mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
remove all references to CLI
This commit is contained in:
Lincoln Stein
psychedelicious
parent
9fa8e38163
commit
d27392cc2d
@ -488,7 +488,7 @@ sections describe what's new for InvokeAI.
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- A choice of installer scripts that automate installation and configuration.
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See
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[Installation](installation/index.md).
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[Installation](installation/INSTALLATION.md).
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- A streamlined manual installation process that works for both Conda and
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PIP-only installs. See
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[Manual Installation](installation/020_INSTALL_MANUAL.md).
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@ -657,7 +657,7 @@ sections describe what's new for InvokeAI.
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## v1.13 <small>(3 September 2022)</small>
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- Support image variations (see [VARIATIONS](features/VARIATIONS.md)
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- Support image variations (see [VARIATIONS](deprecated/VARIATIONS.md)
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([Kevin Gibbons](https://github.com/bakkot) and many contributors and
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reviewers)
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- Supports a Google Colab notebook for a standalone server running on Google
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@ -45,5 +45,5 @@ For backend related work, please reach out to **@blessedcoolant**, **@lstein**,
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## **What does the Code of Conduct mean for me?**
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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.
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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.
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@ -211,8 +211,8 @@ Here are the invoke> command that apply to txt2img:
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| `--facetool <name>` | `-ft <name>` | `-ft gfpgan` | Select face restoration algorithm to use: gfpgan, codeformer |
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| `--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 |
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| `--save_original` | `-save_orig` | `False` | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced. |
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| `--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). |
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| `--with_variations <pattern>` | | `None` | Combine two or more variations. See [Variations](../features/VARIATIONS.md) for now to use this. |
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| `--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). |
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| `--with_variations <pattern>` | | `None` | Combine two or more variations. See [Variations](VARIATIONS.md) for now to use this. |
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| `--save_intermediates <n>` | | `None` | Save the image from every nth step into an "intermediates" folder inside the output directory |
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| `--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.) |
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| `--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.) |
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@ -126,6 +126,6 @@ amounts of image-to-image variation even when the seed is fixed and the
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`-v` argument is very low. Others are more deterministic. Feel free to
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experiment until you find the combination that you like.
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Also be aware of the [Perlin Noise](OTHER.md#thresholding-and-perlin-noise-initialization-options)
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Also be aware of the [Perlin Noise](../features/OTHER.md#thresholding-and-perlin-noise-initialization-options)
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feature, which provides another way of introducing variability into your
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image generation requests.
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@ -28,8 +28,9 @@ by placing them in the designated directory for the compatible model type
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### An Example
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Here are a few examples to illustrate how it works. All these images were
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generated using the command-line client and the Stable Diffusion 1.5 model:
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Here are a few examples to illustrate how it works. All these images
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were generated using the legacy command-line client and the Stable
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Diffusion 1.5 model:
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| Japanese gardener | Japanese gardener <ghibli-face> | Japanese gardener <hoi4-leaders> | Japanese gardener <cartoona-animals> |
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| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
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@ -82,7 +82,7 @@ format of YAML files can be found
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[here](https://circleci.com/blog/what-is-yaml-a-beginner-s-guide/).
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You can fix a broken `invokeai.yaml` by deleting it and running the
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configuration script again -- option [7] in the launcher, "Re-run the
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configuration script again -- option [6] in the launcher, "Re-run the
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configure script".
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#### Reading Environment Variables
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@ -46,7 +46,7 @@ Diffuser-style ControlNet models are available at HuggingFace
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(http://huggingface.co) and accessed via their repo IDs (identifiers
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in the format "author/modelname"). The easiest way to install them is
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to use the InvokeAI model installer application. Use the
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`invoke.sh`/`invoke.bat` launcher to select item [5] and then navigate
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`invoke.sh`/`invoke.bat` launcher to select item [4] and then navigate
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to the CONTROLNETS section. Select the models you wish to install and
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press "APPLY CHANGES". You may also enter additional HuggingFace
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repo_ids in the "Additional models" textbox:
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@ -145,8 +145,8 @@ Additionally, each ControlNet section can be expanded in order to manipulate set
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#### Installation
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There are several ways to install IP-Adapter models with an existing InvokeAI installation:
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1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [5] to download models.
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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.
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1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [4] to download models.
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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.
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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.
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#### Using IP-Adapter
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@ -16,9 +16,10 @@ Model Merging can be be done by navigating to the Model Manager and clicking the
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display all the diffusers-style models that InvokeAI knows about.
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If you do not see the model you are looking for, then it is probably
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a legacy checkpoint model and needs to be converted using the
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`invoke` command-line client and its `!optimize` command. You
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must select at least two models to merge. The third can be left at
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"None" if you desire.
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"Convert" option in the Web-based Model Manager tab.
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You must select at least two models to merge. The third can be left
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at "None" if you desire.
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* Alpha: This is the ratio to use when combining models. It ranges
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from 0 to 1. The higher the value, the more weight is given to the
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@ -8,7 +8,7 @@ title: Command-line Utilities
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InvokeAI comes with several scripts that are accessible via the
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command line. To access these commands, start the "developer's
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console" from the launcher (`invoke.bat` menu item [8]). Users who are
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console" from the launcher (`invoke.bat` menu item [7]). Users who are
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familiar with Python can alternatively activate InvokeAI's virtual
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environment (typically, but not necessarily `invokeai/.venv`).
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@ -34,7 +34,7 @@ invokeai-web --ram 7
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## **invokeai-merge**
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This is the model merge script, the same as launcher option [4]. Call
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This is the model merge script, the same as launcher option [3]. Call
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it with the `--gui` command-line argument to start the interactive
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console-based GUI. Alternatively, you can run it non-interactively
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using command-line arguments as illustrated in the example below which
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@ -48,7 +48,7 @@ invokeai-merge --force --base-model sd-1 --models stable-diffusion-1.5 inkdiffus
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## **invokeai-ti**
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This is the textual inversion training script that is run by launcher
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option [3]. Call it with `--gui` to run the interactive console-based
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option [2]. Call it with `--gui` to run the interactive console-based
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front end. It can also be run non-interactively. It has about a
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zillion arguments, but a typical training session can be launched
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with:
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@ -68,7 +68,7 @@ in Windows).
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## **invokeai-install**
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This is the console-based model install script that is run by launcher
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option [5]. If called without arguments, it will launch the
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option [4]. If called without arguments, it will launch the
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interactive console-based interface. It can also be used
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non-interactively to list, add and remove models as shown by these
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examples:
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@ -148,7 +148,7 @@ launch the web server against it with `invokeai-web --root InvokeAI-New`.
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## **invokeai-update**
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This is the interactive console-based script that is run by launcher
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menu item [9] to update to a new version of InvokeAI. It takes no
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menu item [8] to update to a new version of InvokeAI. It takes no
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command-line arguments.
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## **invokeai-metadata**
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@ -28,7 +28,7 @@ Learn how to install and use ControlNet models for fine control over
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image output.
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### * [Image-to-Image Guide](IMG2IMG.md)
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Use a seed image to build new creations in the CLI.
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Use a seed image to build new creations.
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## Model Management
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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.
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<!-- seperator -->
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### Prompt Engineering
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- [Prompt Syntax](features/PROMPTS.md)
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- [Generating Variations](features/VARIATIONS.md)
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### InvokeAI Configuration
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- [Guide to InvokeAI Runtime Settings](features/CONFIGURATION.md)
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@ -166,10 +165,8 @@ still a work in progress, but coming soon.
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### Command-Line Interface Retired
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The original "invokeai" command-line interface has been retired. The
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`invokeai` command will now launch a new command-line client that can
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be used by developers to create and test nodes. It is not intended to
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be used for routine image generation or manipulation.
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All "invokeai" command-line interfaces have been retired as of version
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3.4.
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To launch the Web GUI from the command-line, use the command
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`invokeai-web` rather than the traditional `invokeai --web`.
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@ -84,7 +84,7 @@ InvokeAI root directory's `autoimport` folder.
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### Installation via `invokeai-model-install`
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From the `invoke` launcher, choose option [5] "Download and install
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From the `invoke` launcher, choose option [4] "Download and install
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models." This will launch the same script that prompted you to select
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models at install time. You can use this to add models that you
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skipped the first time around. It is all right to specify a model that
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@ -79,7 +79,7 @@ title: Manual Installation, Linux
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and obtaining an access token for downloading. It will then download and
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install the weights files for you.
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Please look [here](../INSTALL_MANUAL.md) for a manual process for doing
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Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing
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the same thing.
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7. Start generating images!
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@ -112,7 +112,7 @@ title: Manual Installation, Linux
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To use an alternative model you may invoke the `!switch` command in
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the CLI, or pass `--model <model_name>` during `invoke.py` launch for
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either the CLI or the Web UI. See [Command Line
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Client](../../features/CLI.md#model-selection-and-importation). The
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Client](../../deprecated/CLI.md#model-selection-and-importation). The
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model names are defined in `configs/models.yaml`.
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8. Subsequently, to relaunch the script, be sure to run "conda activate
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@ -150,7 +150,7 @@ will do our best to help.
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To use an alternative model you may invoke the `!switch` command in
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the CLI, or pass `--model <model_name>` during `invoke.py` launch for
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either the CLI or the Web UI. See [Command Line
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Client](../../features/CLI.md#model-selection-and-importation). The
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Client](../../deprecated/CLI.md#model-selection-and-importation). The
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model names are defined in `configs/models.yaml`.
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---
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@ -128,7 +128,7 @@ python scripts/invoke.py --web --max_load_models=3 \
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```
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These options are described in detail in the
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[Command-Line Interface](../../features/CLI.md) documentation.
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[Command-Line Interface](../../deprecated/CLI.md) documentation.
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## Troubleshooting
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@ -75,7 +75,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
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obtaining an access token for downloading. It will then download and install the
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weights files for you.
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Please look [here](../INSTALL_MANUAL.md) for a manual process for doing the
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Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing the
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same thing.
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8. Start generating images!
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@ -108,7 +108,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
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To use an alternative model you may invoke the `!switch` command in
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the CLI, or pass `--model <model_name>` during `invoke.py` launch for
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either the CLI or the Web UI. See [Command Line
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Client](../../features/CLI.md#model-selection-and-importation). The
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Client](../../deprecated/CLI.md#model-selection-and-importation). The
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model names are defined in `configs/models.yaml`.
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9. Subsequently, to relaunch the script, first activate the Anaconda
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@ -9,41 +9,37 @@ set INVOKEAI_ROOT=.
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:start
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echo Desired action:
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echo 1. Generate images with the browser-based interface
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echo 2. Explore InvokeAI nodes using a command-line interface
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echo 3. Run textual inversion training
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echo 4. Merge models (diffusers type only)
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echo 5. Download and install models
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echo 6. Change InvokeAI startup options
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echo 7. Re-run the configure script to fix a broken install or to complete a major upgrade
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echo 8. Open the developer console
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echo 9. Update InvokeAI
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echo 10. Run the InvokeAI image database maintenance script
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echo 11. Command-line help
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echo 2. Run textual inversion training
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echo 3. Merge models (diffusers type only)
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echo 4. Download and install models
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echo 5. Change InvokeAI startup options
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echo 6. Re-run the configure script to fix a broken install or to complete a major upgrade
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echo 7. Open the developer console
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echo 8. Update InvokeAI
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echo 9. Run the InvokeAI image database maintenance script
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echo 10. Command-line help
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echo Q - Quit
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set /P choice="Please enter 1-11, Q: [1] "
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set /P choice="Please enter 1-10, Q: [1] "
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if not defined choice set choice=1
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IF /I "%choice%" == "1" (
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echo Starting the InvokeAI browser-based UI..
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python .venv\Scripts\invokeai-web.exe %*
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) ELSE IF /I "%choice%" == "2" (
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echo Starting the InvokeAI command-line..
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python .venv\Scripts\invokeai.exe %*
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) ELSE IF /I "%choice%" == "3" (
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echo Starting textual inversion training..
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python .venv\Scripts\invokeai-ti.exe --gui
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) ELSE IF /I "%choice%" == "4" (
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) ELSE IF /I "%choice%" == "3" (
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echo Starting model merging script..
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python .venv\Scripts\invokeai-merge.exe --gui
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) ELSE IF /I "%choice%" == "5" (
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) ELSE IF /I "%choice%" == "4" (
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echo Running invokeai-model-install...
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python .venv\Scripts\invokeai-model-install.exe
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) ELSE IF /I "%choice%" == "6" (
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) ELSE IF /I "%choice%" == "5" (
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echo Running invokeai-configure...
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python .venv\Scripts\invokeai-configure.exe --skip-sd-weight --skip-support-models
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) ELSE IF /I "%choice%" == "7" (
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) ELSE IF /I "%choice%" == "6" (
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echo Running invokeai-configure...
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python .venv\Scripts\invokeai-configure.exe --yes --skip-sd-weight
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) ELSE IF /I "%choice%" == "8" (
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) ELSE IF /I "%choice%" == "7" (
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echo Developer Console
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echo Python command is:
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where python
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@ -55,13 +51,13 @@ IF /I "%choice%" == "1" (
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echo *************************
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echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
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call cmd /k
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) ELSE IF /I "%choice%" == "9" (
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) ELSE IF /I "%choice%" == "8" (
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echo Running invokeai-update...
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python -m invokeai.frontend.install.invokeai_update
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) ELSE IF /I "%choice%" == "10" (
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) ELSE IF /I "%choice%" == "9" (
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echo Running the db maintenance script...
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python .venv\Scripts\invokeai-db-maintenance.exe
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) ELSE IF /I "%choice%" == "11" (
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) ELSE IF /I "%choice%" == "10" (
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echo Displaying command line help...
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python .venv\Scripts\invokeai-web.exe --help %*
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pause
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@ -58,52 +58,47 @@ do_choice() {
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invokeai-web $PARAMS
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;;
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2)
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clear
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printf "Explore InvokeAI nodes using a command-line interface\n"
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invokeai $PARAMS
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;;
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3)
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clear
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printf "Textual inversion training\n"
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invokeai-ti --gui $PARAMS
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;;
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4)
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3)
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clear
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printf "Merge models (diffusers type only)\n"
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invokeai-merge --gui $PARAMS
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;;
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5)
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4)
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clear
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printf "Download and install models\n"
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invokeai-model-install --root ${INVOKEAI_ROOT}
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;;
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6)
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5)
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clear
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printf "Change InvokeAI startup options\n"
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invokeai-configure --root ${INVOKEAI_ROOT} --skip-sd-weights --skip-support-models
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;;
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7)
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6)
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clear
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printf "Re-run the configure script to fix a broken install or to complete a major upgrade\n"
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invokeai-configure --root ${INVOKEAI_ROOT} --yes --default_only --skip-sd-weights
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;;
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8)
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7)
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||||
clear
|
||||
printf "Open the developer console\n"
|
||||
file_name=$(basename "${BASH_SOURCE[0]}")
|
||||
bash --init-file "$file_name"
|
||||
;;
|
||||
9)
|
||||
8)
|
||||
clear
|
||||
printf "Update InvokeAI\n"
|
||||
python -m invokeai.frontend.install.invokeai_update
|
||||
;;
|
||||
10)
|
||||
9)
|
||||
clear
|
||||
printf "Running the db maintenance script\n"
|
||||
invokeai-db-maintenance --root ${INVOKEAI_ROOT}
|
||||
;;
|
||||
11)
|
||||
10)
|
||||
clear
|
||||
printf "Command-line help\n"
|
||||
invokeai-web --help
|
||||
@ -121,16 +116,15 @@ do_choice() {
|
||||
do_dialog() {
|
||||
options=(
|
||||
1 "Generate images with a browser-based interface"
|
||||
2 "Explore InvokeAI nodes using a command-line interface"
|
||||
3 "Textual inversion training"
|
||||
4 "Merge models (diffusers type only)"
|
||||
5 "Download and install models"
|
||||
6 "Change InvokeAI startup options"
|
||||
7 "Re-run the configure script to fix a broken install or to complete a major upgrade"
|
||||
8 "Open the developer console"
|
||||
9 "Update InvokeAI"
|
||||
10 "Run the InvokeAI image database maintenance script"
|
||||
11 "Command-line help"
|
||||
2 "Textual inversion training"
|
||||
3 "Merge models (diffusers type only)"
|
||||
4 "Download and install models"
|
||||
5 "Change InvokeAI startup options"
|
||||
6 "Re-run the configure script to fix a broken install or to complete a major upgrade"
|
||||
7 "Open the developer console"
|
||||
8 "Update InvokeAI"
|
||||
9 "Run the InvokeAI image database maintenance script"
|
||||
10 "Command-line help"
|
||||
)
|
||||
|
||||
choice=$(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 "What would you like to do?\n"
|
||||
printf "1: Generate images using the browser-based interface\n"
|
||||
printf "2: Explore InvokeAI nodes using the command-line interface\n"
|
||||
printf "3: Run textual inversion training\n"
|
||||
printf "4: Merge models (diffusers type only)\n"
|
||||
printf "5: Download and install models\n"
|
||||
printf "6: Change InvokeAI startup options\n"
|
||||
printf "7: Re-run the configure script to fix a broken install\n"
|
||||
printf "8: Open the developer console\n"
|
||||
printf "9: Update InvokeAI\n"
|
||||
printf "10: Run the InvokeAI image database maintenance script\n"
|
||||
printf "11: Command-line help\n"
|
||||
printf "2: Run textual inversion training\n"
|
||||
printf "3: Merge models (diffusers type only)\n"
|
||||
printf "4: Download and install models\n"
|
||||
printf "5: Change InvokeAI startup options\n"
|
||||
printf "6: Re-run the configure script to fix a broken install\n"
|
||||
printf "7: Open the developer console\n"
|
||||
printf "8: Update InvokeAI\n"
|
||||
printf "9: Run the InvokeAI image database maintenance script\n"
|
||||
printf "10: Command-line help\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'}
|
||||
do_choice $choice
|
||||
clear
|
||||
|
||||
@ -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()
|
||||
@ -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)
|
||||
@ -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()
|
||||
@ -134,6 +134,7 @@ nav:
|
||||
- List of Default Nodes: 'nodes/defaultNodes.md'
|
||||
- Workflow Editor Usage: 'nodes/NODES.md'
|
||||
- ComfyUI to InvokeAI: 'nodes/comfyToInvoke.md'
|
||||
- Facetool Node: 'nodes/detailedNodes/faceTools.md'
|
||||
- Contributing Nodes: 'nodes/contributingNodes.md'
|
||||
- Features:
|
||||
- Overview: 'features/index.md'
|
||||
@ -144,7 +145,7 @@ nav:
|
||||
- Image-to-Image: 'features/IMG2IMG.md'
|
||||
- Controlling Logging: 'features/LOGGING.md'
|
||||
- Model Merging: 'features/MODEL_MERGING.md'
|
||||
- Using Nodes : './nodes/overview'
|
||||
- Using Nodes : 'nodes/overview.md'
|
||||
- NSFW Checker: 'features/WATERMARK+NSFW.md'
|
||||
- Postprocessing: 'features/POSTPROCESS.md'
|
||||
- Prompting Features: 'features/PROMPTS.md'
|
||||
@ -152,15 +153,18 @@ nav:
|
||||
- Unified Canvas: 'features/UNIFIED_CANVAS.md'
|
||||
- InvokeAI Web Server: 'features/WEB.md'
|
||||
- WebUI Hotkeys: "features/WEBUIHOTKEYS.md"
|
||||
- Maintenance Utilities: "features/UTILITIES.md"
|
||||
- Other: 'features/OTHER.md'
|
||||
- Contributing:
|
||||
- How to Contribute: 'contributing/CONTRIBUTING.md'
|
||||
- InvokeAI Code of Conduct: 'CODE_OF_CONDUCT.md'
|
||||
- Development:
|
||||
- Overview: 'contributing/contribution_guides/development.md'
|
||||
- New Contributors: 'contributing/contribution_guides/newContributorChecklist.md'
|
||||
- InvokeAI Architecture: 'contributing/ARCHITECTURE.md'
|
||||
- Frontend Documentation: 'contributing/contribution_guides/contributingToFrontend.md'
|
||||
- Local Development: 'contributing/LOCAL_DEVELOPMENT.md'
|
||||
- Adding Tests: 'contributing/TESTS.md'
|
||||
- Documentation: 'contributing/contribution_guides/documentation.md'
|
||||
- Nodes: 'contributing/INVOCATIONS.md'
|
||||
- Translation: 'contributing/contribution_guides/translation.md'
|
||||
@ -168,9 +172,12 @@ nav:
|
||||
- Changelog: 'CHANGELOG.md'
|
||||
- Deprecated:
|
||||
- Command Line Interface: 'deprecated/CLI.md'
|
||||
- Variations: 'deprecated/VARIATIONS.md'
|
||||
- Translations: 'deprecated/TRANSLATION.md'
|
||||
- Embiggen: 'deprecated/EMBIGGEN.md'
|
||||
- Inpainting: 'deprecated/INPAINTING.md'
|
||||
- Outpainting: 'deprecated/OUTPAINTING.md'
|
||||
- Troubleshooting: 'help/deprecated/TROUBLESHOOT.md'
|
||||
- Help:
|
||||
- Getting Started: 'help/gettingStartedWithAI.md'
|
||||
- Diffusion Overview: 'help/diffusion.md'
|
||||
|
||||
@ -125,7 +125,7 @@ dependencies = [
|
||||
# shortcut commands to start cli and web
|
||||
# "invokeai --web" will launch the web interface
|
||||
# "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
|
||||
"invokeai-web" = "invokeai.app.api_app:invoke_api"
|
||||
@ -138,7 +138,6 @@ dependencies = [
|
||||
"invokeai-migrate3" = "invokeai.backend.install.migrate_to_3:main"
|
||||
"invokeai-update" = "invokeai.frontend.install.invokeai_update: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-import-images" = "invokeai.frontend.install.import_images:main"
|
||||
"invokeai-db-maintenance" = "invokeai.backend.util.db_maintenance:main"
|
||||
|
||||
Loading…
Reference in New Issue
Block a user