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remove all references to CLI

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Lincoln Stein 2023-10-17 12:59:48 -04:00 committed by psychedelicious
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26 changed files with 86 additions and 1059 deletions
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4
docs/CHANGELOG.md
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@ -488,7 +488,7 @@ sections describe what's new for InvokeAI.
- A choice of installer scripts that automate installation and configuration. - A choice of installer scripts that automate installation and configuration.
See See
[Installation](installation/index.md). [Installation](installation/INSTALLATION.md).
- A streamlined manual installation process that works for both Conda and - A streamlined manual installation process that works for both Conda and
PIP-only installs. See PIP-only installs. See
[Manual Installation](installation/020_INSTALL_MANUAL.md). [Manual Installation](installation/020_INSTALL_MANUAL.md).
@ -657,7 +657,7 @@ sections describe what's new for InvokeAI.
## v1.13 <small>(3 September 2022)</small> ## v1.13 <small>(3 September 2022)</small>
- Support image variations (see [VARIATIONS](features/VARIATIONS.md) - Support image variations (see [VARIATIONS](deprecated/VARIATIONS.md)
([Kevin Gibbons](https://github.com/bakkot) and many contributors and ([Kevin Gibbons](https://github.com/bakkot) and many contributors and
reviewers) reviewers)
- Supports a Google Colab notebook for a standalone server running on Google - Supports a Google Colab notebook for a standalone server running on Google

0
CODE_OF_CONDUCT.md → docs/CODE_OF_CONDUCT.md
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2
docs/contributing/contribution_guides/development.md
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@ -45,5 +45,5 @@ For backend related work, please reach out to **@blessedcoolant**, **@lstein**,
## **What does the Code of Conduct mean for me?** ## **What does the Code of Conduct mean for me?**
Our [Code of Conduct](CODE_OF_CONDUCT.md) means that you are responsible for treating everyone on the project with respect and courtesy regardless of their identity. If you are the victim of any inappropriate behavior or comments as described in our Code of Conduct, we are here for you and will do the best to ensure that the abuser is reprimanded appropriately, per our code. Our [Code of Conduct](../../CODE_OF_CONDUCT.md) means that you are responsible for treating everyone on the project with respect and courtesy regardless of their identity. If you are the victim of any inappropriate behavior or comments as described in our Code of Conduct, we are here for you and will do the best to ensure that the abuser is reprimanded appropriately, per our code.

4
docs/deprecated/CLI.md
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@ -211,8 +211,8 @@ Here are the invoke> command that apply to txt2img:
| `--facetool <name>` | `-ft <name>` | `-ft gfpgan` | Select face restoration algorithm to use: gfpgan, codeformer | | `--facetool <name>` | `-ft <name>` | `-ft gfpgan` | Select face restoration algorithm to use: gfpgan, codeformer |
| `--codeformer_fidelity` | `-cf <float>` | `0.75` | Used along with CodeFormer. Takes values between 0 and 1. 0 produces high quality but low accuracy. 1 produces high accuracy but low quality | | `--codeformer_fidelity` | `-cf <float>` | `0.75` | Used along with CodeFormer. Takes values between 0 and 1. 0 produces high quality but low accuracy. 1 produces high accuracy but low quality |
| `--save_original` | `-save_orig` | `False` | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced. | | `--save_original` | `-save_orig` | `False` | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced. |
| `--variation <float>` | `-v<float>` | `0.0` | Add a bit of noise (0.0=none, 1.0=high) to the image in order to generate a series of variations. Usually used in combination with `-S<seed>` and `-n<int>` to generate a series a riffs on a starting image. See [Variations](../features/VARIATIONS.md). | | `--variation <float>` | `-v<float>` | `0.0` | Add a bit of noise (0.0=none, 1.0=high) to the image in order to generate a series of variations. Usually used in combination with `-S<seed>` and `-n<int>` to generate a series a riffs on a starting image. See [Variations](VARIATIONS.md). |
| `--with_variations <pattern>` | | `None` | Combine two or more variations. See [Variations](../features/VARIATIONS.md) for now to use this. | | `--with_variations <pattern>` | | `None` | Combine two or more variations. See [Variations](VARIATIONS.md) for now to use this. |
| `--save_intermediates <n>` | | `None` | Save the image from every nth step into an "intermediates" folder inside the output directory | | `--save_intermediates <n>` | | `None` | Save the image from every nth step into an "intermediates" folder inside the output directory |
| `--h_symmetry_time_pct <float>` | | `None` | Create symmetry along the X axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.) | | `--h_symmetry_time_pct <float>` | | `None` | Create symmetry along the X axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.) |
| `--v_symmetry_time_pct <float>` | | `None` | Create symmetry along the Y axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.) | | `--v_symmetry_time_pct <float>` | | `None` | Create symmetry along the Y axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.) |

0
docs/other/TRANSLATION.md → docs/deprecated/TRANSLATION.md
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2
docs/features/VARIATIONS.md → docs/deprecated/VARIATIONS.md
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@ -126,6 +126,6 @@ amounts of image-to-image variation even when the seed is fixed and the
`-v` argument is very low. Others are more deterministic. Feel free to `-v` argument is very low. Others are more deterministic. Feel free to
experiment until you find the combination that you like. experiment until you find the combination that you like.
Also be aware of the [Perlin Noise](OTHER.md#thresholding-and-perlin-noise-initialization-options) Also be aware of the [Perlin Noise](../features/OTHER.md#thresholding-and-perlin-noise-initialization-options)
feature, which provides another way of introducing variability into your feature, which provides another way of introducing variability into your
image generation requests. image generation requests.

5
docs/features/CONCEPTS.md
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@ -28,8 +28,9 @@ by placing them in the designated directory for the compatible model type
### An Example ### An Example
Here are a few examples to illustrate how it works. All these images were Here are a few examples to illustrate how it works. All these images
generated using the command-line client and the Stable Diffusion 1.5 model: were generated using the legacy command-line client and the Stable
Diffusion 1.5 model:
| Japanese gardener | Japanese gardener &lt;ghibli-face&gt; | Japanese gardener &lt;hoi4-leaders&gt; | Japanese gardener &lt;cartoona-animals&gt; | | Japanese gardener | Japanese gardener &lt;ghibli-face&gt; | Japanese gardener &lt;hoi4-leaders&gt; | Japanese gardener &lt;cartoona-animals&gt; |
| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: | | :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |

2
docs/features/CONFIGURATION.md
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@ -82,7 +82,7 @@ format of YAML files can be found
[here](https://circleci.com/blog/what-is-yaml-a-beginner-s-guide/). [here](https://circleci.com/blog/what-is-yaml-a-beginner-s-guide/).
You can fix a broken `invokeai.yaml` by deleting it and running the You can fix a broken `invokeai.yaml` by deleting it and running the
configuration script again -- option [7] in the launcher, "Re-run the configuration script again -- option [6] in the launcher, "Re-run the
configure script". configure script".
#### Reading Environment Variables #### Reading Environment Variables

6
docs/features/CONTROLNET.md
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@ -46,7 +46,7 @@ Diffuser-style ControlNet models are available at HuggingFace
(http://huggingface.co) and accessed via their repo IDs (identifiers (http://huggingface.co) and accessed via their repo IDs (identifiers
in the format "author/modelname"). The easiest way to install them is in the format "author/modelname"). The easiest way to install them is
to use the InvokeAI model installer application. Use the to use the InvokeAI model installer application. Use the
`invoke.sh`/`invoke.bat` launcher to select item [5] and then navigate `invoke.sh`/`invoke.bat` launcher to select item [4] and then navigate
to the CONTROLNETS section. Select the models you wish to install and to the CONTROLNETS section. Select the models you wish to install and
press "APPLY CHANGES". You may also enter additional HuggingFace press "APPLY CHANGES". You may also enter additional HuggingFace
repo_ids in the "Additional models" textbox: repo_ids in the "Additional models" textbox:
@ -145,8 +145,8 @@ Additionally, each ControlNet section can be expanded in order to manipulate set
#### Installation #### Installation
There are several ways to install IP-Adapter models with an existing InvokeAI installation: There are several ways to install IP-Adapter models with an existing InvokeAI installation:
1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [5] to download models. 1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [4] to download models.
2. Through the Model Manager UI with models from the *Tools* section of [www.models.invoke.ai](www.models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models. 2. Through the Model Manager UI with models from the *Tools* section of [www.models.invoke.ai](https://www.models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models.
3. **Advanced -- Not recommended ** Manually downloading the IP-Adapter and Image Encoder files - Image Encoder folders shouid be placed in the `models\any\clip_vision` folders. IP Adapter Model folders should be placed in the relevant `ip-adapter` folder of relevant base model folder of Invoke root directory. For example, for the SDXL IP-Adapter, files should be added to the `model/sdxl/ip_adapter/` folder. 3. **Advanced -- Not recommended ** Manually downloading the IP-Adapter and Image Encoder files - Image Encoder folders shouid be placed in the `models\any\clip_vision` folders. IP Adapter Model folders should be placed in the relevant `ip-adapter` folder of relevant base model folder of Invoke root directory. For example, for the SDXL IP-Adapter, files should be added to the `model/sdxl/ip_adapter/` folder.
#### Using IP-Adapter #### Using IP-Adapter

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docs/features/MODEL_MERGING.md
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@ -16,9 +16,10 @@ Model Merging can be be done by navigating to the Model Manager and clicking the
display all the diffusers-style models that InvokeAI knows about. display all the diffusers-style models that InvokeAI knows about.
If you do not see the model you are looking for, then it is probably If you do not see the model you are looking for, then it is probably
a legacy checkpoint model and needs to be converted using the a legacy checkpoint model and needs to be converted using the
`invoke` command-line client and its `!optimize` command. You "Convert" option in the Web-based Model Manager tab.
must select at least two models to merge. The third can be left at
"None" if you desire. You must select at least two models to merge. The third can be left
at "None" if you desire.
* Alpha: This is the ratio to use when combining models. It ranges * Alpha: This is the ratio to use when combining models. It ranges
from 0 to 1. The higher the value, the more weight is given to the from 0 to 1. The higher the value, the more weight is given to the

10
docs/features/UTILITIES.md
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@ -8,7 +8,7 @@ title: Command-line Utilities
InvokeAI comes with several scripts that are accessible via the InvokeAI comes with several scripts that are accessible via the
command line. To access these commands, start the "developer's command line. To access these commands, start the "developer's
console" from the launcher (`invoke.bat` menu item [8]). Users who are console" from the launcher (`invoke.bat` menu item [7]). Users who are
familiar with Python can alternatively activate InvokeAI's virtual familiar with Python can alternatively activate InvokeAI's virtual
environment (typically, but not necessarily `invokeai/.venv`). environment (typically, but not necessarily `invokeai/.venv`).
@ -34,7 +34,7 @@ invokeai-web --ram 7
## **invokeai-merge** ## **invokeai-merge**
This is the model merge script, the same as launcher option [4]. Call This is the model merge script, the same as launcher option [3]. Call
it with the `--gui` command-line argument to start the interactive it with the `--gui` command-line argument to start the interactive
console-based GUI. Alternatively, you can run it non-interactively console-based GUI. Alternatively, you can run it non-interactively
using command-line arguments as illustrated in the example below which using command-line arguments as illustrated in the example below which
@ -48,7 +48,7 @@ invokeai-merge --force --base-model sd-1 --models stable-diffusion-1.5 inkdiffus
## **invokeai-ti** ## **invokeai-ti**
This is the textual inversion training script that is run by launcher This is the textual inversion training script that is run by launcher
option [3]. Call it with `--gui` to run the interactive console-based option [2]. Call it with `--gui` to run the interactive console-based
front end. It can also be run non-interactively. It has about a front end. It can also be run non-interactively. It has about a
zillion arguments, but a typical training session can be launched zillion arguments, but a typical training session can be launched
with: with:
@ -68,7 +68,7 @@ in Windows).
## **invokeai-install** ## **invokeai-install**
This is the console-based model install script that is run by launcher This is the console-based model install script that is run by launcher
option [5]. If called without arguments, it will launch the option [4]. If called without arguments, it will launch the
interactive console-based interface. It can also be used interactive console-based interface. It can also be used
non-interactively to list, add and remove models as shown by these non-interactively to list, add and remove models as shown by these
examples: examples:
@ -148,7 +148,7 @@ launch the web server against it with `invokeai-web --root InvokeAI-New`.
## **invokeai-update** ## **invokeai-update**
This is the interactive console-based script that is run by launcher This is the interactive console-based script that is run by launcher
menu item [9] to update to a new version of InvokeAI. It takes no menu item [8] to update to a new version of InvokeAI. It takes no
command-line arguments. command-line arguments.
## **invokeai-metadata** ## **invokeai-metadata**

2
docs/features/index.md
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@ -28,7 +28,7 @@ Learn how to install and use ControlNet models for fine control over
image output. image output.
### * [Image-to-Image Guide](IMG2IMG.md) ### * [Image-to-Image Guide](IMG2IMG.md)
Use a seed image to build new creations in the CLI. Use a seed image to build new creations.
## Model Management ## Model Management

7
docs/index.md
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@ -143,7 +143,6 @@ Mac and Linux machines, and runs on GPU cards with as little as 4 GB of RAM.
<!-- seperator --> <!-- seperator -->
### Prompt Engineering ### Prompt Engineering
- [Prompt Syntax](features/PROMPTS.md) - [Prompt Syntax](features/PROMPTS.md)
- [Generating Variations](features/VARIATIONS.md)
### InvokeAI Configuration ### InvokeAI Configuration
- [Guide to InvokeAI Runtime Settings](features/CONFIGURATION.md) - [Guide to InvokeAI Runtime Settings](features/CONFIGURATION.md)
@ -166,10 +165,8 @@ still a work in progress, but coming soon.
### Command-Line Interface Retired ### Command-Line Interface Retired
The original "invokeai" command-line interface has been retired. The All "invokeai" command-line interfaces have been retired as of version
`invokeai` command will now launch a new command-line client that can 3.4.
be used by developers to create and test nodes. It is not intended to
be used for routine image generation or manipulation.
To launch the Web GUI from the command-line, use the command To launch the Web GUI from the command-line, use the command
`invokeai-web` rather than the traditional `invokeai --web`. `invokeai-web` rather than the traditional `invokeai --web`.

2
docs/installation/050_INSTALLING_MODELS.md
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@ -84,7 +84,7 @@ InvokeAI root directory's `autoimport` folder.
### Installation via `invokeai-model-install` ### Installation via `invokeai-model-install`
From the `invoke` launcher, choose option [5] "Download and install From the `invoke` launcher, choose option [4] "Download and install
models." This will launch the same script that prompted you to select models." This will launch the same script that prompted you to select
models at install time. You can use this to add models that you models at install time. You can use this to add models that you
skipped the first time around. It is all right to specify a model that skipped the first time around. It is all right to specify a model that

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docs/installation/deprecated_documentation/INSTALL_LINUX.md
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@ -79,7 +79,7 @@ title: Manual Installation, Linux
and obtaining an access token for downloading. It will then download and and obtaining an access token for downloading. It will then download and
install the weights files for you. install the weights files for you.
Please look [here](../INSTALL_MANUAL.md) for a manual process for doing Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing
the same thing. the same thing.
7. Start generating images! 7. Start generating images!
@ -112,7 +112,7 @@ title: Manual Installation, Linux
To use an alternative model you may invoke the `!switch` command in To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line either the CLI or the Web UI. See [Command Line
Client](../../features/CLI.md#model-selection-and-importation). The Client](../../deprecated/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`. model names are defined in `configs/models.yaml`.
8. Subsequently, to relaunch the script, be sure to run "conda activate 8. Subsequently, to relaunch the script, be sure to run "conda activate

2
docs/installation/deprecated_documentation/INSTALL_MAC.md
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@ -150,7 +150,7 @@ will do our best to help.
To use an alternative model you may invoke the `!switch` command in To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line either the CLI or the Web UI. See [Command Line
Client](../../features/CLI.md#model-selection-and-importation). The Client](../../deprecated/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`. model names are defined in `configs/models.yaml`.
--- ---

2
docs/installation/deprecated_documentation/INSTALL_SOURCE.md
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@ -128,7 +128,7 @@ python scripts/invoke.py --web --max_load_models=3 \
``` ```
These options are described in detail in the These options are described in detail in the
[Command-Line Interface](../../features/CLI.md) documentation. [Command-Line Interface](../../deprecated/CLI.md) documentation.
## Troubleshooting ## Troubleshooting

4
docs/installation/deprecated_documentation/INSTALL_WINDOWS.md
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@ -75,7 +75,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
obtaining an access token for downloading. It will then download and install the obtaining an access token for downloading. It will then download and install the
weights files for you. weights files for you.
Please look [here](../INSTALL_MANUAL.md) for a manual process for doing the Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing the
same thing. same thing.
8. Start generating images! 8. Start generating images!
@ -108,7 +108,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
To use an alternative model you may invoke the `!switch` command in To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line either the CLI or the Web UI. See [Command Line
Client](../../features/CLI.md#model-selection-and-importation). The Client](../../deprecated/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`. model names are defined in `configs/models.yaml`.
9. Subsequently, to relaunch the script, first activate the Anaconda 9. Subsequently, to relaunch the script, first activate the Anaconda

40
installer/templates/invoke.bat.in
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@ -9,41 +9,37 @@ set INVOKEAI_ROOT=.
:start :start
echo Desired action: echo Desired action:
echo 1. Generate images with the browser-based interface echo 1. Generate images with the browser-based interface
echo 2. Explore InvokeAI nodes using a command-line interface echo 2. Run textual inversion training
echo 3. Run textual inversion training echo 3. Merge models (diffusers type only)
echo 4. Merge models (diffusers type only) echo 4. Download and install models
echo 5. Download and install models echo 5. Change InvokeAI startup options
echo 6. Change InvokeAI startup options echo 6. Re-run the configure script to fix a broken install or to complete a major upgrade
echo 7. Re-run the configure script to fix a broken install or to complete a major upgrade echo 7. Open the developer console
echo 8. Open the developer console echo 8. Update InvokeAI
echo 9. Update InvokeAI echo 9. Run the InvokeAI image database maintenance script
echo 10. Run the InvokeAI image database maintenance script echo 10. Command-line help
echo 11. Command-line help
echo Q - Quit echo Q - Quit
set /P choice="Please enter 1-11, Q: [1] " set /P choice="Please enter 1-10, Q: [1] "
if not defined choice set choice=1 if not defined choice set choice=1
IF /I "%choice%" == "1" ( IF /I "%choice%" == "1" (
echo Starting the InvokeAI browser-based UI.. echo Starting the InvokeAI browser-based UI..
python .venv\Scripts\invokeai-web.exe %* python .venv\Scripts\invokeai-web.exe %*
) ELSE IF /I "%choice%" == "2" ( ) ELSE IF /I "%choice%" == "2" (
echo Starting the InvokeAI command-line..
python .venv\Scripts\invokeai.exe %*
) ELSE IF /I "%choice%" == "3" (
echo Starting textual inversion training.. echo Starting textual inversion training..
python .venv\Scripts\invokeai-ti.exe --gui python .venv\Scripts\invokeai-ti.exe --gui
) ELSE IF /I "%choice%" == "4" ( ) ELSE IF /I "%choice%" == "3" (
echo Starting model merging script.. echo Starting model merging script..
python .venv\Scripts\invokeai-merge.exe --gui python .venv\Scripts\invokeai-merge.exe --gui
) ELSE IF /I "%choice%" == "5" ( ) ELSE IF /I "%choice%" == "4" (
echo Running invokeai-model-install... echo Running invokeai-model-install...
python .venv\Scripts\invokeai-model-install.exe python .venv\Scripts\invokeai-model-install.exe
) ELSE IF /I "%choice%" == "6" ( ) ELSE IF /I "%choice%" == "5" (
echo Running invokeai-configure... echo Running invokeai-configure...
python .venv\Scripts\invokeai-configure.exe --skip-sd-weight --skip-support-models python .venv\Scripts\invokeai-configure.exe --skip-sd-weight --skip-support-models
) ELSE IF /I "%choice%" == "7" ( ) ELSE IF /I "%choice%" == "6" (
echo Running invokeai-configure... echo Running invokeai-configure...
python .venv\Scripts\invokeai-configure.exe --yes --skip-sd-weight python .venv\Scripts\invokeai-configure.exe --yes --skip-sd-weight
) ELSE IF /I "%choice%" == "8" ( ) ELSE IF /I "%choice%" == "7" (
echo Developer Console echo Developer Console
echo Python command is: echo Python command is:
where python where python
@ -55,13 +51,13 @@ IF /I "%choice%" == "1" (
echo ************************* echo *************************
echo *** Type `exit` to quit this shell and deactivate the Python virtual environment *** echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
call cmd /k call cmd /k
) ELSE IF /I "%choice%" == "9" ( ) ELSE IF /I "%choice%" == "8" (
echo Running invokeai-update... echo Running invokeai-update...
python -m invokeai.frontend.install.invokeai_update python -m invokeai.frontend.install.invokeai_update
) ELSE IF /I "%choice%" == "10" ( ) ELSE IF /I "%choice%" == "9" (
echo Running the db maintenance script... echo Running the db maintenance script...
python .venv\Scripts\invokeai-db-maintenance.exe python .venv\Scripts\invokeai-db-maintenance.exe
) ELSE IF /I "%choice%" == "11" ( ) ELSE IF /I "%choice%" == "10" (
echo Displaying command line help... echo Displaying command line help...
python .venv\Scripts\invokeai-web.exe --help %* python .venv\Scripts\invokeai-web.exe --help %*
pause pause

61
installer/templates/invoke.sh.in
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@ -58,52 +58,47 @@ do_choice() {
invokeai-web $PARAMS invokeai-web $PARAMS
;; ;;
2) 2)
clear
printf "Explore InvokeAI nodes using a command-line interface\n"
invokeai $PARAMS
;;
3)
clear clear
printf "Textual inversion training\n" printf "Textual inversion training\n"
invokeai-ti --gui $PARAMS invokeai-ti --gui $PARAMS
;; ;;
4) 3)
clear clear
printf "Merge models (diffusers type only)\n" printf "Merge models (diffusers type only)\n"
invokeai-merge --gui $PARAMS invokeai-merge --gui $PARAMS
;; ;;
5) 4)
clear clear
printf "Download and install models\n" printf "Download and install models\n"
invokeai-model-install --root ${INVOKEAI_ROOT} invokeai-model-install --root ${INVOKEAI_ROOT}
;; ;;
6) 5)
clear clear
printf "Change InvokeAI startup options\n" printf "Change InvokeAI startup options\n"
invokeai-configure --root ${INVOKEAI_ROOT} --skip-sd-weights --skip-support-models invokeai-configure --root ${INVOKEAI_ROOT} --skip-sd-weights --skip-support-models
;; ;;
7) 6)
clear clear
printf "Re-run the configure script to fix a broken install or to complete a major upgrade\n" printf "Re-run the configure script to fix a broken install or to complete a major upgrade\n"
invokeai-configure --root ${INVOKEAI_ROOT} --yes --default_only --skip-sd-weights invokeai-configure --root ${INVOKEAI_ROOT} --yes --default_only --skip-sd-weights
;; ;;
8) 7)
clear clear
printf "Open the developer console\n" printf "Open the developer console\n"
file_name=$(basename "${BASH_SOURCE[0]}") file_name=$(basename "${BASH_SOURCE[0]}")
bash --init-file "$file_name" bash --init-file "$file_name"
;; ;;
9) 8)
clear clear
printf "Update InvokeAI\n" printf "Update InvokeAI\n"
python -m invokeai.frontend.install.invokeai_update python -m invokeai.frontend.install.invokeai_update
;; ;;
10) 9)
clear clear
printf "Running the db maintenance script\n" printf "Running the db maintenance script\n"
invokeai-db-maintenance --root ${INVOKEAI_ROOT} invokeai-db-maintenance --root ${INVOKEAI_ROOT}
;; ;;
11) 10)
clear clear
printf "Command-line help\n" printf "Command-line help\n"
invokeai-web --help invokeai-web --help
@ -121,16 +116,15 @@ do_choice() {
do_dialog() { do_dialog() {
options=( options=(
1 "Generate images with a browser-based interface" 1 "Generate images with a browser-based interface"
2 "Explore InvokeAI nodes using a command-line interface" 2 "Textual inversion training"
3 "Textual inversion training" 3 "Merge models (diffusers type only)"
4 "Merge models (diffusers type only)" 4 "Download and install models"
5 "Download and install models" 5 "Change InvokeAI startup options"
6 "Change InvokeAI startup options" 6 "Re-run the configure script to fix a broken install or to complete a major upgrade"
7 "Re-run the configure script to fix a broken install or to complete a major upgrade" 7 "Open the developer console"
8 "Open the developer console" 8 "Update InvokeAI"
9 "Update InvokeAI" 9 "Run the InvokeAI image database maintenance script"
10 "Run the InvokeAI image database maintenance script" 10 "Command-line help"
11 "Command-line help"
) )
choice=$(dialog --clear \ choice=$(dialog --clear \
@ -155,18 +149,17 @@ do_line_input() {
printf " ** For a more attractive experience, please install the 'dialog' utility using your package manager. **\n\n" printf " ** For a more attractive experience, please install the 'dialog' utility using your package manager. **\n\n"
printf "What would you like to do?\n" printf "What would you like to do?\n"
printf "1: Generate images using the browser-based interface\n" printf "1: Generate images using the browser-based interface\n"
printf "2: Explore InvokeAI nodes using the command-line interface\n" printf "2: Run textual inversion training\n"
printf "3: Run textual inversion training\n" printf "3: Merge models (diffusers type only)\n"
printf "4: Merge models (diffusers type only)\n" printf "4: Download and install models\n"
printf "5: Download and install models\n" printf "5: Change InvokeAI startup options\n"
printf "6: Change InvokeAI startup options\n" printf "6: Re-run the configure script to fix a broken install\n"
printf "7: Re-run the configure script to fix a broken install\n" printf "7: Open the developer console\n"
printf "8: Open the developer console\n" printf "8: Update InvokeAI\n"
printf "9: Update InvokeAI\n" printf "9: Run the InvokeAI image database maintenance script\n"
printf "10: Run the InvokeAI image database maintenance script\n" printf "10: Command-line help\n"
printf "11: Command-line help\n"
printf "Q: Quit\n\n" printf "Q: Quit\n\n"
read -p "Please enter 1-11, Q: [1] " yn read -p "Please enter 1-10, Q: [1] " yn
choice=${yn:='1'} choice=${yn:='1'}
do_choice $choice do_choice $choice
clear clear

0
invokeai/app/cli/__init__.py
View File

312
invokeai/app/cli/commands.py
View File

@ -1,312 +0,0 @@
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
import argparse
from abc import ABC, abstractmethod
from typing import Any, Callable, Iterable, Literal, Union, get_args, get_origin, get_type_hints
import matplotlib.pyplot as plt
import networkx as nx
from pydantic import BaseModel, Field
import invokeai.backend.util.logging as logger
from ..invocations.baseinvocation import BaseInvocation
from ..invocations.image import ImageField
from ..services.graph import Edge, GraphExecutionState, LibraryGraph
from ..services.invoker import Invoker
def add_field_argument(command_parser, name: str, field, default_override=None):
default = (
default_override
if default_override is not None
else field.default
if field.default_factory is None
else field.default_factory()
)
if get_origin(field.annotation) == Literal:
allowed_values = get_args(field.annotation)
allowed_types = set()
for val in allowed_values:
allowed_types.add(type(val))
allowed_types_list = list(allowed_types)
field_type = allowed_types_list[0] if len(allowed_types) == 1 else Union[allowed_types_list] # type: ignore
command_parser.add_argument(
f"--{name}",
dest=name,
type=field_type,
default=default,
choices=allowed_values,
help=field.description,
)
else:
command_parser.add_argument(
f"--{name}",
dest=name,
type=field.annotation,
default=default,
help=field.description,
)
def add_parsers(
subparsers,
commands: list[type],
command_field: str = "type",
exclude_fields: list[str] = ["id", "type"],
add_arguments: Union[Callable[[argparse.ArgumentParser], None], None] = None,
):
"""Adds parsers for each command to the subparsers"""
# Create subparsers for each command
for command in commands:
hints = get_type_hints(command)
cmd_name = get_args(hints[command_field])[0]
command_parser = subparsers.add_parser(cmd_name, help=command.__doc__)
if add_arguments is not None:
add_arguments(command_parser)
# Convert all fields to arguments
fields = command.__fields__ # type: ignore
for name, field in fields.items():
if name in exclude_fields:
continue
add_field_argument(command_parser, name, field)
def add_graph_parsers(
subparsers, graphs: list[LibraryGraph], add_arguments: Union[Callable[[argparse.ArgumentParser], None], None] = None
):
for graph in graphs:
command_parser = subparsers.add_parser(graph.name, help=graph.description)
if add_arguments is not None:
add_arguments(command_parser)
# Add arguments for inputs
for exposed_input in graph.exposed_inputs:
node = graph.graph.get_node(exposed_input.node_path)
field = node.__fields__[exposed_input.field]
default_override = getattr(node, exposed_input.field)
add_field_argument(command_parser, exposed_input.alias, field, default_override)
class CliContext:
invoker: Invoker
session: GraphExecutionState
parser: argparse.ArgumentParser
defaults: dict[str, Any]
graph_nodes: dict[str, str]
nodes_added: list[str]
def __init__(self, invoker: Invoker, session: GraphExecutionState, parser: argparse.ArgumentParser):
self.invoker = invoker
self.session = session
self.parser = parser
self.defaults = dict()
self.graph_nodes = dict()
self.nodes_added = list()
def get_session(self):
self.session = self.invoker.services.graph_execution_manager.get(self.session.id)
return self.session
def reset(self):
self.session = self.invoker.create_execution_state()
self.graph_nodes = dict()
self.nodes_added = list()
# Leave defaults unchanged
def add_node(self, node: BaseInvocation):
self.get_session()
self.session.graph.add_node(node)
self.nodes_added.append(node.id)
self.invoker.services.graph_execution_manager.set(self.session)
def add_edge(self, edge: Edge):
self.get_session()
self.session.add_edge(edge)
self.invoker.services.graph_execution_manager.set(self.session)
class ExitCli(Exception):
"""Exception to exit the CLI"""
pass
class BaseCommand(ABC, BaseModel):
"""A CLI command"""
# All commands must include a type name like this:
@classmethod
def get_all_subclasses(cls):
subclasses = []
toprocess = [cls]
while len(toprocess) > 0:
next = toprocess.pop(0)
next_subclasses = next.__subclasses__()
subclasses.extend(next_subclasses)
toprocess.extend(next_subclasses)
return subclasses
@classmethod
def get_commands(cls):
return tuple(BaseCommand.get_all_subclasses())
@classmethod
def get_commands_map(cls):
# Get the type strings out of the literals and into a dictionary
return dict(map(lambda t: (get_args(get_type_hints(t)["type"])[0], t), BaseCommand.get_all_subclasses()))
@abstractmethod
def run(self, context: CliContext) -> None:
"""Run the command. Raise ExitCli to exit."""
pass
class ExitCommand(BaseCommand):
"""Exits the CLI"""
type: Literal["exit"] = "exit"
def run(self, context: CliContext) -> None:
raise ExitCli()
class HelpCommand(BaseCommand):
"""Shows help"""
type: Literal["help"] = "help"
def run(self, context: CliContext) -> None:
context.parser.print_help()
def get_graph_execution_history(
graph_execution_state: GraphExecutionState,
) -> Iterable[str]:
"""Gets the history of fully-executed invocations for a graph execution"""
return (n for n in reversed(graph_execution_state.executed_history) if n in graph_execution_state.graph.nodes)
def get_invocation_command(invocation) -> str:
fields = invocation.__fields__.items()
type_hints = get_type_hints(type(invocation))
command = [invocation.type]
for name, field in fields:
if name in ["id", "type"]:
continue
# TODO: add links
# Skip image fields when serializing command
type_hint = type_hints.get(name) or None
if type_hint is ImageField or ImageField in get_args(type_hint):
continue
field_value = getattr(invocation, name)
field_default = field.default
if field_value != field_default:
if type_hint is str or str in get_args(type_hint):
command.append(f'--{name} "{field_value}"')
else:
command.append(f"--{name} {field_value}")
return " ".join(command)
class HistoryCommand(BaseCommand):
"""Shows the invocation history"""
type: Literal["history"] = "history"
# Inputs
# fmt: off
count: int = Field(default=5, gt=0, description="The number of history entries to show")
# fmt: on
def run(self, context: CliContext) -> None:
history = list(get_graph_execution_history(context.get_session()))
for i in range(min(self.count, len(history))):
entry_id = history[-1 - i]
entry = context.get_session().graph.get_node(entry_id)
logger.info(f"{entry_id}: {get_invocation_command(entry)}")
class SetDefaultCommand(BaseCommand):
"""Sets a default value for a field"""
type: Literal["default"] = "default"
# Inputs
# fmt: off
field: str = Field(description="The field to set the default for")
value: str = Field(description="The value to set the default to, or None to clear the default")
# fmt: on
def run(self, context: CliContext) -> None:
if self.value is None:
if self.field in context.defaults:
del context.defaults[self.field]
else:
context.defaults[self.field] = self.value
class DrawGraphCommand(BaseCommand):
"""Debugs a graph"""
type: Literal["draw_graph"] = "draw_graph"
def run(self, context: CliContext) -> None:
session: GraphExecutionState = context.invoker.services.graph_execution_manager.get(context.session.id)
nxgraph = session.graph.nx_graph_flat()
# Draw the networkx graph
plt.figure(figsize=(20, 20))
pos = nx.spectral_layout(nxgraph)
nx.draw_networkx_nodes(nxgraph, pos, node_size=1000)
nx.draw_networkx_edges(nxgraph, pos, width=2)
nx.draw_networkx_labels(nxgraph, pos, font_size=20, font_family="sans-serif")
plt.axis("off")
plt.show()
class DrawExecutionGraphCommand(BaseCommand):
"""Debugs an execution graph"""
type: Literal["draw_xgraph"] = "draw_xgraph"
def run(self, context: CliContext) -> None:
session: GraphExecutionState = context.invoker.services.graph_execution_manager.get(context.session.id)
nxgraph = session.execution_graph.nx_graph_flat()
# Draw the networkx graph
plt.figure(figsize=(20, 20))
pos = nx.spectral_layout(nxgraph)
nx.draw_networkx_nodes(nxgraph, pos, node_size=1000)
nx.draw_networkx_edges(nxgraph, pos, width=2)
nx.draw_networkx_labels(nxgraph, pos, font_size=20, font_family="sans-serif")
plt.axis("off")
plt.show()
class SortedHelpFormatter(argparse.HelpFormatter):
def _iter_indented_subactions(self, action):
try:
get_subactions = action._get_subactions
except AttributeError:
pass
else:
self._indent()
if isinstance(action, argparse._SubParsersAction):
for subaction in sorted(get_subactions(), key=lambda x: x.dest):
yield subaction
else:
for subaction in get_subactions():
yield subaction
self._dedent()

171
invokeai/app/cli/completer.py
View File

@ -1,171 +0,0 @@
"""
Readline helper functions for cli_app.py
You may import the global singleton `completer` to get access to the
completer object.
"""
import atexit
import readline
import shlex
from pathlib import Path
from typing import Dict, List, Literal, get_args, get_origin, get_type_hints
import invokeai.backend.util.logging as logger
from ...backend import ModelManager
from ..invocations.baseinvocation import BaseInvocation
from ..services.invocation_services import InvocationServices
from .commands import BaseCommand
# singleton object, class variable
completer = None
class Completer(object):
def __init__(self, model_manager: ModelManager):
self.commands = self.get_commands()
self.matches = None
self.linebuffer = None
self.manager = model_manager
return
def complete(self, text, state):
"""
Complete commands and switches fromm the node CLI command line.
Switches are determined in a context-specific manner.
"""
buffer = readline.get_line_buffer()
if state == 0:
options = None
try:
current_command, current_switch = self.get_current_command(buffer)
options = self.get_command_options(current_command, current_switch)
except IndexError:
pass
options = options or list(self.parse_commands().keys())
if not text: # first time
self.matches = options
else:
self.matches = [s for s in options if s and s.startswith(text)]
try:
match = self.matches[state]
except IndexError:
match = None
return match
@classmethod
def get_commands(self) -> List[object]:
"""
Return a list of all the client commands and invocations.
"""
return BaseCommand.get_commands() + BaseInvocation.get_invocations()
def get_current_command(self, buffer: str) -> tuple[str, str]:
"""
Parse the readline buffer to find the most recent command and its switch.
"""
if len(buffer) == 0:
return None, None
tokens = shlex.split(buffer)
command = None
switch = None
for t in tokens:
if t[0].isalpha():
if switch is None:
command = t
else:
switch = t
# don't try to autocomplete switches that are already complete
if switch and buffer.endswith(" "):
switch = None
return command or "", switch or ""
def parse_commands(self) -> Dict[str, List[str]]:
"""
Return a dict in which the keys are the command name
and the values are the parameters the command takes.
"""
result = dict()
for command in self.commands:
hints = get_type_hints(command)
name = get_args(hints["type"])[0]
result.update({name: hints})
return result
def get_command_options(self, command: str, switch: str) -> List[str]:
"""
Return all the parameters that can be passed to the command as
command-line switches. Returns None if the command is unrecognized.
"""
parsed_commands = self.parse_commands()
if command not in parsed_commands:
return None
# handle switches in the format "-foo=bar"
argument = None
if switch and "=" in switch:
switch, argument = switch.split("=")
parameter = switch.strip("-")
if parameter in parsed_commands[command]:
if argument is None:
return self.get_parameter_options(parameter, parsed_commands[command][parameter])
else:
return [
f"--{parameter}={x}"
for x in self.get_parameter_options(parameter, parsed_commands[command][parameter])
]
else:
return [f"--{x}" for x in parsed_commands[command].keys()]
def get_parameter_options(self, parameter: str, typehint) -> List[str]:
"""
Given a parameter type (such as Literal), offers autocompletions.
"""
if get_origin(typehint) == Literal:
return get_args(typehint)
if parameter == "model":
return self.manager.model_names()
def _pre_input_hook(self):
if self.linebuffer:
readline.insert_text(self.linebuffer)
readline.redisplay()
self.linebuffer = None
def set_autocompleter(services: InvocationServices) -> Completer:
global completer
if completer:
return completer
completer = Completer(services.model_manager)
readline.set_completer(completer.complete)
try:
readline.set_auto_history(True)
except AttributeError:
# pyreadline3 does not have a set_auto_history() method
pass
readline.set_pre_input_hook(completer._pre_input_hook)
readline.set_completer_delims(" ")
readline.parse_and_bind("tab: complete")
readline.parse_and_bind("set print-completions-horizontally off")
readline.parse_and_bind("set page-completions on")
readline.parse_and_bind("set skip-completed-text on")
readline.parse_and_bind("set show-all-if-ambiguous on")
histfile = Path(services.configuration.root_dir / ".invoke_history")
try:
readline.read_history_file(histfile)
readline.set_history_length(1000)
except FileNotFoundError:
pass
except OSError: # file likely corrupted
newname = f"{histfile}.old"
logger.error(f"Your history file {histfile} couldn't be loaded and may be corrupted. Renaming it to {newname}")
histfile.replace(Path(newname))
atexit.register(readline.write_history_file, histfile)

484
invokeai/app/cli_app.py
View File

@ -1,484 +0,0 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
from .services.config import InvokeAIAppConfig
# parse_args() must be called before any other imports. if it is not called first, consumers of the config
# which are imported/used before parse_args() is called will get the default config values instead of the
# values from the command line or config file.
if True: # hack to make flake8 happy with imports coming after setting up the config
import argparse
import re
import shlex
import sqlite3
import sys
import time
from typing import Optional, Union, get_type_hints
import torch
from pydantic import BaseModel, ValidationError
from pydantic.fields import Field
import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
from invokeai.app.services.board_image_record_storage import SqliteBoardImageRecordStorage
from invokeai.app.services.board_images import BoardImagesService, BoardImagesServiceDependencies
from invokeai.app.services.board_record_storage import SqliteBoardRecordStorage
from invokeai.app.services.boards import BoardService, BoardServiceDependencies
from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
from invokeai.app.services.images import ImageService, ImageServiceDependencies
from invokeai.app.services.invocation_stats import InvocationStatsService
from invokeai.app.services.resource_name import SimpleNameService
from invokeai.app.services.urls import LocalUrlService
from invokeai.backend.util.logging import InvokeAILogger
from invokeai.version.invokeai_version import __version__
from .cli.commands import BaseCommand, CliContext, ExitCli, SortedHelpFormatter, add_graph_parsers, add_parsers
from .cli.completer import set_autocompleter
from .invocations.baseinvocation import BaseInvocation
from .services.default_graphs import create_system_graphs, default_text_to_image_graph_id
from .services.events import EventServiceBase
from .services.graph import (
Edge,
EdgeConnection,
GraphExecutionState,
GraphInvocation,
LibraryGraph,
are_connection_types_compatible,
)
from .services.image_file_storage import DiskImageFileStorage
from .services.invocation_queue import MemoryInvocationQueue
from .services.invocation_services import InvocationServices
from .services.invoker import Invoker
from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
from .services.model_manager_service import ModelManagerService
from .services.processor import DefaultInvocationProcessor
from .services.sqlite import SqliteItemStorage
if torch.backends.mps.is_available():
import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
config = InvokeAIAppConfig.get_config()
config.parse_args()
logger = InvokeAILogger().get_logger(config=config)
class CliCommand(BaseModel):
command: Union[BaseCommand.get_commands() + BaseInvocation.get_invocations()] = Field(discriminator="type") # type: ignore
class InvalidArgs(Exception):
pass
def add_invocation_args(command_parser):
# Add linking capability
command_parser.add_argument(
"--link",
"-l",
action="append",
nargs=3,
help="A link in the format 'source_node source_field dest_field'. source_node can be relative to history (e.g. -1)",
)
command_parser.add_argument(
"--link_node",
"-ln",
action="append",
help="A link from all fields in the specified node. Node can be relative to history (e.g. -1)",
)
def get_command_parser(services: InvocationServices) -> argparse.ArgumentParser:
# Create invocation parser
parser = argparse.ArgumentParser(formatter_class=SortedHelpFormatter)
def exit(*args, **kwargs):
raise InvalidArgs
parser.exit = exit
subparsers = parser.add_subparsers(dest="type")
# Create subparsers for each invocation
invocations = BaseInvocation.get_all_subclasses()
add_parsers(subparsers, invocations, add_arguments=add_invocation_args)
# Create subparsers for each command
commands = BaseCommand.get_all_subclasses()
add_parsers(subparsers, commands, exclude_fields=["type"])
# Create subparsers for exposed CLI graphs
# TODO: add a way to identify these graphs
text_to_image = services.graph_library.get(default_text_to_image_graph_id)
add_graph_parsers(subparsers, [text_to_image], add_arguments=add_invocation_args)
return parser
class NodeField:
alias: str
node_path: str
field: str
field_type: type
def __init__(self, alias: str, node_path: str, field: str, field_type: type):
self.alias = alias
self.node_path = node_path
self.field = field
self.field_type = field_type
def fields_from_type_hints(hints: dict[str, type], node_path: str) -> dict[str, NodeField]:
return {k: NodeField(alias=k, node_path=node_path, field=k, field_type=v) for k, v in hints.items()}
def get_node_input_field(graph: LibraryGraph, field_alias: str, node_id: str) -> NodeField:
"""Gets the node field for the specified field alias"""
exposed_input = next(e for e in graph.exposed_inputs if e.alias == field_alias)
node_type = type(graph.graph.get_node(exposed_input.node_path))
return NodeField(
alias=exposed_input.alias,
node_path=f"{node_id}.{exposed_input.node_path}",
field=exposed_input.field,
field_type=get_type_hints(node_type)[exposed_input.field],
)
def get_node_output_field(graph: LibraryGraph, field_alias: str, node_id: str) -> NodeField:
"""Gets the node field for the specified field alias"""
exposed_output = next(e for e in graph.exposed_outputs if e.alias == field_alias)
node_type = type(graph.graph.get_node(exposed_output.node_path))
node_output_type = node_type.get_output_type()
return NodeField(
alias=exposed_output.alias,
node_path=f"{node_id}.{exposed_output.node_path}",
field=exposed_output.field,
field_type=get_type_hints(node_output_type)[exposed_output.field],
)
def get_node_inputs(invocation: BaseInvocation, context: CliContext) -> dict[str, NodeField]:
"""Gets the inputs for the specified invocation from the context"""
node_type = type(invocation)
if node_type is not GraphInvocation:
return fields_from_type_hints(get_type_hints(node_type), invocation.id)
else:
graph: LibraryGraph = context.invoker.services.graph_library.get(context.graph_nodes[invocation.id])
return {e.alias: get_node_input_field(graph, e.alias, invocation.id) for e in graph.exposed_inputs}
def get_node_outputs(invocation: BaseInvocation, context: CliContext) -> dict[str, NodeField]:
"""Gets the outputs for the specified invocation from the context"""
node_type = type(invocation)
if node_type is not GraphInvocation:
return fields_from_type_hints(get_type_hints(node_type.get_output_type()), invocation.id)
else:
graph: LibraryGraph = context.invoker.services.graph_library.get(context.graph_nodes[invocation.id])
return {e.alias: get_node_output_field(graph, e.alias, invocation.id) for e in graph.exposed_outputs}
def generate_matching_edges(a: BaseInvocation, b: BaseInvocation, context: CliContext) -> list[Edge]:
"""Generates all possible edges between two invocations"""
afields = get_node_outputs(a, context)
bfields = get_node_inputs(b, context)
matching_fields = set(afields.keys()).intersection(bfields.keys())
# Remove invalid fields
invalid_fields = set(["type", "id"])
matching_fields = matching_fields.difference(invalid_fields)
# Validate types
matching_fields = [
f for f in matching_fields if are_connection_types_compatible(afields[f].field_type, bfields[f].field_type)
]
edges = [
Edge(
source=EdgeConnection(node_id=afields[alias].node_path, field=afields[alias].field),
destination=EdgeConnection(node_id=bfields[alias].node_path, field=bfields[alias].field),
)
for alias in matching_fields
]
return edges
class SessionError(Exception):
"""Raised when a session error has occurred"""
pass
def invoke_all(context: CliContext):
"""Runs all invocations in the specified session"""
context.invoker.invoke(context.session, invoke_all=True)
while not context.get_session().is_complete():
# Wait some time
time.sleep(0.1)
# Print any errors
if context.session.has_error():
for n in context.session.errors:
context.invoker.services.logger.error(
f"Error in node {n} (source node {context.session.prepared_source_mapping[n]}): {context.session.errors[n]}"
)
raise SessionError()
def invoke_cli():
logger.info(f"InvokeAI version {__version__}")
# get the optional list of invocations to execute on the command line
parser = config.get_parser()
parser.add_argument("commands", nargs="*")
invocation_commands = parser.parse_args().commands
# get the optional file to read commands from.
# Simplest is to use it for STDIN
if infile := config.from_file:
sys.stdin = open(infile, "r")
model_manager = ModelManagerService(config, logger)
events = EventServiceBase()
output_folder = config.output_path
# TODO: build a file/path manager?
if config.use_memory_db:
db_location = ":memory:"
else:
db_location = config.db_path
db_location.parent.mkdir(parents=True, exist_ok=True)
db_conn = sqlite3.connect(db_location, check_same_thread=False) # TODO: figure out a better threading solution
logger.info(f'InvokeAI database location is "{db_location}"')
graph_execution_manager = SqliteItemStorage[GraphExecutionState](conn=db_conn, table_name="graph_executions")
urls = LocalUrlService()
image_record_storage = SqliteImageRecordStorage(conn=db_conn)
image_file_storage = DiskImageFileStorage(f"{output_folder}/images")
names = SimpleNameService()
board_record_storage = SqliteBoardRecordStorage(conn=db_conn)
board_image_record_storage = SqliteBoardImageRecordStorage(conn=db_conn)
boards = BoardService(
services=BoardServiceDependencies(
board_image_record_storage=board_image_record_storage,
board_record_storage=board_record_storage,
image_record_storage=image_record_storage,
url=urls,
logger=logger,
)
)
board_images = BoardImagesService(
services=BoardImagesServiceDependencies(
board_image_record_storage=board_image_record_storage,
board_record_storage=board_record_storage,
image_record_storage=image_record_storage,
url=urls,
logger=logger,
)
)
images = ImageService(
services=ImageServiceDependencies(
board_image_record_storage=board_image_record_storage,
image_record_storage=image_record_storage,
image_file_storage=image_file_storage,
url=urls,
logger=logger,
names=names,
graph_execution_manager=graph_execution_manager,
)
)
services = InvocationServices(
model_manager=model_manager,
events=events,
latents=ForwardCacheLatentsStorage(DiskLatentsStorage(f"{output_folder}/latents")),
images=images,
boards=boards,
board_images=board_images,
queue=MemoryInvocationQueue(),
graph_library=SqliteItemStorage[LibraryGraph](conn=db_conn, table_name="graphs"),
graph_execution_manager=graph_execution_manager,
processor=DefaultInvocationProcessor(),
performance_statistics=InvocationStatsService(graph_execution_manager),
logger=logger,
configuration=config,
invocation_cache=MemoryInvocationCache(max_cache_size=config.node_cache_size),
)
system_graphs = create_system_graphs(services.graph_library)
system_graph_names = set([g.name for g in system_graphs])
set_autocompleter(services)
invoker = Invoker(services)
session: GraphExecutionState = invoker.create_execution_state()
parser = get_command_parser(services)
re_negid = re.compile("^-[0-9]+$")
# Uncomment to print out previous sessions at startup
# print(services.session_manager.list())
context = CliContext(invoker, session, parser)
set_autocompleter(services)
command_line_args_exist = len(invocation_commands) > 0
done = False
while not done:
try:
if command_line_args_exist:
cmd_input = invocation_commands.pop(0)
done = len(invocation_commands) == 0
else:
cmd_input = input("invoke> ")
except (KeyboardInterrupt, EOFError):
# Ctrl-c exits
break
try:
# Refresh the state of the session
# history = list(get_graph_execution_history(context.session))
history = list(reversed(context.nodes_added))
# Split the command for piping
cmds = cmd_input.split("|")
start_id = len(context.nodes_added)
current_id = start_id
new_invocations = list()
for cmd in cmds:
if cmd is None or cmd.strip() == "":
raise InvalidArgs("Empty command")
# Parse args to create invocation
args = vars(context.parser.parse_args(shlex.split(cmd.strip())))
# Override defaults
for field_name, field_default in context.defaults.items():
if field_name in args:
args[field_name] = field_default
# Parse invocation
command: CliCommand = None # type:ignore
system_graph: Optional[LibraryGraph] = None
if args["type"] in system_graph_names:
system_graph = next(filter(lambda g: g.name == args["type"], system_graphs))
invocation = GraphInvocation(graph=system_graph.graph, id=str(current_id))
for exposed_input in system_graph.exposed_inputs:
if exposed_input.alias in args:
node = invocation.graph.get_node(exposed_input.node_path)
field = exposed_input.field
setattr(node, field, args[exposed_input.alias])
command = CliCommand(command=invocation)
context.graph_nodes[invocation.id] = system_graph.id
else:
args["id"] = current_id
command = CliCommand(command=args)
if command is None:
continue
# Run any CLI commands immediately
if isinstance(command.command, BaseCommand):
# Invoke all current nodes to preserve operation order
invoke_all(context)
# Run the command
command.command.run(context)
continue
# TODO: handle linking with library graphs
# Pipe previous command output (if there was a previous command)
edges: list[Edge] = list()
if len(history) > 0 or current_id != start_id:
from_id = history[0] if current_id == start_id else str(current_id - 1)
from_node = (
next(filter(lambda n: n[0].id == from_id, new_invocations))[0]
if current_id != start_id
else context.session.graph.get_node(from_id)
)
matching_edges = generate_matching_edges(from_node, command.command, context)
edges.extend(matching_edges)
# Parse provided links
if "link_node" in args and args["link_node"]:
for link in args["link_node"]:
node_id = link
if re_negid.match(node_id):
node_id = str(current_id + int(node_id))
link_node = context.session.graph.get_node(node_id)
matching_edges = generate_matching_edges(link_node, command.command, context)
matching_destinations = [e.destination for e in matching_edges]
edges = [e for e in edges if e.destination not in matching_destinations]
edges.extend(matching_edges)
if "link" in args and args["link"]:
for link in args["link"]:
edges = [
e
for e in edges
if e.destination.node_id != command.command.id or e.destination.field != link[2]
]
node_id = link[0]
if re_negid.match(node_id):
node_id = str(current_id + int(node_id))
# TODO: handle missing input/output
node_output = get_node_outputs(context.session.graph.get_node(node_id), context)[link[1]]
node_input = get_node_inputs(command.command, context)[link[2]]
edges.append(
Edge(
source=EdgeConnection(node_id=node_output.node_path, field=node_output.field),
destination=EdgeConnection(node_id=node_input.node_path, field=node_input.field),
)
)
new_invocations.append((command.command, edges))
current_id = current_id + 1
# Add the node to the session
context.add_node(command.command)
for edge in edges:
print(edge)
context.add_edge(edge)
# Execute all remaining nodes
invoke_all(context)
except InvalidArgs:
invoker.services.logger.warning('Invalid command, use "help" to list commands')
continue
except ValidationError:
invoker.services.logger.warning('Invalid command arguments, run "<command> --help" for summary')
except SessionError:
# Start a new session
invoker.services.logger.warning("Session error: creating a new session")
context.reset()
except ExitCli:
break
except SystemExit:
continue
invoker.stop()
if __name__ == "__main__":
if config.version:
print(f"InvokeAI version {__version__}")
else:
invoke_cli()

9
mkdocs.yml
View File

@ -134,6 +134,7 @@ nav:
- List of Default Nodes: 'nodes/defaultNodes.md' - List of Default Nodes: 'nodes/defaultNodes.md'
- Workflow Editor Usage: 'nodes/NODES.md' - Workflow Editor Usage: 'nodes/NODES.md'
- ComfyUI to InvokeAI: 'nodes/comfyToInvoke.md' - ComfyUI to InvokeAI: 'nodes/comfyToInvoke.md'
- Facetool Node: 'nodes/detailedNodes/faceTools.md'
- Contributing Nodes: 'nodes/contributingNodes.md' - Contributing Nodes: 'nodes/contributingNodes.md'
- Features: - Features:
- Overview: 'features/index.md' - Overview: 'features/index.md'
@ -144,7 +145,7 @@ nav:
- Image-to-Image: 'features/IMG2IMG.md' - Image-to-Image: 'features/IMG2IMG.md'
- Controlling Logging: 'features/LOGGING.md' - Controlling Logging: 'features/LOGGING.md'
- Model Merging: 'features/MODEL_MERGING.md' - Model Merging: 'features/MODEL_MERGING.md'
- Using Nodes : './nodes/overview' - Using Nodes : 'nodes/overview.md'
- NSFW Checker: 'features/WATERMARK+NSFW.md' - NSFW Checker: 'features/WATERMARK+NSFW.md'
- Postprocessing: 'features/POSTPROCESS.md' - Postprocessing: 'features/POSTPROCESS.md'
- Prompting Features: 'features/PROMPTS.md' - Prompting Features: 'features/PROMPTS.md'
@ -152,15 +153,18 @@ nav:
- Unified Canvas: 'features/UNIFIED_CANVAS.md' - Unified Canvas: 'features/UNIFIED_CANVAS.md'
- InvokeAI Web Server: 'features/WEB.md' - InvokeAI Web Server: 'features/WEB.md'
- WebUI Hotkeys: "features/WEBUIHOTKEYS.md" - WebUI Hotkeys: "features/WEBUIHOTKEYS.md"
- Maintenance Utilities: "features/UTILITIES.md"
- Other: 'features/OTHER.md' - Other: 'features/OTHER.md'
- Contributing: - Contributing:
- How to Contribute: 'contributing/CONTRIBUTING.md' - How to Contribute: 'contributing/CONTRIBUTING.md'
- InvokeAI Code of Conduct: 'CODE_OF_CONDUCT.md'
- Development: - Development:
- Overview: 'contributing/contribution_guides/development.md' - Overview: 'contributing/contribution_guides/development.md'
- New Contributors: 'contributing/contribution_guides/newContributorChecklist.md' - New Contributors: 'contributing/contribution_guides/newContributorChecklist.md'
- InvokeAI Architecture: 'contributing/ARCHITECTURE.md' - InvokeAI Architecture: 'contributing/ARCHITECTURE.md'
- Frontend Documentation: 'contributing/contribution_guides/contributingToFrontend.md' - Frontend Documentation: 'contributing/contribution_guides/contributingToFrontend.md'
- Local Development: 'contributing/LOCAL_DEVELOPMENT.md' - Local Development: 'contributing/LOCAL_DEVELOPMENT.md'
- Adding Tests: 'contributing/TESTS.md'
- Documentation: 'contributing/contribution_guides/documentation.md' - Documentation: 'contributing/contribution_guides/documentation.md'
- Nodes: 'contributing/INVOCATIONS.md' - Nodes: 'contributing/INVOCATIONS.md'
- Translation: 'contributing/contribution_guides/translation.md' - Translation: 'contributing/contribution_guides/translation.md'
@ -168,9 +172,12 @@ nav:
- Changelog: 'CHANGELOG.md' - Changelog: 'CHANGELOG.md'
- Deprecated: - Deprecated:
- Command Line Interface: 'deprecated/CLI.md' - Command Line Interface: 'deprecated/CLI.md'
- Variations: 'deprecated/VARIATIONS.md'
- Translations: 'deprecated/TRANSLATION.md'
- Embiggen: 'deprecated/EMBIGGEN.md' - Embiggen: 'deprecated/EMBIGGEN.md'
- Inpainting: 'deprecated/INPAINTING.md' - Inpainting: 'deprecated/INPAINTING.md'
- Outpainting: 'deprecated/OUTPAINTING.md' - Outpainting: 'deprecated/OUTPAINTING.md'
- Troubleshooting: 'help/deprecated/TROUBLESHOOT.md'
- Help: - Help:
- Getting Started: 'help/gettingStartedWithAI.md' - Getting Started: 'help/gettingStartedWithAI.md'
- Diffusion Overview: 'help/diffusion.md' - Diffusion Overview: 'help/diffusion.md'

3
pyproject.toml
View File

@ -125,7 +125,7 @@ dependencies = [
# shortcut commands to start cli and web # shortcut commands to start cli and web
# "invokeai --web" will launch the web interface # "invokeai --web" will launch the web interface
# "invokeai" will launch the CLI # "invokeai" will launch the CLI
"invokeai" = "invokeai.frontend.legacy_launch_invokeai:main" # "invokeai" = "invokeai.frontend.legacy_launch_invokeai:main"
# new shortcut to launch web interface # new shortcut to launch web interface
"invokeai-web" = "invokeai.app.api_app:invoke_api" "invokeai-web" = "invokeai.app.api_app:invoke_api"
@ -138,7 +138,6 @@ dependencies = [
"invokeai-migrate3" = "invokeai.backend.install.migrate_to_3:main" "invokeai-migrate3" = "invokeai.backend.install.migrate_to_3:main"
"invokeai-update" = "invokeai.frontend.install.invokeai_update:main" "invokeai-update" = "invokeai.frontend.install.invokeai_update:main"
"invokeai-metadata" = "invokeai.backend.image_util.invoke_metadata:main" "invokeai-metadata" = "invokeai.backend.image_util.invoke_metadata:main"
"invokeai-node-cli" = "invokeai.app.cli_app:invoke_cli"
"invokeai-node-web" = "invokeai.app.api_app:invoke_api" "invokeai-node-web" = "invokeai.app.api_app:invoke_api"
"invokeai-import-images" = "invokeai.frontend.install.import_images:main" "invokeai-import-images" = "invokeai.frontend.install.import_images:main"
"invokeai-db-maintenance" = "invokeai.backend.util.db_maintenance:main" "invokeai-db-maintenance" = "invokeai.backend.util.db_maintenance:main"