5f498e10bd
* feat(ui): add axios client generator and simple example * fix(ui): update client & nodes test code w/ new Edge type * chore(ui): organize generated files * chore(ui): update .eslintignore, .prettierignore * chore(ui): update openapi.json * feat(backend): fixes for nodes/generator * feat(ui): generate object args for api client * feat(ui): more nodes api prototyping * feat(ui): nodes cancel * chore(ui): regenerate api client * fix(ui): disable OG web server socket connection * fix(ui): fix scrollbar styles typing and prop just noticed the typo, and made the types stronger. * feat(ui): add socketio types * feat(ui): wip nodes - extract api client method arg types instead of manually declaring them - update example to display images - general tidy up * start building out node translations from frontend state and add notes about missing features * use reference to sampler_name * use reference to sampler_name * add optional apiUrl prop * feat(ui): start hooking up dynamic txt2img node generation, create middleware for session invocation * feat(ui): write separate nodes socket layer, txt2img generating and rendering w single node * feat(ui): img2img implementation * feat(ui): get intermediate images working but types are stubbed out * chore(ui): add support for package mode * feat(ui): add nodes mode script * feat(ui): handle random seeds * fix(ui): fix middleware types * feat(ui): add rtk action type guard * feat(ui): disable NodeAPITest This was polluting the network/socket logs. * feat(ui): fix parameters panel border color This commit should be elsewhere but I don't want to break my flow * feat(ui): make thunk types more consistent * feat(ui): add type guards for outputs * feat(ui): load images on socket connect Rudimentary * chore(ui): bump redux-toolkit * docs(ui): update readme * chore(ui): regenerate api client * chore(ui): add typescript as dev dependency I am having trouble with TS versions after vscode updated and now uses TS 5. `madge` has installed 3.9.10 and for whatever reason my vscode wants to use that. Manually specifying 4.9.5 and then setting vscode to use that as the workspace TS fixes the issue. * feat(ui): begin migrating gallery to nodes Along the way, migrate to use RTK `createEntityAdapter` for gallery images, and separate `results` and `uploads` into separate slices. Much cleaner this way. * feat(ui): clean up & comment results slice * fix(ui): separate thunk for initial gallery load so it properly gets index 0 * feat(ui): POST upload working * fix(ui): restore removed type * feat(ui): patch api generation for headers access * chore(ui): regenerate api * feat(ui): wip gallery migration * feat(ui): wip gallery migration * chore(ui): regenerate api * feat(ui): wip refactor socket events * feat(ui): disable panels based on app props * feat(ui): invert logic to be disabled * disable panels when app mounts * feat(ui): add support to disableTabs * docs(ui): organise and update docs * lang(ui): add toast strings * feat(ui): wip events, comments, and general refactoring * feat(ui): add optional token for auth * feat(ui): export StatusIndicator and ModelSelect for header use * feat(ui) working on making socket URL dynamic * feat(ui): dynamic middleware loading * feat(ui): prep for socket jwt * feat(ui): migrate cancelation also updated action names to be event-like instead of declaration-like sorry, i was scattered and this commit has a lot of unrelated stuff in it. * fix(ui): fix img2img type * chore(ui): regenerate api client * feat(ui): improve InvocationCompleteEvent types * feat(ui): increase StatusIndicator font size * fix(ui): fix middleware order for multi-node graphs * feat(ui): add exampleGraphs object w/ iterations example * feat(ui): generate iterations graph * feat(ui): update ModelSelect for nodes API * feat(ui): add hi-res functionality for txt2img generations * feat(ui): "subscribe" to particular nodes feels like a dirty hack but oh well it works * feat(ui): first steps to node editor ui * fix(ui): disable event subscription it is not fully baked just yet * feat(ui): wip node editor * feat(ui): remove extraneous field types * feat(ui): nodes before deleting stuff * feat(ui): cleanup nodes ui stuff * feat(ui): hook up nodes to redux * fix(ui): fix handle * fix(ui): add basic node edges & connection validation * feat(ui): add connection validation styling * feat(ui): increase edge width * feat(ui): it blends * feat(ui): wip model handling and graph topology validation * feat(ui): validation connections w/ graphlib * docs(ui): update nodes doc * feat(ui): wip node editor * chore(ui): rebuild api, update types * add redux-dynamic-middlewares as a dependency * feat(ui): add url host transformation * feat(ui): handle already-connected fields * feat(ui): rewrite SqliteItemStore in sqlalchemy * fix(ui): fix sqlalchemy dynamic model instantiation * feat(ui, nodes): metadata wip * feat(ui, nodes): models * feat(ui, nodes): more metadata wip * feat(ui): wip range/iterate * fix(nodes): fix sqlite typing * feat(ui): export new type for invoke component * tests(nodes): fix test instantiation of ImageField * feat(nodes): fix LoadImageInvocation * feat(nodes): add `title` ui hint * feat(nodes): make ImageField attrs optional * feat(ui): wip nodes etc * feat(nodes): roll back sqlalchemy * fix(nodes): partially address feedback * fix(backend): roll back changes to pngwriter * feat(nodes): wip address metadata feedback * feat(nodes): add seeded rng to RandomRange * feat(nodes): address feedback * feat(nodes): move GET images error handling to DiskImageStorage * feat(nodes): move GET images error handling to DiskImageStorage * fix(nodes): fix image output schema customization * feat(ui): img2img/txt2img -> linear - remove txt2img and img2img tabs - add linear tab - add initial image selection to linear parameters accordion * feat(ui): tidy graph builders * feat(ui): tidy misc * feat(ui): improve invocation union types * feat(ui): wip metadata viewer recall * feat(ui): move fonts to normal deps * feat(nodes): fix broken upload * feat(nodes): add metadata module + tests, thumbnails - `MetadataModule` is stateless and needed in places where the `InvocationContext` is not available, so have not made it a `service` - Handles loading/parsing/building metadata, and creating png info objects - added tests for MetadataModule - Lifted thumbnail stuff to util * fix(nodes): revert change to RandomRangeInvocation * feat(nodes): address feedback - make metadata a service - rip out pydantic validation, implement metadata parsing as simple functions - update tests - address other minor feedback items * fix(nodes): fix other tests * fix(nodes): add metadata service to cli * fix(nodes): fix latents/image field parsing * feat(nodes): customise LatentsField schema * feat(nodes): move metadata parsing to frontend * fix(nodes): fix metadata test --------- Co-authored-by: maryhipp <maryhipp@gmail.com> Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local> |
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.dev_scripts | ||
.github | ||
binary_installer | ||
coverage | ||
docker | ||
docs | ||
installer | ||
invokeai | ||
notebooks | ||
scripts | ||
static | ||
tests | ||
.dockerignore | ||
.editorconfig | ||
.git-blame-ignore-revs | ||
.gitattributes | ||
.gitignore | ||
.gitmodules | ||
.prettierrc.yaml | ||
CODE_OF_CONDUCT.md | ||
InvokeAI_Statement_of_Values.md | ||
LICENSE | ||
LICENSE-ModelWeights.txt | ||
mkdocs.yml | ||
pyproject.toml | ||
README.md | ||
shell.nix | ||
Stable_Diffusion_v1_Model_Card.md |
InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
Quick links: [How to Install] [Discord Server] [Documentation and Tutorials] [Code and Downloads] [Bug Reports] [Discussion, Ideas & Q&A]
Note: InvokeAI is rapidly evolving. Please use the Issues tab to report bugs and make feature requests. Be sure to use the provided templates. They will help us diagnose issues faster.
Table of Contents
- Quick Start
- Installation
- Hardware Requirements
- Features
- Latest Changes
- Troubleshooting
- Contributing
- Contributors
- Support
- Further Reading
Getting Started with InvokeAI
For full installation and upgrade instructions, please see: InvokeAI Installation Overview
Automatic Installer (suggested for 1st time users)
-
Go to the bottom of the Latest Release Page
-
Download the .zip file for your OS (Windows/macOS/Linux).
-
Unzip the file.
-
If you are on Windows, double-click on the
install.bat
script. On macOS, open a Terminal window, drag the fileinstall.sh
from Finder into the Terminal, and press return. On Linux, runinstall.sh
. -
You'll be asked to confirm the location of the folder in which to install InvokeAI and its image generation model files. Pick a location with at least 15 GB of free memory. More if you plan on installing lots of models.
-
Wait while the installer does its thing. After installing the software, the installer will launch a script that lets you configure InvokeAI and select a set of starting image generation models.
-
Find the folder that InvokeAI was installed into (it is not the same as the unpacked zip file directory!) The default location of this folder (if you didn't change it in step 5) is
~/invokeai
on Linux/Mac systems, andC:\Users\YourName\invokeai
on Windows. This directory will contain launcher scripts namedinvoke.sh
andinvoke.bat
. -
On Windows systems, double-click on the
invoke.bat
file. On macOS, open a Terminal window, draginvoke.sh
from the folder into the Terminal, and press return. On Linux, runinvoke.sh
-
Press 2 to open the "browser-based UI", press enter/return, wait a minute or two for Stable Diffusion to start up, then open your browser and go to http://localhost:9090.
-
Type
banana sushi
in the box on the top left and clickInvoke
Command-Line Installation (for users familiar with Terminals)
You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are not supported.
-
Open a command-line window on your machine. The PowerShell is recommended for Windows.
-
Create a directory to install InvokeAI into. You'll need at least 15 GB of free space:
mkdir invokeai
-
Create a virtual environment named
.venv
inside this directory and activate it:cd invokeai python -m venv .venv --prompt InvokeAI
-
Activate the virtual environment (do it every time you run InvokeAI)
For Linux/Mac users:
source .venv/bin/activate
For Windows users:
.venv\Scripts\activate
-
Install the InvokeAI module and its dependencies. Choose the command suited for your platform & GPU.
For Windows/Linux with an NVIDIA GPU:
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu117
For Linux with an AMD GPU:
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
For non-GPU systems:
pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
For Macintoshes, either Intel or M1/M2:
pip install InvokeAI --use-pep517
-
Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
invokeai-configure
-
Launch the web server (do it every time you run InvokeAI):
invokeai --web
-
Point your browser to http://localhost:9090 to bring up the web interface.
-
Type
banana sushi
in the box on the top left and clickInvoke
.
Be sure to activate the virtual environment each time before re-launching InvokeAI,
using source .venv/bin/activate
or .venv\Scripts\activate
.
Detailed Installation Instructions
This fork is supported across Linux, Windows and Macintosh. Linux users can use either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm driver). For full installation and upgrade instructions, please see: InvokeAI Installation Overview
Hardware Requirements
InvokeAI is supported across Linux, Windows and macOS. Linux users can use either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm driver).
System
You will need one of the following:
- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- An Apple computer with an M1 chip.
- An AMD-based graphics card with 4GB or more VRAM memory. (Linux only)
We do not recommend the GTX 1650 or 1660 series video cards. They are unable to run in half-precision mode and do not have sufficient VRAM to render 512x512 images.
Memory
- At least 12 GB Main Memory RAM.
Disk
- At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
Features
Feature documentation can be reviewed by navigating to the InvokeAI Documentation page
Web Server & UI
InvokeAI offers a locally hosted Web Server & React Frontend, with an industry leading user experience. The Web-based UI allows for simple and intuitive workflows, and is responsive for use on mobile devices and tablets accessing the web server.
Unified Canvas
The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/outpainting, brush tools, and more. This creative tool unlocks the capability for artists to create with AI as a creative collaborator, and can be used to augment AI-generated imagery, sketches, photography, renders, and more.
Advanced Prompt Syntax
InvokeAI's advanced prompt syntax allows for token weighting, cross-attention control, and prompt blending, allowing for fine-tuned tweaking of your invocations and exploration of the latent space.
Command Line Interface
For users utilizing a terminal-based environment, or who want to take advantage of CLI features, InvokeAI offers an extensive and actively supported command-line interface that provides the full suite of generation functionality available in the tool.
Other features
- Support for both ckpt and diffusers models
- SD 2.0, 2.1 support
- Noise Control & Tresholding
- Popular Sampler Support
- Upscaling & Face Restoration Tools
- Embedding Manager & Support
- Model Manager & Support
Coming Soon
- Node-Based Architecture & UI
- And more...
Latest Changes
For our latest changes, view our Release Notes and the CHANGELOG.
Troubleshooting
Please check out our Q&A to get solutions for common installation problems and other issues.
Contributing
Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code cleanup, testing, or code reviews, is very much encouraged to do so.
To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
If you'd like to help with translation, please see our translation guide.
If you are unfamiliar with how to contribute to GitHub projects, here is a Getting Started Guide. A full set of contribution guidelines, along with templates, are in progress. You can make your pull request against the "main" branch.
We hope you enjoy using our software as much as we enjoy creating it, and we hope that some of those of you who are reading this will elect to become part of our community.
Welcome to InvokeAI!
Contributors
This fork is a combined effort of various people from across the world. Check out the list of all these amazing people. We thank them for their time, hard work and effort.
Thanks to Weblate for generously providing translation services to this project.
Support
For support, please use this repository's GitHub Issues tracking service, or join the Discord.
Original portions of the software are Copyright (c) 2023 by respective contributors.