Merge remote-tracking branch 'origin/main' into dev/diffusers

# Conflicts:
#	scripts/configure_invokeai.py

README.md

@@ -38,18 +38,32 @@ This is a fork of
 [CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion),
 the open source text-to-image generator. It provides a streamlined
 process with various new features and options to aid the image
-generation process. It runs on Windows, Mac and Linux machines, with
+generation process. It runs on Windows, macOS and Linux machines, with
 GPU cards with as little as 4 GB of RAM. It provides both a polished
 Web interface (see below), and an easy-to-use command-line interface.
 
-**Quick links**: [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
+**Quick links**: [[How to Install](#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]
+
+_Note: InvokeAI is rapidly evolving. Please use the
+[Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
+requests. Be sure to use the provided templates. They will help us diagnose issues faster._
+
+## Installation Quick-Start
+
+1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/tag/v2.2.3)
+2. Download the .zip file for your OS (Windows/macOS/Linux).
+3. Unzip the file. 
+4. If you are on Windows, double-click on the `install.bat` script. On macOS, open a Terminal window, drag the file `install.sh` from Finder into the Terminal, and press return. On Linux, run `install.sh`.
+5. Wait a while, until it is done. 
+6. The folder where you ran the installer from will now be filled with lots of files. If you are on Windows, double-click on the `invoke.bat` file. On macOS, open a Terminal window, drag `invoke.sh` from the folder into the Terminal, and press return. On Linux, run `invoke.sh`
+7. 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. 
+8. Type `banana sushi` in the box on the top left and click `Invoke`:
 
 <div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
 
 
-_Note: This fork is rapidly evolving. Please use the
+For full installation and upgrade instructions, please see:
-[Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature
+[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
-requests. Be sure to use the provided templates. They will help aid diagnose issues faster._
 
 ## Table of Contents
 
@@ -69,10 +83,13 @@ 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](https://invoke-ai.github.io/InvokeAI/installation/)
+[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_SOURCE/)
 
 ### 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 wil need one of the following:
@@ -80,6 +97,10 @@ You wil need one of the following:
 - An NVIDIA-based graphics card with 4 GB or more VRAM memory.
 - An Apple computer with an M1 chip.
 
+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.
@@ -130,12 +151,12 @@ you can try starting `invoke.py` with the `--precision=float32` flag:
 
 ### Latest Changes
 
-- v2.0.1 (13 October 2022)
+- v2.0.1 (13 November 2022)
   - fix noisy images at high step count when using k* samplers
   - dream.py script now calls invoke.py module directly rather than
     via a new python process (which could break the environment)
 
-- v2.0.0 (9 October 2022)
+- v2.0.0 (9 November 2022)
 
   - `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
     for backward compatibility.
@@ -144,7 +165,7 @@ you can try starting `invoke.py` with the `--precision=float32` flag:
   - img2img runs on all k* samplers
   - Support for <a href="https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#negative-and-unconditioned-prompts">negative prompts</a>
   - Support for CodeFormer face reconstruction
-  - Support for Textual Inversion on Macintoshes
+  - Support for Textual Inversion on macOS
   - Support in both WebGUI and CLI for <a href="https://invoke-ai.github.io/InvokeAI/features/POSTPROCESS/">post-processing of previously-generated images</a>
     using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
     and "embiggen" upscaling. See the `!fix` command.
@@ -153,7 +174,7 @@ you can try starting `invoke.py` with the `--precision=float32` flag:
     during image generation (see <a href="https://github.com/invoke-ai/InvokeAI/blob/main/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options">Thresholding and Perlin Noise Initialization</a>
   - Extensive metadata now written into PNG files, allowing reliable regeneration of images
     and tweaking of previous settings.
-  - Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
+  - Command-line completion in `invoke.py` now works on Windows, Linux and macOS platforms.
   - Improved <a href="https://invoke-ai.github.io/InvokeAI/features/CLI/">command-line completion behavior</a>.
     New commands added:
     - List command-line history with `!history`

backend/invoke_ai_web_server.py

@@ -206,9 +206,10 @@ class InvokeAIWebServer:
                 FlaskUI(
                     app=self.app,
                     socketio=self.socketio,
-                    server="flask_socketio",
+                    start_server="flask-socketio",
                     width=1600,
                     height=1000,
+                    idle_interval=10,
                     port=self.port
                 ).run()
             except KeyboardInterrupt:

binary_installer/create_installers.sh

@@ -6,6 +6,8 @@ IFS=$'\n\t'
 echo "Be certain that you're in the 'installer' directory before continuing."
 read -p "Press any key to continue, or CTRL-C to exit..."
 
+VERSION='2.2.3'
+
 # make the installer zip for linux and mac
 rm -rf InvokeAI
 mkdir -p InvokeAI
@@ -13,8 +15,8 @@ cp install.sh.in InvokeAI/install.sh
 chmod a+x InvokeAI/install.sh
 cp readme.txt InvokeAI
 
-zip -r InvokeAI-binary-linux.zip InvokeAI
+zip -r InvokeAI-binary-$VERSION-linux.zip InvokeAI
-zip -r InvokeAI-binary-mac.zip InvokeAI
+zip -r InvokeAI-binary-$VERSION-mac.zip InvokeAI
 
 # make the installer zip for windows
 rm -rf InvokeAI
@@ -23,7 +25,7 @@ cp install.bat.in InvokeAI/install.bat
 cp readme.txt InvokeAI
 cp WinLongPathsEnabled.reg InvokeAI
 
-zip -r InvokeAI-binary-windows.zip InvokeAI
+zip -r InvokeAI-binary-$VERSION-windows.zip InvokeAI
 
 rm -rf InvokeAI
 

binary_installer/install.bat.in

@@ -10,13 +10,15 @@
 
 @rem This enables a user to install this project without manually installing git or Python
 
+@rem change to the script's directory
+PUSHD "%~dp0"
+
 set "no_cache_dir=--no-cache-dir"
 if "%1" == "use-cache" (
     set "no_cache_dir="
 )
 
 echo ***** Installing InvokeAI.. *****
-echo "USING development BRANCH. REMEMBER TO CHANGE TO main BEFORE RELEASE"
 @rem Config
 set INSTALL_ENV_DIR=%cd%\installer_files\env
 @rem https://mamba.readthedocs.io/en/latest/installation.html

binary_installer/install.sh.in

@@ -214,7 +214,7 @@ _err_exit $? _err_msg
 echo -e "\n***** Installed InvokeAI *****\n"
 
 cp binary_installer/invoke.sh.in ./invoke.sh
-chmod a+x ./invoke.sh
+chmod a+rx ./invoke.sh
 echo -e "\n***** Installed invoke launcher script ******\n"
 
 # more cleanup
@@ -229,7 +229,7 @@ deactivate
 echo -e "\n***** Finished downloading models *****\n"
 
 echo "All done! Run the command"
-echo "  \"$scriptdir/invoke.sh\""
+echo "  $scriptdir/invoke.sh"
 echo "to start InvokeAI."
 read -p "Press any key to exit..."
 exit

binary_installer/invoke.bat.in

@@ -1,5 +1,6 @@
 @echo off
 
+PUSHD "%~dp0"
 call .venv\Scripts\activate.bat
 
 echo Do you want to generate images using the
@@ -10,10 +11,10 @@ echo 3. open the developer console
 set /p choice="Please enter 1, 2 or 3: "
 if /i "%choice%" == "1" (
     echo Starting the InvokeAI command-line.
-    .venv\Scripts\python scripts\invoke.py
+    .venv\Scripts\python scripts\invoke.py %*
 ) else if /i "%choice%" == "2" (
     echo Starting the InvokeAI browser-based UI.
-    .venv\Scripts\python scripts\invoke.py --web
+    .venv\Scripts\python scripts\invoke.py --web %*
 ) else if /i "%choice%" == "3" (
     echo Developer Console
     echo Python command is:

binary_installer/invoke.sh.in

@@ -4,6 +4,11 @@ set -eu
 
 . .venv/bin/activate
 
+# set required env var for torch on mac MPS
+ if [ "$(uname -s)" == "Darwin" ]; then
+     export PYTORCH_ENABLE_MPS_FALLBACK=1
+ fi
+
 echo "Do you want to generate images using the"
 echo "1. command-line"
 echo "2. browser-based UI"
@@ -15,11 +20,11 @@ read choice
 case $choice in
     1)
         printf "\nStarting the InvokeAI command-line..\n";
-        .venv/bin/python scripts/invoke.py;
+        .venv/bin/python scripts/invoke.py $*;
     ;;
     2)
         printf "\nStarting the InvokeAI browser-based UI..\n";
-        .venv/bin/python scripts/invoke.py --web;
+        .venv/bin/python scripts/invoke.py --web $*;
     ;;
     3)
         printf "\nDeveloper Console:\n";

binary_installer/py3.10-darwin-x86_64-cpu-reqs.txt

@@ -4,7 +4,7 @@
 #
 #    pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-darwin-x86_64-cpu-reqs.txt installer/requirements.in
 #
---extra-index-url https://download.pytorch.org/whl/torch_stable.html
+--extra-index-url https://download.pytorch.org/whl/cu116
 --trusted-host https
 
 absl-py==1.3.0 \
@@ -987,7 +987,6 @@ numpy==1.23.4 \
     #   pandas
     #   pyarrow
     #   pydeck
-    #   pypatchmatch
     #   pytorch-lightning
     #   pywavelets
     #   qudida
@@ -1160,7 +1159,6 @@ pillow==9.3.0 \
     #   imageio
     #   k-diffusion
     #   matplotlib
-    #   pypatchmatch
     #   realesrgan
     #   scikit-image
     #   streamlit
@@ -1296,9 +1294,6 @@ pyparsing==3.0.9 \
     # via
     #   matplotlib
     #   packaging
-pypatchmatch @ https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip \
-    --hash=sha256:4ad6ec95379e7d122d494ff76633cc7cf9b71330d5efda147fceba81e3dc6cd2
-    # via -r installer/requirements.in
 pyreadline3==3.4.1 \
     --hash=sha256:6f3d1f7b8a31ba32b73917cefc1f28cc660562f39aea8646d30bd6eff21f7bae \
     --hash=sha256:b0efb6516fd4fb07b45949053826a62fa4cb353db5be2bbb4a7aa1fdd1e345fb
@@ -1831,27 +1826,27 @@ toolz==0.12.0 \
     --hash=sha256:2059bd4148deb1884bb0eb770a3cde70e7f954cfbbdc2285f1f2de01fd21eb6f \
     --hash=sha256:88c570861c440ee3f2f6037c4654613228ff40c93a6c25e0eba70d17282c6194
     # via altair
-torch==1.12.1 ; platform_system == "Darwin" \
+torch==1.12.0 ; platform_system == "Darwin" \
-    --hash=sha256:03e31c37711db2cd201e02de5826de875529e45a55631d317aadce2f1ed45aa8 \
+    --hash=sha256:0399746f83b4541bcb5b219a18dbe8cade760aba1c660d2748a38c6dc338ebc7 \
-    --hash=sha256:0b44601ec56f7dd44ad8afc00846051162ef9c26a8579dda0a02194327f2d55e \
+    --hash=sha256:0986685f2ec8b7c4d3593e8cfe96be85d462943f1a8f54112fc48d4d9fbbe903 \
-    --hash=sha256:42e115dab26f60c29e298559dbec88444175528b729ae994ec4c65d56fe267dd \
+    --hash=sha256:13c7cca6b2ea3704d775444f02af53c5f072d145247e17b8cd7813ac57869f03 \
-    --hash=sha256:42f639501928caabb9d1d55ddd17f07cd694de146686c24489ab8c615c2871f2 \
+    --hash=sha256:201abf43a99bb4980cc827dd4b38ac28f35e4dddac7832718be3d5479cafd2c1 \
-    --hash=sha256:4e1b9c14cf13fd2ab8d769529050629a0e68a6fc5cb8e84b4a3cc1dd8c4fe541 \
+    --hash=sha256:2143d5fe192fd908b70b494349de5b1ac02854a8a902bd5f47d13d85b410e430 \
-    --hash=sha256:68104e4715a55c4bb29a85c6a8d57d820e0757da363be1ba680fa8cc5be17b52 \
+    --hash=sha256:2568f011dddeb5990d8698cc375d237f14568ffa8489854e3b94113b4b6b7c8b \
-    --hash=sha256:69fe2cae7c39ccadd65a123793d30e0db881f1c1927945519c5c17323131437e \
+    --hash=sha256:3322d33a06e440d715bb214334bd41314c94632d9a2f07d22006bf21da3a2be4 \
-    --hash=sha256:6cf6f54b43c0c30335428195589bd00e764a6d27f3b9ba637aaa8c11aaf93073 \
+    --hash=sha256:349ea3ba0c0e789e0507876c023181f13b35307aebc2e771efd0e045b8e03e84 \
-    --hash=sha256:743784ccea0dc8f2a3fe6a536bec8c4763bd82c1352f314937cb4008d4805de1 \
+    --hash=sha256:44a3804e9bb189574f5d02ccc2dc6e32e26a81b3e095463b7067b786048c6072 \
-    --hash=sha256:8a34a2fbbaa07c921e1b203f59d3d6e00ed379f2b384445773bd14e328a5b6c8 \
+    --hash=sha256:5ed69d5af232c5c3287d44cef998880dadcc9721cd020e9ae02f42e56b79c2e4 \
-    --hash=sha256:976c3f997cea38ee91a0dd3c3a42322785414748d1761ef926b789dfa97c6134 \
+    --hash=sha256:60d06ee2abfa85f10582d205404d52889d69bcbb71f7e211cfc37e3957ac19ca \
-    --hash=sha256:9b356aea223772cd754edb4d9ecf2a025909b8615a7668ac7d5130f86e7ec421 \
+    --hash=sha256:63341f96840a223f277e498d2737b39da30d9f57c7a1ef88857b920096317739 \
-    --hash=sha256:9c038662db894a23e49e385df13d47b2a777ffd56d9bcd5b832593fab0a7e286 \
+    --hash=sha256:72207b8733523388c49d43ffcc4416d1d8cd64c40f7826332e714605ace9b1d2 \
-    --hash=sha256:a8320ba9ad87e80ca5a6a016e46ada4d1ba0c54626e135d99b2129a4541c509d \
+    --hash=sha256:7ddb167827170c4e3ff6a27157414a00b9fef93dea175da04caf92a0619b7aee \
-    --hash=sha256:b5dbcca369800ce99ba7ae6dee3466607a66958afca3b740690d88168752abcf \
+    --hash=sha256:844f1db41173b53fe40c44b3e04fcca23a6ce00ac328b7099f2800e611766845 \
-    --hash=sha256:bfec2843daa654f04fda23ba823af03e7b6f7650a873cdb726752d0e3718dada \
+    --hash=sha256:a1325c9c28823af497cbf443369bddac9ac59f67f1e600f8ab9b754958e55b76 \
-    --hash=sha256:cd26d8c5640c3a28c526d41ccdca14cf1cbca0d0f2e14e8263a7ac17194ab1d2 \
+    --hash=sha256:abbdc5483359b9495dc76e3bd7911ccd2ddc57706c117f8316832e31590af871 \
-    --hash=sha256:e9c8f4a311ac29fc7e8e955cfb7733deb5dbe1bdaabf5d4af2765695824b7e0d \
+    --hash=sha256:c0313438bc36448ffd209f5fb4e5f325b3af158cdf61c8829b8ddaf128c57816 \
-    --hash=sha256:f00c721f489089dc6364a01fd84906348fe02243d0af737f944fddb36003400d \
+    --hash=sha256:e3e8348edca3e3cee5a67a2b452b85c57712efe1cc3ffdb87c128b3dde54534e \
-    --hash=sha256:f3b52a634e62821e747e872084ab32fbcb01b7fa7dbb7471b6218279f02a178a
+    --hash=sha256:fb47291596677570246d723ee6abbcbac07eeba89d8f83de31e3954f21f44879
     # via
     #   -r installer/requirements.in
     #   accelerate
@@ -1882,26 +1877,26 @@ torchmetrics==0.10.2 \
     --hash=sha256:43757d82266969906fc74b6e80766fcb2a0d52d6c3d09e3b7c98cf3b733fd20c \
     --hash=sha256:daa29d96bff5cff04d80eec5b9f5076993d6ac9c2d2163e88b6b31f8d38f7c25
     # via pytorch-lightning
-torchvision==0.13.1 ; platform_system == "Darwin" \
+torchvision==0.13.0 ; platform_system == "Darwin" \
-    --hash=sha256:0298bae3b09ac361866088434008d82b99d6458fe8888c8df90720ef4b347d44 \
+    --hash=sha256:01e9e7b2e7724e66561e8d98f900985d80191e977c5c0b3f33ed31800ba0210c \
-    --hash=sha256:08f592ea61836ebeceb5c97f4d7a813b9d7dc651bbf7ce4401563ccfae6a21fc \
+    --hash=sha256:0e28740bd5695076f7c449af650fc474d6566722d446461c2ceebf9c9599b37f \
-    --hash=sha256:099874088df104d54d8008f2a28539ca0117b512daed8bf3c2bbfa2b7ccb187a \
+    --hash=sha256:1b703701f0b99f307ad925b1abda2b3d5bdbf30643ff02102b6aeeb8840ae278 \
-    --hash=sha256:0e77706cc90462653620e336bb90daf03d7bf1b88c3a9a3037df8d111823a56e \
+    --hash=sha256:1e2049f1207631d42d743205f663f1d2235796565be3f18b0339d479626faf30 \
-    --hash=sha256:19286a733c69dcbd417b86793df807bd227db5786ed787c17297741a9b0d0fc7 \
+    --hash=sha256:253eb0c67bf88cef4a79ec69058c3e94f9fde28b9e3699ad1afc0b3ed50f8075 \
-    --hash=sha256:3567fb3def829229ec217c1e38f08c5128ff7fb65854cac17ebac358ff7aa309 \
+    --hash=sha256:42d95ab197d090efc5669fec02fbc603d05c859e50ca2c60180d1a113aa9b3e2 \
-    --hash=sha256:4d8bf321c4380854ef04613935fdd415dce29d1088a7ff99e06e113f0efe9203 \
+    --hash=sha256:5c31e9b3004142dbfdf32adc4cf2d4fd709b820833e9786f839ae3a91ff65ef0 \
-    --hash=sha256:5e631241bee3661de64f83616656224af2e3512eb2580da7c08e08b8c965a8ac \
+    --hash=sha256:61d5093a50b7923a4e5bf9e0271001c29e01abec2348b7dd93370a0a9d15836c \
-    --hash=sha256:7552e80fa222252b8b217a951c85e172a710ea4cad0ae0c06fbb67addece7871 \
+    --hash=sha256:667cac55afb13cda7d362466e7eba3119e529b210e55507d231bead09aca5e1f \
-    --hash=sha256:7cb789ceefe6dcd0dc8eeda37bfc45efb7cf34770eac9533861d51ca508eb5b3 \
+    --hash=sha256:6c4c35428c758adc485ff8f239b5ed68c1b6c26efa261a52e431cab0f7f22aec \
-    --hash=sha256:83e9e2457f23110fd53b0177e1bc621518d6ea2108f570e853b768ce36b7c679 \
+    --hash=sha256:83a4d9d50787d1e886c94486b63b15978391f6cf1892fce6a93132c09b14e128 \
-    --hash=sha256:87c137f343197769a51333076e66bfcd576301d2cd8614b06657187c71b06c4f \
+    --hash=sha256:a20662c11dc14fd4eff102ceb946a7ee80b9f98303bb52435cc903f2c4c1fe10 \
-    --hash=sha256:899eec0b9f3b99b96d6f85b9aa58c002db41c672437677b553015b9135b3be7e \
+    --hash=sha256:acb72a40e5dc0cd454d28514dbdd589a5057afd9bb5c785b87a54718b999bfa1 \
-    --hash=sha256:8e4d02e4d8a203e0c09c10dfb478214c224d080d31efc0dbf36d9c4051f7f3c6 \
+    --hash=sha256:ad458146aca15f652f9b0c227bebd5403602c7341f15f68f20ec119fa8e8f4a5 \
-    --hash=sha256:b167934a5943242da7b1e59318f911d2d253feeca0d13ad5d832b58eed943401 \
+    --hash=sha256:ada295dbfe55017b02acfab960a997387f5addbadd28ee5e575e24f692992ce4 \
-    --hash=sha256:c5ed609c8bc88c575226400b2232e0309094477c82af38952e0373edef0003fd \
+    --hash=sha256:b620a43df4131ad09f5761c415a016a9ea95aaf8ec8c91d030fb59bad591094a \
-    --hash=sha256:e9a563894f9fa40692e24d1aa58c3ef040450017cfed3598ff9637f404f3fe3b \
+    --hash=sha256:b7a2c9aebc7ef265777fe7e82577364288d98cf6b8cf0a63bb2621df78a7af1a \
-    --hash=sha256:ef5fe3ec1848123cd0ec74c07658192b3147dcd38e507308c790d5943e87b88c \
+    --hash=sha256:c2278a189663087bb8e65915062aa7a25b8f8e5a3cfaa5879fe277e23e4bbf40 \
-    --hash=sha256:f230a1a40ed70d51e463ce43df243ec520902f8725de2502e485efc5eea9d864
+    --hash=sha256:df16abf31e7a5fce8db1f781bf1e4f20c8bc730c7c3f657e946cc5820c04e465
     # via
     #   -r installer/requirements.in
     #   basicsr

binary_installer/py3.10-linux-x86_64-cuda-reqs.txt

@@ -1,10 +1,11 @@
 #
-# This file is autogenerated by pip-compile with python 3.9
+# This file is autogenerated by pip-compile with Python 3.9
-# To update, run:
+# by the following command:
 #
-#    pip-compile --allow-unsafe --generate-hashes --output-file=installer/py3.10-linux-x86_64-cuda-reqs.txt installer/requirements.in
+#    pip-compile --allow-unsafe --generate-hashes --output-file=binary_installer/py3.10-linux-x86_64-cuda-reqs.txt binary_installer/requirements.in
 #
 --extra-index-url https://download.pytorch.org/whl/torch_stable.html
+--extra-index-url https://download.pytorch.org/whl/cu116
 --trusted-host https
 
 absl-py==1.3.0 \
@@ -17,7 +18,7 @@ accelerate==0.14.0 \
     --hash=sha256:31c5bcc40564ef849b5bc1c4424a43ccaf9e26413b7df89c2e36bf81f070fd44 \
     --hash=sha256:b15d562c0889d0cf441b01faa025dfc29b163d061b6cc7d489c2c83b0a55ffab
     # via
-    #   -r installer/requirements.in
+    #   -r binary_installer/requirements.in
     #   k-diffusion
 addict==2.4.0 \
     --hash=sha256:249bb56bbfd3cdc2a004ea0ff4c2b6ddc84d53bc2194761636eb314d5cfa5dfc \
@@ -119,7 +120,7 @@ aiosignal==1.2.0 \
 albumentations==1.3.0 \
     --hash=sha256:294165d87d03bc8323e484927f0a5c1a3c64b0e7b9c32a979582a6c93c363bdf \
     --hash=sha256:be1af36832c8893314f2a5550e8ac19801e04770734c1b70fa3c996b41f37bed
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 altair==4.2.0 \
     --hash=sha256:0c724848ae53410c13fa28be2b3b9a9dcb7b5caa1a70f7f217bd663bb419935a \
     --hash=sha256:d87d9372e63b48cd96b2a6415f0cf9457f50162ab79dc7a31cd7e024dd840026
@@ -150,6 +151,10 @@ blinker==1.5 \
     --hash=sha256:1eb563df6fdbc39eeddc177d953203f99f097e9bf0e2b8f9f3cf18b6ca425e36 \
     --hash=sha256:923e5e2f69c155f2cc42dafbbd70e16e3fde24d2d4aa2ab72fbe386238892462
     # via streamlit
+boltons==21.0.0 \
+    --hash=sha256:65e70a79a731a7fe6e98592ecfb5ccf2115873d01dbc576079874629e5c90f13 \
+    --hash=sha256:b9bb7b58b2b420bbe11a6025fdef6d3e5edc9f76a42fb467afe7ca212ef9948b
+    # via torchsde
 cachetools==5.2.0 \
     --hash=sha256:6a94c6402995a99c3970cc7e4884bb60b4a8639938157eeed436098bf9831757 \
     --hash=sha256:f9f17d2aec496a9aa6b76f53e3b614c965223c061982d434d160f930c698a9db
@@ -183,11 +188,11 @@ click==8.1.3 \
 clip @ https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip \
     --hash=sha256:b5842c25da441d6c581b53a5c60e0c2127ebafe0f746f8e15561a006c6c3be6a
     # via
-    #   -r installer/requirements.in
+    #   -r binary_installer/requirements.in
     #   clipseg
 clipseg @ https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip \
     --hash=sha256:14f43ed42f90be3fe57f06de483cb8be0f67f87a6f62a011339d45a39f4b4189
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 commonmark==0.9.1 \
     --hash=sha256:452f9dc859be7f06631ddcb328b6919c67984aca654e5fefb3914d54691aed60 \
     --hash=sha256:da2f38c92590f83de410ba1a3cbceafbc74fee9def35f9251ba9a971d6d66fd9
@@ -274,7 +279,7 @@ decorator==5.1.1 \
 diffusers==0.7.2 \
     --hash=sha256:4a5f8b3a5fbd936bba7d459611cb35ec62875030367be32b232f9e19543e25a9 \
     --hash=sha256:fb814ffd150cc6f470380b8c6a521181a77beb2f44134d2aad2e4cd8aa2ced0e
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 dnspython==2.2.1 \
     --hash=sha256:0f7569a4a6ff151958b64304071d370daa3243d15941a7beedf0c9fe5105603e \
     --hash=sha256:a851e51367fb93e9e1361732c1d60dab63eff98712e503ea7d92e6eccb109b4f
@@ -294,7 +299,7 @@ entrypoints==0.4 \
 eventlet==0.33.1 \
     --hash=sha256:a085922698e5029f820cf311a648ac324d73cec0e4792877609d978a4b5bbf31 \
     --hash=sha256:afbe17f06a58491e9aebd7a4a03e70b0b63fd4cf76d8307bae07f280479b1515
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 facexlib==0.2.5 \
     --hash=sha256:31e20cc4ed5d63562d380e4564bae14ac0d5d1899a079bad87621e13564567e4 \
     --hash=sha256:cc7ceb56c5424319c47223cf75eef6828c34c66082707c6eb35b95d39779f02d
@@ -320,15 +325,15 @@ flask==2.2.2 \
 flask-cors==3.0.10 \
     --hash=sha256:74efc975af1194fc7891ff5cd85b0f7478be4f7f59fe158102e91abb72bb4438 \
     --hash=sha256:b60839393f3b84a0f3746f6cdca56c1ad7426aa738b70d6c61375857823181de
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 flask-socketio==5.3.1 \
     --hash=sha256:fd0ed0fc1341671d92d5f5b2f5503916deb7aa7e2940e6636cfa2c087c828bf9 \
     --hash=sha256:ff0c721f20bff1e2cfba77948727a8db48f187e89a72fe50c34478ce6efb3353
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 flaskwebgui==0.3.7 \
     --hash=sha256:4a69955308eaa8bb256ba04a994dc8f58a48dcd6f9599694ab1bcd9f43d88a5d \
     --hash=sha256:535974ce2672dcc74787c254de24cceed4101be75d96952dae82014dd57f061e
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 fonttools==4.38.0 \
     --hash=sha256:2bb244009f9bf3fa100fc3ead6aeb99febe5985fa20afbfbaa2f8946c2fbdaf1 \
     --hash=sha256:820466f43c8be8c3009aef8b87e785014133508f0de64ec469e4efb643ae54fb
@@ -412,11 +417,11 @@ future==0.18.2 \
 getpass-asterisk==1.0.1 \
     --hash=sha256:20d45cafda0066d761961e0919728526baf7bb5151fbf48a7d5ea4034127d857 \
     --hash=sha256:7cc357a924cf62fa4e15b73cb4e5e30685c9084e464ffdc3fd9000a2b54ea9e9
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
-gfpgan @ https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip \
+gfpgan @ https://github.com/invoke-ai/GFPGAN/archive/c796277a1cf77954e5fc0b288d7062d162894248.zip ; platform_system == "Linux" or platform_system == "Darwin" \
-    --hash=sha256:79e6d71c8f1df7c7ccb0ac6b9a2ccb615ad5cde818c8b6f285a8711c05aebf85
+    --hash=sha256:4155907b8b7db3686324554df7007eedd245cdf8656c21da9d9a3f44bef2fcaa
     # via
-    #   -r installer/requirements.in
+    #   -r binary_installer/requirements.in
     #   realesrgan
 gitdb==4.0.9 \
     --hash=sha256:8033ad4e853066ba6ca92050b9df2f89301b8fc8bf7e9324d412a63f8bf1a8fd \
@@ -577,7 +582,7 @@ imageio-ffmpeg==0.4.7 \
     --hash=sha256:7a08838f97f363e37ca41821b864fd3fdc99ab1fe2421040c78eb5f56a9e723e \
     --hash=sha256:8e724d12dfe83e2a6eb39619e820243ca96c81c47c2648e66e05f7ee24e14312 \
     --hash=sha256:fc60686ef03c2d0f842901b206223c30051a6a120384458761390104470846fd
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 importlib-metadata==5.0.0 \
     --hash=sha256:da31db32b304314d044d3c12c79bd59e307889b287ad12ff387b3500835fc2ab \
     --hash=sha256:ddb0e35065e8938f867ed4928d0ae5bf2a53b7773871bfe6bcc7e4fcdc7dea43
@@ -610,9 +615,9 @@ jsonschema==4.17.0 \
     # via
     #   altair
     #   jsonmerge
-k-diffusion @ https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip \
+k-diffusion @ https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip \
-    --hash=sha256:c3f2c84036aa98c3abf4552fafab04df5ca472aa639982795e05bb1db43ce5e4
+    --hash=sha256:8eac5cdc08736e6d61908a1b2948f2b2f62691b01dc1aab978bddb3451af0d66
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 kiwisolver==1.4.4 \
     --hash=sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b \
     --hash=sha256:03baab2d6b4a54ddbb43bba1a3a2d1627e82d205c5cf8f4c924dc49284b87166 \
@@ -1005,6 +1010,7 @@ numpy==1.23.4 \
     #   tifffile
     #   torch-fidelity
     #   torchmetrics
+    #   torchsde
     #   torchvision
     #   transformers
 oauthlib==3.2.2 \
@@ -1091,7 +1097,7 @@ pathtools==0.1.2 \
 picklescan==0.0.5 \
     --hash=sha256:368cf1b9a075bc1b6460ad82b694f260532b836c82f99d13846cd36e1bbe7f9a \
     --hash=sha256:57153eca04d5df5009f2cdd595aef261b8a6f27e03046a1c84f672aa6869c592
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 pillow==9.3.0 \
     --hash=sha256:03150abd92771742d4a8cd6f2fa6246d847dcd2e332a18d0c15cc75bf6703040 \
     --hash=sha256:073adb2ae23431d3b9bcbcff3fe698b62ed47211d0716b067385538a1b0f28b8 \
@@ -1300,11 +1306,11 @@ pyparsing==3.0.9 \
     #   packaging
 pypatchmatch @ https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip \
     --hash=sha256:4ad6ec95379e7d122d494ff76633cc7cf9b71330d5efda147fceba81e3dc6cd2
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 pyreadline3==3.4.1 \
     --hash=sha256:6f3d1f7b8a31ba32b73917cefc1f28cc660562f39aea8646d30bd6eff21f7bae \
     --hash=sha256:b0efb6516fd4fb07b45949053826a62fa4cb353db5be2bbb4a7aa1fdd1e345fb
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 pyrsistent==0.19.2 \
     --hash=sha256:055ab45d5911d7cae397dc418808d8802fb95262751872c841c170b0dbf51eed \
     --hash=sha256:111156137b2e71f3a9936baf27cb322e8024dac3dc54ec7fb9f0bcf3249e68bb \
@@ -1441,7 +1447,7 @@ qudida==0.0.4 \
 realesrgan==0.3.0 \
     --hash=sha256:0d36da96ab9f447071606e91f502ccdfb08f80cc82ee4f8caf720c7745ccec7e \
     --hash=sha256:59336c16c30dd5130eff350dd27424acb9b7281d18a6810130e265606c9a6088
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 regex==2022.10.31 \
     --hash=sha256:052b670fafbe30966bbe5d025e90b2a491f85dfe5b2583a163b5e60a85a321ad \
     --hash=sha256:0653d012b3bf45f194e5e6a41df9258811ac8fc395579fa82958a8b76286bea4 \
@@ -1656,6 +1662,7 @@ scipy==1.9.3 \
     #   scikit-learn
     #   torch-fidelity
     #   torchdiffeq
+    #   torchsde
 semver==2.13.0 \
     --hash=sha256:ced8b23dceb22134307c1b8abfa523da14198793d9787ac838e70e29e77458d4 \
     --hash=sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f
@@ -1663,7 +1670,7 @@ semver==2.13.0 \
 send2trash==1.8.0 \
     --hash=sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d \
     --hash=sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 sentry-sdk==1.10.1 \
     --hash=sha256:06c0fa9ccfdc80d7e3b5d2021978d6eb9351fa49db9b5847cf4d1f2a473414ad \
     --hash=sha256:105faf7bd7b7fa25653404619ee261527266b14103fe1389e0ce077bd23a9691
@@ -1754,11 +1761,11 @@ smmap==5.0.0 \
 streamlit==1.14.0 \
     --hash=sha256:62556d873567e1b3427bcd118a57ee6946619f363bd6bba38df2d1f8225ecba0 \
     --hash=sha256:e078b8143d150ba721bdb9194218e311c5fe1d6d4156473a2dea6cc848a6c9fc
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 taming-transformers-rom1504==0.0.6 \
     --hash=sha256:051b5804c58caa247bcd51d17ddb525b4d5f892a29d42dc460f40e3e9e34e5d8 \
     --hash=sha256:73fe5fc1108accee4236ee6976e0987ab236afad0af06cb9f037641a908d2c32
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 tb-nightly==2.11.0a20221106 \
     --hash=sha256:8940457ee42db92f01da8bcdbbea1a476735eda559dde5976f5728919960af4a
     # via
@@ -1783,7 +1790,7 @@ tensorboard-plugin-wit==1.8.1 \
     #   tensorboard
 test-tube==0.7.5 \
     --hash=sha256:1379c33eb8cde3e9b36610f87da0f16c2e06496b1cfebac473df4e7be2faa124
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 threadpoolctl==3.1.0 \
     --hash=sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b \
     --hash=sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380
@@ -1843,7 +1850,7 @@ torch==1.12.0+cu116 ; platform_system == "Linux" or platform_system == "Windows"
     --hash=sha256:aa43d7b54b86f723f17c5c44df1078c59a6149fc4d42fbef08aafab9d61451c9 \
     --hash=sha256:f772be831447dd01ebd26cbedf619e668d1b269d69bf6b4ff46b1378362bff26
     # via
-    #   -r installer/requirements.in
+    #   -r binary_installer/requirements.in
     #   accelerate
     #   basicsr
     #   clean-fid
@@ -1859,11 +1866,12 @@ torch==1.12.0+cu116 ; platform_system == "Linux" or platform_system == "Windows"
     #   torch-fidelity
     #   torchdiffeq
     #   torchmetrics
+    #   torchsde
     #   torchvision
 torch-fidelity==0.3.0 \
     --hash=sha256:3d3e33db98919759cc4f3f24cb27e1e74bdc7c905d90a780630e4e1c18492b66 \
     --hash=sha256:d01284825595feb7dc3eae3dc9a0d8ced02be764813a3483f109bc142b52a1d3
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 torchdiffeq==0.2.3 \
     --hash=sha256:b5b01ec1294a2d8d5f77e567bf17c5de1237c0573cb94deefa88326f0e18c338 \
     --hash=sha256:fe75f434b9090ac0c27702e02bed21472b0f87035be6581f51edc5d4013ea31a
@@ -1872,6 +1880,10 @@ torchmetrics==0.10.2 \
     --hash=sha256:43757d82266969906fc74b6e80766fcb2a0d52d6c3d09e3b7c98cf3b733fd20c \
     --hash=sha256:daa29d96bff5cff04d80eec5b9f5076993d6ac9c2d2163e88b6b31f8d38f7c25
     # via pytorch-lightning
+torchsde==0.2.5 \
+    --hash=sha256:222be9e15610d37a4b5a71cfa0c442178f9fd9ca02f6522a3e11c370b3d0906b \
+    --hash=sha256:4c34373a94a357bdf60bbfee00c850f3563d634491555820b900c9a4f7eff300
+    # via k-diffusion
 torchvision==0.13.0+cu116 ; platform_system == "Linux" or platform_system == "Windows" \
     --hash=sha256:1696feadf1921c8fa1549bad774221293298288ebedaa14e44bc3e57e964a369 \
     --hash=sha256:572544b108eaf12638f3dca0f496a453c4b8d8256bcc8333d5355df641c0380c \
@@ -1882,7 +1894,7 @@ torchvision==0.13.0+cu116 ; platform_system == "Linux" or platform_system == "Wi
     --hash=sha256:cb6bf0117b8f4b601baeae54e8a6bb5c4942b054835ba997f438ddcb7adcfb90 \
     --hash=sha256:d1a3c124645e3460b3e50b54eb89a2575a5036bfa618f15dc4f5d635c716069d
     # via
-    #   -r installer/requirements.in
+    #   -r binary_installer/requirements.in
     #   basicsr
     #   clean-fid
     #   clip
@@ -1921,10 +1933,13 @@ tqdm==4.64.1 \
     #   taming-transformers-rom1504
     #   torch-fidelity
     #   transformers
+trampoline==0.1.2 \
+    --hash=sha256:36cc9a4ff9811843d177fc0e0740efbd7da39eadfe6e50c9e2937cbc06d899d9
+    # via torchsde
 transformers==4.24.0 \
     --hash=sha256:486f353a8e594002e48be0e2aba723d96eda839e63bfe274702a4b5eda85559b \
     --hash=sha256:b7ab50039ef9bf817eff14ab974f306fd20a72350bdc9df3a858fd009419322e
-    # via -r installer/requirements.in
+    # via -r binary_installer/requirements.in
 typing-extensions==4.4.0 \
     --hash=sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa \
     --hash=sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e

binary_installer/requirements.in

@@ -1,5 +1,6 @@
 --prefer-binary
 --extra-index-url https://download.pytorch.org/whl/torch_stable.html
+--extra-index-url https://download.pytorch.org/whl/cu116
 --trusted-host https://download.pytorch.org
 accelerate~=0.14
 albumentations
@@ -26,6 +27,7 @@ transformers
 picklescan
 https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
 https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip
-https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip
+https://github.com/invoke-ai/GFPGAN/archive/3f5d2397361199bc4a91c08bb7d80f04d7805615.zip ; platform_system=='Windows'
-https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip
+https://github.com/invoke-ai/GFPGAN/archive/c796277a1cf77954e5fc0b288d7062d162894248.zip ; platform_system=='Linux' or platform_system=='Darwin'
+https://github.com/Birch-san/k-diffusion/archive/363386981fee88620709cf8f6f2eea167bd6cd74.zip
 https://github.com/invoke-ai/PyPatchMatch/archive/129863937a8ab37f6bbcec327c994c0f932abdbc.zip

docs/features/CLI.md

@@ -130,20 +130,34 @@ file should contain the startup options as you would type them on the
 command line (`--steps=10 --grid`), one argument per line, or a
 mixture of both using any of the accepted command switch formats:
 
-!!! example ""
+!!! example "my unmodified initialization file"
 
-    ```bash
+    ```bash title="~/.invokeai" linenums="1"
-    --web
+    # InvokeAI initialization file
-    --steps=28
+    # This is the InvokeAI initialization file, which contains command-line default values.
-    --grid
+    # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
-    -f 0.6 -C 11.0 -A k_euler_a
+    # or renaming it and then running configure_invokeai.py again.
+
+    # The --root option below points to the folder in which InvokeAI stores its models, configs and outputs.
+    --root="/Users/mauwii/invokeai"
+
+    # the --outdir option controls the default location of image files.
+    --outdir="/Users/mauwii/invokeai/outputs"
+
+    # You may place other  frequently-used startup commands here, one or more per line.
+    # Examples:
+    # --web --host=0.0.0.0
+    # --steps=20
+    # -Ak_euler_a -C10.0
     ```
 
-Note that the initialization file only accepts the command line arguments.
+!!! note
-There are additional arguments that you can provide on the `invoke>` command
+
-line (such as `-n` or `--iterations`) that cannot be entered into this file.
+    The  initialization file only accepts the command line arguments.
-Also be alert for empty blank lines at the end of the file, which will cause
+    There are additional arguments that you can provide on the `invoke>` command
-an arguments error at startup time.
+    line (such as `-n` or `--iterations`) that cannot be entered into this file.
+    Also be alert for empty blank lines at the end of the file, which will cause
+    an arguments error at startup time.
 
 ## List of prompt arguments
 
@@ -195,15 +209,17 @@ Here are the invoke> command that apply to txt2img:
 | `--with_variations <pattern>`             |                                           | `None`                                   | Combine two or more variations. See [Variations](./VARIATIONS.md) for now to use this.                                                                                                                                                           |
 | `--save_intermediates <n>`                |                                           | `None`                                   | Save the image from every nth step into an "intermediates" folder inside the output directory                                                                                                                                                    |
 
-Note that the width and height of the image must be multiples of 64. You can
+!!! note
-provide different values, but they will be rounded down to the nearest multiple
-of 64.
 
-### This is an example of img2img:
+    the width and height of the image must be multiples of 64. You can
+    provide different values, but they will be rounded down to the nearest multiple
+    of 64.
 
-```
+!!! example "This is a example of img2img"
-invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
+
-```
+    ```bash
+    invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
+    ```
 
 This will modify the indicated vacation photograph by making it more like the
 prompt. Results will vary greatly depending on what is in the image. We also ask
@@ -253,7 +269,7 @@ description of the part of the image to replace. For example, if you have an
 image of a breakfast plate with a bagel, toast and scrambled eggs, you can
 selectively mask the bagel and replace it with a piece of cake this way:
 
-```
+```bash
 invoke> a piece of cake -I /path/to/breakfast.png -tm bagel
 ```
 
@@ -265,7 +281,7 @@ are getting too much or too little masking you can adjust the threshold down (to
 get more mask), or up (to get less). In this example, by passing `-tm` a higher
 value, we are insisting on a more stringent classification.
 
-```
+```bash
 invoke> a piece of cake -I /path/to/breakfast.png -tm bagel 0.6
 ```
 
@@ -275,16 +291,16 @@ You can load and use hundreds of community-contributed Textual
 Inversion models just by typing the appropriate trigger phrase. Please
 see [Concepts Library](CONCEPTS.md) for more details.
 
-# Other Commands
+## Other Commands
 
 The CLI offers a number of commands that begin with "!".
 
-## Postprocessing images
+### Postprocessing images
 
 To postprocess a file using face restoration or upscaling, use the `!fix`
 command.
 
-### `!fix`
+#### `!fix`
 
 This command runs a post-processor on a previously-generated image. It takes a
 PNG filename or path and applies your choice of the `-U`, `-G`, or `--embiggen`
@@ -311,19 +327,19 @@ Some examples:
     [1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S  -W 512 -H 512 -C 7.5 -A k_lms -G 0.8
     ```
 
-### !mask
+#### `!mask`
 
 This command takes an image, a text prompt, and uses the `clipseg` algorithm to
 automatically generate a mask of the area that matches the text prompt. It is
 useful for debugging the text masking process prior to inpainting with the
 `--text_mask` argument. See [INPAINTING.md] for details.
 
-## Model selection and importation
+### Model selection and importation
 
 The CLI allows you to add new models on the fly, as well as to switch among them
 rapidly without leaving the script.
 
-### !models
+#### `!models`
 
 This prints out a list of the models defined in `config/models.yaml'. The active
 model is bold-faced
@@ -336,7 +352,7 @@ laion400m                 not loaded  <no description>
 waifu-diffusion           not loaded  Waifu Diffusion v1.3
 </pre>
 
-### !switch <model>
+#### `!switch <model>`
 
 This quickly switches from one model to another without leaving the CLI script.
 `invoke.py` uses a memory caching system; once a model has been loaded,
@@ -361,7 +377,7 @@ invoke> !switch waifu-diffusion
    | Making attention of type 'vanilla' with 512 in_channels
    | Using faster float16 precision
 >> Model loaded in 18.24s
->> Max VRAM used to load the model: 2.17G 
+>> Max VRAM used to load the model: 2.17G
 >> Current VRAM usage:2.17G
 >> Setting Sampler to k_lms
 
@@ -381,7 +397,7 @@ laion400m                 not loaded  <no description>
 waifu-diffusion               cached  Waifu Diffusion v1.3
 </pre>
 
-### !import_model <path/to/model/weights>
+#### `!import_model <path/to/model/weights>`
 
 This command imports a new model weights file into InvokeAI, makes it available
 for image generation within the script, and writes out the configuration for the
@@ -428,10 +444,10 @@ OK to import [n]? <b>y</b>
    | Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
    | Making attention of type 'vanilla' with 512 in_channels
    | Using faster float16 precision
-invoke> 
+invoke>
 </pre>
 
-###!edit_model <name_of_model>
+#### `!edit_model <name_of_model>`
 
 The `!edit_model` command can be used to modify a model that is already defined
 in `config/models.yaml`. Call it with the short name of the model you wish to
@@ -468,12 +484,12 @@ text... Outputs: [2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix
 "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512
 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25 ```
 
-## History processing
+### History processing
 
 The CLI provides a series of convenient commands for reviewing previous actions,
 retrieving them, modifying them, and re-running them.
 
-### !history
+#### `!history`
 
 The invoke script keeps track of all the commands you issue during a session,
 allowing you to re-run them. On Mac and Linux systems, it also writes the
@@ -485,20 +501,22 @@ during the session (Windows), or the most recent 1000 commands (Mac|Linux). You
 can then repeat a command by using the command `!NNN`, where "NNN" is the
 history line number. For example:
 
-```bash
+!!! example ""
-invoke> !history
-...
-[14] happy woman sitting under tree wearing broad hat and flowing garment
-[15] beautiful woman sitting under tree wearing broad hat and flowing garment
-[18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
-[20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
-[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
-...
-invoke> !20
-invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
-```
 
-### !fetch
+    ```bash
+    invoke> !history
+    ...
+    [14] happy woman sitting under tree wearing broad hat and flowing garment
+    [15] beautiful woman sitting under tree wearing broad hat and flowing garment
+    [18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
+    [20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    ...
+    invoke> !20
+    invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    ```
+
+####`!fetch`
 
 This command retrieves the generation parameters from a previously generated
 image and either loads them into the command line (Linux|Mac), or prints them
@@ -508,33 +526,36 @@ a folder with image png files, and wildcard \*.png to retrieve the dream command
 used to generate the images, and save them to a file commands.txt for further
 processing.
 
-This example loads the generation command for a single png file:
+!!! example "load the generation command for a single png file"
 
-```bash
+    ```bash
-invoke> !fetch 0000015.8929913.png
+    invoke> !fetch 0000015.8929913.png
-# the script returns the next line, ready for editing and running:
+    # the script returns the next line, ready for editing and running:
-invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
+    invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
-```
+    ```
 
-This one fetches the generation commands from a batch of files and stores them
+!!! example "fetch the generation commands from a batch of files and store them into `selected.txt`"
-into `selected.txt`:
 
-```bash
+    ```bash
-invoke> !fetch outputs\selected-imgs\*.png selected.txt
+    invoke> !fetch outputs\selected-imgs\*.png selected.txt
-```
+    ```
 
-### !replay
+#### `!replay`
 
 This command replays a text file generated by !fetch or created manually
 
-```
+!!! example
-invoke> !replay outputs\selected-imgs\selected.txt
-```
 
-Note that these commands may behave unexpectedly if given a PNG file that was
+    ```bash
-not generated by InvokeAI.
+    invoke> !replay outputs\selected-imgs\selected.txt
+    ```
 
-### !search <search string>
+!!! note
+
+    These commands may behave unexpectedly if given a PNG file that was
+    not generated by InvokeAI.
+
+#### `!search <search string>`
 
 This is similar to !history but it only returns lines that contain
 `search string`. For example:
@@ -544,7 +565,7 @@ invoke> !search surreal
 [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
 ```
 
-### `!clear`
+#### `!clear`
 
 This clears the search history from memory and disk. Be advised that this
 operation is irreversible and does not issue any warnings!

docs/features/CONCEPTS.md

@@ -1,130 +1,110 @@
 ---
-title: The Hugging Face Concepts Library and Importing Textual Inversion files
+title: Concepts Library
 ---
 
-# :material-file-document: Concepts Library
+# :material-library-shelves: The Hugging Face Concepts Library and Importing Textual Inversion files
 
 ## Using Textual Inversion Files
 
 Textual inversion (TI) files are small models that customize the output of
-Stable Diffusion image generation. They can augment SD with
+Stable Diffusion image generation. They can augment SD with specialized subjects
-specialized subjects and artistic styles. They are also known as
+and artistic styles. They are also known as "embeds" in the machine learning
-"embeds" in the machine learning world.
+world.
 
-Each TI file introduces one or more vocabulary terms to the SD
+Each TI file introduces one or more vocabulary terms to the SD model. These are
-model. These are known in InvokeAI as "triggers." Triggers are often,
+known in InvokeAI as "triggers." Triggers are often, but not always, denoted
-but not always, denoted using angle brackets as in
+using angle brackets as in "<trigger-phrase>". The two most common type of
-"<trigger-phrase>". The two most common type of TI files that you'll
+TI files that you'll encounter are `.pt` and `.bin` files, which are produced by
-encounter are `.pt` and `.bin` files, which are produced by different
+different TI training packages. InvokeAI supports both formats, but its
-TI training packages. InvokeAI supports both formats, but its [built-in
+[built-in TI training system](TEXTUAL_INVERSION.md) produces `.pt`.
-TI training system](TEXTUAL_INVERSION.md) produces `.pt`.
 
-The [Hugging Face company](https://huggingface.co/sd-concepts-library)
+The [Hugging Face company](https://huggingface.co/sd-concepts-library) has
-has amassed a large ligrary of >800 community-contributed TI files
+amassed a large ligrary of >800 community-contributed TI files covering a
-covering a broad range of subjects and styles. InvokeAI has built-in
+broad range of subjects and styles. InvokeAI has built-in support for this
-support for this library which downloads and merges TI files
+library which downloads and merges TI files automatically upon request. You can
-automatically upon request. You can also install your own or others'
+also install your own or others' TI files by placing them in a designated
-TI files by placing them in a designated directory.
+directory.
 
 ### An Example
 
-Here are a few examples to illustrate how it works. All these images
+Here are a few examples to illustrate how it works. All these images were
-were generated using the command-line client and the Stable Diffusion
+generated using the command-line client and the Stable Diffusion 1.5 model:
-1.5 model:
 
-Japanese gardener
+|         Japanese gardener          | Japanese gardener <ghibli-face> | Japanese gardener <hoi4-leaders> | Japanese gardener <cartoona-animals> |
-<br>
+| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
-<img src="../assets/concepts/image1.png">
+| ![](../assets/concepts/image1.png) |  ![](../assets/concepts/image2.png)   |   ![](../assets/concepts/image3.png)   |     ![](../assets/concepts/image4.png)     |
-
-Japanese gardener &lt;ghibli-face&gt;
-<br>
-<img src="../assets/concepts/image2.png">
-
-Japanese gardener &lt;hoi4-leaders&gt;
-<br>
-<img src="../assets/concepts/image3.png">
-
-Japanese gardener &lt;cartoona-animals&gt;
-<br>
-<img src="../assets/concepts/image4.png">
 
 You can also combine styles and concepts:
 
-A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style
+<figure markdown>
-<br>
+  ![](../assets/concepts/image5.png)
-<img src="../assets/concepts/image5.png">
+  <figcaption>A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style</figcaption>
-
+</figure>
 ## Using a Hugging Face Concept
 
-Hugging Face TI concepts are downloaded and installed automatically as
+Hugging Face TI concepts are downloaded and installed automatically as you
-you require them. This requires your machine to be connected to the
+require them. This requires your machine to be connected to the Internet. To
-Internet. To find out what each concept is for, you can browse the
+find out what each concept is for, you can browse the
-[Hugging Face concepts
+[Hugging Face concepts library](https://huggingface.co/sd-concepts-library) and
-library](https://huggingface.co/sd-concepts-library) and look at
+look at examples of what each concept produces.
-examples of what each concept produces.
 
-When you have an idea of a concept you wish to try, go to the
+When you have an idea of a concept you wish to try, go to the command-line
-command-line client (CLI) and type a "&lt;" character and the beginning
+client (CLI) and type a "&lt;" character and the beginning of the Hugging Face
-of the Hugging Face concept name you wish to load.  Press the Tab key,
+concept name you wish to load. Press the Tab key, and the CLI will show you all
-and the CLI will show you all matching concepts. You can also type "&lt;"
+matching concepts. You can also type "&lt;" and Tab to get a listing of all ~800
-and Tab to get a listing of all ~800 concepts, but be prepared to
+concepts, but be prepared to scroll up to see them all! If there is more than
-scroll up to see them all! If there is more than one match you can
+one match you can continue to type and Tab until the concept is completed.
-continue to type and Tab until the concept is completed.
 
-For example if you type "&lt;x" and Tab, you'll be prompted with the completions:
+For example if you type "&lt;x" and Tab, you'll be prompted with the
+completions:
 
 ```
-<xatu2>        <xatu>         <xbh>          <xi>           <xidiversity>  <xioboma>      <xuna>         <xyz>          
+<xatu2>        <xatu>         <xbh>          <xi>           <xidiversity>  <xioboma>      <xuna>         <xyz>
 ```
 
-Now type "id" and press Tab. It will be autocompleted to
+Now type "id" and press Tab. It will be autocompleted to "&lt;xidiversity&gt;"
-"&lt;xidiversity&gt;" because this is a unique match.
+because this is a unique match.
 
-Finish your prompt and generate as usual. You may include multiple
+Finish your prompt and generate as usual. You may include multiple concept terms
-concept terms in the prompt.
+in the prompt.
 
-If you have never used this concept before, you will see a message
+If you have never used this concept before, you will see a message that the TI
-that the TI model is being downloaded and installed. After this, the
+model is being downloaded and installed. After this, the concept will be saved
-concept will be saved locally (in the `models/sd-concepts-library`
+locally (in the `models/sd-concepts-library` directory) for future use.
-directory) for future use.
 
-Several steps happen during downloading and
+Several steps happen during downloading and installation, including a scan of
-installation, including a scan of the file for malicious code. Should
+the file for malicious code. Should any errors occur, you will be warned and the
-any errors occur, you will be warned and the concept will fail to
+concept will fail to load. Generation will then continue treating the trigger
-load. Generation will then continue treating the trigger term as a
+term as a normal string of characters (e.g. as literal "&lt;ghibli-face&gt;").
-normal string of characters (e.g. as literal "&lt;ghibli-face&gt;").
 
-Currently auto-installation of concepts is a feature only available on
+Currently auto-installation of concepts is a feature only available on the
-the command-line client. Support for the WebUI is a work in progress.
+command-line client. Support for the WebUI is a work in progress.
 
 ## Installing your Own TI Files
 
-You may install any number of `.pt` and `.bin` files simply by copying
+You may install any number of `.pt` and `.bin` files simply by copying them into
-them into the `embeddings` directory of the InvokeAI runtime directory
+the `embeddings` directory of the InvokeAI runtime directory (usually `invokeai`
-(usually `invokeai` in your home directory). You may create
+in your home directory). You may create subdirectories in order to organize the
-subdirectories in order to organize the files in any way you wish. Be
+files in any way you wish. Be careful not to overwrite one file with another.
-careful not to overwrite one file with another. For example, TI files
+For example, TI files generated by the Hugging Face toolkit share the named
-generated by the Hugging Face toolkit share the named
+`learned_embedding.bin`. You can use subdirectories to keep them distinct.
-`learned_embedding.bin`. You can use subdirectories to keep them
-distinct.
 
-At startup time, InvokeAI will scan the `embeddings` directory and
+At startup time, InvokeAI will scan the `embeddings` directory and load any TI
-load any TI files it finds there. At startup you will see a message
+files it finds there. At startup you will see a message similar to this one:
-similar to this one:
 
-```
+```bash
 >> Current embedding manager terms: *, <HOI4-Leader>, <princess-knight>
 ```
 
-Note the "*" trigger term. This is a placeholder term that many early
+Note the `*` trigger term. This is a placeholder term that many early TI
-TI tutorials taught people to use rather than a more descriptive
+tutorials taught people to use rather than a more descriptive term.
-term. Unfortunately, if you have multiple TI files that all use this
+Unfortunately, if you have multiple TI files that all use this term, only the
-term, only the first one loaded will be triggered by use of the term.
+first one loaded will be triggered by use of the term.
 
-To avoid this problem, you can use the `merge_embeddings.py` script to
+To avoid this problem, you can use the `merge_embeddings.py` script to merge two
-merge two or more TI files together. If it encounters a collision of
+or more TI files together. If it encounters a collision of terms, the script
-terms, the script will prompt you to select new terms that do not
+will prompt you to select new terms that do not collide. See
-collide. See [Textual Inversion](TEXTUAL_INVERSION.md) for details.
+[Textual Inversion](TEXTUAL_INVERSION.md) for details.
 
 ## Further Reading
 

docs/features/IMG2IMG.md

@@ -12,21 +12,19 @@ stable diffusion to build the prompt on top of the image you provide, preserving
 the original's basic shape and layout. To use it, provide the `--init_img`
 option as shown here:
 
-```commandline
+!!! example ""
-tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
-```
 
-This will take the original image shown here:
+    ```commandline
+    tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
+    ```
 
-<figure markdown>
+    <figure markdown>
-![original-image](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png){ width=320 }
-</figure>
 
-and generate a new image based on it as shown here:
+    | original image | generated image |
+    | :------------: | :-------------: |
+    | ![original-image](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png){ width=320 } | ![generated-image](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png){ width=320 } |
 
-<figure markdown>
+    </figure>
-![generated-image](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png){ width=320 }
-</figure>
 
 The `--init_img` (`-I`) option gives the path to the seed picture. `--strength`
 (`-f`) controls how much the original will be modified, ranging from `0.0` (keep
@@ -88,13 +86,15 @@ from a prompt. If the step count is 10, then the "latent space" (Stable
 Diffusion's internal representation of the image) for the prompt "fire" with
 seed `1592514025` develops something like this:
 
-```bash
+!!! example ""
-invoke> "fire" -s10 -W384 -H384 -S1592514025
-```
 
-<figure markdown>
+    ```bash
-![latent steps](../assets/img2img/000019.steps.png)
+    invoke> "fire" -s10 -W384 -H384 -S1592514025
-</figure>
+    ```
+
+    <figure markdown>
+    ![latent steps](../assets/img2img/000019.steps.png){ width=720 }
+    </figure>
 
 Put simply: starting from a frame of fuzz/static, SD finds details in each frame
 that it thinks look like "fire" and brings them a little bit more into focus,
@@ -109,25 +109,23 @@ into the sequence at the appropriate point, with just the right amount of noise.
 
 ### A concrete example
 
-I want SD to draw a fire based on this hand-drawn image:
+!!! example "I want SD to draw a fire based on this hand-drawn image"
 
-<figure markdown>
+    ![drawing of a fireplace](../assets/img2img/fire-drawing.png){ align=left }
-![drawing of a fireplace](../assets/img2img/fire-drawing.png)
-</figure>
 
-Let's only do 10 steps, to make it easier to see what's happening. If strength
+    Let's only do 10 steps, to make it easier to see what's happening. If strength
-is `0.7`, this is what the internal steps the algorithm has to take will look
+    is `0.7`, this is what the internal steps the algorithm has to take will look
-like:
+    like:
 
-<figure markdown>
+    <figure markdown>
-![gravity32](../assets/img2img/000032.steps.gravity.png)
+    ![gravity32](../assets/img2img/000032.steps.gravity.png)
-</figure>
+    </figure>
 
-With strength `0.4`, the steps look more like this:
+    With strength `0.4`, the steps look more like this:
 
-<figure markdown>
+    <figure markdown>
-![gravity30](../assets/img2img/000030.steps.gravity.png)
+    ![gravity30](../assets/img2img/000030.steps.gravity.png)
-</figure>
+    </figure>
 
 Notice how much more fuzzy the starting image is for strength `0.7` compared to
 `0.4`, and notice also how much longer the sequence is with `0.7`:

docs/features/POSTPROCESS.md

@@ -39,10 +39,6 @@ If you do not run this script in advance, the GFPGAN module will attempt to
 download the models files the first time you try to perform facial
 reconstruction.
 
-## Usage
-
-You will now have access to two new prompt arguments.
-
 ### Upscaling
 
 `-U : <upscaling_factor> <upscaling_strength>`
@@ -119,7 +115,7 @@ You can use `-ft` prompt argument to swap between CodeFormer and the default
 GFPGAN. The above mentioned `-G` prompt argument will allow you to control the
 strength of the restoration effect.
 
-### Usage
+### CodeFormer Usage
 
 The following command will perform face restoration with CodeFormer instead of
 the default gfpgan.
@@ -160,7 +156,7 @@ A new file named `000044.2945021133.fixed.png` will be created in the output
 directory. Note that the `!fix` command does not replace the original file,
 unlike the behavior at generate time.
 
-### Disabling
+## How to disable
 
 If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries,
 you can disable them on the invoke.py command line with the `--no_restore` and

docs/features/index.md

@@ -0,0 +1,5 @@
+---
+title: Overview
+---
+
+Here you can find the documentation for different features.

docs/index.md

@@ -100,6 +100,10 @@ You wil need one of the following:
 - :simple-amd: An AMD-based graphics card with 4 GB or more VRAM memory (Linux only)
 - :fontawesome-brands-apple: An Apple computer with an M1 chip.
 
+We do not recommend the GTX 1650 or 1660 series video cards. They are
+unable to run in half-precision mode and do not come with sufficient VRAM
+to render 512x512 images.
+
 ### :fontawesome-solid-memory: Memory
 
 - At least 12 GB Main Memory RAM.

docs/installation/BUILDING_BINARY_INSTALLERS.md

@@ -1,4 +1,8 @@
-# How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
+---
+title: build binary installers
+---
+
+# :simple-buildkite: How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
 
 ## 1. Ensure `installers/requirements.in` is correct
 

docs/installation/INSTALLING_MODELS.md

@@ -162,6 +162,12 @@ the command-line client's `!import_model` command.
          Type a bit of the path name and hit ++tab++ in order to get a choice of
          possible completions.
 
+    !!! tip "on Windows, you can drag model files onto the command-line"
+
+         Once you have typed in `!import_model `, you can drag the model `.ckpt` file
+         onto the command-line to insert the model path. This way, you don't need to
+         type it or copy/paste.
+
 4.  Follow the wizard's instructions to complete installation as shown in the
     example here:
 

docs/installation/INSTALL_INVOKE.md

@@ -35,7 +35,7 @@ recommended model weights files.
 ## Steps to Install
 
 1. Download the
-   [latest release](https://github.com/invoke-ai/InvokeAI/releases/tag/2.2.0-rc4) of
+   [latest release](https://github.com/invoke-ai/InvokeAI/releases/latest) of
    InvokeAI's installer for your platform. Look for a file named `InvokeAI-binary-<your platform>.zip`
 
 2. Place the downloaded package someplace where you have plenty of HDD space,

docs/installation/INSTALL_SOURCE.md

@@ -10,7 +10,6 @@ The source installer is a shell script that attempts to automate every step
 needed to install and run InvokeAI on a stock computer running recent versions
 of Linux, MacOS or Windows. It will leave you with a version that runs a stable
 version of InvokeAI with the option to upgrade to experimental versions later.
-It is not as foolproof as the [InvokeAI installer](INSTALL_INVOKE.md)
 
 Before you begin, make sure that you meet the
 [hardware requirements](index.md#Hardware_Requirements) and has the appropriate
@@ -27,12 +26,12 @@ Though there are multiple steps, there really is only one click involved to kick
 off the process.
 
 1.  The source installer is distributed in ZIP files. Go to the
-    [latest release](https://github.com/invoke-ai/InvokeAI/releases/tag/2.2.0-rc4), and
+    [latest release](https://github.com/invoke-ai/InvokeAI/releases/latest), and
     look for a series of files named:
 
-    - invokeAI-src-installer-mac.zip
+    - [invokeAI-src-installer-2.2.3-mac.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/invokeAI-src-installer-2.2.3-mac.zip)
-    - invokeAI-src-installer-windows.zip
+    - [invokeAI-src-installer-2.2.3-windows.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/invokeAI-src-installer-2.2.3-windows.zip)
-    - invokeAI-src-installer-linux.zip
+    - [invokeAI-src-installer-2.2.3-linux.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/invokeAI-src-installer-2.2.3-linux.zip)
 
     Download the one that is appropriate for your operating system.
 
@@ -51,18 +50,30 @@ off the process.
     inflating: invokeAI\readme.txt
     ```
 
-3.  If you are using a desktop GUI, double-click the installer file. It will be
+3. If you are a macOS user, you may need to install the Xcode command line tools. 
+   These are a set of tools that are needed to run certain applications in a Terminal, 
+   including InvokeAI. This package is provided directly by Apple.
+   
+   To install, open a terminal window and run `xcode-select --install`. You will get
+   a macOS system popup guiding you through the install. If you already have them
+   installed, you will instead see some output in the Terminal advising you that the 
+   tools are already installed.
+   
+   More information can be found here:
+   https://www.freecodecamp.org/news/install-xcode-command-line-tools/
+
+4.  If you are using a desktop GUI, double-click the installer file. It will be
     named `install.bat` on Windows systems and `install.sh` on Linux and
     Macintosh systems.
 
-4.  Alternatively, from the command line, run the shell script or .bat file:
+5.  Alternatively, from the command line, run the shell script or .bat file:
 
     ```cmd
     C:\Documents\Linco> cd invokeAI
     C:\Documents\Linco\invokeAI> install.bat
     ```
 
-5.  Sit back and let the install script work. It will install various binary
+6.  Sit back and let the install script work. It will install various binary
     requirements including Conda, Git and Python, then download the current
     InvokeAI code and install it along with its dependencies.
 
@@ -75,7 +86,7 @@ off the process.
     and nothing is happening, you can interrupt the script with ^C. You may restart
     it and it will pick up where it left off.
 
-6.  After installation completes, the installer will launch a script called
+7.  After installation completes, the installer will launch a script called
     `configure_invokeai.py`, which will guide you through the first-time process of
     selecting one or more Stable Diffusion model weights files, downloading and
     configuring them.
@@ -91,7 +102,7 @@ off the process.
     prompted) and configure InvokeAI to use the previously-downloaded files. The
     process for this is described in [Installing Models](INSTALLING_MODELS.md).
 
-7.  The script will now exit and you'll be ready to generate some images. The
+8.  The script will now exit and you'll be ready to generate some images. The
     invokeAI directory will contain numerous files. Look for a shell script
     named `invoke.sh` (Linux/Mac) or `invoke.bat` (Windows). Launch the script
     by double-clicking it or typing its name at the command-line:

docs/installation/index.md

@@ -5,32 +5,7 @@ title: Overview
 We offer several ways to install InvokeAI, each one suited to your
 experience and preferences.
 
-1. [InvokeAI binary installer](INSTALL_INVOKE.md)
+1.  [InvokeAI source code installer](INSTALL_SOURCE.md)
-
-    This is a installer script that installs InvokeAI and all the
-    third party libraries it depends on. It includes access to a
-    "developer console" which will help us debug problems with you and
-    give you to access experimental features.
-
-    When a new InvokeAI release is available, you will run an `update`
-    script to download and install the new version. Intermediate versions
-    that contain experimental and possibly unstable features will not be
-    available.
-
-    This installer is designed for people who want the system to "just
-    work", don't have an interest in tinkering with it, and do not
-    care about upgrading to unreleased experimental features.
-
-    **Important Caveats**
-    - This script does not support AMD GPUs. For Linux AMD support,
-    please use the manual or source code installer methods.
-    - The tab autocomplete feature of the command-line client,
-    which completes commonly used filenames and commands, will
-    not work in this version. All Web UI functions are fully
-    operational, however.
-
-2. [InvokeAI source code installer](INSTALL_SOURCE.md)
-
     This is a script that will install Python, the Anaconda ("conda")
     package manager, all of InvokeAI's its essential third party
     libraries and InvokeAI itself. It includes access to a "developer
@@ -42,12 +17,20 @@ experience and preferences.
     script. This method is recommended for individuals who wish to
     stay on the cutting edge of InvokeAI development and are not
     afraid of occasional breakage.
+    
+    To get started go to the bottom of the
+    [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
+    and download the .zip file for your platform. Unzip the file.
+    If you are on a Windows system, double-click on the `install.bat`
+    script. On a Mac or Linux system, navigate to the file `install.sh`
+    from within the terminal application, and run the script.
+    
+    Sit back and watch the script run.
 
     **Important Caveats**
     - This script is a bit cranky and occasionally hangs or times out,
     forcing you to cancel and restart the script (it will pick up where
-    it left off). It also takes noticeably longer to run than the
+    it left off).
-    binary installer.
 
 2. [Manual Installation](INSTALL_MANUAL.md)
 

docs/installation/older_docs_to_be_removed/INSTALL_LINUX.md

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

docs/installation/older_docs_to_be_removed/INSTALL_MAC.md

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

docs/installation/older_docs_to_be_removed/INSTALL_WINDOWS.md

@@ -7,7 +7,7 @@ title: Manual Installation, Windows
 ## **Notebook install (semi-automated)**
 
 We have a
-[Jupyter notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable-Diffusion-local-Windows.ipynb)
+[Jupyter notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
 with cell-by-cell installation steps. It will download the code in this repo as
 one of the steps, so instead of cloning this repo, simply download the notebook
 from the link above and load it up in VSCode (with the appropriate extensions
@@ -75,7 +75,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
           obtaining an access token for downloading. It will then download and install the
           weights files for you.
 
-          Please look [here](INSTALLING_MODELS.md) for a manual process for doing the
+          Please look [here](../INSTALL_MANUAL.md) for a manual process for doing the
           same thing.
 
 8. Start generating images!
@@ -108,7 +108,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
         To use an alternative model you may invoke the `!switch` command in
         the CLI, or pass `--model <model_name>` during `invoke.py` launch for
         either the CLI or the Web UI. See [Command Line
-        Client](../features/CLI.md#model-selection-and-importation). The
+        Client](../../features/CLI.md#model-selection-and-importation). The
         model names are defined in `configs/models.yaml`.
 
 9. Subsequently, to relaunch the script, first activate the Anaconda

docs/other/CONTRIBUTORS.md

@@ -15,16 +15,16 @@ We thank them for all of their time and hard work.
 
 ## **Current core team**
 
-* lstein (Lincoln Stein) - Co-maintainer
+* @lstein (Lincoln Stein) - Co-maintainer
-* blessedcoolant - Co-maintainer
+* @blessedcoolant - Co-maintainer
-* hipsterusername (Kent Keirsey) - Product Manager
+* @hipsterusername (Kent Keirsey) - Product Manager
-* psychedelicious - Web Team Leader
+* @psychedelicious - Web Team Leader
-* Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
+* @Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
-* damian0815 - Attention Systems and Gameplay Engineer
+* @damian0815 - Attention Systems and Gameplay Engineer
-* mauwii (Matthias Wild) - Continuous integration and product maintenance engineer
+* @mauwii (Matthias Wild) - Continuous integration and product maintenance engineer
-* Netsvetaev (Artur Netsvetaev) - UI/UX Developer
+* @Netsvetaev (Artur Netsvetaev) - UI/UX Developer
-* tildebyte - general gadfly and resident (self-appointed) know-it-all
+* @tildebyte - general gadfly and resident (self-appointed) know-it-all
-* keturn - Lead for Diffusers port
+* @keturn - Lead for Diffusers port
 
 ## **Contributions by**
 

ldm/invoke/globals.py

@@ -5,7 +5,9 @@ otherwise have to be passed through long and complex call chains.
 It defines a Namespace object named "Globals" that contains
 the attributes:
 
-  - root    - the root directory under which "models" and "outputs" can be found
+  - root           - the root directory under which "models" and "outputs" can be found
+  - initfile       - path to the initialization file
+  - try_patchmatch - option to globally disable loading of 'patchmatch' module
 '''
 
 import os

scripts/configure_invokeai.py

@@ -15,7 +15,7 @@ import sys
 import traceback
 import warnings
 from pathlib import Path
-from typing import Dict
+from typing import Dict, Union
 from urllib import request
 
 import requests
@@ -70,9 +70,9 @@ this program and resume later.\n'''
     )
 
 #--------------------------------------------
-def postscript():
+def postscript(errors: None):
-    print(
+    if not any(errors):
-        '''\n** Model Installation Successful **\nYou're all set! You may now launch InvokeAI using one of these two commands:
+        message='''\n** Model Installation Successful **\nYou're all set! You may now launch InvokeAI using one of these two commands:
 Web version:
     python scripts/invoke.py --web  (connect to http://localhost:9090)
 Command-line version:
@@ -85,7 +85,14 @@ automated installation script, execute "invoke.sh" (Linux/Mac) or
 
 Have fun!
 '''
-)
+
+    else:
+        message=f"\n** There were errors during installation. It is possible some of the models were not fully downloaded.\n"
+        for err in errors:
+            message += f"\t - {err}\n"
+        message += "Please check the logs above and correct any issues."
+
+    print(message)
 
 #---------------------------------------------
 def yes_or_no(prompt:str, default_yes=True):
@@ -220,8 +227,7 @@ This involves a few easy steps.
     access_token = HfFolder.get_token()
     if access_token is not None:
         print('found')
-
+    else:
-    if access_token is None:
         print('not found')
         print('''
 4. Thank you! The last step is to enter your HuggingFace access token so that
@@ -239,6 +245,7 @@ This involves a few easy steps.
    Token: '''
         )
         access_token = getpass_asterisk.getpass_asterisk()
+        HfFolder.save_token(access_token)
     return access_token
 
 #---------------------------------------------
@@ -594,17 +601,27 @@ def download_safety_checker():
     print('...success',file=sys.stderr)
 
 #-------------------------------------
-def download_weights(opt:dict):
+def download_weights(opt:dict) -> Union[str, None]:
+    # Authenticate to Huggingface using environment variables.
+    # If successful, authentication will persist for either interactive or non-interactive use.
+    # Default env var expected by HuggingFace is HUGGING_FACE_HUB_TOKEN.
+    if not (access_token := HfFolder.get_token()):
+        # If unable to find an existing token or expected environment, try the non-canonical environment variable (widely used in the community and supported as per docs)
+        if (access_token := os.getenv("HUGGINGFACE_TOKEN")):
+            # set the environment variable here instead of simply calling huggingface_hub.login(token), to maintain consistent behaviour.
+            # when calling the .login() method, the token is cached in the user's home directory. When the env var is used, the token is NOT cached.
+            os.environ['HUGGING_FACE_HUB_TOKEN'] = access_token
+
     if opt.yes_to_all:
         models = recommended_datasets()
-        access_token = HfFolder.get_token()
         if len(models)>0 and access_token is not None:
             successfully_downloaded = download_weight_datasets(models, access_token)
             update_config_file(successfully_downloaded,opt)
             return
         else:
             print('** Cannot download models because no Hugging Face access token could be found. Please re-run without --yes')
-            return
+            return "could not download model weights from Huggingface due to missing or invalid access token"
+
     else:
         choice = user_wants_to_download_weights()
 
@@ -620,10 +637,13 @@ def download_weights(opt:dict):
         return
 
     print('** LICENSE AGREEMENT FOR WEIGHT FILES **')
+    # We are either already authenticated, or will be asked to provide the token interactively
     access_token = authenticate()
     print('\n** DOWNLOADING WEIGHTS **')
     successfully_downloaded = download_weight_datasets(models, access_token)
     update_config_file(successfully_downloaded,opt)
+    if len(successfully_downloaded) < len(models):
+        return "some of the model weights downloads were not successful"
 
 #-------------------------------------
 def get_root(root:str=None)->str:
@@ -818,9 +838,12 @@ def main():
            or not os.path.exists(os.path.join(Globals.root,'configs/stable-diffusion/v1-inference.yaml')):
             initialize_rootdir(Globals.root,opt.yes_to_all)
 
+        # Optimistically try to download all required assets. If any errors occur, add them and proceed anyway.
+        errors=set()
+
         if opt.interactive:
             print('** DOWNLOADING DIFFUSION WEIGHTS **')
-            download_weights(opt)
+            errors.add(download_weights(opt))
         else:
             config_path = Path(Globals.root, opt.config_file or Default_config_file)
             if config_path.exists():
@@ -835,7 +858,7 @@ def main():
         download_codeformer()
         download_clipseg()
         download_safety_checker()
-        postscript()
+        postscript(errors=errors)
     except KeyboardInterrupt:
         print('\nGoodbye! Come back soon.')
     except Exception as e:

source_installer/create_installers.sh

@@ -2,6 +2,8 @@
 
 cd "$(dirname "${BASH_SOURCE[0]}")"
 
+VERSION='2.2.3'
+
 # make the installer zip for linux and mac
 rm -rf invokeAI
 mkdir -p invokeAI
@@ -9,8 +11,8 @@ cp install.sh.in invokeAI/install.sh
 chmod a+x invokeAI/install.sh
 cp readme.txt invokeAI
 
-zip -r invokeAI-src-installer-linux.zip invokeAI
+zip -r invokeAI-src-installer-$VERSION-linux.zip invokeAI
-zip -r invokeAI-src-installer-mac.zip invokeAI
+zip -r invokeAI-src-installer-$VERSION-mac.zip invokeAI
 
 # make the installer zip for windows
 rm -rf invokeAI
@@ -19,7 +21,7 @@ cp install.bat.in invokeAI/install.bat
 cp readme.txt invokeAI
 cp WinLongPathsEnabled.reg invokeAI
 
-zip -r invokeAI-src-installer-windows.zip invokeAI
+zip -r invokeAI-src-installer-$VERSION-windows.zip invokeAI
 
 rm -rf invokeAI
 echo "The installer zips are ready to be distributed.."

source_installer/install.bat.in

@@ -9,6 +9,9 @@
 
 @rem This enables a user to install this project without manually installing conda and git.
 
+@rem change to the script's directory
+PUSHD "%~dp0"
+
 echo "InvokeAI source installer..."
 echo ""
 echo "Some of the installation steps take a long time to run. Please be patient."

source_installer/install.sh.in

@@ -116,13 +116,22 @@ status=$?
 
 if test $status -ne 0
 then
-    echo "Something went wrong while installing Python libraries and cannot continue."
+    if [ "$OS_NAME" == "osx" ]; then
-    echo "See https://invoke-ai.github.io/InvokeAI/INSTALL_SOURCE#troubleshooting for troubleshooting"
+	echo "Python failed to install the environment. You may need to install"
-    echo "tips, or visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
+	echo "the Xcode command line tools to proceed. See step number 3 of"
-    echo "installation methods"
+	echo "https://invoke-ai.github.io/InvokeAI/INSTALL_SOURCE#walk_through for"
+	echo "installation instructions and then run this script again."
+    else
+	echo "Something went wrong while installing Python libraries and cannot continue."
+	echo "See https://invoke-ai.github.io/InvokeAI/INSTALL_SOURCE#troubleshooting for troubleshooting"
+	echo "tips, or visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
+	echo "installation methods"
+    fi
 else
-    ln -sf ./source_installer/invoke.sh.in ./invoke.sh
+    cp ./source_installer/invoke.sh.in ./invoke.sh
-    ln -sf ./source_installer/update.sh.in ./update.sh
+    cp ./source_installer/update.sh.in ./update.sh
+    chmod a+rx ./source_installer/invoke.sh.in
+    chmod a+rx ./source_installer/update.sh.in
 
     conda activate invokeai
     # configure

source_installer/invoke.bat.in

@@ -1,5 +1,6 @@
 @echo off
 
+PUSHD "%~dp0"
 set INSTALL_ENV_DIR=%cd%\installer_files\env
 set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
 
@@ -12,10 +13,10 @@ echo 3. open the developer console
 set /P restore="Please enter 1, 2 or 3: "
 IF /I "%restore%" == "1" (
     echo Starting the InvokeAI command-line..
-    python scripts\invoke.py
+    python scripts\invoke.py %*
 ) ELSE IF /I "%restore%" == "2" (
     echo Starting the InvokeAI browser-based UI..
-    python scripts\invoke.py --web
+    python scripts\invoke.py --web %*
 ) ELSE IF /I "%restore%" == "3" (
     echo Developer Console
     call where python

source_installer/invoke.sh.in

@@ -10,6 +10,11 @@ source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains abou
 
 conda activate invokeai
 
+# set required env var for torch on mac MPS
+if [ "$(uname -s)" == "Darwin" ]; then
+    export PYTORCH_ENABLE_MPS_FALLBACK=1
+fi
+
 if [ "$0" != "bash" ]; then
     echo "Do you want to generate images using the"
     echo "1. command-line"
@@ -17,8 +22,8 @@ if [ "$0" != "bash" ]; then
     echo "3. open the developer console"
     read -p "Please enter 1, 2, or 3: " yn
     case $yn in
-        1 ) printf "\nStarting the InvokeAI command-line..\n"; python scripts/invoke.py;;
+        1 ) printf "\nStarting the InvokeAI command-line..\n"; python scripts/invoke.py $*;;
-        2 ) printf "\nStarting the InvokeAI browser-based UI..\n"; python scripts/invoke.py --web;;
+        2 ) printf "\nStarting the InvokeAI browser-based UI..\n"; python scripts/invoke.py --web $*;;
         3 ) printf "\nDeveloper Console:\n"; file_name=$(basename "${BASH_SOURCE[0]}"); bash --init-file "$file_name";;
         * ) echo "Invalid selection"; exit;;
     esac