installation (#3123)
Now, for python 3.9 installer run upgrade pip command like this:
`pip install --upgrade pip`
And because pip binary locked as running process this lead to error(at
least on windows):
```
ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'e:\invokeai\.venv\scripts\pip.exe'
Check the permissions.
```
To prevent this recomended command to upgrade pip is:
`python -m pip install --upgrade pip`
Which not locking pip file.
2023-04-05 23:50:50 -04:00
1a4d229650 Merge branch 'v2.3' into bugfix/pip-upgrade 2023-04-05 22:44:58 -04:00
e9d2205976 rebuild frontend 2023-04-05 22:03:52 -04:00
4b624dccf0 Merge branch 'feat/lora-support-2.3' of github.com:invoke-ai/InvokeAI into feat/lora-support-2.3 2023-04-05 22:02:01 -04:00
3dffa33097 Merge branch 'v2.3' into feat/lora-support-2.3 2023-04-05 21:59:54 -04:00
ab9756b8d2 [FEATURE] LyCORIS support in 2.3 (#3118)
Implementation of LyCORIS(extended LoRA), which is 2 formats - LoCon and
LoHa([info1](https://github.com/KohakuBlueleaf/LyCORIS/blob/locon-archive/README.md),
[info2](https://github.com/KohakuBlueleaf/LyCORIS/blob/main/Algo.md)).

It's works but i found 2 a bit different implementations of forward
function for LoHa. Both works, but I don't know which is better.

2 functions generate same images if remove `self.org_module.weight.data`
addition from LyCORIS implementation, but who's right?
2023-04-05 21:58:56 -04:00
4b74b51ffe Fix naming 2023-04-06 04:55:10 +03:00
0a020e1c06 Change pip upgrade command 2023-04-06 04:24:25 +03:00
baf60948ee Update kohya_lora_manager.py
Bias parsing, fix LoHa parsing and weight calculation
2023-04-06 01:44:20 +03:00
4e4fa1b71d [Enhancement] save name of last model to disk whenever model changes (#3102)
- this allows invokeai to restore the last used model on startup, even
after a crash or keyboard interrupt.
2023-04-05 17:37:10 -04:00
7bd870febb decrease minimum number of likes to 5 2023-04-05 15:51:58 -04:00
b62cce20b8 Clean up 2023-04-05 20:18:04 +03:00
6a8848b61f Draft implementation if LyCORIS(LoCon and LoHi) 2023-04-05 17:59:29 +03:00
c8fa01908c remove app tests
- removed app directory (a 3.0 feature), so app tests had to go too
- fixed regular expression in the concepts lib which was causing deprecation warnings
2023-04-04 23:41:26 -04:00
261be4e2e5 adjust debouncing timeout; fix duplicated ti triggers in menu 2023-04-04 23:15:09 -04:00
e0695234e7 bump compel version 2023-04-04 22:47:54 -04:00
cb1d433f30 create loras directory at update time 2023-04-04 22:47:15 -04:00
e3772f674d sort loras and TIs in case-insensitive fashion 2023-04-04 11:24:10 -04:00
ad5142d6f7 remove nodes app directory
- This was inadvertently included in the PR when rebased from main
2023-04-04 06:45:51 -04:00
fc4b76c8b9 change label for HF concepts library option 2023-04-03 16:54:54 -04:00
1e6d804104 Merge branch 'feat/lora-support-2.3' of github.com:invoke-ai/InvokeAI into feat/lora-support-2.3 2023-04-03 16:20:00 -04:00
793488e90a sort lora list alphabetically 2023-04-03 16:19:30 -04:00
11cd8d026f build: Frontend (Lora Support) 2023-04-04 04:35:19 +12:00
25faec8d70 feat(ui): Make HuggingFace Concepts display optional 2023-04-04 04:29:56 +12:00
a14fc3ace5 fix: Fix Lora / TI Prompt Interaction 2023-04-04 04:29:13 +12:00
667dee7b22 add scrollbars to textual inversion button menu 2023-04-03 08:39:47 -04:00
f75a20b218 rebuild frontend 2023-04-02 23:34:15 -04:00
8246e4abf2 fix cpu overload issue with TI trigger button 2023-04-02 23:33:21 -04:00
afcb278e66 fix crash when no extra conditioning provided (redux) 2023-04-02 19:43:56 -04:00
0a0e44b51e fix crash when no extra conditioning provided 2023-04-02 17:13:08 -04:00
d4d3441a52 save name of last model to disk whenever model changes
- this allows invokeai to restore the last used model on startup, even
  after a crash or keyboard interrupt.
2023-04-02 15:46:39 -04:00
3a0fed2fda add withLora() readline autocompletion support 2023-04-02 15:35:39 -04:00
fad6fc807b fix(ui): LoraManager UI causing overload 2023-04-02 19:37:47 +12:00
63ecdb19fe rebuild frontend 2023-04-02 00:34:33 -04:00
d7b2dbba66 limit number of suggested concepts to those with at least 6 likes 2023-04-02 00:31:55 -04:00
16aeb8d640 tweak debugging message for lora unloading 2023-04-01 23:45:36 -04:00
e0bd30b98c more elegant handling of lora context 2023-04-01 23:41:22 -04:00
90f77c047c Update ldm/modules/lora_manager.py
Co-authored-by: neecapp <ryree0@gmail.com>
2023-04-01 23:24:50 -04:00
941fc2297f Update ldm/modules/kohya_lora_manager.py
Co-authored-by: neecapp <ryree0@gmail.com>
2023-04-01 23:23:49 -04:00
110b067c52 Update ldm/modules/kohya_lora_manager.py
Co-authored-by: neecapp <ryree0@gmail.com>
2023-04-01 23:23:29 -04:00
71e4addd10 add debugging to where spinloop is occurring 2023-04-01 23:12:10 -04:00
67435da996 added a button to retrieve textual inversion triggers; but causes high browser load 2023-04-01 22:57:54 -04:00
8518f8c2ac LoRA alpha can be 0 2023-04-01 17:28:36 -04:00
d3b63ca0fe detect lora files with .pt suffix 2023-04-01 17:25:54 -04:00
605ceb2e95 add support for loras ending with .pt 2023-04-01 17:12:07 -04:00
b632b35079 remove direct legacy checkpoint rendering capabilities 2023-04-01 17:08:30 -04:00
c9372f919c moved LoRA manager cleanup routines into a context 2023-04-01 16:49:23 -04:00
acd9838559 Merge branch 'v2.3' into feat/lora-support-2.3 2023-04-01 10:55:22 -04:00
fd74f51384 Release 2.3.3 (#3058)
(note that this is actually release candidate 7, but I made the mistake
of including an old rc number in the branch and can't easily change it)

## Updating Root directory

- Introduced new mechanism for updating the root directory when
necessary. Currently only used to update the invoke.sh script using new
dialog colors.
- Fixed ROCm torch module version number

## Loading legacy 2.0/2.1 models
- Due to not converting the torch.dtype precision correctly, the
`load_pipeline_from_original_stable_diffusion_ckpt()` was returning
models of dtype float32 regardless of the precision setting. This caused
a precision mismatch crash.
- Problem now fixed (also see #3057 for the same fix to `main`)

## Support for a fourth textual inversion embedding file format
- This variant, exemplified by "easynegative.safetensors" has a single
'embparam' key containing a Tensor.
- Also refactored code to make it easier to read.
- Handle both pickle and safetensor formats.

## Persistent model selection
- To be consistent with WebUI parameter behavior, the currently selected
model is saved on exit and restored on restart for both WebUI and CLI

## Bug fixes
- Name of VAE cache directory was "hug", not "hub". This is fixed.

## VAE fixes
- Allow custom VAEs to be assigned to a legacy model by placing a
like-named vae file adjacent to the checkpoint file.
- The custom VAE will be picked up and incorporated into the diffusers
model if the user chooses to convert/optimize.

## Custom config file loading
- Some of the civitai models instruct users to place a custom .yaml file
adjacent to the checkpoint file. This generally wasn't working because
some of the .yaml files use FrozenCLIPEmbedder rather than
WeightedFrozenCLIPEmbedder, and our FrozenCLIPEmbedder class doesn't
handle the `personalization_config` section used by the the textual
inversion manager. Other .yaml files don't have the
`personalization_config` section at all. Both these issues are
fixed.#1685

## Consistent pytorch version
- There was an inconsistency between the pytorch version requirement in
`pyproject.toml` and the requirement in the installer (which does a
little jiggery-pokery to load torch with the right CUDA/ROCm version
prior to the main pip install. This was causing torch to be installed,
then uninstalled, and reinstalled with a different version number. This
is now fixed.
2023-04-01 10:17:43 -04:00
1e5a44a474 bump version to 2.3.3 final 2023-04-01 09:43:46 -04:00
78ea5d773d Update ldm/invoke/config/invokeai_update.py
Co-authored-by: Eugene Brodsky <ebr@users.noreply.github.com>
2023-04-01 09:43:02 -04:00
7547784e98 Update installer/lib/installer.py
Co-authored-by: Eugene Brodsky <ebr@users.noreply.github.com>
2023-04-01 09:41:38 -04:00
e82641d5f9 Update installer/lib/installer.py
Co-authored-by: Eugene Brodsky <ebr@users.noreply.github.com>
2023-04-01 09:41:25 -04:00
beff122d90 build(ui): Add Lora To Other Tabs
Sorry my bad. Forgot to add it to imagetoimage and unified canvas. Done now.
2023-04-01 00:26:23 +13:00
dabf56bee8 feat: Add Lora Manager to remaining tabs 2023-04-01 00:24:58 +13:00
4faf902ec4 build(ui): Rebuild Frontend - Add Lora WebUI
Typescript was broken for some reason. Fixed it and also did a clean build that passes lints.
2023-04-01 00:20:07 +13:00
2c5c20c8a0 localization(ui): Localize Lora Stuff 2023-04-01 00:18:41 +13:00
a8b9458de2 fix: LoraManager UI not returning a component 2023-04-01 00:17:22 +13:00
274d6238fa fix: Typescript being broken 2023-04-01 00:11:20 +13:00
10400761f0 build(ui): Add Lora to WebUI 2023-04-01 00:01:01 +13:00
b598b844e4 fix(ui): Missing Colors
husky was causing issues
2023-03-31 23:58:06 +13:00
8554f81e57 feat(ui): Add Lora To WebUI 2023-03-31 23:53:47 +13:00
74ff73ffc8 default --ckpt_convert to true 2023-03-31 01:51:45 -04:00
993baadc22 making this a prerelease for zipfile purposes 2023-03-31 00:44:39 -04:00
ccfb0b94b9 added @EgoringKosmos recipe for fixing ROCm installs 2023-03-31 00:38:30 -04:00
8fbe019273 Merge branch 'release/2.3.3-rc3' into feat/lora-support-2.3 2023-03-31 00:33:47 -04:00
352805d607 fix for python 3.9 2023-03-31 00:33:10 -04:00
879c80022e preliminary LoRA support ready for testing
Instructions:

1. Download LoRA .safetensors files of your choice and place in
   `INVOKEAIROOT/loras`. Unlike the draft version of this, the file
   names can contain underscores and alphanumerics. Names with
   arbitrary unicode characters are not supported.

2. Add `withLora(lora-file-basename,weight)` to your prompt. The
   weight is optional and will default to 1.0. A few examples, assuming
   that a LoRA file named `loras/sushi.safetensors` is present:

```
family sitting at dinner table eating sushi withLora(sushi,0.9)
family sitting at dinner table eating sushi withLora(sushi, 0.75)
family sitting at dinner table eating sushi withLora(sushi)
```

Multiple `withLora()` prompt fragments are allowed. The weight can be
arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher
weights make the LoRA's influence stronger.

In my limited testing, I found it useful to reduce the CFG to avoid
oversharpening. Also I got better results when running the LoRA on top
of the model on which it was based during training.

Don't try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice
versa. You will get a nasty stack trace. This needs to be cleaned up.

3. You can change the location of the `loras` directory by passing the
   `--lora_directory` option to `invokeai.

Documentation can be found in docs/features/LORAS.md.
2023-03-31 00:03:16 -04:00
ea5f6b9826 Merge branch 'release/2.3.3-rc3' into feat/lora-support-2.3 2023-03-30 22:02:37 -04:00
4145e27ce6 move personalization fallback section into a static method 2023-03-30 21:53:19 -04:00
3d4f4b677f support external legacy config files with no personalization section 2023-03-30 21:39:05 -04:00
249173faf5 remove extraneous warnings about overwriting trigger terms 2023-03-30 20:37:10 -04:00
794ef868af fix incorrect loading of external VAEs
- Closes #3073
2023-03-30 18:50:27 -04:00
a1ed22517f reenable line completion during CLI edit_model cmd 2023-03-30 15:54:10 -04:00
3765ee9b59 make invokeai-model-install work with editable install 2023-03-30 14:32:35 -04:00
91e4c60876 add solution to ROCm fail-to-install error 2023-03-30 13:50:23 -04:00
46e578e1ef Merge branch 'release/2.3.3-rc3' of github.com:invoke-ai/InvokeAI into release/2.3.3-rc3 2023-03-30 13:22:26 -04:00
3a8ef0a00c make CONCEPTS documentation title more meaningful 2023-03-30 13:21:50 -04:00
2a586f3179 upgrade compel to work with lora syntax 2023-03-30 08:08:33 -04:00
6ce24846eb merge with 2.3 release candidate 6 2023-03-30 07:39:54 -04:00
c2487e4330 Kohya lora models load but generate freezes 2023-03-30 07:38:39 -04:00
cf262dd2ea Update installer/lib/installer.py
Co-authored-by: Eugene Brodsky <ebr@users.noreply.github.com>
2023-03-29 12:44:02 -04:00
5a8d66ab02 merge lora support 2023-03-28 23:54:17 -04:00
b0b0c48d8a bump version to 2.3.3 2023-03-28 23:20:05 -04:00
8404e06d77 update documentation
- Add link to Statcomm's visual guide to docs (his permission pending)
- Update the what's new sections.
2023-03-28 17:52:22 -04:00
a91d01c27a enhancements to update routines
- Allow invokeai-update to update using a release, tag or branch.
- Allow CLI's root directory update routine to update directory
  contents regardless of whether current version is released.
- In model importation routine, clarify wording of instructions when user is
  asked to choose the type of model being imported.
2023-03-28 15:58:36 -04:00
5eeca47887 bump rc version number 2023-03-28 13:08:38 -04:00
66b361294b update embedding file documentation 2023-03-28 12:24:01 -04:00
0fb1e79a0b update model installation documentation 2023-03-28 12:07:47 -04:00
14f1efaf4f launch --model supersedes persistent model 2023-03-28 10:53:32 -04:00
23aa17e387 fix typo in name of vae cache 2023-03-28 10:48:03 -04:00
f23cc54e1b save and restore selected model on startup/exit 2023-03-28 10:39:19 -04:00
e3d992d5d7 add metadata dump script 2023-03-28 10:01:31 -04:00
bb972b2e3d Add support for yet another TI embedding file format (2.3 version) (#3045)
- This variant, exemplified by "easynegative.safetensors" has a single
'embparam' key containing a Tensor.
- Also refactored code to make it easier to read.
- Handle both pickle and safetensor formats.
2023-03-28 00:46:30 -04:00
41a8fdea53 fix bugs in online ckpt conversion of 2.0 models
This commit fixes bugs related to the on-the-fly conversion and loading of
legacy checkpoint models built on SD-2.0 base.

- When legacy checkpoints built on SD-2.0 models were converted
  on-the-fly using --ckpt_convert, generation would crash with a
  precision incompatibility error.

- In addition, broken logic was causing some 2.0-derived ckpt files to
  be converted into diffusers and then processed through the legacy
  generation routines - not good.
2023-03-28 00:11:37 -04:00
a78ff86e42 Merge branch 'v2.3' into enhance/handle-another-embedding-variant 2023-03-27 22:38:36 -04:00
8e2fd4c96a fix ROCm version 2023-03-27 22:38:04 -04:00
2f424f29a0 generalized root directory version updating 2023-03-27 22:35:12 -04:00
90f00db032 version 2.3.3-rc2
- installer now installs the pretty dialog-based console launcher
- added dialogrc for custom colors
- add updater to download new launcher when users do an update
2023-03-27 21:10:24 -04:00
77a63e5310 this is release candidate 2.3.3-rc1 (#3033)
This includes a number of bug fixes described in the draft release
notes.

It also incorporates a modified version of the dialog-based invoke.sh
script suggested by JoshuaKimsey:
https://discord.com/channels/1020123559063990373/1089119602425995304
2023-03-27 12:09:56 -04:00
8f921741a5 Update installer/templates/invoke.sh.in
Co-authored-by: Eugene Brodsky <ebr@users.noreply.github.com>
2023-03-26 23:45:00 -04:00
071df30597 handle a fourth variant of embedding .pt files
- This variant, exemplified by "easynegative.safetensors" has a single
  'embparam' key containing a Tensor.
- Also refactored code to make it easier to read.
- Handle both pickle and safetensor formats.
2023-03-26 23:40:29 -04:00
589a817952 enhance model autodetection during import (#3043)
- Imported V2 legacy models will now autoconvert into diffusers at load
time regardless of setting of --ckpt_convert.

- model manager `heuristic_import()` function now looks for side-by-side
yaml and vae files for custom configuration and VAE respectively.

Example of this:

illuminati-v1.1.safetensors illuminati-v1.1.vae.safetensors
illuminati-v1.1.yaml

When the user tries to import `illuminati-v1.1.safetensors`, the yaml
file will be used for its configuration, and the VAE will be used for
its VAE. Conversion to diffusers will happen if needed, and the yaml
file will be used to determine which V2 format (if any) to apply.

NOTE that the changes to `ckpt_to_diffusers.py` were previously reviewed
by @JPPhoto on the `main` branch and approved.
2023-03-26 11:49:00 -04:00
dcb21c0f46 enhance model autodetection during import
- Imported V2 legacy models will now autoconvert into diffusers
  at load time regardless of setting of --ckpt_convert.

- model manager `heuristic_import()` function now looks for
  side-by-side yaml and vae files for custom configuration and VAE
  respectively.

Example of this:

  illuminati-v1.1.safetensors
  illuminati-v1.1.vae.safetensors
  illuminati-v1.1.yaml

When the user tries to import `illuminati-v1.1.safetensors`, the yaml
file will be used for its configuration, and the VAE will be used for
its VAE. Conversion to diffusers will happen if needed, and the yaml
file will be used to determine which V2 format (if any) to apply.
2023-03-26 10:20:51 -04:00
1cb88960fe this is release candidate 2.3.3-rc1
Incorporates a modified version of the dialog-based invoke.sh script
suggested by JoshuaKimsey:
https://discord.com/channels/1020123559063990373/1089119602425995304
2023-03-25 16:58:08 -04:00
610a1483b7 installer: fix indentation in invoke.sh template (tabs -> spaces) 2023-03-25 13:52:37 -04:00
b4e7fc0d1d prevent infinite loop when launching developer's console 2023-03-25 13:52:37 -04:00
b792b7d68c Security patch: Scan all pickle files, including VAEs; default to safetensor loading (#3011)
Several related security fixes:

1. Port #2946 from main to 2.3.2 branch - this closes a hole that allows
a pickle checkpoint file to masquerade as a safetensors file.
2. Add pickle scanning to the checkpoint to diffusers conversion script.
3. Pickle scan VAE non-safetensors files
4. Avoid running scanner twice on same file during the probing and
conversion process.
5. Clean up diagnostic messages.
2023-03-24 22:35:15 +13:00
abaa91195d Merge branch 'v2.3' into security/scan-ckpt-models 2023-03-24 22:11:34 +13:00
1806bfb755 fix batch generation logfile name to be compatible with Windows OS (#3018)
- The command `invokeai-batch --invoke` was created a time-stamped
logfile with colons in its name, which is a Windows no-no. This corrects
the problem by writing the timestamp out as "13-06-2023_8-35-10"

- Closes #3005
2023-03-24 01:32:24 -04:00
7377855c02 Merge branch 'v2.3' into bugfix/batch-logfile-format 2023-03-24 18:10:00 +13:00
5f2a6f24cf fix corrupted outputs/.next_prefix file (#3020)
- Since 2.3.2 invokeai stores the next PNG file's numeric prefix in a
file named `.next_prefix` in the outputs directory. This avoids the
overhead of doing a directory listing to find out what file number comes
next.

- The code uses advisory locking to prevent corruption of this file in
the event that multiple invokeai's try to access it simultaneously, but
some users have experienced corruption of the file nevertheless.

- This PR addresses the problem by detecting a potentially corrupted
`.next_prefix` file and falling back to the directory listing method. A
fixed version of the file is then written out.

- Closes #3001
2023-03-23 23:53:10 -04:00
5b8b92d957 Merge branch 'v2.3' into bugfix/batch-logfile-format 2023-03-23 23:34:05 -04:00
352202a7bc Merge branch 'v2.3' into bugfix/fix-corrupted-image-sequence-file 2023-03-23 23:28:11 -04:00
82144de85f Fix textual inversion documentation and code (#3015)
This PR addresses issues raised by #3008.
    
1. Update documentation to indicate the correct maximum batch size for
TI training when xformers is and isn't used.
    
2. Update textual inversion code so that the default for batch size is
aware of xformer availability.
    
3. Add documentation for how to launch TI with distributed learning.
2023-03-24 16:14:47 +13:00
b70d713e89 Merge branch 'v2.3' into bugfix/batch-logfile-format 2023-03-23 23:12:43 -04:00
e39dde4140 Merge branch 'v2.3' into feat/adjust-ti-param-for-xformers 2023-03-24 15:40:38 +13:00
c151541703 bump version to 2.3.3-rc1 (#3019)
Lots of little bugs have been squashed since 2.3.2 and a new minor point
release is imminent. This PR updates the version number in preparation
for a RC.
2023-03-24 15:27:57 +13:00
29b348ece1 fix corrupted outputs/.next_prefix file
- Since 2.3.2 invokeai stores the next PNG file's numeric prefix in a
  file named `.next_prefix` in the outputs directory. This avoids the
  overhead of doing a directory listing to find out what file number
  comes next.

- The code uses advisory locking to prevent corruption of this file in
  the event that multiple invokeai's try to access it simultaneously,
  but some users have experienced corruption of the file nevertheless.

- This PR addresses the problem by detecting a potentially corrupted
  `.next_prefix` file and falling back to the directory listing method.
  A fixed version of the file is then written out.

- Closes #3001
2023-03-23 22:07:05 -04:00
9f7c86c33e bump version to 2.3.3-rc1
Lots of little bugs have been squashed since 2.3.2 and a new minor
point release is imminent. This PR updates the version number in
preparation for a RC.
2023-03-23 21:47:56 -04:00
a79d40519c fix batch generation logfile name to be compatible with Windows OS
- `invokeai-batch --invoke` was created a time-stamped logfile with colons in its
  name, which is a Windows no-no. This corrects the problem by writing
  the timestamp out as "13-06-2023_8-35-10"

- Closes #3005
2023-03-23 21:43:21 -04:00
4515d52a42 fix textual inversion documentation and code
This PR addresses issues raised by #3008.

1. Update documentation to indicate the correct maximum batch size for
   TI training when xformers is and isn't used.

2. Update textual inversion code so that the default for batch size
   is aware of xformer availability.

3. Add documentation for how to launch TI with distributed learning.
2023-03-23 21:00:54 -04:00
2a8513eee0 adjust textual inversion training parameters according to xformers availability
- If xformers is available, then default "use xformers" checkbox to on.
- Increase batch size to 8 (from 3).
2023-03-23 19:49:13 -04:00
b856fac713 Keep torch version at 1.13.1 (#2985)
Now that torch 2.0 is out, Invoke 2.3 should lock down its version to 1.13.1 for new installs and upgrades.
2023-03-23 15:27:12 -04:00
4a3951681c prevent double-scanning during convert
- Avoid running scanner twice on same file during the probing and
  conversion process.

- Clean up diagnostic messages.
2023-03-23 14:24:10 -04:00
ba89444e36 scan legacy checkpoint models in converter script prior to unpickling
Two related security fixes:

1. Port #2946 from main to 2.3.2 branch - this closes a hole that
   allows a pickle checkpoint file to masquerade as a safetensors
   file.

2. Add pickle scanning to the checkpoint to diffusers conversion
   script. This will be ported to main in a separate PR.
2023-03-23 13:44:08 -04:00
a044403ac3 Bugfix/fix 2.3.2 upgrade path (#2943)
This fixes #2930 by adding a missing line in `pyproject.toml` needed to create the `config/stable-diffusion` directory.
2023-03-13 10:14:37 -07:00
16dea46b79 remove outdated comment 2023-03-13 12:51:27 -04:00
1f80b5335b reenable run_patches() 2023-03-13 10:38:08 -04:00
eee7f13771 add back stable diffusion config files 2023-03-13 10:35:39 -04:00
6db509a4ff add --upgrade to update script 2023-03-13 10:15:33 -04:00
b7965e1ee6 restore find-packages to pyproject.toml 2023-03-13 10:11:37 -04:00
c3d292e8f9 bump version to post1 2023-03-13 09:35:25 -04:00
206593ec99 update version number 2023-03-13 09:34:00 -04:00
1b62c781d7 temporarily disable run-patches 2023-03-13 09:33:32 -04:00
c4de509983 fix failure to update to 2.3.2
- fixes #2930 #2941
2023-03-13 09:19:26 -04:00
8d80802a35 improve support for V2 variant legacy checkpoints (#2926)
This commit enhances support for V2 variant (epsilon and v-predict)
import and conversion to diffusers, by prompting the user to select the
proper config file during startup time autoimport as well as in the
invokeai installer script. Previously the user was only prompted when
doing an `!import` from the command line or when using the WebUI Model
Manager.
2023-03-11 20:54:01 -05:00
694925f427 improve support for V2 variant legacy checkpoints
This commit enhances support for V2 variant (epsilon and v-predict)
import and conversion to diffusers, by prompting the user to select
the proper config file during startup time autoimport as well as
in the invokeai installer script..
2023-03-11 19:34:10 -05:00
61d5cb2536 rebuild frontend/dist 2023-03-11 18:34:17 -05:00
c23fe4f6d2 Restore invokeai-update (#2909)
At some point `pyproject.toml` was modified to remove the
invokeai-update and invokeai-model-install scripts. This PR fixes the
issue.

If this was an intentional change, let me know and we'll discuss.
2023-03-11 18:31:30 -05:00
e6e93bbb80 Merge branch 'v2.3' into bugfix/restore-update-command 2023-03-11 17:52:09 -05:00
b5bd5240b6 Support both v2-v and v2-e legacy ckpt models in v2.3 (#2907)
# Support SD version 2 "epsilon" and "v-predict" inference
configurations in v2.3

This is a port of the `main` PR #2870 back into V2.3. It allows both
"epsilon" inference V2 models (e.g. "v2-base") and "v-predict" models
(e.g. "V2-768") to be imported and converted into correct diffusers
models. This depends on picking the right configuration file to use, and
since there is no intrinsic difference between the two types of models,
when we detect that a V2 model is being imported, we fall back to asking
the user to select the model type.
2023-03-12 04:42:16 +13:00
827ac82d54 Merge branch 'v2.3' into bugfix/support-both-v2-variants 2023-03-12 04:18:11 +13:00
9c2f3259ca use diffusers 0.14 cache layout, upgrade transformers, safetensors, accelerate (#2913)
This PR ports the `main` PR #2871 to the v2.3 branch. This adjusts the
global diffusers model cache to work with the 0.14 diffusers layout of
placing models in HF_HOME/hub rather than HF_HOME/diffusers. It also
implements the one-time migration action to the new layout.
2023-03-11 10:17:46 -05:00
6abe2bfe42 Merge branch 'v2.3' into bugfix/support-both-v2-variants 2023-03-11 10:01:32 -05:00
acf955fc7b upgrade transformers, accelerate, safetensors 2023-03-10 06:58:46 -05:00
023db8ac41 use diffusers 0.14 cache layout
This PR ports the `main` PR #2871 to the v2.3 branch. This adjusts
the global diffusers model cache to work with the 0.14 diffusers
layout of placing models in HF_HOME/hub rather than HF_HOME/diffusers.
2023-03-09 22:35:43 -05:00
65cf733a0c Merge branch 'v2.3' into bugfix/restore-update-command 2023-03-09 21:45:17 -05:00
8323169864 Dynamic prompt generation script for parameter scans (#2831)
# Programatically generate a large number of images varying by prompt
and other image generation parameters

This is a little standalone script named `dynamic_prompting.py` that
enables the generation of dynamic prompts. Using YAML syntax, you
specify a template of prompt phrases and lists of generation parameters,
and the script will generate a cross product of prompts and generation
settings for you. You can save these prompts to disk for later use, or
pipe them to the invokeai CLI to generate the images on the fly.

Typical uses are testing step and CFG values systematically while
holding the seed and prompt constant, testing out various artist's
styles, and comparing the results of the same prompt across different
models.

A typical template will look like this:

```
model: stable-diffusion-1.5
steps: 30;50;10
seed: 50
dimensions: 512x512
cfg:
  - 7
  - 12
sampler:
  - k_euler_a
  - k_lms
prompt:
  style:
       - greg rutkowski
       - gustav klimt
  location:
       - the mountains
       - a desert
  object:
       - luxurious dwelling
       - crude tent
  template: a {object} in {location}, in the style of {style}
```

This will generate 96 different images, each of which varies by one of
the dimensions specified in the template. For example, the prompt axis
will generate a cross product list like:
```
a luxurious dwelling in the mountains, in the style of greg rutkowski
a luxurious dwelling in the mountains, in the style of gustav klimt
a luxious dwelling in a desert, in the style of greg rutkowski
... etc
```

A typical usage would be:
```
python scripts/dynamic_prompts.py --invoke --outdir=/tmp/scanning my_template.yaml
```
This will populate `/tmp/scanning` with each of the requested images,
and also generate a `log.md` file which you can open with an e-book
reader to show something like this:


![image](https://user-images.githubusercontent.com/111189/221970165-4bbd9070-3f32-4d89-8ff2-b03a82ada575.png)

Full instructions can be obtained using the `--instructions` switch, and
an example template can be printed out using `--example`:

```
python scripts/dynamic_prompts.py --instructions
python scripts/dynamic_prompts.py --example > my_first_template.yaml
```
2023-03-09 20:18:28 -05:00
bf5cd1bd3b Merge branch 'v2.3' into enhance/simple-param-scanner-script 2023-03-09 16:08:27 -08:00
c9db01e272 Disable built-in NSFW checker on models converted with --ckpt_convert (#2908)
When a legacy ckpt model was converted into diffusers in RAM, the
built-in NSFW checker was not being disabled, in contrast to models
converted and saved to disk. Because InvokeAI does its NSFW checking as
a separate post-processing step (in order to generate blurred images
rather than black ones), this defeated the
--nsfw and --no-nsfw switches.

This closes #2836 and #2580.

Note - this fix will be applied to `main` as a separate PR.
2023-03-09 18:06:40 -05:00
6d5e9161fb make version pep 440 compliant 2023-03-09 18:00:31 -05:00
0636348585 bump version number to +a0 2023-03-09 17:57:19 -05:00
4c44523ba0 Restore invokeai-update
At some point `pyproject.toml` was modified to remove the
invokeai-update script, which in turn breaks the update
function in the launcher scripts. This PR fixes the
issue.

If this was an intentional change, let me know and we'll discuss.
2023-03-09 17:49:58 -05:00
5372800e60 Disable built-in NSFW checker on models converted with --ckpt_convert
When a legacy ckpt model was converted into diffusers in RAM, the
built-in NSFW checker was not being disabled, in contrast to models
converted and saved to disk. Because InvokeAI does its NSFW checking
as a separate post-processing step (in order to generate blurred
images rather than black ones), this defeated the
--nsfw and --no-nsfw switches.

This closes #2836 and #2580.
2023-03-09 17:38:58 -05:00
2ae396640b Support both v2-v and v2-e legacy ckpt models 2023-03-09 15:35:17 -05:00
252f222068 Merge branch 'v2.3' into enhance/simple-param-scanner-script 2023-03-09 12:02:40 -05:00
142ba8c8ea add logging, support for prompts with shell metachars 2023-03-09 11:57:44 -05:00
84dfd2003e fix documentation of range syntax 2023-03-09 02:29:07 -05:00
5a633ba811 [WebUI] Fix 'Use All' Params not Respecting Hi-Res Fix (#2840)
This is a different source/base branch from
https://github.com/invoke-ai/InvokeAI/pull/2823 but is otherwise the
same content. `yarn build` was ran on this clean branch.

## What was the problem/requirement? (What/Why)
As part of a [change in
2.3.0](d74c4009cb),
the high resolution fix was no longer being applied when 'Use all' was
selected. This effectively meant that users had to manually analyze
images to ensure that the parameters were set to match.
~~Additionally, and never actually working, Upscaling and Face
Restoration parameters were also not pulling through with the action,
causing a similar usability issue.~~ See:
https://github.com/invoke-ai/InvokeAI/pull/2823#issuecomment-1445530362

## What was the solution? (How)
This change adds a new reducer to the `postprocessingSlice` file,
mimicking the `generationSlice` reducer to assign all parameters
appropriate for the post processing options. This reducer assigns:
* Hi-res's toggle button only if the type is `txt2img`, since `img2img`
hi-res was removed previously
* ~~Upscaling's toggle button, scale, denoising strength, and upscale
strength~~
* ~~Face Restoration's toggle button, type, strength, and fidelity (if
present/applicable)~~

### Minor
* Added `endOfLine: 'crlf'` to prettier's config to prevent all files
from being checked out on Windows due to difference of line endings (and
git not picking up those changes as modifications, causing ghost
modified files from Git)

### Revision 2:
* Removed out upscaling and face restoration pulling of parameters
### Revision 3:
* More defensive coding for the `hires_fix` not present (assume false)

### Out of Scope
* Hi-res strength (applied as img2img strength in the initial image that
is generated) is not in the metadata of the final image and can't be
reconstructed easily
* Upscaling and face restoration have some peculiarities for multi-post
processing outside of the UI, which complicates it enough to scope out
of this PR.

## How were these changes tested?
* `yarn dev` => Server started successfully
* Manual testing on the development server to ensure parameters pulled
correctly
* `yarn build` => Success

## Notes
As with `generationSlice`, this code assumes `action.payload.image` is
valid and doesn't do a formal check on it to ensure it is valid.
2023-03-08 22:38:41 +13:00
f207647f0f CLI now writes hires_fix to metadata 2023-03-07 17:22:16 -08:00
ad16581ab8 Change to auto EoL and fix property missing from assignment of hires fix 2023-03-07 17:22:16 -08:00
fd722ddf7d Fix High Resolution not Pulling for Use All Parameters 2023-03-07 17:22:16 -08:00
d669e69755 Merge branch 'v2.3' into enhance/simple-param-scanner-script 2023-03-07 11:45:45 -06:00
d912bab4c2 install the script as "invokeai-batch" 2023-03-07 10:10:18 -05:00
68c2722c02 Prevent crash when converting models from within CLI using legacy model URL (#2846)
- Crash would occur at the end of this sequence:
  - launch CLI
  - !convert &lt;URL pointing to a legacy ckpt file&gt;
  - Answer "Y" when asked to delete original .ckpt file

- This commit modifies model_manager.heuristic_import() to silently
delete the downloaded legacy file after it has been converted into a
diffusers model. The user is no longer asked to approve deletion.

NB: This should be cherry-picked into main once refactor is done.
2023-03-07 00:09:11 -05:00
426fea9681 Merge branch 'v2.3' into bugfix/crash-on-unlink-after-convert 2023-03-06 20:51:58 -06:00
62cfdb9f11 fix newlines causing negative prompt to be parsed incorrectly (#2838)
This is the same fix that was applied to main in PR 2837.
2023-03-06 18:37:44 -05:00
46b4d6497c Merge branch 'v2.3' into bugfix/crash-on-unlink-after-convert 2023-03-06 18:14:53 -05:00
757c0a5775 Merge branch 'v2.3' into bugfix/negative_prompt_newline 2023-03-06 18:14:06 -05:00
9c8f0b44ad propose more restrictive codeowners (#2781)
For your consideration, here is a revised set of codeowners for the v2.3
branch. The previous set had the bad property that both @blessedcoolant
and @lstein were codeowners of everything, meaning that we had the
superpower of being able to put in a PR and get full approval if any
other member of the team (not a codeowner) approved.

The proposed file is a bit more sensible but needs many eyes on it.
Please take a look and make improvements. I wasn't sure where to put
some people, such as @netsvetaev or @GreggHelt2

I don't think it makes sense to tinker with the `main` CODEOWNERS until
the "Big Freeze" code reorganization happens.

I subscribed everyone to this PR. Apologies
2023-03-06 18:12:29 -05:00
21433a948c Merge branch 'v2.3' into dev/fix-codeowners 2023-03-06 18:11:19 -05:00
183344b878 Merge branch 'v2.3' into bugfix/negative_prompt_newline 2023-03-06 12:06:58 -05:00
fc164d5be2 updated template styles. 2023-03-06 00:34:49 -05:00
45aa770cd1 implemented multiprocessing across multiple GPUs 2023-03-05 01:52:28 -05:00
6d0e782d71 add perlin, init_img, threshold & strength 2023-03-04 17:28:19 -05:00
117f70e1ec implement locking when acquiring next output file prefix 2023-03-04 09:13:17 -05:00
c840bd8c12 this prevents a crash when converting models from CLI
- Crash would occur at the end of this sequence:
  - launch CLI
  - !convert <URL pointing to a legacy ckpt file>
  - Answer "Y" when asked to delete original .ckpt file

- This commit modifies model_manager.heuristic_import()
  to silently delete the downloaded legacy file after
  it has been converted into a diffusers model. The user
  is no longer asked to approve deletion.

NB: This should be cherry-picked into main once refactor
is done.
2023-03-02 10:49:53 -05:00
3c64fad379 Merge branch 'v2.3' into enhance/simple-param-scanner-script 2023-03-02 08:11:57 -05:00
bc813e4065 Introduce pre-commit, black, isort, ... (#2822)
basically the changes I tried to introduce in #2687 (which could imho be
closed then 🙈)
2023-02-28 23:11:28 -05:00
7c1d2422f0 Merge branch 'v2.3' into dev/v2.3/add-dev-tools 2023-02-28 22:45:38 -05:00
a5b11e1071 fix newlines causing negative prompt to be parsed incorrectly
This is the same fix that was applied to main in PR 2837.
2023-02-28 17:32:17 -05:00
c7e4daf431 add support for templates written in JSON 2023-02-28 17:27:37 -05:00
4c61f3a514 add multiple enhancements
- ability to cycle through models and dimensions
- process automatically through invokeai
- create an .md file to display the grid results
2023-02-28 15:10:20 -05:00
2a179799d8 add a simple parameter scanning script to the scripts directory
Simple script to generate a file of InvokeAI prompts and settings
that scan across steps and other parameters.

To use, create a file named "template.yaml" (or similar) formatted like this
>>> cut here <<<
steps: "30:50:1"
seed: 50
cfg:
  - 7
  - 8
  - 12
sampler:
  - ddim
  - k_lms
prompt:
  - a sunny meadow in the mountains
  - a gathering storm in the mountains
>>> cut here <<<

Create sections named "steps", "seed", "cfg", "sampler" and "prompt".
- Each section can have a constant value such as this:
     steps: 50
- Or a range of numeric values in the format:
     steps: "<start>:<stop>:<step>"
- Or a list of values in the format:
     - value1
     - value2
     - value3

Be careful to: 1) put quotation marks around numeric ranges; 2) put a
space between the "-" and the value in a list of values; and 3) use spaces,
not tabs, at the beginnings of indented lines.

When you run this script, capture the output into a text file like this:

    python generate_param_scan.py template.yaml > output_prompts.txt

"output_prompts.txt" will now contain an expansion of all the list
values you provided. You can examine it in a text editor such as
Notepad.

Now start the CLI, and feed the expanded prompt file to it using the
"!replay" command:

   !replay output_prompts.txt

Alternatively, you can directly feed the output of this script
by issuing a command like this from the developer's console:

   python generate_param_scan.py template.yaml | invokeai

You can use the web interface to view the resulting images and their
metadata.
2023-02-27 17:30:57 -05:00
650f4bb58c quote output, embedding and autoscan directores in invokeai.init (#2827)
This should prevent the errors that users are seeing with spaces in the
file paths
2023-02-27 00:17:37 -05:00
7b92b27ceb Merge branch 'v2.3' into bugfix/quote-initfile-paths 2023-02-26 23:54:20 -05:00
8f1b301d01 restore previous naming scheme for sd-2.x models: (#2820)
- stable-diffusion-2.1-base base model from
stabilityai/stable-diffusion-2-1-base

- stable-diffusion-2.1-768 768 pixel model from
stabilityai/stable-diffusion-2-1-768

- sd-inpainting-2.0 512 pixel inpainting model from
runwayml/stable-diffusion-inpainting

This PR also bumps the version number up to v2.3.1.post2
2023-02-26 23:54:06 -05:00
e3a19d4f3e quote output, embedding and autoscan directores in invokeai.init
- this should prevent the errors that users are seeing with
  spaces in the file pathsa

quot
2023-02-26 23:02:18 -05:00
70283f7d8d increase line_length to 120 2023-02-26 22:11:11 +01:00
ecbb385447 bump version number 2023-02-26 16:11:07 -05:00
8dc56471ef fix compel version in pyproject.toml 2023-02-26 22:08:07 +01:00
282ba201d2 Revert "parent 9eed1919c2071f9199996df747c8638c4a75e8fb"
This reverts commit 357601e2d6.
2023-02-26 21:54:13 +01:00
2394f6458f Revert "[nodes] Removed InvokerServices, simplying service model"
This reverts commit 81fd2ee8c1.
2023-02-26 21:54:06 +01:00
47c1be3322 Revert "doc(invoke_ai_web_server): put docstrings inside their functions"
This reverts commit 1e7a6dc676.
2023-02-26 21:53:38 +01:00
741464b053 restore previous naming scheme for sd-2.x models:
- stable-diffusion-2.1-base
  base model from stabilityai/stable-diffusion-2-1-base

- stable-diffusion-2.1-768
  768 pixel model from stabilityai/stable-diffusion-2-1-768

- sd-inpainting-2.0
  512 pixel inpainting model from runwayml/stable-diffusion-inpainting
2023-02-26 15:31:43 -05:00
3aab5e7e20 update .editorconfig
- set `max_line_length = 88` for .py
2023-02-26 21:28:00 +01:00
1e7a6dc676 doc(invoke_ai_web_server): put docstrings inside their functions
Documentation strings are the first thing inside the function body.
https://docs.python.org/3/tutorial/controlflow.html#defining-functions
2023-02-26 21:28:00 +01:00
81fd2ee8c1 [nodes] Removed InvokerServices, simplying service model 2023-02-26 21:28:00 +01:00
357601e2d6 parent 9eed1919c2
author Kyle Schouviller <kyle0654@hotmail.com> 1669872800 -0800
committer Kyle Schouviller <kyle0654@hotmail.com> 1676240900 -0800

Adding base node architecture

Fix type annotation errors

Runs and generates, but breaks in saving session

Fix default model value setting. Fix deprecation warning.

Fixed node api

Adding markdown docs

Simplifying Generate construction in apps

[nodes] A few minor changes (#2510)

* Pin api-related requirements

* Remove confusing extra CORS origins list

* Adds response models for HTTP 200

[nodes] Adding graph_execution_state to soon replace session. Adding tests with pytest.

Minor typing fixes

[nodes] Fix some small output query hookups

[node] Fixing some additional typing issues

[nodes] Move and expand graph code. Add base item storage and sqlite implementation.

Update startup to match new code

[nodes] Add callbacks to item storage

[nodes] Adding an InvocationContext object to use for invocations to provide easier extensibility

[nodes] New execution model that handles iteration

[nodes] Fixing the CLI

[nodes] Adding a note to the CLI

[nodes] Split processing thread into separate service

[node] Add error message on node processing failure

Removing old files and duplicated packages

Adding python-multipart
2023-02-26 21:28:00 +01:00
71ff759692 minor improvement to mermaid diagrams 2023-02-26 21:28:00 +01:00
b0657d5fde just4fun 2023-02-26 21:27:59 +01:00
fa391c0b78 fix pyproject.toml
- add missing asterisk for backend package
- remove old comment
2023-02-26 21:27:47 +01:00
6082aace6d update docs/help/contributing/010_PULL_REQUEST
- prepend brand icons on tabs
2023-02-26 21:27:02 +01:00
7ef63161ba add icons to some docs
- this also reformated `docs/index.md`
2023-02-26 21:27:02 +01:00
b731b55de4 update title in docs/help/contributing/index.md 2023-02-26 21:27:02 +01:00
51956ba356 update vs-code.md, fix docs/help/index.md 2023-02-26 21:27:02 +01:00
f494077003 enable content.code.copy
- to get a handy copy button in code blocks
- also sort the features alphabetically
2023-02-26 21:27:02 +01:00
317165c410 remove previous attempt for contributing docs 2023-02-26 21:27:02 +01:00
f5aadbc200 rename docs/help/contributing`
- update vs-code.md
- update 30_DOCS.md
2023-02-26 21:27:02 +01:00
774230f7b9 re-format docs/features/index.md 2023-02-26 21:27:02 +01:00
72e25d99c7 add docs/help/contribute/030_DOCS.md 2023-02-26 21:27:02 +01:00
7c7c1ba02d add docs/help/index.md 2023-02-26 21:27:01 +01:00
9c6af74556 add docs/help/IDE-Settings 2023-02-26 21:27:01 +01:00
57daa3e1c2 re-ignore .vscode 2023-02-26 21:27:01 +01:00
ce98fdc5c4 after some complaints reomove .vscode
I still think they would be beneficial, but to lazy to re-discuss this
2023-02-26 21:27:01 +01:00
f901645c12 use pip517 2023-02-26 21:27:01 +01:00
f514f17e92 add variables to define:
- repo_url
- repo_name
- site_url
2023-02-26 21:27:01 +01:00
8744dd0c46 fix edit_uri in mkdocs.yml 2023-02-26 21:27:01 +01:00
f3d669319e get rid of requirements-mkdocs.txt 2023-02-26 21:27:01 +01:00
ace7032067 add docs/help/contribute/issues, update index 2023-02-26 21:27:01 +01:00
d32819875a fix docs/requirements-mkdocs.txt 2023-02-26 21:27:01 +01:00
5b5898827c update vscode settings 2023-02-26 21:27:00 +01:00
8a233174de update MkDocs-Material to v9 2023-02-26 21:27:00 +01:00
bec81170b5 move contribution docs to help section, add index 2023-02-26 21:27:00 +01:00
2f25363d76 update "how to contribute" doc and md indentation 2023-02-26 21:27:00 +01:00
2aa5688d90 update docs/.markdownlint.jsonc
- disable ul-indent
- disable list-marker-space
2023-02-26 21:27:00 +01:00
ed06a70eca add pre-commit hook no-commit-to-branch
additional layer to prevent accidential commits directly to main branch
2023-02-26 21:27:00 +01:00
e80160f8dd update config of black and isort
black:
- extend-exclude legacy scripts
- config for python 3.9 as long as we support it
isort:
- set atomic to true to only apply if no syntax errors are introduced
- config for python 3.9 as long as we support it
- extend_skib_glob legacy scripts
- filter_files
- match line_length with black
- remove_redundant_aliases
- skip_gitignore
- set src paths
- include virtual_env to detect third party modules
2023-02-26 21:27:00 +01:00
bfe64b1510 allign prettierrc with config in frontend 2023-02-26 21:27:00 +01:00
bb1769abab remove non working .editorconfig entrys 2023-02-26 21:27:00 +01:00
e3f906e90d update .flake8 - use extend-exclude
so that default excludes are not overwritten
2023-02-26 21:27:00 +01:00
d77dc68119 better config of pre-commit hooks:
- better order of hooks
- add flake8-comprehensions and flake8-simplify
- remove unecesarry hooks which are covered by previous hooks
- add hooks
  - check-executables-have-shebangs
  - check-shebang-scripts-are-executable
2023-02-26 21:27:00 +01:00
ee3d695e2e remove command from json to be compliant 2023-02-26 21:27:00 +01:00
0443befd2f update pyproject.toml and vscode settings 2023-02-26 21:26:59 +01:00
b4fd02b910 add more hooks, reorder hooks, update .flake8 2023-02-26 21:26:59 +01:00
4e0fe4ad6e update black / flake8 related settings
- add flake8-black to dev extras
- update `.flake8`
- update flake8 pre-commit hook
2023-02-26 21:26:59 +01:00
3231499992 update .vscode settings and extensions 2023-02-26 21:26:59 +01:00
c134161a45 update .editorconfig 2023-02-26 21:26:59 +01:00
c3f533f20f update .pre-commit-config.yaml 2023-02-26 21:26:59 +01:00
519a9071a8 add "How to contribute" to docs
- not yet finished
2023-02-26 21:26:59 +01:00
87b4663026 add /docs/.markdownlint.jsonc
- for now only disable `MD046`
2023-02-26 21:26:59 +01:00
6c11e8ee06 update mkdocs.yml
- add feature `content.tabs.link`
2023-02-26 21:26:59 +01:00
2a739890a3 add .pre-commit-config.yaml 2023-02-26 21:26:59 +01:00
02e84c9565 add .flake8 2023-02-26 21:26:59 +01:00
39715017f9 update pyproject.toml 2023-02-26 21:26:44 +01:00
35518542f8 add .vscode files 2023-02-26 21:25:45 +01:00
0aa1106c96 update .editorconfig 2023-02-26 21:25:45 +01:00
9cf7e5f634 Merge branch 'main' into add_lora_support 2023-02-25 19:21:31 -08:00
d9c46277ea add peft setup (need to install huggingface/peft) 2023-02-25 20:21:20 -07:00
33f832e6ab [ui]: 2.3 hotfixes (#2806)
- Updated Spanish translation
- Updated Portuguese (Brazil) translation
- Fix a number of translation issues and add missing strings
- Fix vertical symmetry and symmetry steps issue when generation steps
is adjusted
2023-02-26 12:30:59 +13:00
281c788489 chore(ui): build frontend 2023-02-25 14:26:50 +11:00
3858bef185 fix(ui): clamp symmetry steps to generation steps
Also renamed the variables to `horizontalSymmetrySteps` as `TimePercentage` is not accurate.
2023-02-25 14:26:46 +11:00
f9a1afd09c fix(ui): fix #2802 vertical symmetry not working 2023-02-25 11:28:17 +11:00
251e9c0294 fix(ui): add missing strings
Fixes #2797
Fixes #2798
2023-02-25 11:27:47 +11:00
d8bf2e3c10 fix(ui): fix translation typing, fix strings
I had inadvertently un-safe-d our translation types when migrating to Weblate.

This PR fixes that, and a number of translation string bugs that went unnoticed due to the lack of type safety,
2023-02-25 11:26:35 +11:00
218f30b7d0 translationBot(ui): update translation (Portuguese (Brazil))
Currently translated at 91.8% (431 of 469 strings)

Co-authored-by: Gabriel Mackievicz Telles <telles.gabriel@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/pt_BR/
Translation: InvokeAI/Web UI
2023-02-25 11:13:23 +11:00
da983c7773 translationBot(ui): added translation (Romanian)
Co-authored-by: Jeff Mahoney <jbmahoney@gmail.com>
2023-02-25 11:13:23 +11:00
7012e16c43 translationBot(ui): update translation (Spanish)
Currently translated at 100.0% (469 of 469 strings)

Co-authored-by: gallegonovato <fran-carro@hotmail.es>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/es/
Translation: InvokeAI/Web UI
2023-02-25 11:13:23 +11:00
b1050abf7f hotfix for broken merge function (#2801)
Bump version up to accommodate a hotfix on v2.3.1 release.
(model merge functionality was broken)
2023-02-24 15:33:54 -05:00
210998081a use right pep-440 standard version number 2023-02-24 15:14:39 -05:00
604acb9d91 use pep-440 standard version number 2023-02-24 15:07:54 -05:00
ef822902d4 Merge branch 'main' into add_lora_support 2023-02-24 12:06:31 -08:00
5beeb1a897 hotfix for broken merge function 2023-02-24 15:00:22 -05:00
de6304b729 fixes crashes on merge in both WebUI and console (#2800)
- an inadvertent change to the model manager broke the merging functions
- corrected here - will be a hotfix
2023-02-24 14:58:06 -05:00
d0be79c33d fixes crashes on merge in both WebUI and console
- an inadvertent change to the model manager broke the merging functions
- corrected here - will be a hotfix
2023-02-24 14:54:23 -05:00
036ca31282 Merge pull request #4 from damian0815/pr/2712
tweaks and small refactors
2023-02-24 03:49:41 -08:00
7dbe027b18 tweaks and small refactors 2023-02-24 12:46:57 +01:00
523e44ccfe simplify manager 2023-02-24 01:32:09 -07:00
6a7948466e Merge branch 'main' into add_lora_support 2023-02-23 18:33:52 -08:00
4ce8b1ba21 setup cross conditioning for lora 2023-02-23 19:27:45 -07:00
68a3132d81 move legacy lora manager to its own file 2023-02-23 17:41:20 -07:00
b69f9d4af1 initial setup of cross attention 2023-02-23 17:30:34 -07:00
6a1129ab64 switch all none diffusers stuff to legacy, and load through compel prompts 2023-02-23 16:48:33 -07:00
8e1fd92e7f Merge branch 'main' into add_lora_support 2023-02-23 15:15:46 -08:00
c22326f9f8 propose more restrictive codeowners 2023-02-23 17:28:30 -05:00
f64a4db5fa setup legacy class to abstract hacky logic for none diffusers lora and format prompt for compel 2023-02-23 05:56:39 -07:00
3f477da46c Merge branch 'add_lora_support' of https://github.com/jordanramstad/InvokeAI into add_lora_support 2023-02-23 01:45:34 -07:00
71972c3709 re-enable load attn procs support (no multiplier) 2023-02-23 01:44:13 -07:00
d4083221a6 Merge branch 'main' into add_lora_support 2023-02-22 13:28:04 -08:00
5b4a241f5c Merge branch 'main' into add_lora_support 2023-02-21 20:38:33 -08:00
cd333e414b move key converter to wrapper 2023-02-21 21:38:15 -07:00
af3543a8c7 further cleanup and implement wrapper 2023-02-21 20:42:40 -07:00
686f6ef8d6 Merge branch 'main' into add_lora_support 2023-02-21 18:35:11 -08:00
f70b7272f3 cleanup / concept of loading through diffusers 2023-02-21 19:33:39 -07:00
24d92979db fix typo 2023-02-21 02:08:02 -07:00
c669336d6b Update lora_manager.py 2023-02-21 02:05:11 -07:00
5529309e73 adjusting back to hooks, forcing to be last in execution 2023-02-21 01:34:06 -07:00
49c0516602 change hook to override 2023-02-20 23:45:57 -07:00
c1c62f770f Merge branch 'main' into add_lora_support 2023-02-20 20:33:59 -08:00
e2b6dfeeb9 Update generate.py 2023-02-20 21:33:20 -07:00
8f527c2b2d Merge pull request #2 from jordanramstad/prompt-fix
fix prompt
2023-02-20 20:11:00 -08:00
3732af63e8 fix prompt 2023-02-20 23:06:05 -05:00
de89041779 optimize functions for unloading 2023-02-20 17:02:36 -07:00
488326dd95 Merge branch 'add_lora_support' of https://github.com/jordanramstad/InvokeAI into add_lora_support 2023-02-20 16:50:16 -07:00
c3edede73f add notes and adjust functions 2023-02-20 16:49:59 -07:00
6e730bd654 Merge branch 'main' into add_lora_support 2023-02-20 15:34:52 -08:00
884a5543c7 adjust loader to use a settings dict 2023-02-20 16:33:53 -07:00
ac972ebbe3 update prompt setup so lora's can be loaded in other ways 2023-02-20 16:06:30 -07:00
3c6c18b34c cleanup suggestions from neecap 2023-02-20 15:19:29 -07:00
8f6e43d4a4 code cleanup 2023-02-20 14:06:58 -07:00
404000bf93 Merge pull request #1 from neecapp/add_lora_support
Rewrite lora manager with hooks
2023-02-20 12:31:03 -08:00
e744774171 Rewrite lora manager with hooks 2023-02-20 13:49:16 -05:00
096e1d3a5d start of rewrite for add / remove 2023-02-20 02:37:44 -07:00
82e4d5aed2 change to new method to load safetensors 2023-02-19 17:33:24 -07:00
5a7145c485 Create convert_lora.py 2023-02-18 23:18:41 -07:00
afc8639c25 add pending support for safetensors with cloneofsimo/lora 2023-02-18 21:07:34 -07:00
141be95c2c initial setup of lora support 2023-02-18 05:29:04 -07:00
2003 changed files with 295892 additions and 183904 deletions

6
.coveragerc Normal file
View File

@ -0,0 +1,6 @@
[run]
omit='.env/*'
source='.'
[report]
show_missing = true

View File

@ -20,13 +20,13 @@ def calc_images_mean_L1(image1_path, image2_path):
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("image1_path")
parser.add_argument("image2_path")
parser.add_argument('image1_path')
parser.add_argument('image2_path')
args = parser.parse_args()
return args
if __name__ == "__main__":
if __name__ == '__main__':
args = parse_args()
mean_L1 = calc_images_mean_L1(args.image1_path, args.image2_path)
print(mean_L1)

View File

@ -1,9 +1,25 @@
# use this file as a whitelist
*
!invokeai
!ldm
!pyproject.toml
!docker/docker-entrypoint.sh
!LICENSE
**/node_modules
**/__pycache__
**/*.egg-info
# Guard against pulling in any models that might exist in the directory tree
**/*.pt*
**/*.ckpt
# ignore frontend but whitelist dist
invokeai/frontend/
!invokeai/frontend/dist/
# ignore invokeai/assets but whitelist invokeai/assets/web
invokeai/assets/
!invokeai/assets/web/
# Byte-compiled / optimized / DLL files
**/__pycache__/
**/*.py[cod]
# Distribution / packaging
*.egg-info/
*.egg

View File

@ -1,5 +1,8 @@
root = true
# All files
[*]
max_line_length = 80
charset = utf-8
end_of_line = lf
indent_size = 2
@ -10,3 +13,18 @@ trim_trailing_whitespace = true
# Python
[*.py]
indent_size = 4
max_line_length = 120
# css
[*.css]
indent_size = 4
# flake8
[.flake8]
indent_size = 4
# Markdown MkDocs
[docs/**/*.md]
max_line_length = 80
indent_size = 4
indent_style = unset

37
.flake8 Normal file
View File

@ -0,0 +1,37 @@
[flake8]
max-line-length = 120
extend-ignore =
# See https://github.com/PyCQA/pycodestyle/issues/373
E203,
# use Bugbear's B950 instead
E501,
# from black repo https://github.com/psf/black/blob/main/.flake8
E266, W503, B907
extend-select =
# Bugbear line length
B950
extend-exclude =
scripts/orig_scripts/*
ldm/models/*
ldm/modules/*
ldm/data/*
ldm/generate.py
ldm/util.py
ldm/simplet2i.py
per-file-ignores =
# B950 line too long
# W605 invalid escape sequence
# F841 assigned to but never used
# F401 imported but unused
tests/test_prompt_parser.py: B950, W605, F401
tests/test_textual_inversion.py: F841, B950
# B023 Function definition does not bind loop variable
scripts/legacy_api.py: F401, B950, B023, F841
ldm/invoke/__init__.py: F401
# B010 Do not call setattr with a constant attribute value
ldm/invoke/server_legacy.py: B010
# =====================
# flake-quote settings:
# =====================
# Set this to match black style:
inline-quotes = double

View File

@ -1,2 +0,0 @@
b3dccfaeb636599c02effc377cdd8a87d658256c
218b6d0546b990fc449c876fb99f44b50c4daa35

1
.gitattributes vendored
View File

@ -2,4 +2,3 @@
# Only affects text files and ignores other file types.
# For more info see: https://www.aleksandrhovhannisyan.com/blog/crlf-vs-lf-normalizing-line-endings-in-git/
* text=auto
docker/** text eol=lf

75
.github/CODEOWNERS vendored
View File

@ -1,32 +1,61 @@
# continuous integration
/.github/workflows/ @lstein @blessedcoolant @hipsterusername @ebr
/.github/workflows/ @mauwii @lstein @blessedcoolant
# documentation
/docs/ @lstein @blessedcoolant @hipsterusername @Millu
/mkdocs.yml @lstein @blessedcoolant @hipsterusername @Millu
# nodes
/invokeai/app/ @Kyle0654 @blessedcoolant @psychedelicious @brandonrising @hipsterusername
/docs/ @lstein @mauwii @blessedcoolant
mkdocs.yml @mauwii @lstein
# installation and configuration
/pyproject.toml @lstein @blessedcoolant @hipsterusername
/docker/ @lstein @blessedcoolant @hipsterusername @ebr
/scripts/ @ebr @lstein @hipsterusername
/installer/ @lstein @ebr @hipsterusername
/invokeai/assets @lstein @ebr @hipsterusername
/invokeai/configs @lstein @hipsterusername
/invokeai/version @lstein @blessedcoolant @hipsterusername
/pyproject.toml @mauwii @lstein @ebr
/docker/ @mauwii
/scripts/ @ebr @lstein @blessedcoolant
/installer/ @ebr @lstein
ldm/invoke/config @lstein @ebr
invokeai/assets @lstein @blessedcoolant
invokeai/configs @lstein @ebr @blessedcoolant
/ldm/invoke/_version.py @lstein @blessedcoolant
# web ui
/invokeai/frontend @blessedcoolant @psychedelicious @lstein @maryhipp @hipsterusername
/invokeai/backend @blessedcoolant @psychedelicious @lstein @maryhipp @hipsterusername
/invokeai/frontend @blessedcoolant @psychedelicious
/invokeai/backend @blessedcoolant @psychedelicious
# generation and model management
/ldm/*.py @lstein @blessedcoolant
/ldm/generate.py @lstein @keturn
/ldm/invoke/args.py @lstein @blessedcoolant
/ldm/invoke/ckpt* @lstein @blessedcoolant
/ldm/invoke/ckpt_generator @lstein @blessedcoolant
/ldm/invoke/CLI.py @lstein @blessedcoolant
/ldm/invoke/config @lstein @ebr @mauwii @blessedcoolant
/ldm/invoke/generator @keturn @damian0815
/ldm/invoke/globals.py @lstein @blessedcoolant
/ldm/invoke/merge_diffusers.py @lstein @blessedcoolant
/ldm/invoke/model_manager.py @lstein @blessedcoolant
/ldm/invoke/txt2mask.py @lstein @blessedcoolant
/ldm/invoke/patchmatch.py @Kyle0654 @lstein
/ldm/invoke/restoration @lstein @blessedcoolant
# attention, textual inversion, model configuration
/ldm/models @damian0815 @keturn @blessedcoolant
/ldm/modules/textual_inversion_manager.py @lstein @blessedcoolant
/ldm/modules/attention.py @damian0815 @keturn
/ldm/modules/diffusionmodules @damian0815 @keturn
/ldm/modules/distributions @damian0815 @keturn
/ldm/modules/ema.py @damian0815 @keturn
/ldm/modules/embedding_manager.py @lstein
/ldm/modules/encoders @damian0815 @keturn
/ldm/modules/image_degradation @damian0815 @keturn
/ldm/modules/losses @damian0815 @keturn
/ldm/modules/x_transformer.py @damian0815 @keturn
# Nodes
apps/ @Kyle0654 @jpphoto
# legacy REST API
# these are dead code
#/ldm/invoke/pngwriter.py @CapableWeb
#/ldm/invoke/server_legacy.py @CapableWeb
#/scripts/legacy_api.py @CapableWeb
#/tests/legacy_tests.sh @CapableWeb
# generation, model management, postprocessing
/invokeai/backend @damian0815 @lstein @blessedcoolant @gregghelt2 @StAlKeR7779 @brandonrising @ryanjdick @hipsterusername
# front ends
/invokeai/frontend/CLI @lstein @hipsterusername
/invokeai/frontend/install @lstein @ebr @hipsterusername
/invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
/invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
/invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp @hipsterusername

View File

@ -6,6 +6,10 @@ title: '[bug]: '
labels: ['bug']
# assignees:
# - moderator_bot
# - lstein
body:
- type: markdown
attributes:
@ -14,9 +18,10 @@ body:
- type: checkboxes
attributes:
label: Is there an existing issue for this problem?
label: Is there an existing issue for this?
description: |
Please [search](https://github.com/invoke-ai/InvokeAI/issues) first to see if an issue already exists for the problem.
Please use the [search function](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen+label%3Abug)
irst to see if an issue already exists for the bug you encountered.
options:
- label: I have searched the existing issues
required: true
@ -28,119 +33,70 @@ body:
- type: dropdown
id: os_dropdown
attributes:
label: Operating system
description: Your computer's operating system.
label: OS
description: Which operating System did you use when the bug occured
multiple: false
options:
- 'Linux'
- 'Windows'
- 'macOS'
- 'other'
validations:
required: true
- type: dropdown
id: gpu_dropdown
attributes:
label: GPU vendor
description: Your GPU's vendor.
label: GPU
description: Which kind of Graphic-Adapter is your System using
multiple: false
options:
- 'Nvidia (CUDA)'
- 'AMD (ROCm)'
- 'Apple Silicon (MPS)'
- 'None (CPU)'
- 'cuda'
- 'amd'
- 'mps'
- 'cpu'
validations:
required: true
- type: input
id: gpu_model
attributes:
label: GPU model
description: Your GPU's model. If on Apple Silicon, this is your Mac's chip. Leave blank if on CPU.
placeholder: ex. RTX 2080 Ti, Mac M1 Pro
validations:
required: false
- type: input
id: vram
attributes:
label: GPU VRAM
description: Your GPU's VRAM. If on Apple Silicon, this is your Mac's unified memory. Leave blank if on CPU.
label: VRAM
description: Size of the VRAM if known
placeholder: 8GB
validations:
required: false
- type: input
id: version-number
attributes:
label: Version number
description: |
The version of Invoke you have installed. If it is not the latest version, please update and try again to confirm the issue still exists. If you are testing main, please include the commit hash instead.
placeholder: ex. 3.6.1
validations:
required: true
- type: input
id: browser-version
attributes:
label: Browser
description: Your web browser and version.
placeholder: ex. Firefox 123.0b3
validations:
required: true
- type: textarea
id: python-deps
attributes:
label: Python dependencies
description: |
If the problem occurred during image generation, click the gear icon at the bottom left corner, click "About", click the copy button and then paste here.
validations:
required: false
- type: textarea
id: what-happened
attributes:
label: What happened
label: What happened?
description: |
Describe what happened. Include any relevant error messages, stack traces and screenshots here.
placeholder: I clicked button X and then Y happened.
Briefly describe what happened, what you expected to happen and how to reproduce this bug.
placeholder: When using the webinterface and right-clicking on button X instead of the popup-menu there error Y appears
validations:
required: true
- type: textarea
id: what-you-expected
attributes:
label: What you expected to happen
description: Describe what you expected to happen.
placeholder: I expected Z to happen.
validations:
required: true
- type: textarea
id: how-to-repro
attributes:
label: How to reproduce the problem
description: List steps to reproduce the problem.
placeholder: Start the app, generate an image with these settings, then click button X.
label: Screenshots
description: If applicable, add screenshots to help explain your problem
placeholder: this is what the result looked like <screenshot>
validations:
required: false
- type: textarea
id: additional-context
attributes:
label: Additional context
description: Any other context that might help us to understand the problem.
description: Add any other context about the problem here
placeholder: Only happens when there is full moon and Friday the 13th on Christmas Eve 🎅🏻
validations:
required: false
- type: input
id: discord-username
id: contact
attributes:
label: Discord username
description: If you are on the Invoke discord and would prefer to be contacted there, please provide your username.
placeholder: supercoolusername123
label: Contact Details
description: __OPTIONAL__ How can we get in touch with you if we need more info (besides this issue)?
placeholder: ex. email@example.com, discordname, twitter, ...
validations:
required: false

View File

@ -1,5 +1,5 @@
name: Feature Request
description: Contribute a idea or request a new feature
description: Commit a idea or Request a new feature
title: '[enhancement]: '
labels: ['enhancement']
# assignees:
@ -9,14 +9,14 @@ body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this feature request!
Thanks for taking the time to fill out this Feature request!
- type: checkboxes
attributes:
label: Is there an existing issue for this?
description: |
Please make use of the [search function](https://github.com/invoke-ai/InvokeAI/labels/enhancement)
to see if a similar issue already exists for the feature you want to request
to see if a simmilar issue already exists for the feature you want to request
options:
- label: I have searched the existing issues
required: true
@ -34,9 +34,12 @@ body:
id: whatisexpected
attributes:
label: What should this feature add?
description: Explain the functionality this feature should add. Feature requests should be for single features. Please create multiple requests if you want to request multiple features.
description: Please try to explain the functionality this feature should add
placeholder: |
I'd like a button that creates an image of banana sushi every time I press it. Each image should be different. There should be a toggle next to the button that enables strawberry mode, in which the images are of strawberry sushi instead.
Instead of one huge textfield, it would be nice to have forms for bug-reports, feature-requests, ...
Great benefits with automatic labeling, assigning and other functionalitys not available in that form
via old-fashioned markdown-templates. I would also love to see the use of a moderator bot 🤖 like
https://github.com/marketplace/actions/issue-moderator-with-commands to auto close old issues and other things
validations:
required: true
@ -48,6 +51,6 @@ body:
- type: textarea
attributes:
label: Additional Content
label: Aditional Content
description: Add any other context or screenshots about the feature request here.
placeholder: This is a mockup of the design how I imagine it <screenshot>
placeholder: This is a Mockup of the design how I imagine it <screenshot>

View File

@ -1,33 +0,0 @@
name: install frontend dependencies
description: Installs frontend dependencies with pnpm, with caching
runs:
using: 'composite'
steps:
- name: setup node 18
uses: actions/setup-node@v4
with:
node-version: '18'
- name: setup pnpm
uses: pnpm/action-setup@v2
with:
version: 8
run_install: false
- name: get pnpm store directory
shell: bash
run: |
echo "STORE_PATH=$(pnpm store path --silent)" >> $GITHUB_ENV
- name: setup cache
uses: actions/cache@v4
with:
path: ${{ env.STORE_PATH }}
key: ${{ runner.os }}-pnpm-store-${{ hashFiles('**/pnpm-lock.yaml') }}
restore-keys: |
${{ runner.os }}-pnpm-store-
- name: install frontend dependencies
run: pnpm install --prefer-frozen-lockfile
shell: bash
working-directory: invokeai/frontend/web

59
.github/pr_labels.yml vendored
View File

@ -1,59 +0,0 @@
root:
- changed-files:
- any-glob-to-any-file: '*'
python-deps:
- changed-files:
- any-glob-to-any-file: 'pyproject.toml'
python:
- changed-files:
- all-globs-to-any-file:
- 'invokeai/**'
- '!invokeai/frontend/web/**'
python-tests:
- changed-files:
- any-glob-to-any-file: 'tests/**'
ci-cd:
- changed-files:
- any-glob-to-any-file: .github/**
docker:
- changed-files:
- any-glob-to-any-file: docker/**
installer:
- changed-files:
- any-glob-to-any-file: installer/**
docs:
- changed-files:
- any-glob-to-any-file: docs/**
invocations:
- changed-files:
- any-glob-to-any-file: 'invokeai/app/invocations/**'
backend:
- changed-files:
- any-glob-to-any-file: 'invokeai/backend/**'
api:
- changed-files:
- any-glob-to-any-file: 'invokeai/app/api/**'
services:
- changed-files:
- any-glob-to-any-file: 'invokeai/app/services/**'
frontend-deps:
- changed-files:
- any-glob-to-any-file:
- '**/*/package.json'
- '**/*/pnpm-lock.yaml'
frontend:
- changed-files:
- any-glob-to-any-file: 'invokeai/frontend/web/**'

View File

@ -1,21 +0,0 @@
## Summary
<!--A description of the changes in this PR. Include the kind of change (fix, feature, docs, etc), the "why" and the "how". Screenshots or videos are useful for frontend changes.-->
## Related Issues / Discussions
<!--WHEN APPLICABLE: List any related issues or discussions on github or discord. If this PR closes an issue, please use the "Closes #1234" format, so that the issue will be automatically closed when the PR merges.-->
## QA Instructions
<!--WHEN APPLICABLE: Describe how we can test the changes in this PR.-->
## Merge Plan
<!--WHEN APPLICABLE: Large PRs, or PRs that touch sensitive things like DB schemas, may need some care when merging. For example, a careful rebase by the change author, timing to not interfere with a pending release, or a message to contributors on discord after merging.-->
## Checklist
- [ ] _The PR has a short but descriptive title, suitable for a changelog_
- [ ] _Tests added / updated (if applicable)_
- [ ] _Documentation added / updated (if applicable)_

19
.github/stale.yaml vendored
View File

@ -1,19 +0,0 @@
# Number of days of inactivity before an issue becomes stale
daysUntilStale: 28
# Number of days of inactivity before a stale issue is closed
daysUntilClose: 14
# Issues with these labels will never be considered stale
exemptLabels:
- pinned
- security
# Label to use when marking an issue as stale
staleLabel: stale
# Comment to post when marking an issue as stale. Set to `false` to disable
markComment: >
This issue has been automatically marked as stale because it has not had
recent activity. It will be closed if no further activity occurs. Please
update the ticket if this is still a problem on the latest release.
# Comment to post when closing a stale issue. Set to `false` to disable
closeComment: >
Due to inactivity, this issue has been automatically closed. If this is
still a problem on the latest release, please recreate the issue.

View File

@ -3,20 +3,19 @@ on:
push:
branches:
- 'main'
- 'update/ci/docker/*'
- 'update/docker/*'
paths:
- 'pyproject.toml'
- '.dockerignore'
- 'invokeai/**'
- 'ldm/**'
- 'invokeai/backend/**'
- 'invokeai/configs/**'
- 'invokeai/frontend/dist/**'
- 'docker/Dockerfile'
- 'docker/docker-entrypoint.sh'
- 'workflows/build-container.yml'
tags:
- 'v*.*.*'
workflow_dispatch:
permissions:
contents: write
packages: write
jobs:
docker:
@ -24,31 +23,23 @@ jobs:
strategy:
fail-fast: false
matrix:
gpu-driver:
- cuda
- cpu
- rocm
flavor:
- amd
- cuda
- cpu
include:
- flavor: amd
pip-extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
- flavor: cuda
pip-extra-index-url: ''
- flavor: cpu
pip-extra-index-url: 'https://download.pytorch.org/whl/cpu'
runs-on: ubuntu-latest
name: ${{ matrix.gpu-driver }}
name: ${{ matrix.flavor }}
env:
# torch/arm64 does not support GPU currently, so arm64 builds
# would not be GPU-accelerated.
# re-enable arm64 if there is sufficient demand.
# PLATFORMS: 'linux/amd64,linux/arm64'
PLATFORMS: 'linux/amd64'
PLATFORMS: 'linux/amd64,linux/arm64'
DOCKERFILE: 'docker/Dockerfile'
steps:
- name: Free up more disk space on the runner
# https://github.com/actions/runner-images/issues/2840#issuecomment-1284059930
run: |
echo "----- Free space before cleanup"
df -h
sudo rm -rf /usr/share/dotnet
sudo rm -rf "$AGENT_TOOLSDIRECTORY"
sudo swapoff /mnt/swapfile
sudo rm -rf /mnt/swapfile
echo "----- Free space after cleanup"
df -h
- name: Checkout
uses: actions/checkout@v3
@ -59,17 +50,17 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
images: |
ghcr.io/${{ github.repository }}
${{ env.DOCKERHUB_REPOSITORY }}
${{ vars.DOCKERHUB_REPOSITORY }}
tags: |
type=ref,event=branch
type=ref,event=tag
type=pep440,pattern={{version}}
type=pep440,pattern={{major}}.{{minor}}
type=pep440,pattern={{major}}
type=semver,pattern={{version}}
type=semver,pattern={{major}}.{{minor}}
type=semver,pattern={{major}}
type=sha,enable=true,prefix=sha-,format=short
flavor: |
latest=${{ matrix.gpu-driver == 'cuda' && github.ref == 'refs/heads/main' }}
suffix=-${{ matrix.gpu-driver }},onlatest=false
latest=${{ matrix.flavor == 'cuda' && github.ref == 'refs/heads/main' }}
suffix=-${{ matrix.flavor }},onlatest=false
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
@ -87,34 +78,34 @@ jobs:
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
# - name: Login to Docker Hub
# if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
# uses: docker/login-action@v2
# with:
# username: ${{ secrets.DOCKERHUB_USERNAME }}
# password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Login to Docker Hub
if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
uses: docker/login-action@v2
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Build container
timeout-minutes: 40
id: docker_build
uses: docker/build-push-action@v4
with:
context: .
file: docker/Dockerfile
file: ${{ env.DOCKERFILE }}
platforms: ${{ env.PLATFORMS }}
push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
push: ${{ github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
build-args: PIP_EXTRA_INDEX_URL=${{ matrix.pip-extra-index-url }}
cache-from: |
type=gha,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
type=gha,scope=main-${{ matrix.gpu-driver }}
cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
type=gha,scope=${{ github.ref_name }}-${{ matrix.flavor }}
type=gha,scope=main-${{ matrix.flavor }}
cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.flavor }}
# - name: Docker Hub Description
# if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
# uses: peter-evans/dockerhub-description@v3
# with:
# username: ${{ secrets.DOCKERHUB_USERNAME }}
# password: ${{ secrets.DOCKERHUB_TOKEN }}
# repository: ${{ vars.DOCKERHUB_REPOSITORY }}
# short-description: ${{ github.event.repository.description }}
- name: Docker Hub Description
if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
uses: peter-evans/dockerhub-description@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
repository: ${{ vars.DOCKERHUB_REPOSITORY }}
short-description: ${{ github.event.repository.description }}

View File

@ -1,45 +0,0 @@
# Builds and uploads the installer and python build artifacts.
name: build installer
on:
workflow_dispatch:
workflow_call:
jobs:
build-installer:
runs-on: ubuntu-latest
timeout-minutes: 5 # expected run time: <2 min
steps:
- name: checkout
uses: actions/checkout@v4
- name: setup python
uses: actions/setup-python@v5
with:
python-version: '3.10'
cache: pip
cache-dependency-path: pyproject.toml
- name: install pypa/build
run: pip install --upgrade build
- name: setup frontend
uses: ./.github/actions/install-frontend-deps
- name: create installer
id: create_installer
run: ./create_installer.sh
working-directory: installer
- name: upload python distribution artifact
uses: actions/upload-artifact@v4
with:
name: dist
path: ${{ steps.create_installer.outputs.DIST_PATH }}
- name: upload installer artifact
uses: actions/upload-artifact@v4
with:
name: installer
path: ${{ steps.create_installer.outputs.INSTALLER_PATH }}

View File

@ -1,28 +0,0 @@
name: Close inactive issues
on:
schedule:
- cron: "00 4 * * *"
env:
DAYS_BEFORE_ISSUE_STALE: 30
DAYS_BEFORE_ISSUE_CLOSE: 14
jobs:
close-issues:
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- uses: actions/stale@v8
with:
days-before-issue-stale: ${{ env.DAYS_BEFORE_ISSUE_STALE }}
days-before-issue-close: ${{ env.DAYS_BEFORE_ISSUE_CLOSE }}
stale-issue-label: "Inactive Issue"
stale-issue-message: "There has been no activity in this issue for ${{ env.DAYS_BEFORE_ISSUE_STALE }} days. If this issue is still being experienced, please reply with an updated confirmation that the issue is still being experienced with the latest release."
close-issue-message: "Due to inactivity, this issue was automatically closed. If you are still experiencing the issue, please recreate the issue."
days-before-pr-stale: -1
days-before-pr-close: -1
exempt-issue-labels: "Active Issue"
repo-token: ${{ secrets.GITHUB_TOKEN }}
operations-per-run: 500

View File

@ -1,80 +0,0 @@
# Runs frontend code quality checks.
#
# Checks for changes to frontend files before running the checks.
# If always_run is true, always runs the checks.
name: 'frontend checks'
on:
push:
branches:
- 'main'
pull_request:
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
merge_group:
workflow_dispatch:
inputs:
always_run:
description: 'Always run the checks'
required: true
type: boolean
default: true
workflow_call:
inputs:
always_run:
description: 'Always run the checks'
required: true
type: boolean
default: true
defaults:
run:
working-directory: invokeai/frontend/web
jobs:
frontend-checks:
runs-on: ubuntu-latest
timeout-minutes: 10 # expected run time: <2 min
steps:
- uses: actions/checkout@v4
- name: check for changed frontend files
if: ${{ inputs.always_run != true }}
id: changed-files
uses: tj-actions/changed-files@v42
with:
files_yaml: |
frontend:
- 'invokeai/frontend/web/**'
- name: install dependencies
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
uses: ./.github/actions/install-frontend-deps
- name: tsc
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
run: 'pnpm lint:tsc'
shell: bash
- name: dpdm
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
run: 'pnpm lint:dpdm'
shell: bash
- name: eslint
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
run: 'pnpm lint:eslint'
shell: bash
- name: prettier
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
run: 'pnpm lint:prettier'
shell: bash
- name: knip
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
run: 'pnpm lint:knip'
shell: bash

View File

@ -1,60 +0,0 @@
# Runs frontend tests.
#
# Checks for changes to frontend files before running the tests.
# If always_run is true, always runs the tests.
name: 'frontend tests'
on:
push:
branches:
- 'main'
pull_request:
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
merge_group:
workflow_dispatch:
inputs:
always_run:
description: 'Always run the tests'
required: true
type: boolean
default: true
workflow_call:
inputs:
always_run:
description: 'Always run the tests'
required: true
type: boolean
default: true
defaults:
run:
working-directory: invokeai/frontend/web
jobs:
frontend-tests:
runs-on: ubuntu-latest
timeout-minutes: 10 # expected run time: <2 min
steps:
- uses: actions/checkout@v4
- name: check for changed frontend files
if: ${{ inputs.always_run != true }}
id: changed-files
uses: tj-actions/changed-files@v42
with:
files_yaml: |
frontend:
- 'invokeai/frontend/web/**'
- name: install dependencies
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
uses: ./.github/actions/install-frontend-deps
- name: vitest
if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
run: 'pnpm test:no-watch'
shell: bash

View File

@ -1,18 +0,0 @@
name: 'label PRs'
on:
- pull_request_target
jobs:
labeler:
permissions:
contents: read
pull-requests: write
runs-on: ubuntu-latest
steps:
- name: checkout
uses: actions/checkout@v4
- name: label PRs
uses: actions/labeler@v5
with:
configuration-path: .github/pr_labels.yml

29
.github/workflows/lint-frontend.yml vendored Normal file
View File

@ -0,0 +1,29 @@
name: Lint frontend
on:
pull_request:
paths:
- 'invokeai/frontend/**'
push:
paths:
- 'invokeai/frontend/**'
defaults:
run:
working-directory: invokeai/frontend
jobs:
lint-frontend:
if: github.event.pull_request.draft == false
runs-on: ubuntu-22.04
steps:
- name: Setup Node 18
uses: actions/setup-node@v3
with:
node-version: '18'
- uses: actions/checkout@v3
- run: 'yarn install --frozen-lockfile'
- run: 'yarn tsc'
- run: 'yarn run madge'
- run: 'yarn run lint --max-warnings=0'
- run: 'yarn run prettier --check'

View File

@ -1,49 +1,49 @@
# This is a mostly a copy-paste from https://github.com/squidfunk/mkdocs-material/blob/master/docs/publishing-your-site.md
name: mkdocs
name: mkdocs-material
on:
push:
branches:
- main
workflow_dispatch:
permissions:
contents: write
- 'main'
- 'development'
jobs:
deploy:
mkdocs-material:
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
env:
REPO_URL: '${{ github.server_url }}/${{ github.repository }}'
REPO_NAME: '${{ github.repository }}'
SITE_URL: 'https://${{ github.repository_owner }}.github.io/InvokeAI'
steps:
- name: checkout
uses: actions/checkout@v4
- name: checkout sources
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: setup python
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: '3.10'
cache: pip
cache-dependency-path: pyproject.toml
- name: set cache id
run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
- name: install requirements
env:
PIP_USE_PEP517: 1
run: |
python -m \
pip install ".[docs]"
- name: use cache
uses: actions/cache@v4
with:
key: mkdocs-material-${{ env.cache_id }}
path: .cache
restore-keys: |
mkdocs-material-
- name: confirm buildability
run: |
python -m \
mkdocs build \
--clean \
--verbose
- name: install dependencies
run: python -m pip install ".[docs]"
- name: build & deploy
run: mkdocs gh-deploy --force
- name: deploy to gh-pages
if: ${{ github.ref == 'refs/heads/main' }}
run: |
python -m \
mkdocs gh-deploy \
--clean \
--force

20
.github/workflows/pyflakes.yml vendored Normal file
View File

@ -0,0 +1,20 @@
on:
pull_request:
push:
branches:
- main
- development
- 'release-candidate-*'
jobs:
pyflakes:
name: runner / pyflakes
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: pyflakes
uses: reviewdog/action-pyflakes@v1
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
reporter: github-pr-review

41
.github/workflows/pypi-release.yml vendored Normal file
View File

@ -0,0 +1,41 @@
name: PyPI Release
on:
push:
paths:
- 'ldm/invoke/_version.py'
workflow_dispatch:
jobs:
release:
if: github.repository == 'invoke-ai/InvokeAI'
runs-on: ubuntu-22.04
env:
TWINE_USERNAME: __token__
TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
TWINE_NON_INTERACTIVE: 1
steps:
- name: checkout sources
uses: actions/checkout@v3
- name: install deps
run: pip install --upgrade build twine
- name: build package
run: python3 -m build
- name: check distribution
run: twine check dist/*
- name: check PyPI versions
if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/v2.3'
run: |
pip install --upgrade requests
python -c "\
import scripts.pypi_helper; \
EXISTS=scripts.pypi_helper.local_on_pypi(); \
print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
- name: upload package
if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
run: twine upload dist/*

View File

@ -1,76 +0,0 @@
# Runs python code quality checks.
#
# Checks for changes to python files before running the checks.
# If always_run is true, always runs the checks.
#
# TODO: Add mypy or pyright to the checks.
name: 'python checks'
on:
push:
branches:
- 'main'
pull_request:
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
merge_group:
workflow_dispatch:
inputs:
always_run:
description: 'Always run the checks'
required: true
type: boolean
default: true
workflow_call:
inputs:
always_run:
description: 'Always run the checks'
required: true
type: boolean
default: true
jobs:
python-checks:
runs-on: ubuntu-latest
timeout-minutes: 5 # expected run time: <1 min
steps:
- name: checkout
uses: actions/checkout@v4
- name: check for changed python files
if: ${{ inputs.always_run != true }}
id: changed-files
uses: tj-actions/changed-files@v42
with:
files_yaml: |
python:
- 'pyproject.toml'
- 'invokeai/**'
- '!invokeai/frontend/web/**'
- 'tests/**'
- name: setup python
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
uses: actions/setup-python@v5
with:
python-version: '3.10'
cache: pip
cache-dependency-path: pyproject.toml
- name: install ruff
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: pip install ruff
shell: bash
- name: ruff check
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: ruff check --output-format=github .
shell: bash
- name: ruff format
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: ruff format --check .
shell: bash

View File

@ -1,106 +0,0 @@
# Runs python tests on a matrix of python versions and platforms.
#
# Checks for changes to python files before running the tests.
# If always_run is true, always runs the tests.
name: 'python tests'
on:
push:
branches:
- 'main'
pull_request:
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
merge_group:
workflow_dispatch:
inputs:
always_run:
description: 'Always run the tests'
required: true
type: boolean
default: true
workflow_call:
inputs:
always_run:
description: 'Always run the tests'
required: true
type: boolean
default: true
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
matrix:
strategy:
matrix:
python-version:
- '3.10'
- '3.11'
platform:
- linux-cuda-11_7
- linux-rocm-5_2
- linux-cpu
- macos-default
- windows-cpu
include:
- platform: linux-cuda-11_7
os: ubuntu-22.04
github-env: $GITHUB_ENV
- platform: linux-rocm-5_2
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
github-env: $GITHUB_ENV
- platform: linux-cpu
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/cpu'
github-env: $GITHUB_ENV
- platform: macos-default
os: macOS-12
github-env: $GITHUB_ENV
- platform: windows-cpu
os: windows-2022
github-env: $env:GITHUB_ENV
name: 'py${{ matrix.python-version }}: ${{ matrix.platform }}'
runs-on: ${{ matrix.os }}
timeout-minutes: 15 # expected run time: 2-6 min, depending on platform
env:
PIP_USE_PEP517: '1'
steps:
- name: checkout
uses: actions/checkout@v4
- name: check for changed python files
if: ${{ inputs.always_run != true }}
id: changed-files
uses: tj-actions/changed-files@v42
with:
files_yaml: |
python:
- 'pyproject.toml'
- 'invokeai/**'
- '!invokeai/frontend/web/**'
- 'tests/**'
- name: setup python
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: pyproject.toml
- name: install dependencies
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
env:
PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
run: >
pip3 install --editable=".[test]"
- name: run pytest
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: pytest

View File

@ -1,108 +0,0 @@
# Main release workflow. Triggered on tag push or manual trigger.
#
# - Runs all code checks and tests
# - Verifies the app version matches the tag version.
# - Builds the installer and build, uploading them as artifacts.
# - Publishes to TestPyPI and PyPI. Both are conditional on the previous steps passing and require a manual approval.
#
# See docs/RELEASE.md for more information on the release process.
name: release
on:
push:
tags:
- 'v*'
workflow_dispatch:
jobs:
check-version:
runs-on: ubuntu-latest
steps:
- name: checkout
uses: actions/checkout@v4
- name: check python version
uses: samuelcolvin/check-python-version@v4
id: check-python-version
with:
version_file_path: invokeai/version/invokeai_version.py
frontend-checks:
uses: ./.github/workflows/frontend-checks.yml
with:
always_run: true
frontend-tests:
uses: ./.github/workflows/frontend-tests.yml
with:
always_run: true
python-checks:
uses: ./.github/workflows/python-checks.yml
with:
always_run: true
python-tests:
uses: ./.github/workflows/python-tests.yml
with:
always_run: true
build:
uses: ./.github/workflows/build-installer.yml
publish-testpypi:
runs-on: ubuntu-latest
timeout-minutes: 5 # expected run time: <1 min
needs:
[
check-version,
frontend-checks,
frontend-tests,
python-checks,
python-tests,
build,
]
environment:
name: testpypi
url: https://test.pypi.org/p/invokeai
permissions:
id-token: write
steps:
- name: download distribution from build job
uses: actions/download-artifact@v4
with:
name: dist
path: dist/
- name: publish distribution to TestPyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:
repository-url: https://test.pypi.org/legacy/
publish-pypi:
runs-on: ubuntu-latest
timeout-minutes: 5 # expected run time: <1 min
needs:
[
check-version,
frontend-checks,
frontend-tests,
python-checks,
python-tests,
build,
]
environment:
name: pypi
url: https://pypi.org/p/invokeai
permissions:
id-token: write
steps:
- name: download distribution from build job
uses: actions/download-artifact@v4
with:
name: dist
path: dist/
- name: publish distribution to PyPI
uses: pypa/gh-action-pypi-publish@release/v1

View File

@ -0,0 +1,67 @@
name: Test invoke.py pip
on:
pull_request:
paths-ignore:
- 'pyproject.toml'
- 'ldm/**'
- 'invokeai/backend/**'
- 'invokeai/configs/**'
- 'invokeai/frontend/dist/**'
merge_group:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
matrix:
if: github.event.pull_request.draft == false
strategy:
matrix:
python-version:
# - '3.9'
- '3.10'
pytorch:
# - linux-cuda-11_6
- linux-cuda-11_7
- linux-rocm-5_2
- linux-cpu
- macos-default
- windows-cpu
# - windows-cuda-11_6
# - windows-cuda-11_7
include:
# - pytorch: linux-cuda-11_6
# os: ubuntu-22.04
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $GITHUB_ENV
- pytorch: linux-cuda-11_7
os: ubuntu-22.04
github-env: $GITHUB_ENV
- pytorch: linux-rocm-5_2
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
github-env: $GITHUB_ENV
- pytorch: linux-cpu
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/cpu'
github-env: $GITHUB_ENV
- pytorch: macos-default
os: macOS-12
github-env: $GITHUB_ENV
- pytorch: windows-cpu
os: windows-2022
github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_6
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_7
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu117'
# github-env: $env:GITHUB_ENV
name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
runs-on: ${{ matrix.os }}
steps:
- run: 'echo "No build required"'

148
.github/workflows/test-invoke-pip.yml vendored Normal file
View File

@ -0,0 +1,148 @@
name: Test invoke.py pip
on:
push:
branches:
- 'main'
paths:
- 'pyproject.toml'
- 'ldm/**'
- 'invokeai/backend/**'
- 'invokeai/configs/**'
- 'invokeai/frontend/dist/**'
pull_request:
paths:
- 'pyproject.toml'
- 'ldm/**'
- 'invokeai/backend/**'
- 'invokeai/configs/**'
- 'invokeai/frontend/dist/**'
types:
- 'ready_for_review'
- 'opened'
- 'synchronize'
merge_group:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
matrix:
if: github.event.pull_request.draft == false
strategy:
matrix:
python-version:
# - '3.9'
- '3.10'
pytorch:
# - linux-cuda-11_6
- linux-cuda-11_7
- linux-rocm-5_2
- linux-cpu
- macos-default
- windows-cpu
# - windows-cuda-11_6
# - windows-cuda-11_7
include:
# - pytorch: linux-cuda-11_6
# os: ubuntu-22.04
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $GITHUB_ENV
- pytorch: linux-cuda-11_7
os: ubuntu-22.04
github-env: $GITHUB_ENV
- pytorch: linux-rocm-5_2
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
github-env: $GITHUB_ENV
- pytorch: linux-cpu
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/cpu'
github-env: $GITHUB_ENV
- pytorch: macos-default
os: macOS-12
github-env: $GITHUB_ENV
- pytorch: windows-cpu
os: windows-2022
github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_6
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu116'
# github-env: $env:GITHUB_ENV
# - pytorch: windows-cuda-11_7
# os: windows-2022
# extra-index-url: 'https://download.pytorch.org/whl/cu117'
# github-env: $env:GITHUB_ENV
name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
runs-on: ${{ matrix.os }}
env:
PIP_USE_PEP517: '1'
steps:
- name: Checkout sources
id: checkout-sources
uses: actions/checkout@v3
- name: set test prompt to main branch validation
if: ${{ github.ref == 'refs/heads/main' }}
run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> ${{ matrix.github-env }}
- name: set test prompt to Pull Request validation
if: ${{ github.ref != 'refs/heads/main' }}
run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
- name: setup python
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: pyproject.toml
- name: install invokeai
env:
PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
run: >
pip3 install
--editable=".[test]"
- name: run pytest
id: run-pytest
run: pytest
- name: set INVOKEAI_OUTDIR
run: >
python -c
"import os;from ldm.invoke.globals import Globals;OUTDIR=os.path.join(Globals.root,str('outputs'));print(f'INVOKEAI_OUTDIR={OUTDIR}')"
>> ${{ matrix.github-env }}
- name: run invokeai-configure
id: run-preload-models
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGINGFACE_TOKEN }}
run: >
invokeai-configure
--yes
--default_only
--full-precision
# can't use fp16 weights without a GPU
- name: run invokeai
id: run-invokeai
env:
# Set offline mode to make sure configure preloaded successfully.
HF_HUB_OFFLINE: 1
HF_DATASETS_OFFLINE: 1
TRANSFORMERS_OFFLINE: 1
run: >
invokeai
--no-patchmatch
--no-nsfw_checker
--from_file ${{ env.TEST_PROMPTS }}
--outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
- name: Archive results
id: archive-results
uses: actions/upload-artifact@v3
with:
name: results
path: ${{ env.INVOKEAI_OUTDIR }}

59
.gitignore vendored
View File

@ -1,4 +1,20 @@
# ignore default image save location and model symbolic link
.idea/
embeddings/
outputs/
models/ldm/stable-diffusion-v1/model.ckpt
**/restoration/codeformer/weights
# ignore user models config
configs/models.user.yaml
config/models.user.yml
invokeai.init
# ignore the Anaconda/Miniconda installer used while building Docker image
anaconda.sh
# ignore a directory which serves as a place for initial images
inputs/
# Byte-compiled / optimized / DLL files
__pycache__/
@ -20,6 +36,7 @@ dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
@ -46,7 +63,6 @@ pip-delete-this-directory.txt
htmlcov/
.tox/
.nox/
.coveragerc
.coverage
.coverage.*
.cache
@ -57,10 +73,8 @@ cov.xml
*.py,cover
.hypothesis/
.pytest_cache/
.pytest.ini
cover/
junit/
notes/
# Translations
*.mo
@ -133,10 +147,12 @@ celerybeat.pid
# Environments
.env
.venv*
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
@ -169,17 +185,46 @@ cython_debug/
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
src
**/__pycache__/
outputs
# Logs and associated folders
# created from generated embeddings.
logs
testtube
checkpoints
# If it's a Mac
.DS_Store
# Let the frontend manage its own gitignore
!invokeai/frontend/web/*
!invokeai/frontend/*
# Scratch folder
.scratch/
.vscode/
gfpgan/
models/ldm/stable-diffusion-v1/*.sha256
# GFPGAN model files
gfpgan/
# config file (will be created by installer)
configs/models.yaml
# weights (will be created by installer)
models/ldm/stable-diffusion-v1/*.ckpt
models/clipseg
models/gfpgan
# ignore initfile
.invokeai
# ignore environment.yml and requirements.txt
# these are links to the real files in environments-and-requirements
environment.yml
requirements.txt
# source installer files
installer/*zip
@ -187,4 +232,6 @@ installer/install.bat
installer/install.sh
installer/update.bat
installer/update.sh
installer/InvokeAI-Installer/
# no longer stored in source directory
models

View File

@ -1,24 +1,41 @@
# See https://pre-commit.com/ for usage and config
# See https://pre-commit.com for more information
# See https://pre-commit.com/hooks.html for more hooks
repos:
- repo: local
hooks:
- id: black
name: black
stages: [commit]
language: system
entry: black
types: [python]
- repo: https://github.com/psf/black
rev: 23.1.0
hooks:
- id: black
- id: flake8
name: flake8
stages: [commit]
language: system
entry: flake8
types: [python]
- repo: https://github.com/pycqa/isort
rev: 5.12.0
hooks:
- id: isort
- id: isort
name: isort
stages: [commit]
language: system
entry: isort
types: [python]
- repo: https://github.com/PyCQA/flake8
rev: 6.0.0
hooks:
- id: flake8
additional_dependencies:
- flake8-black
- flake8-bugbear
- flake8-comprehensions
- flake8-simplify
- repo: https://github.com/pre-commit/mirrors-prettier
rev: 'v3.0.0-alpha.4'
hooks:
- id: prettier
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.4.0
hooks:
- id: check-added-large-files
- id: check-executables-have-shebangs
- id: check-shebang-scripts-are-executable
- id: check-merge-conflict
- id: check-symlinks
- id: check-toml
- id: end-of-file-fixer
- id: no-commit-to-branch
args: ['--branch', 'main']
- id: trailing-whitespace

14
.prettierignore Normal file
View File

@ -0,0 +1,14 @@
invokeai/frontend/.husky
invokeai/frontend/patches
# Ignore artifacts:
build
coverage
static
invokeai/frontend/dist
# Ignore all HTML files:
*.html
# Ignore deprecated docs
docs/installation/deprecated_documentation

View File

@ -1,13 +1,19 @@
endOfLine: lf
tabWidth: 2
useTabs: false
singleQuote: true
quoteProps: as-needed
embeddedLanguageFormatting: auto
endOfLine: lf
singleQuote: true
semi: true
trailingComma: es5
useTabs: false
overrides:
- files: '*.md'
options:
proseWrap: preserve
proseWrap: always
printWidth: 80
parser: markdown
cursorOffset: -1
- files: docs/**/*.md
options:
tabWidth: 4
- files: 'invokeai/frontend/public/locales/*.json'
options:
tabWidth: 4

5
.pytest.ini Normal file
View File

@ -0,0 +1,5 @@
[pytest]
DJANGO_SETTINGS_MODULE = webtas.settings
; python_files = tests.py test_*.py *_tests.py
addopts = --cov=. --cov-config=.coveragerc --cov-report xml:cov.xml

189
LICENSE
View File

@ -1,176 +1,21 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
MIT License
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
Copyright (c) 2022 InvokeAI Team
1. Definitions.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
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of this License, Derivative Works shall not include works that remain
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Notwithstanding the above, nothing herein shall supersede or modify
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6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
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8. Limitation of Liability. In no event and under no legal theory,
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unless required by applicable law (such as deliberate and grossly
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9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
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License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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SOFTWARE.

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@ -1,290 +0,0 @@
Copyright (c) 2023 Stability AI
CreativeML Open RAIL++-M License dated July 26, 2023
Section I: PREAMBLE
Multimodal generative models are being widely adopted and used, and
have the potential to transform the way artists, among other
individuals, conceive and benefit from AI or ML technologies as a tool
for content creation.
Notwithstanding the current and potential benefits that these
artifacts can bring to society at large, there are also concerns about
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In short, this license strives for both the open and responsible
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Even though downstream derivative versions of the model could be
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This CreativeML Open RAIL++-M License governs the use of the model
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NOW THEREFORE, You and Licensor agree as follows:
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law, Licensor reserves the right to restrict (remotely or otherwise)
usage of the Model in violation of this License.
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END OF TERMS AND CONDITIONS
Attachment A
Use Restrictions
You agree not to use the Model or Derivatives of the Model:
* In any way that violates any applicable national, federal, state,
local or international law or regulation;
* For the purpose of exploiting, harming or attempting to exploit or
harm minors in any way;
* To generate or disseminate verifiably false information and/or
content with the purpose of harming others;
* To generate or disseminate personal identifiable information that
can be used to harm an individual;
* To defame, disparage or otherwise harass others;
* For fully automated decision making that adversely impacts an
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binding, enforceable obligation;
* For any use intended to or which has the effect of discriminating
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* To exploit any of the vulnerabilities of a specific group of persons
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* For any use intended to or which has the effect of discriminating
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* To provide medical advice and medical results interpretation;
* To generate or disseminate information for the purpose to be used
for administration of justice, law enforcement, immigration or
asylum processes, such as predicting an individual will commit
fraud/crime commitment (e.g. by text profiling, drawing causal
relationships between assertions made in documents, indiscriminate
and arbitrarily-targeted use).

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@ -1,72 +0,0 @@
# simple Makefile with scripts that are otherwise hard to remember
# to use, run from the repo root `make <command>`
default: help
help:
@echo Developer commands:
@echo
@echo "ruff Run ruff, fixing any safely-fixable errors and formatting"
@echo "ruff-unsafe Run ruff, fixing all fixable errors and formatting"
@echo "mypy Run mypy using the config in pyproject.toml to identify type mismatches and other coding errors"
@echo "mypy-all Run mypy ignoring the config in pyproject.tom but still ignoring missing imports"
@echo "test Run the unit tests."
@echo "update-config-docstring Update the app's config docstring so mkdocs can autogenerate it correctly."
@echo "frontend-install Install the pnpm modules needed for the front end"
@echo "frontend-build Build the frontend in order to run on localhost:9090"
@echo "frontend-dev Run the frontend in developer mode on localhost:5173"
@echo "frontend-typegen Generate types for the frontend from the OpenAPI schema"
@echo "installer-zip Build the installer .zip file for the current version"
@echo "tag-release Tag the GitHub repository with the current version (use at release time only!)"
# Runs ruff, fixing any safely-fixable errors and formatting
ruff:
ruff check . --fix
ruff format .
# Runs ruff, fixing all errors it can fix and formatting
ruff-unsafe:
ruff check . --fix --unsafe-fixes
ruff format .
# Runs mypy, using the config in pyproject.toml
mypy:
mypy scripts/invokeai-web.py
# Runs mypy, ignoring the config in pyproject.toml but still ignoring missing (untyped) imports
# (many files are ignored by the config, so this is useful for checking all files)
mypy-all:
mypy scripts/invokeai-web.py --config-file= --ignore-missing-imports
# Run the unit tests
test:
pytest ./tests
# Update config docstring
update-config-docstring:
python scripts/update_config_docstring.py
# Install the pnpm modules needed for the front end
frontend-install:
rm -rf invokeai/frontend/web/node_modules
cd invokeai/frontend/web && pnpm install
# Build the frontend
frontend-build:
cd invokeai/frontend/web && pnpm build
# Run the frontend in dev mode
frontend-dev:
cd invokeai/frontend/web && pnpm dev
frontend-typegen:
cd invokeai/frontend/web && python ../../../scripts/generate_openapi_schema.py | pnpm typegen
# Installer zip file
installer-zip:
cd installer && ./create_installer.sh
# Tag the release
tag-release:
cd installer && ./tag_release.sh

274
README.md
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@ -1,11 +1,8 @@
<div align="center">
![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/6e3728c7-e90e-4711-905c-3b55844ff5be)
# Invoke - Professional Creative AI Tools for Visual Media
## To learn more about Invoke, or implement our Business solutions, visit [invoke.com](https://www.invoke.com/about)
![project logo](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/invoke_ai_banner.png)
# InvokeAI: A Stable Diffusion Toolkit
[![discord badge]][discord link]
@ -36,57 +33,37 @@
</div>
InvokeAI is a leading creative engine built to empower professionals
and enthusiasts alike. Generate and create stunning visual media using
the latest AI-driven technologies. InvokeAI offers an industry leading
Web Interface, interactive Command Line Interface, and also serves as
the foundation for multiple commercial products.
InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
**Quick links**: [[How to
Install](https://invoke-ai.github.io/InvokeAI/installation/INSTALLATION/)] [<a
href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a
href="https://invoke-ai.github.io/InvokeAI/">Documentation and
Tutorials</a>]
[<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>]
[<a
href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion,
Ideas & Q&A</a>]
[<a
href="https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/">Contributing</a>]
**Quick links**: [[How to Install](https://invoke-ai.github.io/InvokeAI/#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
_Note: InvokeAI is rapidly evolving. Please use the
[Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
requests. Be sure to use the provided templates. They will help us diagnose issues faster._
<div align="center">
![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
</div>
## Table of Contents
Table of Contents 📝
1. [Quick Start](#getting-started-with-invokeai)
2. [Installation](#detailed-installation-instructions)
3. [Hardware Requirements](#hardware-requirements)
4. [Features](#features)
5. [Latest Changes](#latest-changes)
6. [Troubleshooting](#troubleshooting)
7. [Contributing](#contributing)
8. [Contributors](#contributors)
9. [Support](#support)
10. [Further Reading](#further-reading)
**Getting Started**
1. 🏁 [Quick Start](#quick-start)
3. 🖥️ [Hardware Requirements](#hardware-requirements)
**More About Invoke**
1. 🌟 [Features](#features)
2. 📣 [Latest Changes](#latest-changes)
3. 🛠️ [Troubleshooting](#troubleshooting)
**Supporting the Project**
1. 🤝 [Contributing](#contributing)
2. 👥 [Contributors](#contributors)
3. 💕 [Support](#support)
## Quick Start
## Getting Started with InvokeAI
For full installation and upgrade instructions, please see:
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALLATION/)
If upgrading from version 2.3, please read [Migrating a 2.3 root
directory to 3.0](#migrating-to-3) first.
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
### Automatic Installer (suggested for 1st time users)
@ -96,8 +73,9 @@ directory to 3.0](#migrating-to-3) first.
3. Unzip the file.
4. **Windows:** double-click on the `install.bat` script. **macOS:** Open a Terminal window, drag the file `install.sh` from Finder
into the Terminal, and press return. **Linux:** run `install.sh`.
4. If you are on Windows, double-click on the `install.bat` script. On
macOS, open a Terminal window, drag the file `install.sh` from Finder
into the Terminal, and press return. On Linux, run `install.sh`.
5. You'll be asked to confirm the location of the folder in which
to install InvokeAI and its image generation model files. Pick a
@ -106,7 +84,7 @@ installing lots of models.
6. Wait while the installer does its thing. After installing the software,
the installer will launch a script that lets you configure InvokeAI and
select a set of starting image generation models.
select a set of starting image generaiton models.
7. Find the folder that InvokeAI was installed into (it is not the
same as the unpacked zip file directory!) The default location of this
@ -123,12 +101,10 @@ and go to http://localhost:9090.
10. Type `banana sushi` in the box on the top left and click `Invoke`
### Command-Line Installation (for developers and users familiar with Terminals)
### Command-Line Installation (for users familiar with Terminals)
You must have Python 3.10 through 3.11 installed on your machine. Earlier or
later versions are not supported.
Node.js also needs to be installed along with `pnpm` (can be installed with
the command `npm install -g pnpm` if needed)
You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are
not supported.
1. Open a command-line window on your machine. The PowerShell is recommended for Windows.
2. Create a directory to install InvokeAI into. You'll need at least 15 GB of free space:
@ -163,21 +139,16 @@ the command `npm install -g pnpm` if needed)
_For Windows/Linux with an NVIDIA GPU:_
```terminal
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
pip install InvokeAI[xformers] --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu117
```
_For Linux with an AMD GPU:_
```sh
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.6
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
```
_For non-GPU systems:_
```terminal
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
```
_For Macintoshes, either Intel or M1/M2/M3:_
_For Macintoshes, either Intel or M1/M2:_
```sh
pip install InvokeAI --use-pep517
@ -186,24 +157,22 @@ the command `npm install -g pnpm` if needed)
6. Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
```terminal
invokeai-configure --root .
invokeai-configure
```
Don't miss the dot at the end!
7. Launch the web server (do it every time you run InvokeAI):
```terminal
invokeai-web
invokeai --web
```
8. Point your browser to http://localhost:9090 to bring up the web interface.
9. Type `banana sushi` in the box on the top left and click `Invoke`.
Be sure to activate the virtual environment each time before re-launching InvokeAI,
using `source .venv/bin/activate` or `.venv\Scripts\activate`.
## Detailed Installation Instructions
### Detailed Installation Instructions
This fork is supported across Linux, Windows and Macintosh. Linux
users can use either an Nvidia-based card (with CUDA support) or an
@ -211,128 +180,6 @@ AMD card (using the ROCm driver). For full installation and upgrade
instructions, please see:
[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_SOURCE/)
<a name="migrating-to-3"></a>
### Migrating a v2.3 InvokeAI root directory
The InvokeAI root directory is where the InvokeAI startup file,
installed models, and generated images are stored. It is ordinarily
named `invokeai` and located in your home directory. The contents and
layout of this directory has changed between versions 2.3 and 3.0 and
cannot be used directly.
We currently recommend that you use the installer to create a new root
directory named differently from the 2.3 one, e.g. `invokeai-3` and
then use a migration script to copy your 2.3 models into the new
location. However, if you choose, you can upgrade this directory in
place. This section gives both recipes.
#### Creating a new root directory and migrating old models
This is the safer recipe because it leaves your old root directory in
place to fall back on.
1. Follow the instructions above to create and install InvokeAI in a
directory that has a different name from the 2.3 invokeai directory.
In this example, we will use "invokeai-3"
2. When you are prompted to select models to install, select a minimal
set of models, such as stable-diffusion-v1.5 only.
3. After installation is complete launch `invokeai.sh` (Linux/Mac) or
`invokeai.bat` and select option 8 "Open the developers console". This
will take you to the command line.
4. Issue the command `invokeai-migrate3 --from /path/to/v2.3-root --to
/path/to/invokeai-3-root`. Provide the correct `--from` and `--to`
paths for your v2.3 and v3.0 root directories respectively.
This will copy and convert your old models from 2.3 format to 3.0
format and create a new `models` directory in the 3.0 directory. The
old models directory (which contains the models selected at install
time) will be renamed `models.orig` and can be deleted once you have
confirmed that the migration was successful.
If you wish, you can pass the 2.3 root directory to both `--from` and
`--to` in order to update in place. Warning: this directory will no
longer be usable with InvokeAI 2.3.
#### Migrating in place
For the adventurous, you may do an in-place upgrade from 2.3 to 3.0
without touching the command line. ***This recipe does not work on
Windows platforms due to a bug in the Windows version of the 2.3
upgrade script.** See the next section for a Windows recipe.
##### For Mac and Linux Users:
1. Launch the InvokeAI launcher script in your current v2.3 root directory.
2. Select option [9] "Update InvokeAI" to bring up the updater dialog.
3. Select option [1] to upgrade to the latest release.
4. Once the upgrade is finished you will be returned to the launcher
menu. Select option [6] "Re-run the configure script to fix a broken
install or to complete a major upgrade".
This will run the configure script against the v2.3 directory and
update it to the 3.0 format. The following files will be replaced:
- The invokeai.init file, replaced by invokeai.yaml
- The models directory
- The configs/models.yaml model index
The original versions of these files will be saved with the suffix
".orig" appended to the end. Once you have confirmed that the upgrade
worked, you can safely remove these files. Alternatively you can
restore a working v2.3 directory by removing the new files and
restoring the ".orig" files' original names.
##### For Windows Users:
Windows Users can upgrade with the
1. Enter the 2.3 root directory you wish to upgrade
2. Launch `invoke.sh` or `invoke.bat`
3. Select the "Developer's console" option [8]
4. Type the following commands
```
pip install "invokeai @ https://github.com/invoke-ai/InvokeAI/archive/refs/tags/v3.0.0" --use-pep517 --upgrade
invokeai-configure --root .
```
(Replace `v3.0.0` with the current release number if this document is out of date).
The first command will install and upgrade new software to run
InvokeAI. The second will prepare the 2.3 directory for use with 3.0.
You may now launch the WebUI in the usual way, by selecting option [1]
from the launcher script
#### Migrating Images
The migration script will migrate your invokeai settings and models,
including textual inversion models, LoRAs and merges that you may have
installed previously. However it does **not** migrate the generated
images stored in your 2.3-format outputs directory. To do this, you
need to run an additional step:
1. From a working InvokeAI 3.0 root directory, start the launcher and
enter menu option [8] to open the "developer's console".
2. At the developer's console command line, type the command:
```bash
invokeai-import-images
```
3. This will lead you through the process of confirming the desired
source and destination for the imported images. The images will
appear in the gallery board of your choice, and contain the
original prompt, model name, and other parameters used to generate
the image.
(Many kudos to **techjedi** for contributing this script.)
## Hardware Requirements
InvokeAI is supported across Linux, Windows and macOS. Linux
@ -343,20 +190,21 @@ AMD card (using the ROCm driver).
You will need one of the following:
- An NVIDIA-based graphics card with 4 GB or more VRAM memory. 6-8 GB
of VRAM is highly recommended for rendering using the Stable
Diffusion XL models
- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- An Apple computer with an M1 chip.
- An AMD-based graphics card with 4GB or more VRAM memory (Linux
only), 6-8 GB for XL rendering.
- An AMD-based graphics card with 4GB or more VRAM memory. (Linux only)
We do not recommend the GTX 1650 or 1660 series video cards. They are
unable to run in half-precision mode and do not have sufficient VRAM
to render 512x512 images.
**Memory** - At least 12 GB Main Memory RAM.
### Memory
**Disk** - At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
- At least 12 GB Main Memory RAM.
### Disk
- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
## Features
@ -370,24 +218,28 @@ InvokeAI offers a locally hosted Web Server & React Frontend, with an industry l
The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/outpainting, brush tools, and more. This creative tool unlocks the capability for artists to create with AI as a creative collaborator, and can be used to augment AI-generated imagery, sketches, photography, renders, and more.
### *Workflows & Nodes*
### *Advanced Prompt Syntax*
InvokeAI offers a fully featured workflow management solution, enabling users to combine the power of nodes based workflows with the easy of a UI. This allows for customizable generation pipelines to be developed and shared by users looking to create specific workflows to support their production use-cases.
InvokeAI's advanced prompt syntax allows for token weighting, cross-attention control, and prompt blending, allowing for fine-tuned tweaking of your invocations and exploration of the latent space.
### *Board & Gallery Management*
### *Command Line Interface*
Invoke AI provides an organized gallery system for easily storing, accessing, and remixing your content in the Invoke workspace. Images can be dragged/dropped onto any Image-base UI element in the application, and rich metadata within the Image allows for easy recall of key prompts or settings used in your workflow.
For users utilizing a terminal-based environment, or who want to take advantage of CLI features, InvokeAI offers an extensive and actively supported command-line interface that provides the full suite of generation functionality available in the tool.
### Other features
- *Support for both ckpt and diffusers models*
- *SD 2.0, 2.1, XL support*
- *Upscaling Tools*
- *SD 2.0, 2.1 support*
- *Noise Control & Tresholding*
- *Popular Sampler Support*
- *Upscaling & Face Restoration Tools*
- *Embedding Manager & Support*
- *Model Manager & Support*
- *Workflow creation & management*
- *Node-Based Architecture*
### Coming Soon
- *Node-Based Architecture & UI*
- And more...
### Latest Changes
@ -395,21 +247,23 @@ For our latest changes, view our [Release
Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
[CHANGELOG](docs/CHANGELOG.md).
### Troubleshooting / FAQ
## Troubleshooting
Please check out our **[FAQ](https://invoke-ai.github.io/InvokeAI/help/FAQ/)** to get solutions for common installation
problems and other issues. For more help, please join our [Discord][discord link]
Please check out our **[Q&A](https://invoke-ai.github.io/InvokeAI/help/TROUBLESHOOT/#faq)** to get solutions for common installation
problems and other issues.
## Contributing
Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
cleanup, testing, or code reviews, is very much encouraged to do so.
Get started with contributing by reading our [Contribution documentation](https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/), joining the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) or the GitHub discussion board.
To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
If you'd like to help with translation, please see our [translation guide](docs/other/TRANSLATION.md).
If you are unfamiliar with how
to contribute to GitHub projects, we have a new contributor checklist you can follow to get started contributing:
[New Contributor Checklist](https://invoke-ai.github.io/InvokeAI/contributing/contribution_guides/newContributorChecklist/).
to contribute to GitHub projects, here is a
[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). A full set of contribution guidelines, along with templates, are in progress. You can **make your pull request against the "main" branch**.
We hope you enjoy using our software as much as we enjoy creating it,
and we hope that some of those of you who are reading this will elect
@ -423,9 +277,11 @@ This fork is a combined effort of various people from across the world.
[Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for
their time, hard work and effort.
Thanks to [Weblate](https://weblate.org/) for generously providing translation services to this project.
### Support
For support, please use this repository's GitHub Issues tracking service, or join the [Discord][discord link].
For support, please use this repository's GitHub Issues tracking service, or join the Discord.
Original portions of the software are Copyright (c) 2023 by respective contributors.

4
coverage/.gitignore vendored
View File

@ -1,4 +0,0 @@
# Ignore everything in this directory
*
# Except this file
!.gitignore

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@ -1,26 +0,0 @@
## Make a copy of this file named `.env` and fill in the values below.
## Any environment variables supported by InvokeAI can be specified here,
## in addition to the examples below.
## INVOKEAI_ROOT is the path *on the host system* where Invoke will store its data.
## It is mounted into the container and allows both containerized and non-containerized usage of Invoke.
# Usually this is the only variable you need to set. It can be relative or absolute.
# INVOKEAI_ROOT=~/invokeai
## HOST_INVOKEAI_ROOT and CONTAINER_INVOKEAI_ROOT can be used to control the on-host
## and in-container paths separately, if needed.
## HOST_INVOKEAI_ROOT is the path on the docker host's filesystem where Invoke will store data.
## If relative, it will be relative to the docker directory in which the docker-compose.yml file is located
## CONTAINER_INVOKEAI_ROOT is the path within the container where Invoke will expect to find the runtime directory.
## It MUST be absolute. There is usually no need to change this.
# HOST_INVOKEAI_ROOT=../../invokeai-data
# CONTAINER_INVOKEAI_ROOT=/invokeai
## INVOKEAI_PORT is the port on which the InvokeAI web interface will be available
# INVOKEAI_PORT=9090
## GPU_DRIVER can be set to either `nvidia` or `rocm` to enable GPU support in the container accordingly.
# GPU_DRIVER=nvidia #| rocm
## CONTAINER_UID can be set to the UID of the user on the host system that should own the files in the container.
# CONTAINER_UID=1000

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@ -1,123 +1,103 @@
# syntax=docker/dockerfile:1.4
# syntax=docker/dockerfile:1
## Builder stage
ARG PYTHON_VERSION=3.9
##################
## base image ##
##################
FROM python:${PYTHON_VERSION}-slim AS python-base
FROM library/ubuntu:23.04 AS builder
LABEL org.opencontainers.image.authors="mauwii@outlook.de"
ARG DEBIAN_FRONTEND=noninteractive
RUN rm -f /etc/apt/apt.conf.d/docker-clean; echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache
RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt update && apt-get install -y \
git \
python3-venv \
python3-pip \
build-essential
# prepare for buildkit cache
RUN rm -f /etc/apt/apt.conf.d/docker-clean \
&& echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' >/etc/apt/apt.conf.d/keep-cache
ENV INVOKEAI_SRC=/opt/invokeai
ENV VIRTUAL_ENV=/opt/venv/invokeai
# Install necessary packages
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
libgl1-mesa-glx=20.3.* \
libglib2.0-0=2.66.* \
libopencv-dev=4.5.*
ENV PATH="$VIRTUAL_ENV/bin:$PATH"
ARG GPU_DRIVER=cuda
ARG TARGETPLATFORM="linux/amd64"
# unused but available
ARG BUILDPLATFORM
# set working directory and env
ARG APPDIR=/usr/src
ARG APPNAME=InvokeAI
WORKDIR ${APPDIR}
ENV PATH ${APPDIR}/${APPNAME}/bin:$PATH
# Keeps Python from generating .pyc files in the container
ENV PYTHONDONTWRITEBYTECODE 1
# Turns off buffering for easier container logging
ENV PYTHONUNBUFFERED 1
# don't fall back to legacy build system
ENV PIP_USE_PEP517=1
WORKDIR ${INVOKEAI_SRC}
#######################
## build pyproject ##
#######################
FROM python-base AS pyproject-builder
COPY invokeai ./invokeai
COPY pyproject.toml ./
# Install dependencies
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
build-essential=12.9 \
gcc=4:10.2.* \
python3-dev=3.9.*
# Editable mode helps use the same image for development:
# the local working copy can be bind-mounted into the image
# at path defined by ${INVOKEAI_SRC}
# NOTE: there are no pytorch builds for arm64 + cuda, only cpu
# x86_64/CUDA is default
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m venv ${VIRTUAL_ENV} &&\
if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
elif [ "$GPU_DRIVER" = "rocm" ]; then \
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.6"; \
else \
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu121"; \
fi &&\
# prepare pip for buildkit cache
ARG PIP_CACHE_DIR=/var/cache/buildkit/pip
ENV PIP_CACHE_DIR ${PIP_CACHE_DIR}
RUN mkdir -p ${PIP_CACHE_DIR}
# xformers + triton fails to install on arm64
if [ "$GPU_DRIVER" = "cuda" ] && [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
pip install $extra_index_url_arg -e ".[xformers]"; \
else \
pip install $extra_index_url_arg -e "."; \
fi
# create virtual environment
RUN --mount=type=cache,target=${PIP_CACHE_DIR},sharing=locked \
python3 -m venv "${APPNAME}" \
--upgrade-deps
# #### Build the Web UI ------------------------------------
# copy sources
COPY --link . .
FROM node:20-slim AS web-builder
ENV PNPM_HOME="/pnpm"
ENV PATH="$PNPM_HOME:$PATH"
RUN corepack enable
WORKDIR /build
COPY invokeai/frontend/web/ ./
RUN --mount=type=cache,target=/pnpm/store \
pnpm install --frozen-lockfile
RUN npx vite build
#### Runtime stage ---------------------------------------
FROM library/ubuntu:23.04 AS runtime
ARG DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1
RUN apt update && apt install -y --no-install-recommends \
git \
curl \
vim \
tmux \
ncdu \
iotop \
bzip2 \
gosu \
magic-wormhole \
libglib2.0-0 \
libgl1-mesa-glx \
python3-venv \
python3-pip \
build-essential \
libopencv-dev \
libstdc++-10-dev &&\
apt-get clean && apt-get autoclean
ENV INVOKEAI_SRC=/opt/invokeai
ENV VIRTUAL_ENV=/opt/venv/invokeai
ENV INVOKEAI_ROOT=/invokeai
ENV INVOKEAI_HOST=0.0.0.0
ENV INVOKEAI_PORT=9090
ENV PATH="$VIRTUAL_ENV/bin:$INVOKEAI_SRC:$PATH"
ENV CONTAINER_UID=${CONTAINER_UID:-1000}
ENV CONTAINER_GID=${CONTAINER_GID:-1000}
# --link requires buldkit w/ dockerfile syntax 1.4
COPY --link --from=builder ${INVOKEAI_SRC} ${INVOKEAI_SRC}
COPY --link --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
COPY --link --from=web-builder /build/dist ${INVOKEAI_SRC}/invokeai/frontend/web/dist
# Link amdgpu.ids for ROCm builds
# contributed by https://github.com/Rubonnek
RUN mkdir -p "/opt/amdgpu/share/libdrm" &&\
ln -s "/usr/share/libdrm/amdgpu.ids" "/opt/amdgpu/share/libdrm/amdgpu.ids"
WORKDIR ${INVOKEAI_SRC}
# install pyproject.toml
ARG PIP_EXTRA_INDEX_URL
ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
RUN --mount=type=cache,target=${PIP_CACHE_DIR},sharing=locked \
"${APPNAME}/bin/pip" install .
# build patchmatch
RUN cd /usr/lib/$(uname -p)-linux-gnu/pkgconfig/ && ln -sf opencv4.pc opencv.pc
RUN python3 -c "from patchmatch import patch_match"
RUN mkdir -p ${INVOKEAI_ROOT} && chown -R ${CONTAINER_UID}:${CONTAINER_GID} ${INVOKEAI_ROOT}
#####################
## runtime image ##
#####################
FROM python-base AS runtime
COPY docker/docker-entrypoint.sh ./
ENTRYPOINT ["/opt/invokeai/docker-entrypoint.sh"]
CMD ["invokeai-web"]
# Create a new user
ARG UNAME=appuser
RUN useradd \
--no-log-init \
-m \
-U \
"${UNAME}"
# create volume directory
ARG VOLUME_DIR=/data
RUN mkdir -p "${VOLUME_DIR}" \
&& chown -R "${UNAME}" "${VOLUME_DIR}"
# setup runtime environment
USER ${UNAME}
COPY --chown=${UNAME} --from=pyproject-builder ${APPDIR}/${APPNAME} ${APPNAME}
ENV INVOKEAI_ROOT ${VOLUME_DIR}
ENV TRANSFORMERS_CACHE ${VOLUME_DIR}/.cache
ENV INVOKE_MODEL_RECONFIGURE "--yes --default_only"
EXPOSE 9090
ENTRYPOINT [ "invokeai" ]
CMD [ "--web", "--host", "0.0.0.0", "--port", "9090" ]
VOLUME [ "${VOLUME_DIR}" ]

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@ -1,88 +0,0 @@
# InvokeAI Containerized
All commands should be run within the `docker` directory: `cd docker`
## Quickstart :rocket:
On a known working Linux+Docker+CUDA (Nvidia) system, execute `./run.sh` in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open `http://localhost:9090` in your browser to Invoke!
For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
## Detailed setup
#### Linux
1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://docs.docker.com/compose/install/linux/#install-using-the-repository).
- The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
3. Ensure docker daemon is able to access the GPU.
- You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
#### macOS
1. Ensure Docker has at least 16GB RAM
2. Enable VirtioFS for file sharing
3. Enable `docker compose` V2 support
This is done via Docker Desktop preferences
### Configure Invoke environment
1. Make a copy of `.env.sample` and name it `.env` (`cp .env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
a. the desired location of the InvokeAI runtime directory, or
b. an existing, v3.0.0 compatible runtime directory.
1. Execute `run.sh`
The image will be built automatically if needed.
The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. The runtime directory will be populated with the base configs and models necessary to start generating.
### Use a GPU
- Linux is *recommended* for GPU support in Docker.
- WSL2 is *required* for Windows.
- only `x86_64` architecture is supported.
The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
## Customize
Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `run.sh`, your custom values will be used.
You can also set these values in `docker-compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The default is `~/invokeai`. Example:
```bash
INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
HUGGINGFACE_TOKEN=the_actual_token
CONTAINER_UID=1000
GPU_DRIVER=nvidia
```
Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
## Even Moar Customizing!
See the `docker-compose.yml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
### Reconfigure the runtime directory
Can be used to download additional models from the supported model list
In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
```yaml
command:
- invokeai-configure
- --yes
```
Or install models:
```yaml
command:
- invokeai-model-install
```

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docker/build.sh Executable file
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@ -0,0 +1,51 @@
#!/usr/bin/env bash
set -e
# If you want to build a specific flavor, set the CONTAINER_FLAVOR environment variable
# e.g. CONTAINER_FLAVOR=cpu ./build.sh
# Possible Values are:
# - cpu
# - cuda
# - rocm
# Don't forget to also set it when executing run.sh
# if it is not set, the script will try to detect the flavor by itself.
#
# Doc can be found here:
# https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
cd "$SCRIPTDIR" || exit 1
source ./env.sh
DOCKERFILE=${INVOKE_DOCKERFILE:-./Dockerfile}
# print the settings
echo -e "You are using these values:\n"
echo -e "Dockerfile:\t\t${DOCKERFILE}"
echo -e "index-url:\t\t${PIP_EXTRA_INDEX_URL:-none}"
echo -e "Volumename:\t\t${VOLUMENAME}"
echo -e "Platform:\t\t${PLATFORM}"
echo -e "Container Registry:\t${CONTAINER_REGISTRY}"
echo -e "Container Repository:\t${CONTAINER_REPOSITORY}"
echo -e "Container Tag:\t\t${CONTAINER_TAG}"
echo -e "Container Flavor:\t${CONTAINER_FLAVOR}"
echo -e "Container Image:\t${CONTAINER_IMAGE}\n"
# Create docker volume
if [[ -n "$(docker volume ls -f name="${VOLUMENAME}" -q)" ]]; then
echo -e "Volume already exists\n"
else
echo -n "creating docker volume "
docker volume create "${VOLUMENAME}"
fi
# Build Container
DOCKER_BUILDKIT=1 docker build \
--platform="${PLATFORM:-linux/amd64}" \
--tag="${CONTAINER_IMAGE:-invokeai}" \
${CONTAINER_FLAVOR:+--build-arg="CONTAINER_FLAVOR=${CONTAINER_FLAVOR}"} \
${PIP_EXTRA_INDEX_URL:+--build-arg="PIP_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}"} \
${PIP_PACKAGE:+--build-arg="PIP_PACKAGE=${PIP_PACKAGE}"} \
--file="${DOCKERFILE}" \
..

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@ -1,56 +0,0 @@
# Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
version: '3.8'
x-invokeai: &invokeai
image: "local/invokeai:latest"
build:
context: ..
dockerfile: docker/Dockerfile
# Create a .env file in the same directory as this docker-compose.yml file
# and populate it with environment variables. See .env.sample
env_file:
- .env
# variables without a default will automatically inherit from the host environment
environment:
# if set, CONTAINER_INVOKEAI_ROOT will override the Invoke runtime directory location *inside* the container
- INVOKEAI_ROOT=${CONTAINER_INVOKEAI_ROOT:-/invokeai}
- HF_HOME
ports:
- "${INVOKEAI_PORT:-9090}:${INVOKEAI_PORT:-9090}"
volumes:
- type: bind
source: ${HOST_INVOKEAI_ROOT:-${INVOKEAI_ROOT:-~/invokeai}}
target: ${CONTAINER_INVOKEAI_ROOT:-/invokeai}
bind:
create_host_path: true
- ${HF_HOME:-~/.cache/huggingface}:${HF_HOME:-/invokeai/.cache/huggingface}
tty: true
stdin_open: true
services:
invokeai-nvidia:
<<: *invokeai
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
invokeai-cpu:
<<: *invokeai
profiles:
- cpu
invokeai-rocm:
<<: *invokeai
devices:
- /dev/kfd:/dev/kfd
- /dev/dri:/dev/dri
profiles:
- rocm

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@ -1,41 +0,0 @@
#!/bin/bash
set -e -o pipefail
### Container entrypoint
# Runs the CMD as defined by the Dockerfile or passed to `docker run`
# Can be used to configure the runtime dir
# Bypass by using ENTRYPOINT or `--entrypoint`
### Set INVOKEAI_ROOT pointing to a valid runtime directory
# Otherwise configure the runtime dir first.
### Set the CONTAINER_UID envvar to match your user.
# Ensures files created in the container are owned by you:
# docker run --rm -it -v /some/path:/invokeai -e CONTAINER_UID=$(id -u) <this image>
# Default UID: 1000 chosen due to popularity on Linux systems. Possibly 501 on MacOS.
USER_ID=${CONTAINER_UID:-1000}
USER=ubuntu
usermod -u ${USER_ID} ${USER} 1>/dev/null
### Set the $PUBLIC_KEY env var to enable SSH access.
# We do not install openssh-server in the image by default to avoid bloat.
# but it is useful to have the full SSH server e.g. on Runpod.
# (use SCP to copy files to/from the image, etc)
if [[ -v "PUBLIC_KEY" ]] && [[ ! -d "${HOME}/.ssh" ]]; then
apt-get update
apt-get install -y openssh-server
pushd "$HOME"
mkdir -p .ssh
echo "${PUBLIC_KEY}" > .ssh/authorized_keys
chmod -R 700 .ssh
popd
service ssh start
fi
mkdir -p "${INVOKEAI_ROOT}"
chown --recursive ${USER} "${INVOKEAI_ROOT}"
cd "${INVOKEAI_ROOT}"
# Run the CMD as the Container User (not root).
exec gosu ${USER} "$@"

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docker/env.sh Normal file
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@ -0,0 +1,51 @@
#!/usr/bin/env bash
# This file is used to set environment variables for the build.sh and run.sh scripts.
# Try to detect the container flavor if no PIP_EXTRA_INDEX_URL got specified
if [[ -z "$PIP_EXTRA_INDEX_URL" ]]; then
# Activate virtual environment if not already activated and exists
if [[ -z $VIRTUAL_ENV ]]; then
[[ -e "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" ]] \
&& source "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" \
&& echo "Activated virtual environment: $VIRTUAL_ENV"
fi
# Decide which container flavor to build if not specified
if [[ -z "$CONTAINER_FLAVOR" ]] && python -c "import torch" &>/dev/null; then
# Check for CUDA and ROCm
CUDA_AVAILABLE=$(python -c "import torch;print(torch.cuda.is_available())")
ROCM_AVAILABLE=$(python -c "import torch;print(torch.version.hip is not None)")
if [[ "${CUDA_AVAILABLE}" == "True" ]]; then
CONTAINER_FLAVOR="cuda"
elif [[ "${ROCM_AVAILABLE}" == "True" ]]; then
CONTAINER_FLAVOR="rocm"
else
CONTAINER_FLAVOR="cpu"
fi
fi
# Set PIP_EXTRA_INDEX_URL based on container flavor
if [[ "$CONTAINER_FLAVOR" == "rocm" ]]; then
PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/rocm"
elif [[ "$CONTAINER_FLAVOR" == "cpu" ]]; then
PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
# elif [[ -z "$CONTAINER_FLAVOR" || "$CONTAINER_FLAVOR" == "cuda" ]]; then
# PIP_PACKAGE=${PIP_PACKAGE-".[xformers]"}
fi
fi
# Variables shared by build.sh and run.sh
REPOSITORY_NAME="${REPOSITORY_NAME-$(basename "$(git rev-parse --show-toplevel)")}"
REPOSITORY_NAME="${REPOSITORY_NAME,,}"
VOLUMENAME="${VOLUMENAME-"${REPOSITORY_NAME}_data"}"
ARCH="${ARCH-$(uname -m)}"
PLATFORM="${PLATFORM-linux/${ARCH}}"
INVOKEAI_BRANCH="${INVOKEAI_BRANCH-$(git branch --show)}"
CONTAINER_REGISTRY="${CONTAINER_REGISTRY-"ghcr.io"}"
CONTAINER_REPOSITORY="${CONTAINER_REPOSITORY-"$(whoami)/${REPOSITORY_NAME}"}"
CONTAINER_FLAVOR="${CONTAINER_FLAVOR-cuda}"
CONTAINER_TAG="${CONTAINER_TAG-"${INVOKEAI_BRANCH##*/}-${CONTAINER_FLAVOR}"}"
CONTAINER_IMAGE="${CONTAINER_REGISTRY}/${CONTAINER_REPOSITORY}:${CONTAINER_TAG}"
CONTAINER_IMAGE="${CONTAINER_IMAGE,,}"

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@ -1,32 +1,41 @@
#!/usr/bin/env bash
set -e -o pipefail
set -e
run() {
local scriptdir=$(dirname "${BASH_SOURCE[0]}")
cd "$scriptdir" || exit 1
# How to use: https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
local build_args=""
local profile=""
SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
cd "$SCRIPTDIR" || exit 1
touch .env
build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
source ./env.sh
[[ -z "$profile" ]] && profile="nvidia"
# Create outputs directory if it does not exist
[[ -d ./outputs ]] || mkdir ./outputs
local service_name="invokeai-$profile"
echo -e "You are using these values:\n"
echo -e "Volumename:\t${VOLUMENAME}"
echo -e "Invokeai_tag:\t${CONTAINER_IMAGE}"
echo -e "local Models:\t${MODELSPATH:-unset}\n"
if [[ ! -z "$build_args" ]]; then
printf "%s\n" "docker compose build args:"
printf "%s\n" "$build_args"
docker run \
--interactive \
--tty \
--rm \
--platform="${PLATFORM}" \
--name="${REPOSITORY_NAME,,}" \
--hostname="${REPOSITORY_NAME,,}" \
--mount=source="${VOLUMENAME}",target=/data \
--mount type=bind,source="$(pwd)"/outputs,target=/data/outputs \
${MODELSPATH:+--mount="type=bind,source=${MODELSPATH},target=/data/models"} \
${HUGGING_FACE_HUB_TOKEN:+--env="HUGGING_FACE_HUB_TOKEN=${HUGGING_FACE_HUB_TOKEN}"} \
--publish=9090:9090 \
--cap-add=sys_nice \
${GPU_FLAGS:+--gpus="${GPU_FLAGS}"} \
"${CONTAINER_IMAGE}" ${@:+$@}
# Remove Trash folder
for f in outputs/.Trash*; do
if [ -e "$f" ]; then
rm -Rf "$f"
break
fi
docker compose build $build_args $service_name
unset build_args
printf "%s\n" "starting service $service_name"
docker compose --profile "$profile" up -d "$service_name"
docker compose logs -f
}
run
done

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@ -1,60 +0,0 @@
# InvokeAI - A Stable Diffusion Toolkit
Stable Diffusion distribution by InvokeAI: https://github.com/invoke-ai
The Docker image tracks the `main` branch of the InvokeAI project, which means it includes the latest features, but may contain some bugs.
Your working directory is mounted under the `/workspace` path inside the pod. The models are in `/workspace/invokeai/models`, and outputs are in `/workspace/invokeai/outputs`.
> **Only the /workspace directory will persist between pod restarts!**
> **If you _terminate_ (not just _stop_) the pod, the /workspace will be lost.**
## Quickstart
1. Launch a pod from this template. **It will take about 5-10 minutes to run through the initial setup**. Be patient.
1. Wait for the application to load.
- TIP: you know it's ready when the CPU usage goes idle
- You can also check the logs for a line that says "_Point your browser at..._"
1. Open the Invoke AI web UI: click the `Connect` => `connect over HTTP` button.
1. Generate some art!
## Other things you can do
At any point you may edit the pod configuration and set an arbitrary Docker command. For example, you could run a command to downloads some models using `curl`, or fetch some images and place them into your outputs to continue a working session.
If you need to run *multiple commands*, define them in the Docker Command field like this:
`bash -c "cd ${INVOKEAI_ROOT}/outputs; wormhole receive 2-foo-bar; invoke.py --web --host 0.0.0.0"`
### Copying your data in and out of the pod
This image includes a couple of handy tools to help you get the data into the pod (such as your custom models or embeddings), and out of the pod (such as downloading your outputs). Here are your options for getting your data in and out of the pod:
- **SSH server**:
1. Make sure to create and set your Public Key in the RunPod settings (follow the official instructions)
1. Add an exposed port 22 (TCP) in the pod settings!
1. When your pod restarts, you will see a new entry in the `Connect` dialog. Use this SSH server to `scp` or `sftp` your files as necessary, or SSH into the pod using the fully fledged SSH server.
- [**Magic Wormhole**](https://magic-wormhole.readthedocs.io/en/latest/welcome.html):
1. On your computer, `pip install magic-wormhole` (see above instructions for details)
1. Connect to the command line **using the "light" SSH client** or the browser-based console. _Currently there's a bug where `wormhole` isn't available when connected to "full" SSH server, as described above_.
1. `wormhole send /workspace/invokeai/outputs` will send the entire `outputs` directory. You can also send individual files.
1. Once packaged, you will see a `wormhole receive <123-some-words>` command. Copy it
1. Paste this command into the terminal on your local machine to securely download the payload.
1. It works the same in reverse: you can `wormhole send` some models from your computer to the pod. Again, save your files somewhere in `/workspace` or they will be lost when the pod is stopped.
- **RunPod's Cloud Sync feature** may be used to sync the persistent volume to cloud storage. You could, for example, copy the entire `/workspace` to S3, add some custom models to it, and copy it back from S3 when launching new pod configurations. Follow the Cloud Sync instructions.
### Disable the NSFW checker
The NSFW checker is enabled by default. To disable it, edit the pod configuration and set the following command:
```
invoke --web --host 0.0.0.0 --no-nsfw_checker
```
---
Template ©2023 Eugene Brodsky [ebr](https://github.com/ebr)

5
docs/.markdownlint.jsonc Normal file
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@ -0,0 +1,5 @@
{
"MD046": false,
"MD007": false,
"MD030": false
}

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@ -4,236 +4,6 @@ title: Changelog
# :octicons-log-16: **Changelog**
## v2.3.5 <small>(22 May 2023)</small>
This release (along with the post1 and post2 follow-on releases) expands support for additional LoRA and LyCORIS models, upgrades diffusers versions, and fixes a few bugs.
### LoRA and LyCORIS Support Improvement
A number of LoRA/LyCORIS fine-tune files (those which alter the text encoder as well as the unet model) were not having the desired effect in InvokeAI. This bug has now been fixed. Full documentation of LoRA support is available at InvokeAI LoRA Support.
Previously, InvokeAI did not distinguish between LoRA/LyCORIS models based on Stable Diffusion v1.5 vs those based on v2.0 and 2.1, leading to a crash when an incompatible model was loaded. This has now been fixed. In addition, the web pulldown menus for LoRA and Textual Inversion selection have been enhanced to show only those files that are compatible with the currently-selected Stable Diffusion model.
Support for the newer LoKR LyCORIS files has been added.
### Library Updates and Speed/Reproducibility Advancements
The major enhancement in this version is that NVIDIA users no longer need to decide between speed and reproducibility. Previously, if you activated the Xformers library, you would see improvements in speed and memory usage, but multiple images generated with the same seed and other parameters would be slightly different from each other. This is no longer the case. Relative to 2.3.5 you will see improved performance when running without Xformers, and even better performance when Xformers is activated. In both cases, images generated with the same settings will be identical.
Here are the new library versions:
Library Version
Torch 2.0.0
Diffusers 0.16.1
Xformers 0.0.19
Compel 1.1.5
Other Improvements
### Performance Improvements
When a model is loaded for the first time, InvokeAI calculates its checksum for incorporation into the PNG metadata. This process could take up to a minute on network-mounted disks and WSL mounts. This release noticeably speeds up the process.
### Bug Fixes
The "import models from directory" and "import from URL" functionality in the console-based model installer has now been fixed.
When running the WebUI, we have reduced the number of times that InvokeAI reaches out to HuggingFace to fetch the list of embeddable Textual Inversion models. We have also caught and fixed a problem with the updater not correctly detecting when another instance of the updater is running
## v2.3.4 <small>(7 April 2023)</small>
What's New in 2.3.4
This features release adds support for LoRA (Low-Rank Adaptation) and LyCORIS (Lora beYond Conventional) models, as well as some minor bug fixes.
### LoRA and LyCORIS Support
LoRA files contain fine-tuning weights that enable particular styles, subjects or concepts to be applied to generated images. LyCORIS files are an extended variant of LoRA. InvokeAI supports the most common LoRA/LyCORIS format, which ends in the suffix .safetensors. You will find numerous LoRA and LyCORIS models for download at Civitai, and a small but growing number at Hugging Face. Full documentation of LoRA support is available at InvokeAI LoRA Support.( Pre-release note: this page will only be available after release)
To use LoRA/LyCORIS models in InvokeAI:
Download the .safetensors files of your choice and place in /path/to/invokeai/loras. This directory was not present in earlier version of InvokeAI but will be created for you the first time you run the command-line or web client. You can also create the directory manually.
Add withLora(lora-file,weight) to your prompts. The weight is optional and will default to 1.0. A few examples, assuming that a LoRA file named loras/sushi.safetensors is present:
family sitting at dinner table eating sushi withLora(sushi,0.9)
family sitting at dinner table eating sushi withLora(sushi, 0.75)
family sitting at dinner table eating sushi withLora(sushi)
Multiple withLora() prompt fragments are allowed. The weight can be arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher weights make the LoRA's influence stronger. Negative weights are also allowed, which can lead to some interesting effects.
Generate as you usually would! If you find that the image is too "crisp" try reducing the overall CFG value or reducing individual LoRA weights. As is the case with all fine-tunes, you'll get the best results when running the LoRA on top of the model similar to, or identical with, the one that was used during the LoRA's training. Don't try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice versa. This will trigger a non-fatal error message and generation will not proceed.
You can change the location of the loras directory by passing the --lora_directory option to `invokeai.
### New WebUI LoRA and Textual Inversion Buttons
This version adds two new web interface buttons for inserting LoRA and Textual Inversion triggers into the prompt as shown in the screenshot below.
Clicking on one or the other of the buttons will bring up a menu of available LoRA/LyCORIS or Textual Inversion trigger terms. Select a menu item to insert the properly-formatted withLora() or <textual-inversion> prompt fragment into the positive prompt. The number in parentheses indicates the number of trigger terms currently in the prompt. You may click the button again and deselect the LoRA or trigger to remove it from the prompt, or simply edit the prompt directly.
Currently terms are inserted into the positive prompt textbox only. However, some textual inversion embeddings are designed to be used with negative prompts. To move a textual inversion trigger into the negative prompt, simply cut and paste it.
By default the Textual Inversion menu only shows locally installed models found at startup time in /path/to/invokeai/embeddings. However, InvokeAI has the ability to dynamically download and install additional Textual Inversion embeddings from the HuggingFace Concepts Library. You may choose to display the most popular of these (with five or more likes) in the Textual Inversion menu by going to Settings and turning on "Show Textual Inversions from HF Concepts Library." When this option is activated, the locally-installed TI embeddings will be shown first, followed by uninstalled terms from Hugging Face. See The Hugging Face Concepts Library and Importing Textual Inversion files for more information.
### Minor features and fixes
This release changes model switching behavior so that the command-line and Web UIs save the last model used and restore it the next time they are launched. It also improves the behavior of the installer so that the pip utility is kept up to date.
### Known Bugs in 2.3.4
These are known bugs in the release.
The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
## v2.3.3 <small>(28 March 2023)</small>
This is a bugfix and minor feature release.
### Bugfixes
Since version 2.3.2 the following bugs have been fixed:
Bugs
When using legacy checkpoints with an external VAE, the VAE file is now scanned for malware prior to loading. Previously only the main model weights file was scanned.
Textual inversion will select an appropriate batchsize based on whether xformers is active, and will default to xformers enabled if the library is detected.
The batch script log file names have been fixed to be compatible with Windows.
Occasional corruption of the .next_prefix file (which stores the next output file name in sequence) on Windows systems is now detected and corrected.
Support loading of legacy config files that have no personalization (textual inversion) section.
An infinite loop when opening the developer's console from within the invoke.sh script has been corrected.
Documentation fixes, including a recipe for detecting and fixing problems with the AMD GPU ROCm driver.
Enhancements
It is now possible to load and run several community-contributed SD-2.0 based models, including the often-requested "Illuminati" model.
The "NegativePrompts" embedding file, and others like it, can now be loaded by placing it in the InvokeAI embeddings directory.
If no --model is specified at launch time, InvokeAI will remember the last model used and restore it the next time it is launched.
On Linux systems, the invoke.sh launcher now uses a prettier console-based interface. To take advantage of it, install the dialog package using your package manager (e.g. sudo apt install dialog).
When loading legacy models (safetensors/ckpt) you can specify a custom config file and/or a VAE by placing like-named files in the same directory as the model following this example:
my-favorite-model.ckpt
my-favorite-model.yaml
my-favorite-model.vae.pt # or my-favorite-model.vae.safetensors
### Known Bugs in 2.3.3
These are known bugs in the release.
The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
## v2.3.2 <small>(11 March 2023)</small>
This is a bugfix and minor feature release.
### Bugfixes
Since version 2.3.1 the following bugs have been fixed:
Black images appearing for potential NSFW images when generating with legacy checkpoint models and both --no-nsfw_checker and --ckpt_convert turned on.
Black images appearing when generating from models fine-tuned on Stable-Diffusion-2-1-base. When importing V2-derived models, you may be asked to select whether the model was derived from a "base" model (512 pixels) or the 768-pixel SD-2.1 model.
The "Use All" button was not restoring the Hi-Res Fix setting on the WebUI
When using the model installer console app, models failed to import correctly when importing from directories with spaces in their names. A similar issue with the output directory was also fixed.
Crashes that occurred during model merging.
Restore previous naming of Stable Diffusion base and 768 models.
Upgraded to latest versions of diffusers, transformers, safetensors and accelerate libraries upstream. We hope that this will fix the assertion NDArray > 2**32 issue that MacOS users have had when generating images larger than 768x768 pixels. Please report back.
As part of the upgrade to diffusers, the location of the diffusers-based models has changed from models/diffusers to models/hub. When you launch InvokeAI for the first time, it will prompt you to OK a one-time move. This should be quick and harmless, but if you have modified your models/diffusers directory in some way, for example using symlinks, you may wish to cancel the migration and make appropriate adjustments.
New "Invokeai-batch" script
### Invoke AI Batch
2.3.2 introduces a new command-line only script called invokeai-batch that can be used to generate hundreds of images from prompts and settings that vary systematically. This can be used to try the same prompt across multiple combinations of models, steps, CFG settings and so forth. It also allows you to template prompts and generate a combinatorial list like:
a shack in the mountains, photograph
a shack in the mountains, watercolor
a shack in the mountains, oil painting
a chalet in the mountains, photograph
a chalet in the mountains, watercolor
a chalet in the mountains, oil painting
a shack in the desert, photograph
...
If you have a system with multiple GPUs, or a single GPU with lots of VRAM, you can parallelize generation across the combinatorial set, reducing wait times and using your system's resources efficiently (make sure you have good GPU cooling).
To try invokeai-batch out. Launch the "developer's console" using the invoke launcher script, or activate the invokeai virtual environment manually. From the console, give the command invokeai-batch --help in order to learn how the script works and create your first template file for dynamic prompt generation.
### Known Bugs in 2.3.2
These are known bugs in the release.
The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
Windows Defender will sometimes raise a Trojan alert for the codeformer.pth face restoration model. As far as we have been able to determine, this is a false positive and can be safely whitelisted.
## v2.3.1 <small>(22 February 2023)</small>
This is primarily a bugfix release, but it does provide several new features that will improve the user experience.
### Enhanced support for model management
InvokeAI now makes it convenient to add, remove and modify models. You can individually import models that are stored on your local system, scan an entire folder and its subfolders for models and import them automatically, and even directly import models from the internet by providing their download URLs. You also have the option of designating a local folder to scan for new models each time InvokeAI is restarted.
There are three ways of accessing the model management features:
From the WebUI, click on the cube to the right of the model selection menu. This will bring up a form that allows you to import models individually from your local disk or scan a directory for models to import.
Using the Model Installer App
Choose option (5) download and install models from the invoke launcher script to start a new console-based application for model management. You can use this to select from a curated set of starter models, or import checkpoint, safetensors, and diffusers models from a local disk or the internet. The example below shows importing two checkpoint URLs from popular SD sites and a HuggingFace diffusers model using its Repository ID. It also shows how to designate a folder to be scanned at startup time for new models to import.
Command-line users can start this app using the command invokeai-model-install.
Using the Command Line Client (CLI)
The !install_model and !convert_model commands have been enhanced to allow entering of URLs and local directories to scan and import. The first command installs .ckpt and .safetensors files as-is. The second one converts them into the faster diffusers format before installation.
Internally InvokeAI is able to probe the contents of a .ckpt or .safetensors file to distinguish among v1.x, v2.x and inpainting models. This means that you do not need to include "inpaint" in your model names to use an inpainting model. Note that Stable Diffusion v2.x models will be autoconverted into a diffusers model the first time you use it.
Please see INSTALLING MODELS for more information on model management.
### An Improved Installer Experience
The installer now launches a console-based UI for setting and changing commonly-used startup options:
After selecting the desired options, the installer installs several support models needed by InvokeAI's face reconstruction and upscaling features and then launches the interface for selecting and installing models shown earlier. At any time, you can edit the startup options by launching invoke.sh/invoke.bat and entering option (6) change InvokeAI startup options
Command-line users can launch the new configure app using invokeai-configure.
This release also comes with a renewed updater. To do an update without going through a whole reinstallation, launch invoke.sh or invoke.bat and choose option (9) update InvokeAI . This will bring you to a screen that prompts you to update to the latest released version, to the most current development version, or any released or unreleased version you choose by selecting the tag or branch of the desired version.
Command-line users can run this interface by typing invokeai-configure
### Image Symmetry Options
There are now features to generate horizontal and vertical symmetry during generation. The way these work is to wait until a selected step in the generation process and then to turn on a mirror image effect. In addition to generating some cool images, you can also use this to make side-by-side comparisons of how an image will look with more or fewer steps. Access this option from the WebUI by selecting Symmetry from the image generation settings, or within the CLI by using the options --h_symmetry_time_pct and --v_symmetry_time_pct (these can be abbreviated to --h_sym and --v_sym like all other options).
### A New Unified Canvas Look
This release introduces a beta version of the WebUI Unified Canvas. To try it out, open up the settings dialogue in the WebUI (gear icon) and select Use Canvas Beta Layout:
Refresh the screen and go to to Unified Canvas (left side of screen, third icon from the top). The new layout is designed to provide more space to work in and to keep the image controls close to the image itself:
Model conversion and merging within the WebUI
The WebUI now has an intuitive interface for model merging, as well as for permanent conversion of models from legacy .ckpt/.safetensors formats into diffusers format. These options are also available directly from the invoke.sh/invoke.bat scripts.
An easier way to contribute translations to the WebUI
We have migrated our translation efforts to Weblate, a FOSS translation product. Maintaining the growing project's translations is now far simpler for the maintainers and community. Please review our brief translation guide for more information on how to contribute.
Numerous internal bugfixes and performance issues
### Bug Fixes
This releases quashes multiple bugs that were reported in 2.3.0. Major internal changes include upgrading to diffusers 0.13.0, and using the compel library for prompt parsing. See Detailed Change Log for a detailed list of bugs caught and squished.
Summary of InvokeAI command line scripts (all accessible via the launcher menu)
Command Description
invokeai Command line interface
invokeai --web Web interface
invokeai-model-install Model installer with console forms-based front end
invokeai-ti --gui Textual inversion, with a console forms-based front end
invokeai-merge --gui Model merging, with a console forms-based front end
invokeai-configure Startup configuration; can also be used to reinstall support models
invokeai-update InvokeAI software updater
### Known Bugs in 2.3.1
These are known bugs in the release.
MacOS users generating 768x768 pixel images or greater using diffusers models may experience a hard crash with assertion NDArray > 2**32 This appears to be an issu...
## v2.3.0 <small>(15 January 2023)</small>
**Transition to diffusers
@ -488,13 +258,13 @@ sections describe what's new for InvokeAI.
- A choice of installer scripts that automate installation and configuration.
See
[Installation](installation/INSTALLATION.md).
[Installation](installation/index.md).
- A streamlined manual installation process that works for both Conda and
PIP-only installs. See
[Manual Installation](installation/020_INSTALL_MANUAL.md).
- The ability to save frequently-used startup options (model to load, steps,
sampler, etc) in a `.invokeai` file. See
[Client](deprecated/CLI.md)
[Client](features/CLI.md)
- Support for AMD GPU cards (non-CUDA) on Linux machines.
- Multiple bugs and edge cases squashed.
@ -617,6 +387,8 @@ sections describe what's new for InvokeAI.
- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains for
backward compatibility.
- Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
- Support for [inpainting](features/INPAINTING.md) and
[outpainting](features/OUTPAINTING.md)
- img2img runs on all k\* samplers
- Support for
[negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
@ -627,7 +399,7 @@ sections describe what's new for InvokeAI.
using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E
infinite canvas), and "embiggen" upscaling. See the `!fix` command.
- New `--hires` option on `invoke>` line allows
[larger images to be created without duplicating elements](deprecated/CLI.md#this-is-an-example-of-txt2img),
[larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img),
at the cost of some performance.
- New `--perlin` and `--threshold` options allow you to add and control
variation during image generation (see
@ -636,7 +408,7 @@ sections describe what's new for InvokeAI.
of images and tweaking of previous settings.
- Command-line completion in `invoke.py` now works on Windows, Linux and Mac
platforms.
- Improved [command-line completion behavior](deprecated/CLI.md) New commands
- Improved [command-line completion behavior](features/CLI.md) New commands
added:
- List command-line history with `!history`
- Search command-line history with `!search`
@ -657,7 +429,7 @@ sections describe what's new for InvokeAI.
## v1.13 <small>(3 September 2022)</small>
- Support image variations (see [VARIATIONS](deprecated/VARIATIONS.md)
- Support image variations (see [VARIATIONS](features/VARIATIONS.md)
([Kevin Gibbons](https://github.com/bakkot) and many contributors and
reviewers)
- Supports a Google Colab notebook for a standalone server running on Google

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@ -1,173 +0,0 @@
# Release Process
The app is published in twice, in different build formats.
- A [PyPI] distribution. This includes both a source distribution and built distribution (a wheel). Users install with `pip install invokeai`. The updater uses this build.
- An installer on the [InvokeAI Releases Page]. This is a zip file with install scripts and a wheel. This is only used for new installs.
## General Prep
Make a developer call-out for PRs to merge. Merge and test things out.
While the release workflow does not include end-to-end tests, it does pause before publishing so you can download and test the final build.
## Release Workflow
The `release.yml` workflow runs a number of jobs to handle code checks, tests, build and publish on PyPI.
It is triggered on **tag push**, when the tag matches `v*`. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
> Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch. So long as the tag exists, that commit will exist.
### Triggering the Workflow
Run `make tag-release` to tag the current commit and kick off the workflow.
The release may also be dispatched [manually].
### Workflow Jobs and Process
The workflow consists of a number of concurrently-run jobs, and two final publish jobs.
The publish jobs require manual approval and are only run if the other jobs succeed.
#### `check-version` Job
This job checks that the git ref matches the app version. It matches the ref against the `__version__` variable in `invokeai/version/invokeai_version.py`.
When the workflow is triggered by tag push, the ref is the tag. If the workflow is run manually, the ref is the target selected from the **Use workflow from** dropdown.
This job uses [samuelcolvin/check-python-version].
> Any valid [version specifier] works, so long as the tag matches the version. The release workflow works exactly the same for `RC`, `post`, `dev`, etc.
#### Check and Test Jobs
- **`python-tests`**: runs `pytest` on matrix of platforms
- **`python-checks`**: runs `ruff` (format and lint)
- **`frontend-tests`**: runs `vitest`
- **`frontend-checks`**: runs `prettier` (format), `eslint` (lint), `dpdm` (circular refs), `tsc` (static type check) and `knip` (unused imports)
> **TODO** We should add `mypy` or `pyright` to the **`check-python`** job.
> **TODO** We should add an end-to-end test job that generates an image.
#### `build-installer` Job
This sets up both python and frontend dependencies and builds the python package. Internally, this runs `installer/create_installer.sh` and uploads two artifacts:
- **`dist`**: the python distribution, to be published on PyPI
- **`InvokeAI-installer-${VERSION}.zip`**: the installer to be included in the GitHub release
#### Sanity Check & Smoke Test
At this point, the release workflow pauses as the remaining publish jobs require approval. Time to test the installer.
Because the installer pulls from PyPI, and we haven't published to PyPI yet, you will need to install from the wheel:
- Download and unzip `dist.zip` and the installer from the **Summary** tab of the workflow
- Run the installer script using the `--wheel` CLI arg, pointing at the wheel:
```sh
./install.sh --wheel ../InvokeAI-4.0.0rc6-py3-none-any.whl
```
- Install to a temporary directory so you get the new user experience
- Download a model and generate
> The same wheel file is bundled in the installer and in the `dist` artifact, which is uploaded to PyPI. You should end up with the exactly the same installation as if the installer got the wheel from PyPI.
##### Something isn't right
If testing reveals any issues, no worries. Cancel the workflow, which will cancel the pending publish jobs (you didn't approve them prematurely, right?).
Now you can start from the top:
- Fix the issues and PR the fixes per usual
- Get the PR approved and merged per usual
- Switch to `main` and pull in the fixes
- Run `make tag-release` to move the tag to `HEAD` (which has the fixes) and kick off the release workflow again
- Re-do the sanity check
#### PyPI Publish Jobs
The publish jobs will run if any of the previous jobs fail.
They use [GitHub environments], which are configured as [trusted publishers] on PyPI.
Both jobs require a maintainer to approve them from the workflow's **Summary** tab.
- Click the **Review deployments** button
- Select the environment (either `testpypi` or `pypi`)
- Click **Approve and deploy**
> **If the version already exists on PyPI, the publish jobs will fail.** PyPI only allows a given version to be published once - you cannot change it. If version published on PyPI has a problem, you'll need to "fail forward" by bumping the app version and publishing a followup release.
##### Failing PyPI Publish
Check the [python infrastructure status page] for incidents.
If there are no incidents, contact @hipsterusername or @lstein, who have owner access to GH and PyPI, to see if access has expired or something like that.
#### `publish-testpypi` Job
Publishes the distribution on the [Test PyPI] index, using the `testpypi` GitHub environment.
This job is not required for the production PyPI publish, but included just in case you want to test the PyPI release.
If approved and successful, you could try out the test release like this:
```sh
# Create a new virtual environment
python -m venv ~/.test-invokeai-dist --prompt test-invokeai-dist
# Install the distribution from Test PyPI
pip install --index-url https://test.pypi.org/simple/ invokeai
# Run and test the app
invokeai-web
# Cleanup
deactivate
rm -rf ~/.test-invokeai-dist
```
#### `publish-pypi` Job
Publishes the distribution on the production PyPI index, using the `pypi` GitHub environment.
## Publish the GitHub Release with installer
Once the release is published to PyPI, it's time to publish the GitHub release.
1. [Draft a new release] on GitHub, choosing the tag that triggered the release.
1. Write the release notes, describing important changes. The **Generate release notes** button automatically inserts the changelog and new contributors, and you can copy/paste the intro from previous releases.
1. Use `scripts/get_external_contributions.py` to get a list of external contributions to shout out in the release notes.
1. Upload the zip file created in **`build`** job into the Assets section of the release notes.
1. Check **Set as a pre-release** if it's a pre-release.
1. Check **Create a discussion for this release**.
1. Publish the release.
1. Announce the release in Discord.
> **TODO** Workflows can create a GitHub release from a template and upload release assets. One popular action to handle this is [ncipollo/release-action]. A future enhancement to the release process could set this up.
## Manual Build
The `build installer` workflow can be dispatched manually. This is useful to test the installer for a given branch or tag.
No checks are run, it just builds.
## Manual Release
The `release` workflow can be dispatched manually. You must dispatch the workflow from the right tag, else it will fail the version check.
This functionality is available as a fallback in case something goes wonky. Typically, releases should be triggered via tag push as described above.
[InvokeAI Releases Page]: https://github.com/invoke-ai/InvokeAI/releases
[PyPI]: https://pypi.org/
[Draft a new release]: https://github.com/invoke-ai/InvokeAI/releases/new
[Test PyPI]: https://test.pypi.org/
[version specifier]: https://packaging.python.org/en/latest/specifications/version-specifiers/
[ncipollo/release-action]: https://github.com/ncipollo/release-action
[GitHub environments]: https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment
[trusted publishers]: https://docs.pypi.org/trusted-publishers/
[samuelcolvin/check-python-version]: https://github.com/samuelcolvin/check-python-version
[manually]: #manual-release
[python infrastructure status page]: https://status.python.org/

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# Contributing
Invoke AI originated as a project built by the community, and that vision carries forward today as we aim to build the best pro-grade tools available. We work together to incorporate the latest in AI/ML research, making these tools available in over 20 languages to artists and creatives around the world as part of our fully permissive OSS project designed for individual users to self-host and use.
# Methods of Contributing to Invoke AI
Anyone who wishes to contribute to InvokeAI, whether features, bug fixes, code cleanup, testing, code reviews, documentation or translation is very much encouraged to do so.
## Development
If youd like to help with development, please see our [development guide](contribution_guides/development.md).
**New Contributors:** If youre unfamiliar with contributing to open source projects, take a look at our [new contributor guide](contribution_guides/newContributorChecklist.md).
## Nodes
If youd like to add a Node, please see our [nodes contribution guide](../nodes/contributingNodes.md).
## Support and Triaging
Helping support other users in [Discord](https://discord.gg/ZmtBAhwWhy) and on Github are valuable forms of contribution that we greatly appreciate.
We receive many issues and requests for help from users. We're limited in bandwidth relative to our the user base, so providing answers to questions or helping identify causes of issues is very helpful. By doing this, you enable us to spend time on the highest priority work.
## Documentation
If youd like to help with documentation, please see our [documentation guide](contribution_guides/documentation.md).
## Translation
If you'd like to help with translation, please see our [translation guide](contribution_guides/translation.md).
## Tutorials
Please reach out to @imic or @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.
We hope you enjoy using our software as much as we enjoy creating it, and we hope that some of those of you who are reading this will elect to become part of our contributor community.
# Contributors
This project is a combined effort of dedicated people from across the world. [Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for their time, hard work and effort.
# Code of Conduct
The InvokeAI community is a welcoming place, and we want your help in maintaining that. Please review our [Code of Conduct](https://github.com/invoke-ai/InvokeAI/blob/main/CODE_OF_CONDUCT.md) to learn more - it's essential to maintaining a respectful and inclusive environment.
By making a contribution to this project, you certify that:
1. The contribution was created in whole or in part by you and you have the right to submit it under the open-source license indicated in this projects GitHub repository; or
2. The contribution is based upon previous work that, to the best of your knowledge, is covered under an appropriate open-source license and you have the right under that license to submit that work with modifications, whether created in whole or in part by you, under the same open-source license (unless you are permitted to submit under a different license); or
3. The contribution was provided directly to you by some other person who certified (1) or (2) and you have not modified it; or
4. You understand and agree that this project and the contribution are public and that a record of the contribution (including all personal information you submit with it, including your sign-off) is maintained indefinitely and may be redistributed consistent with this project or the open-source license(s) involved.
This disclaimer is not a license and does not grant any rights or permissions. You must obtain necessary permissions and licenses, including from third parties, before contributing to this project.
This disclaimer is provided "as is" without warranty of any kind, whether expressed or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, or non-infringement. In no event shall the authors or copyright holders be liable for any claim, damages, or other liability, whether in an action of contract, tort, or otherwise, arising from, out of, or in connection with the contribution or the use or other dealings in the contribution.
# Support
For support, please use this repository's [GitHub Issues](https://github.com/invoke-ai/InvokeAI/issues), or join the [Discord](https://discord.gg/ZmtBAhwWhy).
Original portions of the software are Copyright (c) 2023 by respective contributors.
---
Remember, your contributions help make this project great. We're excited to see what you'll bring to our community!

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# The InvokeAI Download Queue
The DownloadQueueService provides a multithreaded parallel download
queue for arbitrary URLs, with queue prioritization, event handling,
and restart capabilities.
## Simple Example
```
from invokeai.app.services.download import DownloadQueueService, TqdmProgress
download_queue = DownloadQueueService()
for url in ['https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true',
'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true',
'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png',
'https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor',
]:
# urls start downloading as soon as download() is called
download_queue.download(source=url,
dest='/tmp/downloads',
on_progress=TqdmProgress().update
)
download_queue.join() # wait for all downloads to finish
for job in download_queue.list_jobs():
print(job.model_dump_json(exclude_none=True, indent=4),"\n")
```
Output:
```
{
"source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true",
"dest": "/tmp/downloads",
"id": 0,
"priority": 10,
"status": "completed",
"download_path": "/tmp/downloads/a-painting-of-a-fire.png",
"job_started": "2023-12-04T05:34:41.742174",
"job_ended": "2023-12-04T05:34:42.592035",
"bytes": 666734,
"total_bytes": 666734
}
{
"source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true",
"dest": "/tmp/downloads",
"id": 1,
"priority": 10,
"status": "completed",
"download_path": "/tmp/downloads/birdhouse.png",
"job_started": "2023-12-04T05:34:41.741975",
"job_ended": "2023-12-04T05:34:42.652841",
"bytes": 774949,
"total_bytes": 774949
}
{
"source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png",
"dest": "/tmp/downloads",
"id": 2,
"priority": 10,
"status": "error",
"job_started": "2023-12-04T05:34:41.742079",
"job_ended": "2023-12-04T05:34:42.147625",
"bytes": 0,
"total_bytes": 0,
"error_type": "HTTPError(Not Found)",
"error": "Traceback (most recent call last):\n File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 182, in _download_next_item\n self._do_download(job)\n File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 206, in _do_download\n raise HTTPError(resp.reason)\nrequests.exceptions.HTTPError: Not Found\n"
}
{
"source": "https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor",
"dest": "/tmp/downloads",
"id": 3,
"priority": 10,
"status": "completed",
"download_path": "/tmp/downloads/xl_more_art-full_v1.safetensors",
"job_started": "2023-12-04T05:34:42.147645",
"job_ended": "2023-12-04T05:34:43.735990",
"bytes": 719020768,
"total_bytes": 719020768
}
```
## The API
The default download queue is `DownloadQueueService`, an
implementation of ABC `DownloadQueueServiceBase`. It juggles multiple
background download requests and provides facilities for interrogating
and cancelling the requests. Access to a current or past download task
is mediated via `DownloadJob` objects which report the current status
of a job request
### The Queue Object
A default download queue is located in
`ApiDependencies.invoker.services.download_queue`. However, you can
create additional instances if you need to isolate your queue from the
main one.
```
queue = DownloadQueueService(event_bus=events)
```
`DownloadQueueService()` takes three optional arguments:
| **Argument** | **Type** | **Default** | **Description** |
|----------------|-----------------|---------------|-----------------|
| `max_parallel_dl` | int | 5 | Maximum number of simultaneous downloads allowed |
| `event_bus` | EventServiceBase | None | System-wide FastAPI event bus for reporting download events |
| `requests_session` | requests.sessions.Session | None | An alternative requests Session object to use for the download |
`max_parallel_dl` specifies how many download jobs are allowed to run
simultaneously. Each will run in a different thread of execution.
`event_bus` is an EventServiceBase, typically the one created at
InvokeAI startup. If present, download events are periodically emitted
on this bus to allow clients to follow download progress.
`requests_session` is a url library requests Session object. It is
used for testing.
### The Job object
The queue operates on a series of download job objects. These objects
specify the source and destination of the download, and keep track of
the progress of the download.
The only job type currently implemented is `DownloadJob`, a pydantic object with the
following fields:
| **Field** | **Type** | **Default** | **Description** |
|----------------|-----------------|---------------|-----------------|
| _Fields passed in at job creation time_ |
| `source` | AnyHttpUrl | | Where to download from |
| `dest` | Path | | Where to download to |
| `access_token` | str | | [optional] string containing authentication token for access |
| `on_start` | Callable | | [optional] callback when the download starts |
| `on_progress` | Callable | | [optional] callback called at intervals during download progress |
| `on_complete` | Callable | | [optional] callback called after successful download completion |
| `on_error` | Callable | | [optional] callback called after an error occurs |
| `id` | int | auto assigned | Job ID, an integer >= 0 |
| `priority` | int | 10 | Job priority. Lower priorities run before higher priorities |
| |
| _Fields updated over the course of the download task_
| `status` | DownloadJobStatus| | Status code |
| `download_path` | Path | | Path to the location of the downloaded file |
| `job_started` | float | | Timestamp for when the job started running |
| `job_ended` | float | | Timestamp for when the job completed or errored out |
| `job_sequence` | int | | A counter that is incremented each time a model is dequeued |
| `bytes` | int | 0 | Bytes downloaded so far |
| `total_bytes` | int | 0 | Total size of the file at the remote site |
| `error_type` | str | | String version of the exception that caused an error during download |
| `error` | str | | String version of the traceback associated with an error |
| `cancelled` | bool | False | Set to true if the job was cancelled by the caller|
When you create a job, you can assign it a `priority`. If multiple
jobs are queued, the job with the lowest priority runs first.
Every job has a `source` and a `dest`. `source` is a pydantic.networks AnyHttpUrl object.
The `dest` is a path on the local filesystem that specifies the
destination for the downloaded object. Its semantics are
described below.
When the job is submitted, it is assigned a numeric `id`. The id can
then be used to fetch the job object from the queue.
The `status` field is updated by the queue to indicate where the job
is in its lifecycle. Values are defined in the string enum
`DownloadJobStatus`, a symbol available from
`invokeai.app.services.download_manager`. Possible values are:
| **Value** | **String Value** | ** Description ** |
|--------------|---------------------|-------------------|
| `WAITING` | waiting | Job is on the queue but not yet running|
| `RUNNING` | running | The download is started |
| `COMPLETED` | completed | Job has finished its work without an error |
| `ERROR` | error | Job encountered an error and will not run again|
`job_started` and `job_ended` indicate when the job
was started (using a python timestamp) and when it completed.
In case of an error, the job's status will be set to `DownloadJobStatus.ERROR`, the text of the
Exception that caused the error will be placed in the `error_type`
field and the traceback that led to the error will be in `error`.
A cancelled job will have status `DownloadJobStatus.ERROR` and an
`error_type` field of "DownloadJobCancelledException". In addition,
the job's `cancelled` property will be set to True.
### Callbacks
Download jobs can be associated with a series of callbacks, each with
the signature `Callable[["DownloadJob"], None]`. The callbacks are assigned
using optional arguments `on_start`, `on_progress`, `on_complete` and
`on_error`. When the corresponding event occurs, the callback wil be
invoked and passed the job. The callback will be run in a `try:`
context in the same thread as the download job. Any exceptions that
occur during execution of the callback will be caught and converted
into a log error message, thereby allowing the download to continue.
#### `TqdmProgress`
The `invokeai.app.services.download.download_default` module defines a
class named `TqdmProgress` which can be used as an `on_progress`
handler to display a completion bar in the console. Use as follows:
```
from invokeai.app.services.download import TqdmProgress
download_queue.download(source='http://some.server.somewhere/some_file',
dest='/tmp/downloads',
on_progress=TqdmProgress().update
)
```
### Events
If the queue was initialized with the InvokeAI event bus (the case
when using `ApiDependencies.invoker.services.download_queue`), then
download events will also be issued on the bus. The events are:
* `download_started` -- This is issued when a job is taken off the
queue and a request is made to the remote server for the URL headers, but before any data
has been downloaded. The event payload will contain the keys `source`
and `download_path`. The latter contains the path that the URL will be
downloaded to.
* `download_progress -- This is issued periodically as the download
runs. The payload contains the keys `source`, `download_path`,
`current_bytes` and `total_bytes`. The latter two fields can be
used to display the percent complete.
* `download_complete` -- This is issued when the download completes
successfully. The payload contains the keys `source`, `download_path`
and `total_bytes`.
* `download_error` -- This is issued when the download stops because
of an error condition. The payload contains the fields `error_type`
and `error`. The former is the text representation of the exception,
and the latter is a traceback showing where the error occurred.
### Job control
To create a job call the queue's `download()` method. You can list all
jobs using `list_jobs()`, fetch a single job by its with
`id_to_job()`, cancel a running job with `cancel_job()`, cancel all
running jobs with `cancel_all_jobs()`, and wait for all jobs to finish
with `join()`.
#### job = queue.download(source, dest, priority, access_token)
Create a new download job and put it on the queue, returning the
DownloadJob object.
#### jobs = queue.list_jobs()
Return a list of all active and inactive `DownloadJob`s.
#### job = queue.id_to_job(id)
Return the job corresponding to given ID.
Return a list of all active and inactive `DownloadJob`s.
#### queue.prune_jobs()
Remove inactive (complete or errored) jobs from the listing returned
by `list_jobs()`.
#### queue.join()
Block until all pending jobs have run to completion or errored out.

View File

@ -1,395 +1,105 @@
# Nodes
# Invocations
Features in InvokeAI are added in the form of modular nodes systems called
**Invocations**.
Invocations represent a single operation, its inputs, and its outputs. These operations and their outputs can be chained together to generate and modify images.
An Invocation is simply a single operation that takes in some inputs and gives
out some outputs. We can then chain multiple Invocations together to create more
complex functionality.
## Creating a new invocation
## Invocations Directory
To create a new invocation, either find the appropriate module file in `/ldm/invoke/app/invocations` to add your invocation to, or create a new one in that folder. All invocations in that folder will be discovered and made available to the CLI and API automatically. Invocations make use of [typing](https://docs.python.org/3/library/typing.html) and [pydantic](https://pydantic-docs.helpmanual.io/) for validation and integration into the CLI and API.
InvokeAI Nodes can be found in the `invokeai/app/invocations` directory. These
can be used as examples to create your own nodes.
New nodes should be added to a subfolder in `nodes` direction found at the root
level of the InvokeAI installation location. Nodes added to this folder will be
able to be used upon application startup.
Example `nodes` subfolder structure:
An invocation looks like this:
```py
├── __init__.py # Invoke-managed custom node loader
├── cool_node
├── __init__.py # see example below
└── cool_node.py
└── my_node_pack
├── __init__.py # see example below
├── tasty_node.py
├── bodacious_node.py
├── utils.py
└── extra_nodes
└── fancy_node.py
```
Each node folder must have an `__init__.py` file that imports its nodes. Only
nodes imported in the `__init__.py` file are loaded. See the README in the nodes
folder for more examples:
```py
from .cool_node import CoolInvocation
```
## Creating A New Invocation
In order to understand the process of creating a new Invocation, let us actually
create one.
In our example, let us create an Invocation that will take in an image, resize
it and output the resized image.
The first set of things we need to do when creating a new Invocation are -
- Create a new class that derives from a predefined parent class called
`BaseInvocation`.
- Every Invocation must have a `docstring` that describes what this Invocation
does.
- While not strictly required, we suggest every invocation class name ends in
"Invocation", eg "CropImageInvocation".
- Every Invocation must use the `@invocation` decorator to provide its unique
invocation type. You may also provide its title, tags and category using the
decorator.
- Invocations are strictly typed. We make use of the native
[typing](https://docs.python.org/3/library/typing.html) library and the
installed [pydantic](https://pydantic-docs.helpmanual.io/) library for
validation.
So let us do that.
```python
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
@invocation('resize')
class ResizeInvocation(BaseInvocation):
'''Resizes an image'''
```
That's great.
Now we have setup the base of our new Invocation. Let us think about what inputs
our Invocation takes.
- We need an `image` that we are going to resize.
- We will need new `width` and `height` values to which we need to resize the
image to.
### **Inputs**
Every Invocation input must be defined using the `InputField` function. This is
a wrapper around the pydantic `Field` function, which handles a few extra things
and provides type hints. Like everything else, this should be strictly typed and
defined.
So let us create these inputs for our Invocation. First up, the `image` input we
need. Generally, we can use standard variable types in Python but InvokeAI
already has a custom `ImageField` type that handles all the stuff that is needed
for image inputs.
But what is this `ImageField` ..? It is a special class type specifically
written to handle how images are dealt with in InvokeAI. We will cover how to
create your own custom field types later in this guide. For now, let's go ahead
and use it.
```python
from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation
from invokeai.app.invocations.primitives import ImageField
@invocation('resize')
class ResizeInvocation(BaseInvocation):
class UpscaleInvocation(BaseInvocation):
"""Upscales an image."""
type: Literal['upscale'] = 'upscale'
# Inputs
image: ImageField = InputField(description="The input image")
```
Let us break down our input code.
```python
image: ImageField = InputField(description="The input image")
```
| Part | Value | Description |
| --------- | ------------------------------------------- | ------------------------------------------------------------------------------- |
| Name | `image` | The variable that will hold our image |
| Type Hint | `ImageField` | The types for our field. Indicates that the image must be an `ImageField` type. |
| Field | `InputField(description="The input image")` | The image variable is an `InputField` which needs a description. |
Great. Now let us create our other inputs for `width` and `height`
```python
from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation
from invokeai.app.invocations.primitives import ImageField
@invocation('resize')
class ResizeInvocation(BaseInvocation):
'''Resizes an image'''
image: ImageField = InputField(description="The input image")
width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
```
As you might have noticed, we added two new arguments to the `InputField`
definition for `width` and `height`, called `gt` and `le`. They stand for
_greater than or equal to_ and _less than or equal to_.
These impose contraints on those fields, and will raise an exception if the
values do not meet the constraints. Field constraints are provided by
**pydantic**, so anything you see in the **pydantic docs** will work.
**Note:** _Any time it is possible to define constraints for our field, we
should do it so the frontend has more information on how to parse this field._
Perfect. We now have our inputs. Let us do something with these.
### **Invoke Function**
The `invoke` function is where all the magic happens. This function provides you
the `context` parameter that is of the type `InvocationContext` which will give
you access to the current context of the generation and all the other services
that are provided by it by InvokeAI.
Let us create this function first.
```python
from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation, InvocationContext
from invokeai.app.invocations.primitives import ImageField
@invocation('resize')
class ResizeInvocation(BaseInvocation):
'''Resizes an image'''
image: ImageField = InputField(description="The input image")
width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
def invoke(self, context: InvocationContext):
pass
```
### **Outputs**
The output of our Invocation will be whatever is returned by this `invoke`
function. Like with our inputs, we need to strongly type and define our outputs
too.
What is our output going to be? Another image. Normally you'd have to create a
type for this but InvokeAI already offers you an `ImageOutput` type that handles
all the necessary info related to image outputs. So let us use that.
We will cover how to create your own output types later in this guide.
```python
from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation, InvocationContext
from invokeai.app.invocations.primitives import ImageField
from invokeai.app.invocations.image import ImageOutput
@invocation('resize')
class ResizeInvocation(BaseInvocation):
'''Resizes an image'''
image: ImageField = InputField(description="The input image")
width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
image: Union[ImageField,None] = Field(description="The input image")
strength: float = Field(default=0.75, gt=0, le=1, description="The strength")
level: Literal[2,4] = Field(default=2, description = "The upscale level")
def invoke(self, context: InvocationContext) -> ImageOutput:
pass
image = context.services.images.get(self.image.image_type, self.image.image_name)
results = context.services.generate.upscale_and_reconstruct(
image_list = [[image, 0]],
upscale = (self.level, self.strength),
strength = 0.0, # GFPGAN strength
save_original = False,
image_callback = None,
)
# Results are image and seed, unwrap for now
# TODO: can this return multiple results?
image_type = ImageType.RESULT
image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
context.services.images.save(image_type, image_name, results[0][0])
return ImageOutput(
image = ImageField(image_type = image_type, image_name = image_name)
)
```
Perfect. Now that we have our Invocation setup, let us do what we want to do.
Each portion is important to implement correctly.
- We will first load the image using one of the services provided by InvokeAI to
load the image.
- We will resize the image using `PIL` to our input data.
- We will output this image in the format we set above.
### Class definition and type
```py
class UpscaleInvocation(BaseInvocation):
"""Upscales an image."""
type: Literal['upscale'] = 'upscale'
```
All invocations must derive from `BaseInvocation`. They should have a docstring that declares what they do in a single, short line. They should also have a `type` with a type hint that's `Literal["command_name"]`, where `command_name` is what the user will type on the CLI or use in the API to create this invocation. The `command_name` must be unique. The `type` must be assigned to the value of the literal in the type hint.
So let's do that.
### Inputs
```py
# Inputs
image: Union[ImageField,None] = Field(description="The input image")
strength: float = Field(default=0.75, gt=0, le=1, description="The strength")
level: Literal[2,4] = Field(default=2, description="The upscale level")
```
Inputs consist of three parts: a name, a type hint, and a `Field` with default, description, and validation information. For example:
| Part | Value | Description |
| ---- | ----- | ----------- |
| Name | `strength` | This field is referred to as `strength` |
| Type Hint | `float` | This field must be of type `float` |
| Field | `Field(default=0.75, gt=0, le=1, description="The strength")` | The default value is `0.75`, the value must be in the range (0,1], and help text will show "The strength" for this field. |
```python
from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation, InvocationContext
from invokeai.app.invocations.primitives import ImageField
from invokeai.app.invocations.image import ImageOutput, ResourceOrigin, ImageCategory
Notice that `image` has type `Union[ImageField,None]`. The `Union` allows this field to be parsed with `None` as a value, which enables linking to previous invocations. All fields should either provide a default value or allow `None` as a value, so that they can be overwritten with a linked output from another invocation.
@invocation("resize")
class ResizeInvocation(BaseInvocation):
"""Resizes an image"""
The special type `ImageField` is also used here. All images are passed as `ImageField`, which protects them from pydantic validation errors (since images only ever come from links).
image: ImageField = InputField(description="The input image")
width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
Finally, note that for all linking, the `type` of the linked fields must match. If the `name` also matches, then the field can be **automatically linked** to a previous invocation by name and matching.
### Invoke Function
```py
def invoke(self, context: InvocationContext) -> ImageOutput:
# Load the input image as a PIL image
image = context.images.get_pil(self.image.image_name)
image = context.services.images.get(self.image.image_type, self.image.image_name)
results = context.services.generate.upscale_and_reconstruct(
image_list = [[image, 0]],
upscale = (self.level, self.strength),
strength = 0.0, # GFPGAN strength
save_original = False,
image_callback = None,
)
# Resize the image
resized_image = image.resize((self.width, self.height))
# Save the image
image_dto = context.images.save(image=resized_image)
# Return an ImageOutput
return ImageOutput.build(image_dto)
# Results are image and seed, unwrap for now
image_type = ImageType.RESULT
image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
context.services.images.save(image_type, image_name, results[0][0])
return ImageOutput(
image = ImageField(image_type = image_type, image_name = image_name)
)
```
The `invoke` function is the last portion of an invocation. It is provided an `InvocationContext` which contains services to perform work as well as a `session_id` for use as needed. It should return a class with output values that derives from `BaseInvocationOutput`.
**Note:** Do not be overwhelmed by the `ImageOutput` process. InvokeAI has a
certain way that the images need to be dispatched in order to be stored and read
correctly. In 99% of the cases when dealing with an image output, you can simply
copy-paste the template above.
Before being called, the invocation will have all of its fields set from defaults, inputs, and finally links (overriding in that order).
### Customization
Assume that this invocation may be running simultaneously with other invocations, may be running on another machine, or in other interesting scenarios. If you need functionality, please provide it as a service in the `InvocationServices` class, and make sure it can be overridden.
We can use the `@invocation` decorator to provide some additional info to the
UI, like a custom title, tags and category.
### Outputs
```py
class ImageOutput(BaseInvocationOutput):
"""Base class for invocations that output an image"""
type: Literal['image'] = 'image'
We also encourage providing a version. This must be a
[semver](https://semver.org/) version string ("$MAJOR.$MINOR.$PATCH"). The UI
will let users know if their workflow is using a mismatched version of the node.
```python
@invocation("resize", title="My Resizer", tags=["resize", "image"], category="My Invocations", version="1.0.0")
class ResizeInvocation(BaseInvocation):
"""Resizes an image"""
image: ImageField = InputField(description="The input image")
...
image: ImageField = Field(default=None, description="The output image")
```
That's it. You made your own **Resize Invocation**.
## Result
Once you make your Invocation correctly, the rest of the process is fully
automated for you.
When you launch InvokeAI, you can go to `http://localhost:9090/docs` and see
your new Invocation show up there with all the relevant info.
![resize invocation](../assets/contributing/resize_invocation.png)
When you launch the frontend UI, you can go to the Node Editor tab and find your
new Invocation ready to be used.
![resize node editor](../assets/contributing/resize_node_editor.png)
## Contributing Nodes
Once you've created a Node, the next step is to share it with the community! The
best way to do this is to submit a Pull Request to add the Node to the
[Community Nodes](nodes/communityNodes) list. If you're not sure how to do that,
take a look a at our [contributing nodes overview](contributingNodes).
## Advanced
### Custom Output Types
Like with custom inputs, sometimes you might find yourself needing custom
outputs that InvokeAI does not provide. We can easily set one up.
Now that you are familiar with Invocations and Inputs, let us use that knowledge
to create an output that has an `image` field, a `color` field and a `string`
field.
- An invocation output is a class that derives from the parent class of
`BaseInvocationOutput`.
- All invocation outputs must use the `@invocation_output` decorator to provide
their unique output type.
- Output fields must use the provided `OutputField` function. This is very
similar to the `InputField` function described earlier - it's a wrapper around
`pydantic`'s `Field()`.
- It is not mandatory but we recommend using names ending with `Output` for
output types.
- It is not mandatory but we highly recommend adding a `docstring` to describe
what your output type is for.
Now that we know the basic rules for creating a new output type, let us go ahead
and make it.
```python
from .baseinvocation import BaseInvocationOutput, OutputField, invocation_output
from .primitives import ImageField, ColorField
@invocation_output('image_color_string_output')
class ImageColorStringOutput(BaseInvocationOutput):
'''Base class for nodes that output a single image'''
image: ImageField = OutputField(description="The image")
color: ColorField = OutputField(description="The color")
text: str = OutputField(description="The string")
```
That's all there is to it.
### Custom Input Fields
Now that you know how to create your own Invocations, let us dive into slightly
more advanced topics.
While creating your own Invocations, you might run into a scenario where the
existing fields in InvokeAI do not meet your requirements. In such cases, you
can create your own fields.
Let us create one as an example. Let us say we want to create a color input
field that represents a color code. But before we start on that here are some
general good practices to keep in mind.
### Best Practices
- There is no naming convention for input fields but we highly recommend that
you name it something appropriate like `ColorField`.
- It is not mandatory but it is heavily recommended to add a relevant
`docstring` to describe your field.
- Keep your field in the same file as the Invocation that it is made for or in
another file where it is relevant.
All input types a class that derive from the `BaseModel` type from `pydantic`.
So let's create one.
```python
from pydantic import BaseModel
class ColorField(BaseModel):
'''A field that holds the rgba values of a color'''
pass
```
Perfect. Now let us create the properties for our field. This is similar to how
you created input fields for your Invocation. All the same rules apply. Let us
create four fields representing the _red(r)_, _blue(b)_, _green(g)_ and
_alpha(a)_ channel of the color.
> Technically, the properties are _also_ called fields - but in this case, it
> refers to a `pydantic` field.
```python
class ColorField(BaseModel):
'''A field that holds the rgba values of a color'''
r: int = Field(ge=0, le=255, description="The red channel")
g: int = Field(ge=0, le=255, description="The green channel")
b: int = Field(ge=0, le=255, description="The blue channel")
a: int = Field(ge=0, le=255, description="The alpha channel")
```
That's it. We now have a new input field type that we can use in our Invocations
like this.
```python
color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=0), description='Background color of an image')
```
### Using the custom field
When you start the UI, your custom field will be automatically recognized.
Custom fields only support connection inputs in the Workflow Editor.
Output classes look like an invocation class without the invoke method. Prefer to use an existing output class if available, and prefer to name inputs the same as outputs when possible, to promote automatic invocation linking.

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