Merge branch 'release-candidate-2-1-3' of github.com:/invoke-ai/InvokeAI into release-candidate-2-1-3

moved taming-transformers-rom1504 to pip dependencies

.dockerignore

@@ -1,26 +1,3 @@
 *
-!backend
-!frontend
-!binary_installer
-!ldm
-!main.py
-!scripts
-!server
-!static
-!setup.py
+!environment*.yml
 !docker-build
-!docs
-docker-build/Dockerfile
-
-# Guard against pulling in any models that might exist in the directory tree
-**/*.pt*
-
-# unignore configs, but only ignore the custom models.yaml, in case it exists
-!configs
-configs/models.yaml
-
-# unignore environment dirs/files, but ignore the environment.yml file or symlink in case it exists
-!environment*
-environment.yml
-
-**/__pycache__

.editorconfig

@@ -1,12 +0,0 @@
-# All files
-[*]
-charset = utf-8
-end_of_line = lf
-indent_size = 2
-indent_style = space
-insert_final_newline = true
-trim_trailing_whitespace = true
-
-# Python
-[*.py]
-indent_size = 4

.github/CODEOWNERS

@@ -2,6 +2,3 @@ ldm/invoke/pngwriter.py @CapableWeb
 ldm/invoke/server_legacy.py @CapableWeb
 scripts/legacy_api.py @CapableWeb
 tests/legacy_tests.sh @CapableWeb
-installer/ @tildebyte
-.github/workflows/ @mauwii
-docker_build/ @mauwii

.github/workflows/build-cloud-img.yml

@@ -1,87 +0,0 @@
-name: Build and push cloud image
-on:
-  workflow_dispatch:
-  push:
-    branches:
-    - main
-    tags:
-      - v*
-  # we will NOT push the image on pull requests, only test buildability.
-  pull_request:
-    branches:
-    - main
-
-permissions:
-  contents: read
-  packages: write
-
-env:
-  REGISTRY: ghcr.io
-  IMAGE_NAME: ${{ github.repository }}
-
-jobs:
-  docker:
-    strategy:
-      fail-fast: false
-      matrix:
-        arch:
-        - x86_64
-        # requires resolving a patchmatch issue
-        # - aarch64
-    runs-on: ubuntu-latest
-    name: ${{ matrix.arch }}
-    steps:
-    - name: Checkout
-      uses: actions/checkout@v3
-
-    - name: Set up QEMU
-      uses: docker/setup-qemu-action@v2
-      if: matrix.arch == 'aarch64'
-
-    - name: Docker meta
-      id: meta
-      uses: docker/metadata-action@v4
-      with:
-        images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
-        # see https://github.com/docker/metadata-action
-        # will push the following tags:
-        # :edge
-        # :main (+ any other branches enabled in the workflow)
-        # :<tag>
-        # :1.2.3 (for semver tags)
-        # :1.2 (for semver tags)
-        # :<sha>
-        tags: |
-          type=edge,branch=main
-          type=ref,event=branch
-          type=ref,event=tag
-          type=semver,pattern={{version}}
-          type=semver,pattern={{major}}.{{minor}}
-          type=sha
-        # suffix image tags with architecture
-        flavor: |
-          latest=auto
-          suffix=-${{ matrix.arch }},latest=true
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v2
-
-    # do not login to container registry on PRs
-    - if: github.event_name != 'pull_request'
-      name: Docker login
-      uses: docker/login-action@v2
-      with:
-        registry: ghcr.io
-        username: ${{ github.actor }}
-        password: ${{ secrets.GITHUB_TOKEN }}
-
-    - name: Build and push cloud image
-      uses: docker/build-push-action@v3
-      with:
-        context: .
-        file: docker-build/Dockerfile.cloud
-        platforms: Linux/${{ matrix.arch }}
-        # do not push the image on PRs
-        push: ${{ github.event_name != 'pull_request' }}
-        tags: ${{ steps.meta.outputs.tags }}
-        labels: ${{ steps.meta.outputs.labels }}

.github/workflows/build-container.yml

@@ -5,17 +5,23 @@ on:
   push:
     branches:
       - 'main'
+      - 'development'
 
 jobs:
   docker:
     strategy:
       fail-fast: false
       matrix:
-        pip-requirements:
-          - requirements-lin-amd.txt
-          - requirements-lin-cuda.txt
+        arch:
+          - x86_64
+          - aarch64
+        include:
+          - arch: x86_64
+            conda-env-file: environment-lin-cuda.yml
+          - arch: aarch64
+            conda-env-file: environment-lin-aarch64.yml
     runs-on: ubuntu-latest
-    name: ${{ matrix.pip-requirements }} ${{ matrix.arch }}
+    name: ${{ matrix.arch }}
     steps:
       - name: prepare docker-tag
         env:
@@ -32,7 +38,11 @@ jobs:
         with:
           context: .
           file: docker-build/Dockerfile
-          platforms: linux/amd64,linux/arm64
+          platforms: Linux/${{ matrix.arch }}
           push: false
-          tags: ${{ env.dockertag }}:${{ matrix.pip-requirements }}
-          build-args: pip_requirements=${{ matrix.pip-requirements }}
+          tags: ${{ env.dockertag }}:${{ matrix.arch }}
+          build-args: |
+            conda_env_file=${{ matrix.conda-env-file }}
+            conda_version=py39_4.12.0-Linux-${{ matrix.arch }}
+            invokeai_git=${{ github.repository }}
+            invokeai_branch=${{ github.ref_name }}

.github/workflows/mkdocs-material.yml

@@ -22,7 +22,7 @@ jobs:
       - name: install requirements
         run: |
           python -m \
-            pip install -r docs/requirements-mkdocs.txt
+            pip install -r requirements-mkdocs.txt
 
       - name: confirm buildability
         run: |

.github/workflows/test-invoke-conda.yml

@@ -4,6 +4,7 @@ on:
     branches:
       - 'main'
       - 'development'
+      - 'fix-gh-actions-fork'
   pull_request:
     branches:
       - 'main'
@@ -12,44 +13,31 @@ on:
 jobs:
   matrix:
     strategy:
+      fail-fast: false
       matrix:
         stable-diffusion-model:
-          - 'stable-diffusion-1.5'
-        environment-yaml:
-          - environment-lin-amd.yml
-          - environment-lin-cuda.yml
-          - environment-mac.yml
-          - environment-win-cuda.yml
+          # - 'https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt'
+          - 'https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt'
+        os:
+          - ubuntu-latest
+          - macOS-12
         include:
-          - environment-yaml: environment-lin-amd.yml
-            os: ubuntu-22.04
-            curl-command: curl
-            github-env: $GITHUB_ENV
+          - os: ubuntu-latest
+            environment-file: environment-lin-cuda.yml
             default-shell: bash -l {0}
-          - environment-yaml: environment-lin-cuda.yml
-            os: ubuntu-22.04
-            curl-command: curl
-            github-env: $GITHUB_ENV
+          - os: macOS-12
+            environment-file: environment-mac.yml
             default-shell: bash -l {0}
-          - environment-yaml: environment-mac.yml
-            os: macos-12
-            curl-command: curl
-            github-env: $GITHUB_ENV
-            default-shell: bash -l {0}
-          - environment-yaml: environment-win-cuda.yml
-            os: windows-2022
-            curl-command: curl.exe
-            github-env: $env:GITHUB_ENV
-            default-shell: pwsh
-          - stable-diffusion-model: stable-diffusion-1.5
-            stable-diffusion-model-url: https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
-            stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1
-            stable-diffusion-model-dl-name: v1-5-pruned-emaonly.ckpt
-    name: ${{ matrix.environment-yaml }} on ${{ matrix.os }}
+          # - stable-diffusion-model: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
+          #   stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
+          #   stable-diffusion-model-switch: stable-diffusion-1.4
+          - stable-diffusion-model: https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
+            stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
+            stable-diffusion-model-switch: stable-diffusion-1.5
+    name: ${{ matrix.os }} with ${{ matrix.stable-diffusion-model-switch }}
     runs-on: ${{ matrix.os }}
     env:
       CONDA_ENV_NAME: invokeai
-      INVOKEAI_ROOT: '${{ github.workspace }}/invokeai'
     defaults:
       run:
         shell: ${{ matrix.default-shell }}
@@ -59,19 +47,17 @@ jobs:
         uses: actions/checkout@v3
 
       - name: create models.yaml from example
-        run: |
-          mkdir -p ${{ env.INVOKEAI_ROOT }}/configs
-          cp configs/models.yaml.example ${{ env.INVOKEAI_ROOT }}/configs/models.yaml
+        run: cp configs/models.yaml.example configs/models.yaml
 
       - name: create environment.yml
-        run: cp "environments-and-requirements/${{ matrix.environment-yaml }}" environment.yml
+        run: cp environments-and-requirements/${{ matrix.environment-file }} environment.yml
 
       - name: Use cached conda packages
         id: use-cached-conda-packages
         uses: actions/cache@v3
         with:
           path: ~/conda_pkgs_dir
-          key: conda-pkgs-${{ runner.os }}-${{ runner.arch }}-${{ hashFiles(matrix.environment-yaml) }}
+          key: conda-pkgs-${{ runner.os }}-${{ runner.arch }}-${{ hashFiles(matrix.environment-file) }}
 
       - name: Activate Conda Env
         id: activate-conda-env
@@ -83,64 +69,58 @@ jobs:
 
       - name: set test prompt to main branch validation
         if: ${{ github.ref == 'refs/heads/main' }}
-        run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> ${{ matrix.github-env }}
+        run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> $GITHUB_ENV
 
       - name: set test prompt to development branch validation
         if: ${{ github.ref == 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/dev_prompts.txt" >> ${{ matrix.github-env }}
+        run: echo "TEST_PROMPTS=tests/dev_prompts.txt" >> $GITHUB_ENV
 
       - name: set test prompt to Pull Request validation
         if: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
+        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> $GITHUB_ENV
 
       - name: Use Cached Stable Diffusion Model
         id: cache-sd-model
         uses: actions/cache@v3
         env:
-          cache-name: cache-${{ matrix.stable-diffusion-model }}
+          cache-name: cache-${{ matrix.stable-diffusion-model-switch }}
         with:
-          path: ${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}
+          path: ${{ matrix.stable-diffusion-model-dl-path }}
           key: ${{ env.cache-name }}
 
-      - name: Download ${{ matrix.stable-diffusion-model }}
+      - name: Download ${{ matrix.stable-diffusion-model-switch }}
         id: download-stable-diffusion-model
         if: ${{ steps.cache-sd-model.outputs.cache-hit != 'true' }}
         run: |
-          mkdir -p "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}"
-          ${{ matrix.curl-command }} -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" -o "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}/${{ matrix.stable-diffusion-model-dl-name }}" -L ${{ matrix.stable-diffusion-model-url }}
+          [[ -d models/ldm/stable-diffusion-v1 ]] \
+            || mkdir -p models/ldm/stable-diffusion-v1
+          curl \
+            -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" \
+            -o ${{ matrix.stable-diffusion-model-dl-path }} \
+            -L ${{ matrix.stable-diffusion-model }}
 
-      - name: run configure_invokeai.py
+      - name: run preload_models.py
         id: run-preload-models
         run: |
-          python scripts/configure_invokeai.py --no-interactive --yes
-
-      - name: cat invokeai.init
-        id: cat-invokeai
-        run: cat ${{ env.INVOKEAI_ROOT }}/invokeai.init
+          python scripts/preload_models.py \
+            --no-interactive
 
       - name: Run the tests
         id: run-tests
-        if: matrix.os != 'windows-2022'
         run: |
           time python scripts/invoke.py \
-            --no-patchmatch \
-            --no-nsfw_checker \
-            --model ${{ matrix.stable-diffusion-model }} \
-            --from_file ${{ env.TEST_PROMPTS }} \
-            --root="${{ env.INVOKEAI_ROOT }}" \
-            --outdir="${{ env.INVOKEAI_ROOT }}/outputs"
+            --model ${{ matrix.stable-diffusion-model-switch }} \
+            --from_file ${{ env.TEST_PROMPTS }}
 
       - name: export conda env
         id: export-conda-env
-        if: matrix.os != 'windows-2022'
         run: |
           mkdir -p outputs/img-samples
-          conda env export --name ${{ env.CONDA_ENV_NAME }} > ${{ env.INVOKEAI_ROOT }}/outputs/environment-${{ runner.os }}-${{ runner.arch }}.yml
+          conda env export --name ${{ env.CONDA_ENV_NAME }} > outputs/img-samples/environment-${{ runner.os }}-${{ runner.arch }}.yml
 
       - name: Archive results
-        if: matrix.os != 'windows-2022'
         id: archive-results
         uses: actions/upload-artifact@v3
         with:
-          name: results_${{ matrix.requirements-file }}_${{ matrix.python-version }}
-          path: ${{ env.INVOKEAI_ROOT }}/outputs
+          name: results_${{ matrix.os }}_${{ matrix.stable-diffusion-model-switch }}
+          path: outputs/img-samples

.github/workflows/test-invoke-pip.yml

@@ -1,130 +0,0 @@
-name: Test invoke.py pip
-on:
-  push:
-    branches:
-      - 'main'
-      - 'development'
-  pull_request:
-    branches:
-      - 'main'
-      - 'development'
-
-jobs:
-  matrix:
-    strategy:
-      matrix:
-        stable-diffusion-model:
-          - stable-diffusion-1.5
-        requirements-file:
-          - requirements-lin-cuda.txt
-          - requirements-lin-amd.txt
-          - requirements-mac-mps-cpu.txt
-          - requirements-win-colab-cuda.txt
-        python-version:
-          # - '3.9'
-          - '3.10'
-        include:
-          - requirements-file: requirements-lin-cuda.txt
-            os: ubuntu-22.04
-            curl-command: curl
-            github-env: $GITHUB_ENV
-          - requirements-file: requirements-lin-amd.txt
-            os: ubuntu-22.04
-            curl-command: curl
-            github-env: $GITHUB_ENV
-          - requirements-file: requirements-mac-mps-cpu.txt
-            os: macOS-12
-            curl-command: curl
-            github-env: $GITHUB_ENV
-          - requirements-file: requirements-win-colab-cuda.txt
-            os: windows-2022
-            curl-command: curl.exe
-            github-env: $env:GITHUB_ENV
-          - stable-diffusion-model: stable-diffusion-1.5
-            stable-diffusion-model-url: https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
-            stable-diffusion-model-dl-path: models/ldm/stable-diffusion-v1
-            stable-diffusion-model-dl-name: v1-5-pruned-emaonly.ckpt
-    name: ${{ matrix.requirements-file }} on ${{ matrix.python-version }}
-    runs-on: ${{ matrix.os }}
-    steps:
-      - name: Checkout sources
-        id: checkout-sources
-        uses: actions/checkout@v3
-
-      - name: set INVOKEAI_ROOT Windows
-        if: matrix.os == 'windows-2022'
-        run: |
-          echo "INVOKEAI_ROOT=${{ github.workspace }}\invokeai" >> ${{ matrix.github-env }}
-          echo "INVOKEAI_OUTDIR=${{ github.workspace }}\invokeai\outputs" >> ${{ matrix.github-env }}
-
-      - name: set INVOKEAI_ROOT others
-        if: matrix.os != 'windows-2022'
-        run: |
-          echo "INVOKEAI_ROOT=${{ github.workspace }}/invokeai" >> ${{ matrix.github-env }}
-          echo "INVOKEAI_OUTDIR=${{ github.workspace }}/invokeai/outputs" >> ${{ matrix.github-env }}
-
-      - name: create models.yaml from example
-        run: |
-          mkdir -p ${{ env.INVOKEAI_ROOT }}/configs
-          cp configs/models.yaml.example ${{ env.INVOKEAI_ROOT }}/configs/models.yaml
-
-      - name: set test prompt to main branch validation
-        if: ${{ github.ref == 'refs/heads/main' }}
-        run: echo "TEST_PROMPTS=tests/preflight_prompts.txt" >> ${{ matrix.github-env }}
-
-      - name: set test prompt to development branch validation
-        if: ${{ github.ref == 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/dev_prompts.txt" >> ${{ matrix.github-env }}
-
-      - name: set test prompt to Pull Request validation
-        if: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/development' }}
-        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
-
-      - name: create requirements.txt
-        run: cp 'environments-and-requirements/${{ matrix.requirements-file }}' '${{ matrix.requirements-file }}'
-
-      - name: setup python
-        uses: actions/setup-python@v4
-        with:
-          python-version: ${{ matrix.python-version }}
-          # cache: 'pip'
-          # cache-dependency-path: ${{ matrix.requirements-file }}
-
-      # - name: install dependencies
-      #   run: ${{ env.pythonLocation }}/bin/pip install --upgrade pip setuptools wheel
-
-      - name: install requirements
-        run: pip3 install -r '${{ matrix.requirements-file }}'
-
-      - name: Use Cached Stable Diffusion Model
-        id: cache-sd-model
-        uses: actions/cache@v3
-        env:
-          cache-name: cache-${{ matrix.stable-diffusion-model }}
-        with:
-          path: ${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}
-          key: ${{ env.cache-name }}
-
-      - name: Download ${{ matrix.stable-diffusion-model }}
-        id: download-stable-diffusion-model
-        if: ${{ steps.cache-sd-model.outputs.cache-hit != 'true' }}
-        run: |
-          mkdir -p "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}"
-          ${{ matrix.curl-command }} -H "Authorization: Bearer ${{ secrets.HUGGINGFACE_TOKEN }}" -o "${{ env.INVOKEAI_ROOT }}/${{ matrix.stable-diffusion-model-dl-path }}/${{ matrix.stable-diffusion-model-dl-name }}" -L ${{ matrix.stable-diffusion-model-url }}
-
-      - name: run configure_invokeai.py
-        id: run-preload-models
-        run: python3 scripts/configure_invokeai.py --no-interactive --yes
-
-      - name: Run the tests
-        id: run-tests
-        if: matrix.os != 'windows-2022'
-        run: python3 scripts/invoke.py --no-patchmatch --no-nsfw_checker --model ${{ matrix.stable-diffusion-model }} --from_file ${{ env.TEST_PROMPTS }} --root="${{ env.INVOKEAI_ROOT }}" --outdir="${{ env.INVOKEAI_OUTDIR }}"
-
-      - name: Archive results
-        id: archive-results
-        if: matrix.os != 'windows-2022'
-        uses: actions/upload-artifact@v3
-        with:
-          name: results_${{ matrix.requirements-file }}_${{ matrix.python-version }}
-          path: ${{ env.INVOKEAI_ROOT }}/outputs

.gitignore

@@ -6,7 +6,6 @@ models/ldm/stable-diffusion-v1/model.ckpt
 # ignore user models config
 configs/models.user.yaml
 config/models.user.yml
-invokeai.init
 
 # ignore the Anaconda/Miniconda installer used while building Docker image
 anaconda.sh
@@ -195,6 +194,10 @@ checkpoints
 
 # Let the frontend manage its own gitignore
 !frontend/*
+frontend/apt-get
+frontend/dist
+frontend/sudo
+frontend/update
 
 # Scratch folder
 .scratch/
@@ -215,22 +218,12 @@ models/clipseg
 models/gfpgan
 
 # ignore initfile
-.invokeai
+invokeai.init
 
 # ignore environment.yml and requirements.txt
 # these are links to the real files in environments-and-requirements
 environment.yml
 requirements.txt
 
-# source installer files
-installer/*zip
-installer/install.bat
-installer/install.sh
-installer/update.bat
-installer/update.sh
-
 # this may be present if the user created a venv
 invokeai
-
-# no longer stored in source directory
-models

1-click-installer/create_installers.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+cd "$(dirname "${BASH_SOURCE[0]}")"
+
+# make the installer zip for linux and mac
+rm -rf invokeAI
+mkdir -p invokeAI
+cp install.sh invokeAI
+cp readme.txt invokeAI
+
+zip -r invokeAI-linux.zip invokeAI
+zip -r invokeAI-mac.zip invokeAI
+
+# make the installer zip for windows
+rm -rf invokeAI
+mkdir -p invokeAI
+cp install.bat invokeAI
+cp readme.txt invokeAI
+
+zip -r invokeAI-windows.zip invokeAI
+
+echo "The installer zips are ready to be distributed.."

1-click-installer/install.bat

@@ -0,0 +1,116 @@
+@echo off
+
+@rem This script will install git and conda (if not found on the PATH variable)
+@rem  using micromamba (an 8mb static-linked single-file binary, conda replacement).
+@rem For users who already have git and conda, this step will be skipped.
+
+@rem Next, it'll checkout the project's git repo, if necessary.
+@rem Finally, it'll create the conda environment and preload the models.
+
+@rem This enables a user to install this project without manually installing conda and git.
+
+echo "Installing InvokeAI.."
+echo.
+
+@rem config
+set MAMBA_ROOT_PREFIX=%cd%\installer_files\mamba
+set INSTALL_ENV_DIR=%cd%\installer_files\env
+set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
+set REPO_URL=https://github.com/invoke-ai/InvokeAI.git
+set umamba_exists=F
+@rem Change the download URL to an InvokeAI repo's release URL
+
+@rem figure out whether git and conda needs to be installed
+if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
+
+set PACKAGES_TO_INSTALL=
+
+call conda --version >.tmp1 2>.tmp2
+if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
+
+call git --version >.tmp1 2>.tmp2
+if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
+
+call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version >.tmp1 2>.tmp2
+if "%ERRORLEVEL%" EQU "0" set umamba_exists=T
+
+@rem (if necessary) install git and conda into a contained environment
+if "%PACKAGES_TO_INSTALL%" NEQ "" (
+    @rem download micromamba
+    if "%umamba_exists%" == "F" (
+        echo "Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to %MAMBA_ROOT_PREFIX%\micromamba.exe"
+
+        mkdir "%MAMBA_ROOT_PREFIX%"
+        call curl -L "%MICROMAMBA_DOWNLOAD_URL%" > "%MAMBA_ROOT_PREFIX%\micromamba.exe"
+
+        @rem test the mamba binary
+        echo Micromamba version:
+        call "%MAMBA_ROOT_PREFIX%\micromamba.exe" --version
+    )
+
+    @rem create the installer env
+    if not exist "%INSTALL_ENV_DIR%" (
+        call "%MAMBA_ROOT_PREFIX%\micromamba.exe" create -y --prefix "%INSTALL_ENV_DIR%"
+    )
+
+    echo "Packages to install:%PACKAGES_TO_INSTALL%"
+
+    call "%MAMBA_ROOT_PREFIX%\micromamba.exe" install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
+
+    if not exist "%INSTALL_ENV_DIR%" (
+        echo "There was a problem while installing%PACKAGES_TO_INSTALL% using micromamba. Cannot continue."
+        pause
+        exit /b
+    )
+)
+
+set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Library\bin;%INSTALL_ENV_DIR%\Scripts;%INSTALL_ENV_DIR%\Library\usr\bin;%PATH%
+
+@rem get the repo (and load into the current directory)
+if not exist ".git" (
+    call git init
+    call git config --local init.defaultBranch main
+    call git remote add origin %REPO_URL%
+    call git fetch
+#    call git checkout origin/main -ft
+    call git checkout origin/release-candidate-2-1-3 -ft
+)
+
+@rem activate the base env
+call conda activate
+
+@rem create the environment
+call conda env remove -n invokeai
+cp environments-and-requirements\environment-win-cuda.yml environment.yml 
+call conda env create
+if "%ERRORLEVEL%" NEQ "0" (
+   echo ""
+   echo "Something went wrong while installing Python libraries and cannot continue.
+   echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
+   echo "installation methods."
+   echo "Press any key to continue"
+   pause
+   exit /b
+)
+
+call conda activate invokeai
+@rem preload the models
+call python scripts\preload_models.py
+if "%ERRORLEVEL%" NEQ "0" (
+   echo ""
+   echo "The preload_models.py script crashed or was cancelled."
+   echo "InvokeAI is not ready to run. To run preload_models.py again,"
+   echo "run the command 'update.bat' in this directory."
+   echo "Press any key to continue"
+   pause
+   exit /b
+)
+
+@rem tell the user their next steps
+echo ""
+echo "* InvokeAI installed successfully *"
+echo "You can now start generating images by double-clicking the 'invoke.bat' file (inside this folder)
+echo "Press any key to continue"
+pause
+exit 0
+

1-click-installer/install.sh

@@ -0,0 +1,135 @@
+#!/bin/bash
+
+# This script will install git and conda (if not found on the PATH variable)
+#  using micromamba (an 8mb static-linked single-file binary, conda replacement).
+# For users who already have git and conda, this step will be skipped.
+
+# Next, it'll checkout the project's git repo, if necessary.
+# Finally, it'll create the conda environment and preload the models.
+
+# This enables a user to install this project without manually installing conda and git.
+
+cd "$(dirname "${BASH_SOURCE[0]}")"
+
+echo "Installing InvokeAI.."
+echo ""
+
+OS_NAME=$(uname -s)
+case "${OS_NAME}" in
+    Linux*)     OS_NAME="linux";;
+    Darwin*)    OS_NAME="mac";;
+    *)          echo "Unknown OS: $OS_NAME! This script runs only on Linux or Mac" && exit
+esac
+
+OS_ARCH=$(uname -m)
+case "${OS_ARCH}" in
+    x86_64*)    OS_ARCH="64";;
+    arm64*)     OS_ARCH="arm64";;
+    *)          echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit
+esac
+
+# https://mamba.readthedocs.io/en/latest/installation.html
+if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi
+
+# config
+export MAMBA_ROOT_PREFIX="$(pwd)/installer_files/mamba"
+INSTALL_ENV_DIR="$(pwd)/installer_files/env"
+MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${OS_NAME}-${OS_ARCH}/latest"
+REPO_URL="https://github.com/invoke-ai/InvokeAI.git"
+umamba_exists="F"
+
+# figure out whether git and conda needs to be installed
+if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
+
+PACKAGES_TO_INSTALL=""
+if ! $(which conda) -V &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda"; fi
+if ! which git &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
+
+if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi
+
+# (if necessary) install git and conda into a contained environment
+if [ "$PACKAGES_TO_INSTALL" != "" ]; then
+    # download micromamba
+    if [ "$umamba_exists" == "F" ]; then
+        echo "Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to $MAMBA_ROOT_PREFIX/micromamba"
+
+        mkdir -p "$MAMBA_ROOT_PREFIX"
+        curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvj bin/micromamba -O > "$MAMBA_ROOT_PREFIX/micromamba"
+
+        chmod u+x "$MAMBA_ROOT_PREFIX/micromamba"
+
+        # test the mamba binary
+        echo "Micromamba version:"
+        "$MAMBA_ROOT_PREFIX/micromamba" --version
+    fi
+
+    # create the installer env
+    if [ ! -e "$INSTALL_ENV_DIR" ]; then
+        "$MAMBA_ROOT_PREFIX/micromamba" create -y --prefix "$INSTALL_ENV_DIR"
+    fi
+
+    echo "Packages to install:$PACKAGES_TO_INSTALL"
+
+    "$MAMBA_ROOT_PREFIX/micromamba" install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge $PACKAGES_TO_INSTALL
+
+    if [ ! -e "$INSTALL_ENV_DIR" ]; then
+        echo "There was a problem while initializing micromamba. Cannot continue."
+        exit
+    fi
+fi
+
+if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
+
+# get the repo (and load into the current directory)
+if [ ! -e ".git" ]; then
+    git init
+    git config --local init.defaultBranch main
+    git remote add origin "$REPO_URL"
+    git fetch
+    git checkout origin/release-candidate-2-1-3 -ft
+fi
+
+# create the environment
+CONDA_BASEPATH=$(conda info --base)
+source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
+
+conda activate
+if [ "$OS_NAME" == "mac" ]; then
+    echo "Macintosh system detected. Installing MPS and CPU support."
+    ln -sf environments-and-requirements/environment-mac.yml environment.yml
+else
+    if (lsmod | grep amdgpu) &>/dev/null ; then
+	echo "Linux system with AMD GPU driver detected. Installing ROCm and CPU support"
+	ln -sf environments-and-requirements/environment-lin-amd.yml environment.yml
+    else
+	echo "Linux system detected. Installing CUDA and CPU support."
+	ln -sf environments-and-requirements/environment-lin-cuda.yml environment.yml
+    fi
+fi
+conda env update
+
+status=$?
+
+if test $status -ne 0
+then
+   echo "Something went wrong while installing Python libraries and cannot continue."
+   echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
+   echo "installation methods"
+else
+    conda activate invokeai
+    # preload the models
+    echo "Calling the preload_models.py script"
+    python scripts/preload_models.py
+    status=$?
+    if test $status -ne 0
+       then
+	   echo "The preload_models.py script crashed or was cancelled."
+           echo "InvokeAI is not ready to run. Try again by running"
+           echo "update.sh in this directory."
+       else
+           # tell the user their next steps
+	   echo "You can now start generating images by running invoke.sh (inside this folder), using ./invoke.sh"
+       fi
+fi
+
+conda activate invokeai

1-click-installer/readme.txt

@@ -0,0 +1,11 @@
+InvokeAI
+
+Project homepage: https://github.com/invoke-ai/InvokeAI
+
+Installation on Windows:
+ Please double-click the 'install.bat' file (while keeping it inside the invokeAI folder).
+
+Installation on Linux and Mac:
+ Please open the terminal, and run './install.sh' (while keeping it inside the invokeAI folder).
+
+After installation, please run the 'invoke.bat' file (on Windows) or 'invoke.sh' file (on Linux/Mac) to start InvokeAI.

CODE_OF_CONDUCT.md

@@ -1,128 +0,0 @@
-# Contributor Covenant Code of Conduct
-
-## Our Pledge
-
-We as members, contributors, and leaders pledge to make participation in our
-community a harassment-free experience for everyone, regardless of age, body
-size, visible or invisible disability, ethnicity, sex characteristics, gender
-identity and expression, level of experience, education, socio-economic status,
-nationality, personal appearance, race, religion, or sexual identity
-and orientation.
-
-We pledge to act and interact in ways that contribute to an open, welcoming,
-diverse, inclusive, and healthy community.
-
-## Our Standards
-
-Examples of behavior that contributes to a positive environment for our
-community include:
-
-* Demonstrating empathy and kindness toward other people
-* Being respectful of differing opinions, viewpoints, and experiences
-* Giving and gracefully accepting constructive feedback
-* Accepting responsibility and apologizing to those affected by our mistakes,
-  and learning from the experience
-* Focusing on what is best not just for us as individuals, but for the
-  overall community
-
-Examples of unacceptable behavior include:
-
-* The use of sexualized language or imagery, and sexual attention or
-  advances of any kind
-* Trolling, insulting or derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or email
-  address, without their explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
-  professional setting
-
-## Enforcement Responsibilities
-
-Community leaders are responsible for clarifying and enforcing our standards of
-acceptable behavior and will take appropriate and fair corrective action in
-response to any behavior that they deem inappropriate, threatening, offensive,
-or harmful.
-
-Community leaders have the right and responsibility to remove, edit, or reject
-comments, commits, code, wiki edits, issues, and other contributions that are
-not aligned to this Code of Conduct, and will communicate reasons for moderation
-decisions when appropriate.
-
-## Scope
-
-This Code of Conduct applies within all community spaces, and also applies when
-an individual is officially representing the community in public spaces.
-Examples of representing our community include using an official e-mail address,
-posting via an official social media account, or acting as an appointed
-representative at an online or offline event.
-
-## Enforcement
-
-Instances of abusive, harassing, or otherwise unacceptable behavior
-may be reported to the community leaders responsible for enforcement
-at https://github.com/invoke-ai/InvokeAI/issues.  All complaints will
-be reviewed and investigated promptly and fairly.
-
-All community leaders are obligated to respect the privacy and security of the
-reporter of any incident.
-
-## Enforcement Guidelines
-
-Community leaders will follow these Community Impact Guidelines in determining
-the consequences for any action they deem in violation of this Code of Conduct:
-
-### 1. Correction
-
-**Community Impact**: Use of inappropriate language or other behavior deemed
-unprofessional or unwelcome in the community.
-
-**Consequence**: A private, written warning from community leaders, providing
-clarity around the nature of the violation and an explanation of why the
-behavior was inappropriate. A public apology may be requested.
-
-### 2. Warning
-
-**Community Impact**: A violation through a single incident or series
-of actions.
-
-**Consequence**: A warning with consequences for continued behavior. No
-interaction with the people involved, including unsolicited interaction with
-those enforcing the Code of Conduct, for a specified period of time. This
-includes avoiding interactions in community spaces as well as external channels
-like social media. Violating these terms may lead to a temporary or
-permanent ban.
-
-### 3. Temporary Ban
-
-**Community Impact**: A serious violation of community standards, including
-sustained inappropriate behavior.
-
-**Consequence**: A temporary ban from any sort of interaction or public
-communication with the community for a specified period of time. No public or
-private interaction with the people involved, including unsolicited interaction
-with those enforcing the Code of Conduct, is allowed during this period.
-Violating these terms may lead to a permanent ban.
-
-### 4. Permanent Ban
-
-**Community Impact**: Demonstrating a pattern of violation of community
-standards, including sustained inappropriate behavior,  harassment of an
-individual, or aggression toward or disparagement of classes of individuals.
-
-**Consequence**: A permanent ban from any sort of public interaction within
-the community.
-
-## Attribution
-
-This Code of Conduct is adapted from the [Contributor Covenant][homepage],
-version 2.0, available at
-https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
-
-Community Impact Guidelines were inspired by [Mozilla's code of conduct
-enforcement ladder](https://github.com/mozilla/diversity).
-
-[homepage]: https://www.contributor-covenant.org
-
-For answers to common questions about this code of conduct, see the FAQ at
-https://www.contributor-covenant.org/faq. Translations are available at
-https://www.contributor-covenant.org/translations.

InvokeAI_Statement_of_Values.md

@@ -1,85 +0,0 @@
-<img src="docs/assets/invoke_ai_banner.png" align="center">
-
-Invoke-AI is a community of software developers, researchers, and user
-interface experts who have come together on a voluntary basis to build
-software tools which support cutting edge AI text-to-image
-applications. This community is open to anyone who wishes to
-contribute to the effort and has the skill and time to do so.
-
-# Our Values
-
-The InvokeAI team is a diverse community which includes individuals
-from various parts of the world and many walks of life. Despite our
-differences, we share a number of core values which we ask prospective
-contributors to understand and respect. We believe:
-
-1. That Open Source Software is a positive force in the world. We
-create software that can be used, reused, and redistributed, without
-restrictions, under a straightforward Open Source license (MIT). We
-believe that Open Source benefits society as a whole by increasing the
-availability of high quality software to all.
-
-2. That those who create software should receive proper attribution
-for their creative work. While we support the exchange and reuse of
-Open Source Software, we feel strongly that the original authors of a
-piece of code should receive credit for their contribution, and we
-endeavor to do so whenever possible.
-
-3. That there is moral ambiguity surrounding AI-assisted art. We are
-aware of the moral and ethical issues surrounding the release of the
-Stable Diffusion model and similar products. We are aware that, due to
-the composition of their training sets, current AI-generated image
-models are biased against certain ethnic groups, cultural concepts of
-beauty, ethnic stereotypes, and gender roles.
-
-      1. We recognize the potential for harm to these groups that these biases
-       represent and trust that future AI models will take steps towards
-       reducing or eliminating the biases noted above, respect and give due
-       credit to the artists whose work is sourced, and call on developers
-       and users to favor these models over the older ones as they become
-       available.
-
-4. We are deeply committed to ensuring that this technology benefits
-everyone, including artists. We see AI art not as a replacement for
-the artist, but rather as a tool to empower them. With that
-in mind, we are constantly debating how to build systems that put
-artists’ needs first: tools which can be readily integrated into an
-artist’s existing workflows and practices, enhancing their work and
-helping them to push it further. Every decision we take as a team,
-which includes several artists, aims to build towards that goal.
-
-5. That artificial intelligence can be a force for good in the world,
-but must be used responsibly. Artificial intelligence technologies
-have the potential to improve society, in everything from cancer care,
-to customer service, to creative writing.
-
-     1. While we do not believe that software should arbitrarily limit what
-     users can do with it, we recognize that when used irresponsibly, AI
-     has the potential to do much harm. Our Discord server is actively
-     moderated in order to minimize the potential of harm from
-     user-contributed images. In addition, we ask users of our software to
-     refrain from using it in any way that would cause mental, emotional or
-     physical harm to individuals and vulnerable populations including (but
-     not limited to) women; minors; ethnic minorities; religious groups;
-     members of LGBTQIA communities; and people with disabilities or
-     impairments.
-
-     2. Note that some of the image generation AI models which the Invoke-AI
-     toolkit supports carry licensing agreements which impose restrictions
-     on how the model is used. We ask that our users read and agree to
-     these terms if they wish to make use of these models. These agreements
-     are distinct from the MIT license which applies to the InvokeAI
-     software and source code.
-
-6. That mutual respect is key to a healthy software development
-community. Members of the InvokeAI community are expected to treat
-each other with respect, beneficence, and empathy. Each of us has a
-different background and a unique set of skills. We strive to help
-each other grow and gain new skills, and we apportion expectations in
-a way that balances the members' time, skillset, and interest
-area. Disputes are resolved by open and honest communication.
-
-## Signature
-
-This document has been collectively crafted and approved by the current InvokeAI team members, as of 28 Nov 2022: **lstein** (Lincoln Stein), **blessedcoolant**, **hipsterusername** (Kent Keirsey), **Kyle0654** (Kyle Schouviller), **damian0815**, **mauwii** (Matthias Wild), **Netsvetaev** (Artur Netsvetaev), **psychedelicious**, **tildebyte**, and **keturn**. Although individuals within the group may hold differing views on particular details and/or their implications, we are all in agreement about its fundamental statements, as well as their significance and importance to this project moving forward.  
-

README.md

@@ -1,9 +1,11 @@
 <div align="center">
 
-![project logo](docs/assets/invoke_ai_banner.png)
-
 # InvokeAI: A Stable Diffusion Toolkit
 
+_Formerly known as lstein/stable-diffusion_
+
+![project logo](docs/assets/logo.png)
+
 [![discord badge]][discord link]
 
 [![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link]
@@ -36,33 +38,18 @@ 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, macOS and Linux machines, with
+generation process. It runs on Windows, Mac 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**: [[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._
-
-# Getting Started with InvokeAI
-
-For full installation and upgrade instructions, please see:
-[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
-
-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`:
+**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>]
 
 <div align="center"><img src="docs/assets/invoke-web-server-1.png" width=640></div>
 
 
+_Note: This fork 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 aid diagnose issues faster._
 
 ## Table of Contents
 
@@ -78,17 +65,17 @@ For full installation and upgrade instructions, please see:
 
 ### Installation
 
-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/INSTALL_SOURCE/)
+This fork is supported across multiple platforms. You can find individual installation instructions
+below.
+
+- #### [Linux](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_LINUX/)
+
+- #### [Windows](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_WINDOWS/)
+
+- #### [Macintosh](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_MAC/)
 
 ### 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:
@@ -96,10 +83,6 @@ 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.
@@ -117,12 +100,11 @@ Similarly, specify full-precision mode on Apple M1 hardware.
 
 Precision is auto configured based on the device. If however you encounter
 errors like 'expected type Float but found Half' or 'not implemented for Half'
-you can try starting `invoke.py` with the `--precision=float32` flag to your initialization command
+you can try starting `invoke.py` with the `--precision=float32` flag:
 
 ```bash
 (invokeai) ~/InvokeAI$ python scripts/invoke.py --precision=float32
 ```
-Or by updating your InvokeAI configuration file with this argument.
 
 ### Features
 
@@ -151,7 +133,39 @@ Or by updating your InvokeAI configuration file with this argument.
 
 ### Latest Changes
 
-For our latest changes, view our [Release Notes](https://github.com/invoke-ai/InvokeAI/releases)
+- v2.0.1 (13 October 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)
+
+  - `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
+    for backward compatibility.
+  - Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
+  - Support for <a href="https://invoke-ai.github.io/InvokeAI/features/INPAINTING/">inpainting</a> and <a href="https://invoke-ai.github.io/InvokeAI/features/OUTPAINTING/">outpainting</a>
+  - 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 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.
+  - New `--hires` option on `invoke>` line allows <a href="https://invoke-ai.github.io/InvokeAI/features/CLI/#txt2img">larger images to be created without duplicating elements</a>, at the cost of some performance.
+  - New `--perlin` and `--threshold` options allow you to add and control variation
+    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.
+  - 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`
+    - Search command-line history with `!search`
+    - Clear history with `!clear`
+  - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
+    configure. To switch away from auto use the new flag like `--precision=float32`.
+
+For older changelogs, please visit the **[CHANGELOG](https://invoke-ai.github.io/InvokeAI/CHANGELOG#v114-11-september-2022)**.
 
 ### Troubleshooting
 
@@ -161,23 +175,15 @@ 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 are unfamiliar with how
+cleanup, testing, or code reviews, is very much encouraged to do so. If you are unfamiliar with how
 to contribute to GitHub projects, here is a
-[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). A full set of contribution guidelines, along with templates, are in progress, but for now the most
+[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github).
+
+A full set of contribution guidelines, along with templates, are in progress, but for now the most
 important thing is to **make your pull request against the "development" branch**, and not against
 "main". This will help keep public breakage to a minimum and will allow you to propose more radical
 changes.
 
-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.

backend/modules/get_canvas_generation_mode.py

@@ -1,117 +0,0 @@
-from PIL import Image, ImageChops
-from PIL.Image import Image as ImageType
-from typing import Union, Literal
-
-# https://stackoverflow.com/questions/43864101/python-pil-check-if-image-is-transparent
-def check_for_any_transparency(img: Union[ImageType, str]) -> bool:
-    if type(img) is str:
-        img = Image.open(str)
-
-    if img.info.get("transparency", None) is not None:
-        return True
-    if img.mode == "P":
-        transparent = img.info.get("transparency", -1)
-        for _, index in img.getcolors():
-            if index == transparent:
-                return True
-    elif img.mode == "RGBA":
-        extrema = img.getextrema()
-        if extrema[3][0] < 255:
-            return True
-    return False
-
-
-def get_canvas_generation_mode(
-    init_img: Union[ImageType, str], init_mask: Union[ImageType, str]
-) -> Literal["txt2img", "outpainting", "inpainting", "img2img",]:
-    if type(init_img) is str:
-        init_img = Image.open(init_img)
-
-    if type(init_mask) is str:
-        init_mask = Image.open(init_mask)
-
-    init_img = init_img.convert("RGBA")
-
-    # Get alpha from init_img
-    init_img_alpha = init_img.split()[-1]
-    init_img_alpha_mask = init_img_alpha.convert("L")
-    init_img_has_transparency = check_for_any_transparency(init_img)
-
-    if init_img_has_transparency:
-        init_img_is_fully_transparent = (
-            True if init_img_alpha_mask.getbbox() is None else False
-        )
-
-    """
-    Mask images are white in areas where no change should be made, black where changes 
-    should be made.
-    """
-
-    # Fit the mask to init_img's size and convert it to greyscale
-    init_mask = init_mask.resize(init_img.size).convert("L")
-
-    """
-    PIL.Image.getbbox() returns the bounding box of non-zero areas of the image, so we first
-    invert the mask image so that masked areas are white and other areas black == zero.
-    getbbox() now tells us if the are any masked areas.
-    """
-    init_mask_bbox = ImageChops.invert(init_mask).getbbox()
-    init_mask_exists = False if init_mask_bbox is None else True
-
-    if init_img_has_transparency:
-        if init_img_is_fully_transparent:
-            return "txt2img"
-        else:
-            return "outpainting"
-    else:
-        if init_mask_exists:
-            return "inpainting"
-        else:
-            return "img2img"
-
-
-def main():
-    # Testing
-    init_img_opaque = "test_images/init-img_opaque.png"
-    init_img_partial_transparency = "test_images/init-img_partial_transparency.png"
-    init_img_full_transparency = "test_images/init-img_full_transparency.png"
-    init_mask_no_mask = "test_images/init-mask_no_mask.png"
-    init_mask_has_mask = "test_images/init-mask_has_mask.png"
-
-    print(
-        "OPAQUE IMAGE, NO MASK, expect img2img, got ",
-        get_canvas_generation_mode(init_img_opaque, init_mask_no_mask),
-    )
-
-    print(
-        "IMAGE WITH TRANSPARENCY, NO MASK, expect outpainting, got ",
-        get_canvas_generation_mode(
-            init_img_partial_transparency, init_mask_no_mask
-        ),
-    )
-
-    print(
-        "FULLY TRANSPARENT IMAGE NO MASK, expect txt2img, got ",
-        get_canvas_generation_mode(init_img_full_transparency, init_mask_no_mask),
-    )
-
-    print(
-        "OPAQUE IMAGE, WITH MASK, expect inpainting, got ",
-        get_canvas_generation_mode(init_img_opaque, init_mask_has_mask),
-    )
-
-    print(
-        "IMAGE WITH TRANSPARENCY, WITH MASK, expect outpainting, got ",
-        get_canvas_generation_mode(
-            init_img_partial_transparency, init_mask_has_mask
-        ),
-    )
-
-    print(
-        "FULLY TRANSPARENT IMAGE WITH MASK, expect txt2img, got ",
-        get_canvas_generation_mode(init_img_full_transparency, init_mask_has_mask),
-    )
-
-
-if __name__ == "__main__":
-    main()

backend/modules/parameters.py

@@ -5,8 +5,6 @@ SAMPLER_CHOICES = [
     "ddim",
     "k_dpm_2_a",
     "k_dpm_2",
-    "k_dpmpp_2_a",
-    "k_dpmpp_2",
     "k_euler_a",
     "k_euler",
     "k_heun",

binary_installer/install.bat.in

@@ -1,164 +0,0 @@
-@echo off
-
-@rem This script will install git (if not found on the PATH variable)
-@rem  using micromamba (an 8mb static-linked single-file binary, conda replacement).
-@rem For users who already have git, this step will be skipped.
-
-@rem Next, it'll download the project's source code.
-@rem Then it will download a self-contained, standalone Python and unpack it.
-@rem Finally, it'll create the Python virtual environment and preload the models.
-
-@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.. *****
-@rem Config
-set INSTALL_ENV_DIR=%cd%\installer_files\env
-@rem https://mamba.readthedocs.io/en/latest/installation.html
-set MICROMAMBA_DOWNLOAD_URL=https://github.com/cmdr2/stable-diffusion-ui/releases/download/v1.1/micromamba.exe
-set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
-set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
-set PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
-set PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-x86_64-pc-windows-msvc-shared-install_only.tar.gz
-
-set PACKAGES_TO_INSTALL=
-
-call git --version >.tmp1 2>.tmp2
-if "%ERRORLEVEL%" NEQ "0" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% git
-
-@rem Cleanup
-del /q .tmp1 .tmp2
-
-@rem (if necessary) install git into a contained environment
-if "%PACKAGES_TO_INSTALL%" NEQ "" (
-    @rem download micromamba
-    echo ***** Downloading micromamba from %MICROMAMBA_DOWNLOAD_URL% to micromamba.exe *****
-
-    call curl -L "%MICROMAMBA_DOWNLOAD_URL%" > micromamba.exe
-
-    @rem test the mamba binary
-    echo ***** Micromamba version:  *****
-    call micromamba.exe --version
-
-    @rem create the installer env
-    if not exist "%INSTALL_ENV_DIR%" (
-        call micromamba.exe create -y --prefix "%INSTALL_ENV_DIR%"
-    )
-
-    echo ***** Packages to install:%PACKAGES_TO_INSTALL% *****
-
-    call micromamba.exe install -y --prefix "%INSTALL_ENV_DIR%" -c conda-forge %PACKAGES_TO_INSTALL%
-
-    if not exist "%INSTALL_ENV_DIR%" (
-        echo ----- There was a problem while installing "%PACKAGES_TO_INSTALL%" using micromamba. Cannot continue. -----
-        pause
-        exit /b
-    )
-)
-
-del /q micromamba.exe
-
-@rem For 'git' only
-set PATH=%INSTALL_ENV_DIR%\Library\bin;%PATH%
-
-@rem Download/unpack/clean up InvokeAI release sourceball
-set err_msg=----- InvokeAI source download failed -----
-echo Trying to download "%RELEASE_URL%%RELEASE_SOURCEBALL%"
-curl -L %RELEASE_URL%%RELEASE_SOURCEBALL% --output InvokeAI.tgz
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- InvokeAI source unpack failed -----
-tar -zxf InvokeAI.tgz
-if %errorlevel% neq 0 goto err_exit
-
-del /q InvokeAI.tgz
-
-set err_msg=----- InvokeAI source copy failed -----
-cd InvokeAI-*
-xcopy . .. /e /h
-if %errorlevel% neq 0 goto err_exit
-cd ..
-
-@rem cleanup
-for /f %%i in ('dir /b InvokeAI-*') do rd /s /q %%i
-rd /s /q .dev_scripts .github docker-build tests
-del /q requirements.in requirements-mkdocs.txt shell.nix
-
-echo ***** Unpacked InvokeAI source *****
-
-@rem Download/unpack/clean up python-build-standalone
-set err_msg=----- Python download failed -----
-curl -L %PYTHON_BUILD_STANDALONE_URL%/%PYTHON_BUILD_STANDALONE% --output python.tgz
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- Python unpack failed -----
-tar -zxf python.tgz
-if %errorlevel% neq 0 goto err_exit
-
-del /q python.tgz
-
-echo ***** Unpacked python-build-standalone *****
-
-@rem create venv
-set err_msg=----- problem creating venv -----
-.\python\python -E -s -m venv .venv
-if %errorlevel% neq 0 goto err_exit
-call .venv\Scripts\activate.bat
-
-echo ***** Created Python virtual environment *****
-
-@rem Print venv's Python version
-set err_msg=----- problem calling venv's python -----
-echo We're running under
-.venv\Scripts\python --version
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- pip update failed -----
-.venv\Scripts\python -m pip install %no_cache_dir% --no-warn-script-location --upgrade pip wheel
-if %errorlevel% neq 0 goto err_exit
-
-echo ***** Updated pip and wheel *****
-
-set err_msg=----- requirements file copy failed -----
-copy binary_installer\py3.10-windows-x86_64-cuda-reqs.txt requirements.txt
-if %errorlevel% neq 0 goto err_exit
-
-set err_msg=----- main pip install failed -----
-.venv\Scripts\python -m pip install %no_cache_dir% --no-warn-script-location -r requirements.txt
-if %errorlevel% neq 0 goto err_exit
-
-echo ***** Installed Python dependencies *****
-
-set err_msg=----- InvokeAI setup failed -----
-.venv\Scripts\python -m pip install %no_cache_dir% --no-warn-script-location -e .
-if %errorlevel% neq 0 goto err_exit
-
-copy binary_installer\invoke.bat.in .\invoke.bat
-echo ***** Installed invoke launcher script ******
-
-@rem more cleanup
-rd /s /q binary_installer installer_files
-
-@rem preload the models
-call .venv\Scripts\python scripts\configure_invokeai.py
-set err_msg=----- model download clone failed -----
-if %errorlevel% neq 0 goto err_exit
-deactivate
-
-echo ***** Finished downloading models *****
-
-echo All done! Execute the file invoke.bat in this directory to start InvokeAI
-pause
-exit
-
-:err_exit
-    echo %err_msg%
-    pause
-    exit

binary_installer/install.sh.in

@@ -1,235 +0,0 @@
-#!/usr/bin/env bash
-
-# ensure we're in the correct folder in case user's CWD is somewhere else
-scriptdir=$(dirname "$0")
-cd "$scriptdir"
-
-set -euo pipefail
-IFS=$'\n\t'
-
-function _err_exit {
-    if test "$1" -ne 0
-    then
-        echo -e "Error code $1; Error caught was '$2'"
-        read -p "Press any key to exit..."
-        exit
-    fi
-}
-
-# This script will install git (if not found on the PATH variable)
-#  using micromamba (an 8mb static-linked single-file binary, conda replacement).
-# For users who already have git, this step will be skipped.
-
-# Next, it'll download the project's source code.
-# Then it will download a self-contained, standalone Python and unpack it.
-# Finally, it'll create the Python virtual environment and preload the models.
-
-# This enables a user to install this project without manually installing git or Python
-
-echo -e "\n***** Installing InvokeAI into $(pwd)... *****\n"
-
-export no_cache_dir="--no-cache-dir"
-if [ $# -ge 1 ]; then
-    if [ "$1" = "use-cache" ]; then
-        export no_cache_dir=""
-    fi
-fi
-
-
-OS_NAME=$(uname -s)
-case "${OS_NAME}" in
-    Linux*)     OS_NAME="linux";;
-    Darwin*)    OS_NAME="darwin";;
-    *)          echo -e "\n----- Unknown OS: $OS_NAME! This script runs only on Linux or macOS -----\n" && exit
-esac
-
-OS_ARCH=$(uname -m)
-case "${OS_ARCH}" in
-    x86_64*)    ;;
-    arm64*)     ;;
-    *)          echo -e "\n----- Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64 -----\n" && exit
-esac
-
-# https://mamba.readthedocs.io/en/latest/installation.html
-MAMBA_OS_NAME=$OS_NAME
-MAMBA_ARCH=$OS_ARCH
-if [ "$OS_NAME" == "darwin" ]; then
-    MAMBA_OS_NAME="osx"
-fi
-
-if [ "$OS_ARCH" == "linux" ]; then
-    MAMBA_ARCH="aarch64"
-fi
-
-if [ "$OS_ARCH" == "x86_64" ]; then
-    MAMBA_ARCH="64"
-fi
-
-PY_ARCH=$OS_ARCH
-if [ "$OS_ARCH" == "arm64" ]; then
-    PY_ARCH="aarch64"
-fi
-
-# Compute device ('cd' segment of reqs files) detect goes here
-# This needs a ton of work
-# Suggestions:
-#   - lspci
-#   - check $PATH for nvidia-smi, gtt CUDA/GPU version from output
-#   - Surely there's a similar utility for AMD?
-CD="cuda"
-if [ "$OS_NAME" == "darwin" ] && [ "$OS_ARCH" == "arm64" ]; then
-    CD="mps"
-fi
-
-# config
-INSTALL_ENV_DIR="$(pwd)/installer_files/env"
-MICROMAMBA_DOWNLOAD_URL="https://micro.mamba.pm/api/micromamba/${MAMBA_OS_NAME}-${MAMBA_ARCH}/latest"
-RELEASE_URL=https://github.com/invoke-ai/InvokeAI
-RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
-PYTHON_BUILD_STANDALONE_URL=https://github.com/indygreg/python-build-standalone/releases/download
-if [ "$OS_NAME" == "darwin" ]; then
-    PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-${PY_ARCH}-apple-darwin-install_only.tar.gz
-elif [ "$OS_NAME" == "linux" ]; then
-    PYTHON_BUILD_STANDALONE=20221002/cpython-3.10.7+20221002-${PY_ARCH}-unknown-linux-gnu-install_only.tar.gz
-fi
-echo "INSTALLING $RELEASE_SOURCEBALL FROM $RELEASE_URL"
-
-PACKAGES_TO_INSTALL=""
-
-if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
-
-# (if necessary) install git and conda into a contained environment
-if [ "$PACKAGES_TO_INSTALL" != "" ]; then
-    # download micromamba
-    echo -e "\n***** Downloading micromamba from $MICROMAMBA_DOWNLOAD_URL to micromamba *****\n"
-
-    curl -L "$MICROMAMBA_DOWNLOAD_URL" | tar -xvjO bin/micromamba > micromamba
-
-    chmod u+x ./micromamba
-
-    # test the mamba binary
-    echo -e "\n***** Micromamba version: *****\n"
-    ./micromamba --version
-
-    # create the installer env
-    if [ ! -e "$INSTALL_ENV_DIR" ]; then
-        ./micromamba create -y --prefix "$INSTALL_ENV_DIR"
-    fi
-
-    echo -e "\n***** Packages to install:$PACKAGES_TO_INSTALL *****\n"
-
-    ./micromamba install -y --prefix "$INSTALL_ENV_DIR" -c conda-forge "$PACKAGES_TO_INSTALL"
-
-    if [ ! -e "$INSTALL_ENV_DIR" ]; then
-        echo -e "\n----- There was a problem while initializing micromamba. Cannot continue. -----\n"
-        exit
-    fi
-fi
-
-rm -f micromamba.exe
-
-export PATH="$INSTALL_ENV_DIR/bin:$PATH"
-
-# Download/unpack/clean up InvokeAI release sourceball
-_err_msg="\n----- InvokeAI source download failed -----\n"
-curl -L $RELEASE_URL/$RELEASE_SOURCEBALL --output InvokeAI.tgz
-_err_exit $? _err_msg
-_err_msg="\n----- InvokeAI source unpack failed -----\n"
-tar -zxf InvokeAI.tgz
-_err_exit $? _err_msg
-
-rm -f InvokeAI.tgz
-
-_err_msg="\n----- InvokeAI source copy failed -----\n"
-cd InvokeAI-*
-cp -r . ..
-_err_exit $? _err_msg
-cd ..
-
-# cleanup
-rm -rf InvokeAI-*/
-rm -rf .dev_scripts/ .github/ docker-build/ tests/ requirements.in requirements-mkdocs.txt shell.nix
-
-echo -e "\n***** Unpacked InvokeAI source *****\n"
-
-# Download/unpack/clean up python-build-standalone
-_err_msg="\n----- Python download failed -----\n"
-curl -L $PYTHON_BUILD_STANDALONE_URL/$PYTHON_BUILD_STANDALONE --output python.tgz
-_err_exit $? _err_msg
-_err_msg="\n----- Python unpack failed -----\n"
-tar -zxf python.tgz
-_err_exit $? _err_msg
-
-rm -f python.tgz
-
-echo -e "\n***** Unpacked python-build-standalone *****\n"
-
-# create venv
-_err_msg="\n----- problem creating venv -----\n"
-
-if [ "$OS_NAME" == "darwin" ]; then
-    # patch sysconfig so that extensions can build properly
-    # adapted from https://github.com/cashapp/hermit-packages/commit/fcba384663892f4d9cfb35e8639ff7a28166ee43
-    PYTHON_INSTALL_DIR="$(pwd)/python"
-    SYSCONFIG="$(echo python/lib/python*/_sysconfigdata_*.py)"
-    TMPFILE="$(mktemp)"
-    chmod +w "${SYSCONFIG}"
-    cp "${SYSCONFIG}" "${TMPFILE}"
-    sed "s,'/install,'${PYTHON_INSTALL_DIR},g" "${TMPFILE}" > "${SYSCONFIG}"
-    rm -f "${TMPFILE}"
-fi
-
-./python/bin/python3 -E -s -m venv .venv
-_err_exit $? _err_msg
-source .venv/bin/activate
-
-echo -e "\n***** Created Python virtual environment *****\n"
-
-# Print venv's Python version
-_err_msg="\n----- problem calling venv's python -----\n"
-echo -e "We're running under"
-.venv/bin/python3 --version
-_err_exit $? _err_msg
-
-_err_msg="\n----- pip update failed -----\n"
-.venv/bin/python3 -m pip install $no_cache_dir --no-warn-script-location --upgrade pip
-_err_exit $? _err_msg
-
-echo -e "\n***** Updated pip *****\n"
-
-_err_msg="\n----- requirements file copy failed -----\n"
-cp binary_installer/py3.10-${OS_NAME}-"${OS_ARCH}"-${CD}-reqs.txt requirements.txt
-_err_exit $? _err_msg
-
-_err_msg="\n----- main pip install failed -----\n"
-.venv/bin/python3 -m pip install $no_cache_dir --no-warn-script-location -r requirements.txt
-_err_exit $? _err_msg
-
-echo -e "\n***** Installed Python dependencies *****\n"
-
-_err_msg="\n----- InvokeAI setup failed -----\n"
-.venv/bin/python3 -m pip install $no_cache_dir --no-warn-script-location -e .
-_err_exit $? _err_msg
-
-echo -e "\n***** Installed InvokeAI *****\n"
-
-cp binary_installer/invoke.sh.in ./invoke.sh
-chmod a+rx ./invoke.sh
-echo -e "\n***** Installed invoke launcher script ******\n"
-
-# more cleanup
-rm -rf binary_installer/ installer_files/
-
-# preload the models
-.venv/bin/python3 scripts/configure_invokeai.py
-_err_msg="\n----- model download clone failed -----\n"
-_err_exit $? _err_msg
-deactivate
-
-echo -e "\n***** Finished downloading models *****\n"
-
-echo "All done! Run the command"
-echo "  $scriptdir/invoke.sh"
-echo "to start InvokeAI."
-read -p "Press any key to exit..."
-exit

binary_installer/invoke.bat.in

@@ -1,36 +0,0 @@
-@echo off
-
-PUSHD "%~dp0"
-call .venv\Scripts\activate.bat
-
-echo Do you want to generate images using the
-echo 1. command-line
-echo 2. browser-based UI
-echo OR
-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 %*
-) else if /i "%choice%" == "2" (
-    echo Starting the InvokeAI browser-based UI.
-    .venv\Scripts\python scripts\invoke.py --web %*
-) else if /i "%choice%" == "3" (
-    echo Developer Console
-    echo Python command is:
-    where python
-    echo Python version is:
-    python --version
-    echo *************************
-    echo You are now in the system shell, with the local InvokeAI Python virtual environment activated,
-    echo so that you can troubleshoot this InvokeAI installation as necessary.
-    echo *************************
-    echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
-    call cmd /k
-) else (
-    echo Invalid selection
-    pause
-    exit /b
-)
-
-deactivate

binary_installer/invoke.sh.in

@@ -1,46 +0,0 @@
-#!/usr/bin/env sh
-
-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"
-echo "OR"
-echo "3. open the developer console"
-echo "Please enter 1, 2, or 3:"
-read choice
-
-case $choice in
-    1)
-        printf "\nStarting the InvokeAI command-line..\n";
-        .venv/bin/python scripts/invoke.py $*;
-    ;;
-    2)
-        printf "\nStarting the InvokeAI browser-based UI..\n";
-        .venv/bin/python scripts/invoke.py --web $*;
-    ;;
-    3)
-        printf "\nDeveloper Console:\n";
-        printf "Python command is:\n\t";
-        which python;
-        printf "Python version is:\n\t";
-        python --version;
-        echo "*************************"
-        echo "You are now in your user shell ($SHELL) with the local InvokeAI Python virtual environment activated,";
-        echo "so that you can troubleshoot this InvokeAI installation as necessary.";
-        printf "*************************\n"
-        echo "*** Type \`exit\` to quit this shell and deactivate the Python virtual environment *** ";
-        /usr/bin/env "$SHELL";
-    ;;
-    *)
-        echo "Invalid selection";
-        exit
-    ;;
-esac

binary_installer/readme.txt

@@ -1,17 +0,0 @@
-InvokeAI
-
-Project homepage: https://github.com/invoke-ai/InvokeAI
-
-Installation on Windows:
-    NOTE: You might need to enable Windows Long Paths. If you're not sure,
-    then you almost certainly need to. Simply double-click the 'WinLongPathsEnabled.reg'
-    file. Note that you will need to have admin privileges in order to
-    do this.
-
-    Please double-click the 'install.bat' file (while keeping it inside the invokeAI folder).
-
-Installation on Linux and Mac:
-    Please open the terminal, and run './install.sh' (while keeping it inside the invokeAI folder).
-
-After installation, please run the 'invoke.bat' file (on Windows) or 'invoke.sh'
-file (on Linux/Mac) to start InvokeAI.

binary_installer/requirements.in

@@ -1,32 +0,0 @@
---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
-diffusers
-eventlet
-flask_cors
-flask_socketio
-flaskwebgui==1.0.3
-getpass_asterisk
-imageio-ffmpeg
-pyreadline3
-realesrgan
-send2trash
-streamlit
-taming-transformers-rom1504
-test-tube
-torch-fidelity
-torch==1.12.1 ; platform_system == 'Darwin'
-torch==1.12.0+cu116 ; platform_system == 'Linux' or platform_system == 'Windows'
-torchvision==0.13.1 ; platform_system == 'Darwin'
-torchvision==0.13.0+cu116 ; platform_system == 'Linux' or platform_system == 'Windows'
-transformers
-picklescan
-https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
-https://github.com/invoke-ai/clipseg/archive/1f754751c85d7d4255fa681f4491ff5711c1c288.zip
-https://github.com/invoke-ai/GFPGAN/archive/3f5d2397361199bc4a91c08bb7d80f04d7805615.zip ; platform_system=='Windows'
-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

configs/INITIAL_MODELS.yaml

@@ -1,80 +0,0 @@
-stable-diffusion-1.5:
-   description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
-   repo_id: runwayml/stable-diffusion-v1-5
-   config: v1-inference.yaml
-   file: v1-5-pruned-emaonly.ckpt
-   recommended: true
-   width: 512
-   height: 512
-inpainting-1.5:
-   description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
-   repo_id: runwayml/stable-diffusion-inpainting
-   config: v1-inpainting-inference.yaml
-   file: sd-v1-5-inpainting.ckpt
-   recommended: True
-   width: 512
-   height: 512
-ft-mse-improved-autoencoder-840000:
-   description: StabilityAI improved autoencoder fine-tuned for human faces (recommended; 335 MB)
-   repo_id: stabilityai/sd-vae-ft-mse-original
-   config: VAE/default
-   file: vae-ft-mse-840000-ema-pruned.ckpt
-   recommended: True
-   width: 512
-   height: 512
-stable-diffusion-1.4:
-   description: The original Stable Diffusion version 1.4 weight file (4.27 GB)
-   repo_id: CompVis/stable-diffusion-v-1-4-original
-   config: v1-inference.yaml
-   file: sd-v1-4.ckpt
-   recommended: False
-   width: 512
-   height: 512
-waifu-diffusion-1.3:
-   description: Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
-   repo_id: hakurei/waifu-diffusion-v1-3
-   config: v1-inference.yaml
-   file: model-epoch09-float32.ckpt
-   recommended: False
-   width: 512
-   height: 512
-trinart-2.0:
-   description: An SD model finetuned with ~40,000 assorted high resolution manga/anime-style pictures (2.13 GB)
-   repo_id: naclbit/trinart_stable_diffusion_v2
-   config: v1-inference.yaml
-   file: trinart2_step95000.ckpt
-   recommended: False
-   width: 512
-   height: 512
-trinart_characters-1.0:
-   description: An SD model finetuned with 19.2M anime/manga style images (2.13 GB)
-   repo_id: naclbit/trinart_characters_19.2m_stable_diffusion_v1
-   config: v1-inference.yaml
-   file: trinart_characters_it4_v1.ckpt
-   recommended: False
-   width: 512
-   height: 512
-trinart_vae:
-   description: Custom autoencoder for trinart_characters
-   repo_id: naclbit/trinart_characters_19.2m_stable_diffusion_v1
-   config: VAE/trinart
-   file: autoencoder_fix_kl-f8-trinart_characters.ckpt
-   recommended: False
-   width: 512
-   height: 512
-papercut-1.0:
-   description: SD 1.5 fine-tuned for papercut art (use "PaperCut" in your prompts) (2.13 GB)
-   repo_id: Fictiverse/Stable_Diffusion_PaperCut_Model
-   config: v1-inference.yaml
-   file: PaperCut_v1.ckpt
-   recommended: False
-   width: 512
-   height: 512
-voxel_art-1.0:
-   description: Stable Diffusion trained on voxel art (use "VoxelArt" in your prompts) (4.27 GB)
-   repo_id: Fictiverse/Stable_Diffusion_VoxelArt_Model
-   config: v1-inference.yaml
-   file: VoxelArt_v1.ckpt
-   recommended: False
-   width: 512
-   height: 512

configs/models.yaml.example

@@ -7,8 +7,8 @@
 # was trained on.
 stable-diffusion-1.5:
   description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
-  weights: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
-  config: configs/stable-diffusion/v1-inference.yaml
+  weights: ./models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
+  config: ./configs/stable-diffusion/v1-inference.yaml
   width: 512
   height: 512
   vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
@@ -25,5 +25,3 @@ inpainting-1.5:
   config: configs/stable-diffusion/v1-inpainting-inference.yaml
   vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
   description: RunwayML SD 1.5 model optimized for inpainting
-  width: 512
-  height: 512

configs/sd-concepts.txt

@@ -1,803 +0,0 @@
-sd-concepts-library/001glitch-core
-sd-concepts-library/2814-roth
-sd-concepts-library/3d-female-cyborgs
-sd-concepts-library/4tnght
-sd-concepts-library/80s-anime-ai
-sd-concepts-library/80s-anime-ai-being
-sd-concepts-library/852style-girl
-sd-concepts-library/8bit
-sd-concepts-library/8sconception
-sd-concepts-library/Aflac-duck
-sd-concepts-library/Akitsuki
-sd-concepts-library/Atako
-sd-concepts-library/Exodus-Styling
-sd-concepts-library/RINGAO
-sd-concepts-library/a-female-hero-from-the-legend-of-mir
-sd-concepts-library/a-hat-kid
-sd-concepts-library/a-tale-of-two-empires
-sd-concepts-library/aadhav-face
-sd-concepts-library/aavegotchi
-sd-concepts-library/abby-face
-sd-concepts-library/abstract-concepts
-sd-concepts-library/accurate-angel
-sd-concepts-library/agm-style-nao
-sd-concepts-library/aj-fosik
-sd-concepts-library/alberto-mielgo
-sd-concepts-library/alex-portugal
-sd-concepts-library/alex-thumbnail-object-2000-steps
-sd-concepts-library/aleyna-tilki
-sd-concepts-library/alf
-sd-concepts-library/alicebeta
-sd-concepts-library/alien-avatar
-sd-concepts-library/alisa
-sd-concepts-library/all-rings-albuns
-sd-concepts-library/altvent
-sd-concepts-library/altyn-helmet
-sd-concepts-library/amine
-sd-concepts-library/amogus
-sd-concepts-library/anders-zorn
-sd-concepts-library/angus-mcbride-style
-sd-concepts-library/animalve3-1500seq
-sd-concepts-library/anime-background-style
-sd-concepts-library/anime-background-style-v2
-sd-concepts-library/anime-boy
-sd-concepts-library/anime-girl
-sd-concepts-library/anyXtronXredshift
-sd-concepts-library/anya-forger
-sd-concepts-library/apex-wingman
-sd-concepts-library/apulian-rooster-v0-1
-sd-concepts-library/arcane-face
-sd-concepts-library/arcane-style-jv
-sd-concepts-library/arcimboldo-style
-sd-concepts-library/armando-reveron-style
-sd-concepts-library/armor-concept
-sd-concepts-library/arq-render
-sd-concepts-library/art-brut
-sd-concepts-library/arthur1
-sd-concepts-library/artist-yukiko-kanagai
-sd-concepts-library/arwijn
-sd-concepts-library/ashiok
-sd-concepts-library/at-wolf-boy-object
-sd-concepts-library/atm-ant
-sd-concepts-library/atm-ant-2
-sd-concepts-library/axe-tattoo
-sd-concepts-library/ayush-spider-spr
-sd-concepts-library/azura-from-vibrant-venture
-sd-concepts-library/ba-shiroko
-sd-concepts-library/babau
-sd-concepts-library/babs-bunny
-sd-concepts-library/babushork
-sd-concepts-library/backrooms
-sd-concepts-library/bad_Hub_Hugh
-sd-concepts-library/bada-club
-sd-concepts-library/baldi
-sd-concepts-library/baluchitherian
-sd-concepts-library/bamse
-sd-concepts-library/bamse-og-kylling
-sd-concepts-library/bee
-sd-concepts-library/beholder
-sd-concepts-library/beldam
-sd-concepts-library/belen
-sd-concepts-library/bella-goth
-sd-concepts-library/belle-delphine
-sd-concepts-library/bert-muppet
-sd-concepts-library/better-collage3
-sd-concepts-library/between2-mt-fade
-sd-concepts-library/birb-style
-sd-concepts-library/black-and-white-design
-sd-concepts-library/black-waifu
-sd-concepts-library/bloo
-sd-concepts-library/blue-haired-boy
-sd-concepts-library/blue-zombie
-sd-concepts-library/blue-zombiee
-sd-concepts-library/bluebey
-sd-concepts-library/bluebey-2
-sd-concepts-library/bobs-burgers
-sd-concepts-library/boissonnard
-sd-concepts-library/bonzi-monkey
-sd-concepts-library/borderlands
-sd-concepts-library/bored-ape-textual-inversion
-sd-concepts-library/boris-anderson
-sd-concepts-library/bozo-22
-sd-concepts-library/breakcore
-sd-concepts-library/brittney-williams-art
-sd-concepts-library/bruma
-sd-concepts-library/brunnya
-sd-concepts-library/buddha-statue
-sd-concepts-library/bullvbear
-sd-concepts-library/button-eyes
-sd-concepts-library/canadian-goose
-sd-concepts-library/canary-cap
-sd-concepts-library/cancer_style
-sd-concepts-library/captain-haddock
-sd-concepts-library/captainkirb
-sd-concepts-library/car-toy-rk
-sd-concepts-library/carasibana
-sd-concepts-library/carlitos-el-mago
-sd-concepts-library/carrascharacter
-sd-concepts-library/cartoona-animals
-sd-concepts-library/cat-toy
-sd-concepts-library/centaur
-sd-concepts-library/cgdonny1
-sd-concepts-library/cham
-sd-concepts-library/chandra-nalaar
-sd-concepts-library/char-con
-sd-concepts-library/character-pingu
-sd-concepts-library/cheburashka
-sd-concepts-library/chen-1
-sd-concepts-library/child-zombie
-sd-concepts-library/chillpill
-sd-concepts-library/chonkfrog
-sd-concepts-library/chop
-sd-concepts-library/christo-person
-sd-concepts-library/chuck-walton
-sd-concepts-library/chucky
-sd-concepts-library/chungus-poodl-pet
-sd-concepts-library/cindlop
-sd-concepts-library/collage-cutouts
-sd-concepts-library/collage14
-sd-concepts-library/collage3
-sd-concepts-library/collage3-hubcity
-sd-concepts-library/cologne
-sd-concepts-library/color-page
-sd-concepts-library/colossus
-sd-concepts-library/command-and-conquer-remastered-cameos
-sd-concepts-library/concept-art
-sd-concepts-library/conner-fawcett-style
-sd-concepts-library/conway-pirate
-sd-concepts-library/coop-himmelblau
-sd-concepts-library/coraline
-sd-concepts-library/cornell-box
-sd-concepts-library/cortana
-sd-concepts-library/covid-19-rapid-test
-sd-concepts-library/cow-uwu
-sd-concepts-library/cowboy
-sd-concepts-library/crazy-1
-sd-concepts-library/crazy-2
-sd-concepts-library/crb-portraits
-sd-concepts-library/crb-surrealz
-sd-concepts-library/crbart
-sd-concepts-library/crested-gecko
-sd-concepts-library/crinos-form-garou
-sd-concepts-library/cry-baby-style
-sd-concepts-library/crybaby-style-2-0
-sd-concepts-library/csgo-awp-object
-sd-concepts-library/csgo-awp-texture-map
-sd-concepts-library/cubex
-sd-concepts-library/cumbia-peruana
-sd-concepts-library/cute-bear
-sd-concepts-library/cute-cat
-sd-concepts-library/cute-game-style
-sd-concepts-library/cyberpunk-lucy
-sd-concepts-library/dabotap
-sd-concepts-library/dan-mumford
-sd-concepts-library/dan-seagrave-art-style
-sd-concepts-library/dark-penguin-pinguinanimations
-sd-concepts-library/darkpenguinanimatronic
-sd-concepts-library/darkplane
-sd-concepts-library/david-firth-artstyle
-sd-concepts-library/david-martinez-cyberpunk
-sd-concepts-library/david-martinez-edgerunners
-sd-concepts-library/david-moreno-architecture
-sd-concepts-library/daycare-attendant-sun-fnaf
-sd-concepts-library/ddattender
-sd-concepts-library/degods
-sd-concepts-library/degodsheavy
-sd-concepts-library/depthmap
-sd-concepts-library/depthmap-style
-sd-concepts-library/design
-sd-concepts-library/detectivedinosaur1
-sd-concepts-library/diaosu-toy
-sd-concepts-library/dicoo
-sd-concepts-library/dicoo2
-sd-concepts-library/dishonored-portrait-styles
-sd-concepts-library/disquieting-muses
-sd-concepts-library/ditko
-sd-concepts-library/dlooak
-sd-concepts-library/doc
-sd-concepts-library/doener-red-line-art
-sd-concepts-library/dog
-sd-concepts-library/dog-django
-sd-concepts-library/doge-pound
-sd-concepts-library/dong-ho
-sd-concepts-library/dong-ho2
-sd-concepts-library/doose-s-realistic-art-style
-sd-concepts-library/dq10-anrushia
-sd-concepts-library/dr-livesey
-sd-concepts-library/dr-strange
-sd-concepts-library/dragonborn
-sd-concepts-library/dreamcore
-sd-concepts-library/dreamy-painting
-sd-concepts-library/drive-scorpion-jacket
-sd-concepts-library/dsmuses
-sd-concepts-library/dtv-pkmn
-sd-concepts-library/dullboy-caricature
-sd-concepts-library/duranduran
-sd-concepts-library/durer-style
-sd-concepts-library/dyoudim-style
-sd-concepts-library/early-mishima-kurone
-sd-concepts-library/eastward
-sd-concepts-library/eddie
-sd-concepts-library/edgerunners-style
-sd-concepts-library/edgerunners-style-v2
-sd-concepts-library/el-salvador-style-style
-sd-concepts-library/elegant-flower
-sd-concepts-library/elspeth-tirel
-sd-concepts-library/eru-chitanda-casual
-sd-concepts-library/erwin-olaf-style
-sd-concepts-library/ettblackteapot
-sd-concepts-library/explosions-cat
-sd-concepts-library/eye-of-agamotto
-sd-concepts-library/f-22
-sd-concepts-library/facadeplace
-sd-concepts-library/fairy-tale-painting-style
-sd-concepts-library/fairytale
-sd-concepts-library/fang-yuan-001
-sd-concepts-library/faraon-love-shady
-sd-concepts-library/fasina
-sd-concepts-library/felps
-sd-concepts-library/female-kpop-singer
-sd-concepts-library/fergal-cat
-sd-concepts-library/filename-2
-sd-concepts-library/fileteado-porteno
-sd-concepts-library/final-fantasy-logo
-sd-concepts-library/fireworks-over-water
-sd-concepts-library/fish
-sd-concepts-library/flag-ussr
-sd-concepts-library/flatic
-sd-concepts-library/floral
-sd-concepts-library/fluid-acrylic-jellyfish-creatures-style-of-carl-ingram-art
-sd-concepts-library/fnf-boyfriend
-sd-concepts-library/fold-structure
-sd-concepts-library/fox-purple
-sd-concepts-library/fractal
-sd-concepts-library/fractal-flame
-sd-concepts-library/fractal-temple-style
-sd-concepts-library/frank-frazetta
-sd-concepts-library/franz-unterberger
-sd-concepts-library/freddy-fazbear
-sd-concepts-library/freefonix-style
-sd-concepts-library/furrpopasthetic
-sd-concepts-library/fursona
-sd-concepts-library/fzk
-sd-concepts-library/galaxy-explorer
-sd-concepts-library/ganyu-genshin-impact
-sd-concepts-library/garcon-the-cat
-sd-concepts-library/garfield-pizza-plush
-sd-concepts-library/garfield-pizza-plush-v2
-sd-concepts-library/gba-fe-class-cards
-sd-concepts-library/gba-pokemon-sprites
-sd-concepts-library/geggin
-sd-concepts-library/ggplot2
-sd-concepts-library/ghost-style
-sd-concepts-library/ghostproject-men
-sd-concepts-library/gibasachan-v0
-sd-concepts-library/gim
-sd-concepts-library/gio
-sd-concepts-library/giygas
-sd-concepts-library/glass-pipe
-sd-concepts-library/glass-prism-cube
-sd-concepts-library/glow-forest
-sd-concepts-library/goku
-sd-concepts-library/gram-tops
-sd-concepts-library/green-blue-shanshui
-sd-concepts-library/green-tent
-sd-concepts-library/grifter
-sd-concepts-library/grisstyle
-sd-concepts-library/grit-toy
-sd-concepts-library/gt-color-paint-2
-sd-concepts-library/gta5-artwork
-sd-concepts-library/guttestreker
-sd-concepts-library/gymnastics-leotard-v2
-sd-concepts-library/half-life-2-dog
-sd-concepts-library/handstand
-sd-concepts-library/hanfu-anime-style
-sd-concepts-library/happy-chaos
-sd-concepts-library/happy-person12345
-sd-concepts-library/happy-person12345-assets
-sd-concepts-library/harley-quinn
-sd-concepts-library/harmless-ai-1
-sd-concepts-library/harmless-ai-house-style-1
-sd-concepts-library/hd-emoji
-sd-concepts-library/heather
-sd-concepts-library/henjo-techno-show
-sd-concepts-library/herge-style
-sd-concepts-library/hiten-style-nao
-sd-concepts-library/hitokomoru-style-nao
-sd-concepts-library/hiyuki-chan
-sd-concepts-library/hk-bamboo
-sd-concepts-library/hk-betweenislands
-sd-concepts-library/hk-bicycle
-sd-concepts-library/hk-blackandwhite
-sd-concepts-library/hk-breakfast
-sd-concepts-library/hk-buses
-sd-concepts-library/hk-clouds
-sd-concepts-library/hk-goldbuddha
-sd-concepts-library/hk-goldenlantern
-sd-concepts-library/hk-hkisland
-sd-concepts-library/hk-leaves
-sd-concepts-library/hk-market
-sd-concepts-library/hk-oldcamera
-sd-concepts-library/hk-opencamera
-sd-concepts-library/hk-peach
-sd-concepts-library/hk-phonevax
-sd-concepts-library/hk-streetpeople
-sd-concepts-library/hk-vintage
-sd-concepts-library/hoi4
-sd-concepts-library/hoi4-leaders
-sd-concepts-library/homestuck-sprite
-sd-concepts-library/homestuck-troll
-sd-concepts-library/hours-sentry-fade
-sd-concepts-library/hours-style
-sd-concepts-library/hrgiger-drmacabre
-sd-concepts-library/huang-guang-jian
-sd-concepts-library/huatli
-sd-concepts-library/huayecai820-greyscale
-sd-concepts-library/hub-city
-sd-concepts-library/hubris-oshri
-sd-concepts-library/huckleberry
-sd-concepts-library/hydrasuit
-sd-concepts-library/i-love-chaos
-sd-concepts-library/ibere-thenorio
-sd-concepts-library/ic0n
-sd-concepts-library/ie-gravestone
-sd-concepts-library/ikea-fabler
-sd-concepts-library/illustration-style
-sd-concepts-library/ilo-kunst
-sd-concepts-library/ilya-shkipin
-sd-concepts-library/im-poppy
-sd-concepts-library/ina-art
-sd-concepts-library/indian-watercolor-portraits
-sd-concepts-library/indiana
-sd-concepts-library/ingmar-bergman
-sd-concepts-library/insidewhale
-sd-concepts-library/interchanges
-sd-concepts-library/inuyama-muneto-style-nao
-sd-concepts-library/irasutoya
-sd-concepts-library/iridescent-illustration-style
-sd-concepts-library/iridescent-photo-style
-sd-concepts-library/isabell-schulte-pv-pvii-3000steps
-sd-concepts-library/isabell-schulte-pviii-1-image-style
-sd-concepts-library/isabell-schulte-pviii-1024px-1500-steps-style
-sd-concepts-library/isabell-schulte-pviii-12tiles-3000steps-style
-sd-concepts-library/isabell-schulte-pviii-4-tiles-1-lr-3000-steps-style
-sd-concepts-library/isabell-schulte-pviii-4-tiles-3-lr-5000-steps-style
-sd-concepts-library/isabell-schulte-pviii-4tiles-500steps
-sd-concepts-library/isabell-schulte-pviii-4tiles-6000steps
-sd-concepts-library/isabell-schulte-pviii-style
-sd-concepts-library/isometric-tile-test
-sd-concepts-library/jacqueline-the-unicorn
-sd-concepts-library/james-web-space-telescope
-sd-concepts-library/jamie-hewlett-style
-sd-concepts-library/jamiels
-sd-concepts-library/jang-sung-rak-style
-sd-concepts-library/jetsetdreamcastcovers
-sd-concepts-library/jin-kisaragi
-sd-concepts-library/jinjoon-lee-they
-sd-concepts-library/jm-bergling-monogram
-sd-concepts-library/joe-mad
-sd-concepts-library/joe-whiteford-art-style
-sd-concepts-library/joemad
-sd-concepts-library/john-blanche
-sd-concepts-library/johnny-silverhand
-sd-concepts-library/jojo-bizzare-adventure-manga-lineart
-sd-concepts-library/jos-de-kat
-sd-concepts-library/junji-ito-artstyle
-sd-concepts-library/kaleido
-sd-concepts-library/kaneoya-sachiko
-sd-concepts-library/kanovt
-sd-concepts-library/kanv1
-sd-concepts-library/karan-gloomy
-sd-concepts-library/karl-s-lzx-1
-sd-concepts-library/kasumin
-sd-concepts-library/kawaii-colors
-sd-concepts-library/kawaii-girl-plus-object
-sd-concepts-library/kawaii-girl-plus-style
-sd-concepts-library/kawaii-girl-plus-style-v1-1
-sd-concepts-library/kay
-sd-concepts-library/kaya-ghost-assasin
-sd-concepts-library/ki
-sd-concepts-library/kinda-sus
-sd-concepts-library/kings-quest-agd
-sd-concepts-library/kiora
-sd-concepts-library/kira-sensei
-sd-concepts-library/kirby
-sd-concepts-library/klance
-sd-concepts-library/kodakvision500t
-sd-concepts-library/kogatan-shiny
-sd-concepts-library/kogecha
-sd-concepts-library/kojima-ayami
-sd-concepts-library/koko-dog
-sd-concepts-library/kuvshinov
-sd-concepts-library/kysa-v-style
-sd-concepts-library/laala-character
-sd-concepts-library/larrette
-sd-concepts-library/lavko
-sd-concepts-library/lazytown-stephanie
-sd-concepts-library/ldr
-sd-concepts-library/ldrs
-sd-concepts-library/led-toy
-sd-concepts-library/lego-astronaut
-sd-concepts-library/leica
-sd-concepts-library/leif-jones
-sd-concepts-library/lex
-sd-concepts-library/liliana
-sd-concepts-library/liliana-vess
-sd-concepts-library/liminal-spaces-2-0
-sd-concepts-library/liminalspaces
-sd-concepts-library/line-art
-sd-concepts-library/line-style
-sd-concepts-library/linnopoke
-sd-concepts-library/liquid-light
-sd-concepts-library/liqwid-aquafarmer
-sd-concepts-library/lizardman
-sd-concepts-library/loab-character
-sd-concepts-library/loab-style
-sd-concepts-library/lofa
-sd-concepts-library/logo-with-face-on-shield
-sd-concepts-library/lolo
-sd-concepts-library/looney-anime
-sd-concepts-library/lost-rapper
-sd-concepts-library/lphr-style
-sd-concepts-library/lucario
-sd-concepts-library/lucky-luke
-sd-concepts-library/lugal-ki-en
-sd-concepts-library/luinv2
-sd-concepts-library/lula-13
-sd-concepts-library/lumio
-sd-concepts-library/lxj-o4
-sd-concepts-library/m-geo
-sd-concepts-library/m-geoo
-sd-concepts-library/madhubani-art
-sd-concepts-library/mafalda-character
-sd-concepts-library/magic-pengel
-sd-concepts-library/malika-favre-art-style
-sd-concepts-library/manga-style
-sd-concepts-library/marbling-art
-sd-concepts-library/margo
-sd-concepts-library/marty
-sd-concepts-library/marty6
-sd-concepts-library/mass
-sd-concepts-library/masyanya
-sd-concepts-library/masyunya
-sd-concepts-library/mate
-sd-concepts-library/matthew-stone
-sd-concepts-library/mattvidpro
-sd-concepts-library/maurice-quentin-de-la-tour-style
-sd-concepts-library/maus
-sd-concepts-library/max-foley
-sd-concepts-library/mayor-richard-irvin
-sd-concepts-library/mechasoulall
-sd-concepts-library/medazzaland
-sd-concepts-library/memnarch-mtg
-sd-concepts-library/metagabe
-sd-concepts-library/meyoco
-sd-concepts-library/meze-audio-elite-headphones
-sd-concepts-library/midjourney-style
-sd-concepts-library/mikako-method
-sd-concepts-library/mikako-methodi2i
-sd-concepts-library/miko-3-robot
-sd-concepts-library/milady
-sd-concepts-library/mildemelwe-style
-sd-concepts-library/million-live-akane-15k
-sd-concepts-library/million-live-akane-3k
-sd-concepts-library/million-live-akane-shifuku-3k
-sd-concepts-library/million-live-spade-q-object-3k
-sd-concepts-library/million-live-spade-q-style-3k
-sd-concepts-library/minecraft-concept-art
-sd-concepts-library/mishima-kurone
-sd-concepts-library/mizkif
-sd-concepts-library/moeb-style
-sd-concepts-library/moebius
-sd-concepts-library/mokoko
-sd-concepts-library/mokoko-seed
-sd-concepts-library/monster-girl
-sd-concepts-library/monster-toy
-sd-concepts-library/monte-novo
-sd-concepts-library/moo-moo
-sd-concepts-library/morino-hon-style
-sd-concepts-library/moxxi
-sd-concepts-library/msg
-sd-concepts-library/mtg-card
-sd-concepts-library/mtl-longsky
-sd-concepts-library/mu-sadr
-sd-concepts-library/munch-leaks-style
-sd-concepts-library/museum-by-coop-himmelblau
-sd-concepts-library/muxoyara
-sd-concepts-library/my-hero-academia-style
-sd-concepts-library/my-mug
-sd-concepts-library/mycat
-sd-concepts-library/mystical-nature
-sd-concepts-library/naf
-sd-concepts-library/nahiri
-sd-concepts-library/namine-ritsu
-sd-concepts-library/naoki-saito
-sd-concepts-library/nard-style
-sd-concepts-library/naruto
-sd-concepts-library/natasha-johnston
-sd-concepts-library/nathan-wyatt
-sd-concepts-library/naval-portrait
-sd-concepts-library/nazuna
-sd-concepts-library/nebula
-sd-concepts-library/ned-flanders
-sd-concepts-library/neon-pastel
-sd-concepts-library/new-priests
-sd-concepts-library/nic-papercuts
-sd-concepts-library/nikodim
-sd-concepts-library/nissa-revane
-sd-concepts-library/nixeu
-sd-concepts-library/noggles
-sd-concepts-library/nomad
-sd-concepts-library/nouns-glasses
-sd-concepts-library/obama-based-on-xi
-sd-concepts-library/obama-self-2
-sd-concepts-library/og-mox-style
-sd-concepts-library/ohisashiburi-style
-sd-concepts-library/oleg-kuvaev
-sd-concepts-library/olli-olli
-sd-concepts-library/on-kawara
-sd-concepts-library/one-line-drawing
-sd-concepts-library/onepunchman
-sd-concepts-library/onzpo
-sd-concepts-library/orangejacket
-sd-concepts-library/ori
-sd-concepts-library/ori-toor
-sd-concepts-library/orientalist-art
-sd-concepts-library/osaka-jyo
-sd-concepts-library/osaka-jyo2
-sd-concepts-library/osrsmini2
-sd-concepts-library/osrstiny
-sd-concepts-library/other-mother
-sd-concepts-library/ouroboros
-sd-concepts-library/outfit-items
-sd-concepts-library/overprettified
-sd-concepts-library/owl-house
-sd-concepts-library/painted-by-silver-of-999
-sd-concepts-library/painted-by-silver-of-999-2
-sd-concepts-library/painted-student
-sd-concepts-library/painting
-sd-concepts-library/pantone-milk
-sd-concepts-library/paolo-bonolis
-sd-concepts-library/party-girl
-sd-concepts-library/pascalsibertin
-sd-concepts-library/pastelartstyle
-sd-concepts-library/paul-noir
-sd-concepts-library/pen-ink-portraits-bennorthen
-sd-concepts-library/phan
-sd-concepts-library/phan-s-collage
-sd-concepts-library/phc
-sd-concepts-library/phoenix-01
-sd-concepts-library/pineda-david
-sd-concepts-library/pink-beast-pastelae-style
-sd-concepts-library/pintu
-sd-concepts-library/pion-by-august-semionov
-sd-concepts-library/piotr-jablonski
-sd-concepts-library/pixel-mania
-sd-concepts-library/pixel-toy
-sd-concepts-library/pjablonski-style
-sd-concepts-library/plant-style
-sd-concepts-library/plen-ki-mun
-sd-concepts-library/pokemon-conquest-sprites
-sd-concepts-library/pool-test
-sd-concepts-library/poolrooms
-sd-concepts-library/poring-ragnarok-online
-sd-concepts-library/poutine-dish
-sd-concepts-library/princess-knight-art
-sd-concepts-library/progress-chip
-sd-concepts-library/puerquis-toy
-sd-concepts-library/purplefishli
-sd-concepts-library/pyramidheadcosplay
-sd-concepts-library/qpt-atrium
-sd-concepts-library/quiesel
-sd-concepts-library/r-crumb-style
-sd-concepts-library/rahkshi-bionicle
-sd-concepts-library/raichu
-sd-concepts-library/rail-scene
-sd-concepts-library/rail-scene-style
-sd-concepts-library/ralph-mcquarrie
-sd-concepts-library/ransom
-sd-concepts-library/rayne-weynolds
-sd-concepts-library/rcrumb-portraits-style
-sd-concepts-library/rd-chaos
-sd-concepts-library/rd-paintings
-sd-concepts-library/red-glasses
-sd-concepts-library/reeducation-camp
-sd-concepts-library/reksio-dog
-sd-concepts-library/rektguy
-sd-concepts-library/remert
-sd-concepts-library/renalla
-sd-concepts-library/repeat
-sd-concepts-library/retro-girl
-sd-concepts-library/retro-mecha-rangers
-sd-concepts-library/retropixelart-pinguin
-sd-concepts-library/rex-deno
-sd-concepts-library/rhizomuse-machine-bionic-sculpture
-sd-concepts-library/ricar
-sd-concepts-library/rickyart
-sd-concepts-library/rico-face
-sd-concepts-library/riker-doll
-sd-concepts-library/rikiart
-sd-concepts-library/rikiboy-art
-sd-concepts-library/rilakkuma
-sd-concepts-library/rishusei-style
-sd-concepts-library/rj-palmer
-sd-concepts-library/rl-pkmn-test
-sd-concepts-library/road-to-ruin
-sd-concepts-library/robertnava
-sd-concepts-library/roblox-avatar
-sd-concepts-library/roy-lichtenstein
-sd-concepts-library/ruan-jia
-sd-concepts-library/russian
-sd-concepts-library/s1m-naoto-ohshima
-sd-concepts-library/saheeli-rai
-sd-concepts-library/sakimi-style
-sd-concepts-library/salmonid
-sd-concepts-library/sam-yang
-sd-concepts-library/sanguo-guanyu
-sd-concepts-library/sas-style
-sd-concepts-library/scarlet-witch
-sd-concepts-library/schloss-mosigkau
-sd-concepts-library/scrap-style
-sd-concepts-library/scratch-project
-sd-concepts-library/sculptural-style
-sd-concepts-library/sd-concepts-library-uma-meme
-sd-concepts-library/seamless-ground
-sd-concepts-library/selezneva-alisa
-sd-concepts-library/sem-mac2n
-sd-concepts-library/senneca
-sd-concepts-library/seraphimmoonshadow-art
-sd-concepts-library/sewerslvt
-sd-concepts-library/she-hulk-law-art
-sd-concepts-library/she-mask
-sd-concepts-library/sherhook-painting
-sd-concepts-library/sherhook-painting-v2
-sd-concepts-library/shev-linocut
-sd-concepts-library/shigure-ui-style
-sd-concepts-library/shiny-polyman
-sd-concepts-library/shrunken-head
-sd-concepts-library/shu-doll
-sd-concepts-library/shvoren-style
-sd-concepts-library/sims-2-portrait
-sd-concepts-library/singsing
-sd-concepts-library/singsing-doll
-sd-concepts-library/sintez-ico
-sd-concepts-library/skyfalls
-sd-concepts-library/slm
-sd-concepts-library/smarties
-sd-concepts-library/smiling-friend-style
-sd-concepts-library/smooth-pencils
-sd-concepts-library/smurf-style
-sd-concepts-library/smw-map
-sd-concepts-library/society-finch
-sd-concepts-library/sorami-style
-sd-concepts-library/spider-gwen
-sd-concepts-library/spritual-monsters
-sd-concepts-library/stable-diffusion-conceptualizer
-sd-concepts-library/star-tours-posters
-sd-concepts-library/stardew-valley-pixel-art
-sd-concepts-library/starhavenmachinegods
-sd-concepts-library/sterling-archer
-sd-concepts-library/stretch-re1-robot
-sd-concepts-library/stuffed-penguin-toy
-sd-concepts-library/style-of-marc-allante
-sd-concepts-library/summie-style
-sd-concepts-library/sunfish
-sd-concepts-library/super-nintendo-cartridge
-sd-concepts-library/supitcha-mask
-sd-concepts-library/sushi-pixel
-sd-concepts-library/swamp-choe-2
-sd-concepts-library/t-skrang
-sd-concepts-library/takuji-kawano
-sd-concepts-library/tamiyo
-sd-concepts-library/tangles
-sd-concepts-library/tb303
-sd-concepts-library/tcirle
-sd-concepts-library/teelip-ir-landscape
-sd-concepts-library/teferi
-sd-concepts-library/tela-lenca
-sd-concepts-library/tela-lenca2
-sd-concepts-library/terraria-style
-sd-concepts-library/tesla-bot
-sd-concepts-library/test
-sd-concepts-library/test-epson
-sd-concepts-library/test2
-sd-concepts-library/testing
-sd-concepts-library/thalasin
-sd-concepts-library/thegeneral
-sd-concepts-library/thorneworks
-sd-concepts-library/threestooges
-sd-concepts-library/thunderdome-cover
-sd-concepts-library/thunderdome-covers
-sd-concepts-library/ti-junglepunk-v0
-sd-concepts-library/tili-concept
-sd-concepts-library/titan-robot
-sd-concepts-library/tnj
-sd-concepts-library/toho-pixel
-sd-concepts-library/tomcat
-sd-concepts-library/tonal1
-sd-concepts-library/tony-diterlizzi-s-planescape-art
-sd-concepts-library/towerplace
-sd-concepts-library/toy
-sd-concepts-library/toy-bonnie-plush
-sd-concepts-library/toyota-sera
-sd-concepts-library/transmutation-circles
-sd-concepts-library/trash-polka-artstyle
-sd-concepts-library/travis-bedel
-sd-concepts-library/trigger-studio
-sd-concepts-library/trust-support
-sd-concepts-library/trypophobia
-sd-concepts-library/ttte
-sd-concepts-library/tubby
-sd-concepts-library/tubby-cats
-sd-concepts-library/tudisco
-sd-concepts-library/turtlepics
-sd-concepts-library/type
-sd-concepts-library/ugly-sonic
-sd-concepts-library/uliana-kudinova
-sd-concepts-library/uma
-sd-concepts-library/uma-clean-object
-sd-concepts-library/uma-meme
-sd-concepts-library/uma-meme-style
-sd-concepts-library/uma-style-classic
-sd-concepts-library/unfinished-building
-sd-concepts-library/urivoldemort
-sd-concepts-library/uzumaki
-sd-concepts-library/valorantstyle
-sd-concepts-library/vb-mox
-sd-concepts-library/vcr-classique
-sd-concepts-library/venice
-sd-concepts-library/vespertine
-sd-concepts-library/victor-narm
-sd-concepts-library/vietstoneking
-sd-concepts-library/vivien-reid
-sd-concepts-library/vkuoo1
-sd-concepts-library/vraska
-sd-concepts-library/w3u
-sd-concepts-library/walter-wick-photography
-sd-concepts-library/warhammer-40k-drawing-style
-sd-concepts-library/waterfallshadow
-sd-concepts-library/wayne-reynolds-character
-sd-concepts-library/wedding
-sd-concepts-library/wedding-HandPainted
-sd-concepts-library/werebloops
-sd-concepts-library/wheatland
-sd-concepts-library/wheatland-arknight
-sd-concepts-library/wheelchair
-sd-concepts-library/wildkat
-sd-concepts-library/willy-hd
-sd-concepts-library/wire-angels
-sd-concepts-library/wish-artist-stile
-sd-concepts-library/wlop-style
-sd-concepts-library/wojak
-sd-concepts-library/wojaks-now
-sd-concepts-library/wojaks-now-now-now
-sd-concepts-library/xatu
-sd-concepts-library/xatu2
-sd-concepts-library/xbh
-sd-concepts-library/xi
-sd-concepts-library/xidiversity
-sd-concepts-library/xioboma
-sd-concepts-library/xuna
-sd-concepts-library/xyz
-sd-concepts-library/yb-anime
-sd-concepts-library/yerba-mate
-sd-concepts-library/yesdelete
-sd-concepts-library/yf21
-sd-concepts-library/yilanov2
-sd-concepts-library/yinit
-sd-concepts-library/yoji-shinkawa-style
-sd-concepts-library/yolandi-visser
-sd-concepts-library/yoshi
-sd-concepts-library/youpi2
-sd-concepts-library/youtooz-candy
-sd-concepts-library/yuji-himukai-style
-sd-concepts-library/zaney
-sd-concepts-library/zaneypixelz
-sd-concepts-library/zdenek-art
-sd-concepts-library/zero
-sd-concepts-library/zero-bottle
-sd-concepts-library/zero-suit-samus
-sd-concepts-library/zillertal-can
-sd-concepts-library/zizigooloo
-sd-concepts-library/zk
-sd-concepts-library/zoroark

configs/stable-diffusion/v1-inference.yaml

@@ -30,7 +30,7 @@ model:
       target: ldm.modules.embedding_manager.EmbeddingManager
       params:
         placeholder_strings: ["*"]
-        initializer_words: ['sculpture']
+        initializer_words: ['face', 'man', 'photo', 'africanmale']
         per_image_tokens: false
         num_vectors_per_token: 1
         progressive_words: False

configs/stable-diffusion/v1-inpainting-inference.yaml

@@ -30,9 +30,9 @@ model:
       target: ldm.modules.embedding_manager.EmbeddingManager
       params:
         placeholder_strings: ["*"]
-        initializer_words: ['sculpture']
+        initializer_words: ['face', 'man', 'photo', 'africanmale']
         per_image_tokens: false
-        num_vectors_per_token: 8
+        num_vectors_per_token: 1
         progressive_words: False
 
     unet_config:

configs/stable-diffusion/v1-m1-finetune.yaml

@@ -22,7 +22,7 @@ model:
       target: ldm.modules.embedding_manager.EmbeddingManager
       params:
         placeholder_strings: ["*"]
-        initializer_words: ['sculpture']
+        initializer_words: ['face', 'man', 'photo', 'africanmale']
         per_image_tokens: false
         num_vectors_per_token: 6
         progressive_words: False

docker-build/Dockerfile

@@ -1,48 +1,84 @@
-FROM python:3.10-slim AS builder
+FROM ubuntu AS get_miniconda
+
+SHELL ["/bin/bash", "-c"]
+
+# install wget
+RUN apt-get update \
+  && apt-get install -y \
+    wget \
+  && apt-get clean \
+  && rm -rf /var/lib/apt/lists/*
+
+# download and install miniconda
+ARG conda_version=py39_4.12.0-Linux-x86_64
+ARG conda_prefix=/opt/conda
+RUN wget --progress=dot:giga -O /miniconda.sh \
+  https://repo.anaconda.com/miniconda/Miniconda3-${conda_version}.sh \
+  && bash /miniconda.sh -b -p ${conda_prefix} \
+  && rm -f /miniconda.sh
+
+FROM ubuntu AS invokeai
 
 # use bash
 SHELL [ "/bin/bash", "-c" ]
 
-# Install necesarry packages
-RUN apt-get update \
-  && apt-get install -y \
-    --no-install-recommends \
-    gcc=4:10.2.* \
-    libgl1-mesa-glx=20.3.* \
-    libglib2.0-0=2.66.* \
-    python3-dev=3.9.* \
-  && apt-get clean \
-  && rm -rf /var/lib/apt/lists/*
-
-# set workdir, PATH and copy sources
-WORKDIR /usr/src/app
-ENV PATH /usr/src/app/.venv/bin:$PATH
-ARG PIP_REQUIREMENTS=requirements-lin-cuda.txt
-COPY . ./environments-and-requirements/${PIP_REQUIREMENTS} ./
-
-# install requirements
-RUN python3 -m venv .venv \
-  && pip install \
-    --no-cache-dir \
-    -r ${PIP_REQUIREMENTS}
-
-FROM python:3.10-slim AS runtime
+# clean bashrc
+RUN echo "" > ~/.bashrc
 
 # Install necesarry packages
 RUN apt-get update \
   && apt-get install -y \
     --no-install-recommends \
-    libgl1-mesa-glx=20.3.* \
-    libglib2.0-0=2.66.* \
+    gcc \
+    git \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    pip \
+    python3 \
+    python3-dev \
   && apt-get clean \
   && rm -rf /var/lib/apt/lists/*
 
-WORKDIR /usr/src/app
-COPY --from=builder /usr/src/app .
+# clone repository, create models.yaml and create symlinks
+ARG invokeai_git=invoke-ai/InvokeAI
+ARG invokeai_branch=main
+ARG project_name=invokeai
+ARG conda_env_file=environment-lin-cuda.yml
+RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git "/${project_name}" \
+  && cp \
+    "/${project_name}/configs/models.yaml.example" \
+    "/${project_name}/configs/models.yaml" \
+  && ln -sf \
+    "/${project_name}/environments-and-requirements/${conda_env_file}" \
+    "/${project_name}/environment.yml" \
+  && ln -sf \
+    /data/models/v1-5-pruned-emaonly.ckpt \
+    "/${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt" \
+  && ln -sf \
+    /data/outputs/ \
+    "/${project_name}/outputs"
 
-# set Environment, Entrypoint and default CMD
-ENV INVOKEAI_ROOT /data
-ENV PATH=/usr/src/app/.venv/bin:$PATH
+# set workdir
+WORKDIR "/${project_name}"
 
-ENTRYPOINT [ "python3", "scripts/invoke.py" ]
-CMD [ "--web", "--host=0.0.0.0" ]
+# install conda env and preload models
+ARG conda_prefix=/opt/conda
+COPY --from=get_miniconda "${conda_prefix}" "${conda_prefix}"
+RUN source "${conda_prefix}/etc/profile.d/conda.sh" \
+  && conda init bash \
+  && source ~/.bashrc \
+  && conda env create \
+    --name "${project_name}" \
+  && rm -Rf ~/.cache \
+  && conda clean -afy \
+  && echo "conda activate ${project_name}" >> ~/.bashrc
+
+RUN source ~/.bashrc \
+  && python scripts/preload_models.py \
+    --no-interactive
+
+# Copy entrypoint and set env
+ENV CONDA_PREFIX="${conda_prefix}"
+ENV PROJECT_NAME="${project_name}"
+COPY docker-build/entrypoint.sh /
+ENTRYPOINT [ "/entrypoint.sh" ]

docker-build/Dockerfile.cloud

@@ -1,86 +0,0 @@
-#######################
-#### Builder stage ####
-
-FROM library/ubuntu:22.04 AS builder
-
-ARG DEBIAN_FRONTEND=noninteractive
-RUN rm -f /etc/apt/apt.conf.d/docker-clean; echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    --mount=type=cache,target=/var/lib/apt,sharing=locked \
-    apt update && apt-get install -y \
-        git \
-        libglib2.0-0 \
-        libgl1-mesa-glx \
-        python3-venv \
-        python3-pip \
-        build-essential \
-        python3-opencv \
-        libopencv-dev
-
-# This is needed for patchmatch support
-RUN cd /usr/lib/x86_64-linux-gnu/pkgconfig/ &&\
-   ln -sf opencv4.pc opencv.pc
-
-ARG WORKDIR=/invokeai
-WORKDIR ${WORKDIR}
-
-ENV VIRTUAL_ENV=${WORKDIR}/.venv
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-
-RUN --mount=type=cache,target=/root/.cache/pip \
-    python3 -m venv ${VIRTUAL_ENV} &&\
-    pip install --extra-index-url https://download.pytorch.org/whl/cu116 \
-        torch==1.12.0+cu116 \
-        torchvision==0.13.0+cu116 &&\
-    pip install -e git+https://github.com/invoke-ai/PyPatchMatch@0.1.3#egg=pypatchmatch
-
-COPY . .
-RUN --mount=type=cache,target=/root/.cache/pip \
-    cp environments-and-requirements/requirements-lin-cuda.txt requirements.txt && \
-    pip install -r requirements.txt &&\
-    pip install -e .
-
-
-#######################
-#### Runtime stage ####
-
-FROM library/ubuntu:22.04 as runtime
-
-ARG DEBIAN_FRONTEND=noninteractive
-ENV PYTHONUNBUFFERED=1
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    --mount=type=cache,target=/var/lib/apt,sharing=locked \
-    apt update && apt install -y --no-install-recommends \
-        git \
-        curl \
-        ncdu \
-        iotop \
-        bzip2 \
-        libglib2.0-0 \
-        libgl1-mesa-glx \
-        python3-venv \
-        python3-pip \
-        build-essential \
-        python3-opencv \
-        libopencv-dev &&\
-    apt-get clean && apt-get autoclean
-
-ARG WORKDIR=/invokeai
-WORKDIR ${WORKDIR}
-
-ENV INVOKEAI_ROOT=/mnt/invokeai
-ENV VIRTUAL_ENV=${WORKDIR}/.venv
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-
-COPY --from=builder ${WORKDIR} ${WORKDIR}
-COPY --from=builder /usr/lib/x86_64-linux-gnu/pkgconfig /usr/lib/x86_64-linux-gnu/pkgconfig
-
-# build patchmatch
-RUN python -c "from patchmatch import patch_match"
-
-## workaround for non-existent initfile when runtime directory is mounted; see #1613
-RUN touch /root/.invokeai
-
-ENTRYPOINT ["bash"]
-
-CMD ["-c", "python3 scripts/invoke.py --web --host 0.0.0.0"]

docker-build/Makefile

@@ -1,44 +0,0 @@
-# Directory in the container where the INVOKEAI_ROOT (runtime dir) will be mounted
-INVOKEAI_ROOT=/mnt/invokeai
-# Host directory to contain the runtime dir. Will be mounted at INVOKEAI_ROOT path in the container
-HOST_MOUNT_PATH=${HOME}/invokeai
-
-IMAGE=local/invokeai:latest
-
-USER=$(shell id -u)
-GROUP=$(shell id -g)
-
-# All downloaded models, config, etc will end up in ${HOST_MOUNT_PATH} on the host.
-# This is consistent with the expected non-Docker behaviour.
-# Contents can be moved to a persistent storage and used to prime the cache on another host.
-
-build:
-	DOCKER_BUILDKIT=1 docker build -t local/invokeai:latest -f Dockerfile.cloud ..
-
-configure:
-	docker run --rm -it --runtime=nvidia --gpus=all \
-		-v ${HOST_MOUNT_PATH}:${INVOKEAI_ROOT} \
-		-e INVOKEAI_ROOT=${INVOKEAI_ROOT} \
-		${IMAGE} -c "python scripts/configure_invokeai.py"
-
-# Run the container with the runtime dir mounted and the web server exposed on port 9090
-web:
-	docker run --rm -it --runtime=nvidia --gpus=all \
-		-v ${HOST_MOUNT_PATH}:${INVOKEAI_ROOT} \
-		-e INVOKEAI_ROOT=${INVOKEAI_ROOT} \
-		-p 9090:9090 \
-		${IMAGE} -c "python scripts/invoke.py --web --host 0.0.0.0"
-
-# Run the cli with the runtime dir mounted
-cli:
-	docker run --rm -it --runtime=nvidia --gpus=all \
-		-v ${HOST_MOUNT_PATH}:${INVOKEAI_ROOT} \
-		-e INVOKEAI_ROOT=${INVOKEAI_ROOT} \
-		${IMAGE} -c "python scripts/invoke.py"
-
-# Run the container with the runtime dir mounted and open a bash shell
-shell:
-	docker run --rm -it --runtime=nvidia --gpus=all \
-		-v ${HOST_MOUNT_PATH}:${INVOKEAI_ROOT} ${IMAGE} --
-
-.PHONY: build configure web cli shell

docker-build/build.sh

@@ -1,49 +1,84 @@
 #!/usr/bin/env bash
 set -e
+# IMPORTANT: You need to have a token on huggingface.co to be able to download the checkpoint!!!
+# configure values by using env when executing build.sh
+# f.e. env ARCH=aarch64 GITHUB_INVOKE_AI=https://github.com/yourname/yourfork.git ./build.sh
 
-# IMPORTANT: You need to have a token on huggingface.co to be able to download the checkpoints!!!
-# configure values by using env when executing build.sh f.e. `env ARCH=aarch64 ./build.sh`
+source ./docker-build/env.sh || echo "please run from repository root" || exit 1
 
-source ./docker-build/env.sh \
-  || echo "please execute docker-build/build.sh from repository root" \
-  || exit 1
-
-pip_requirements=${PIP_REQUIREMENTS:-requirements-lin-cuda.txt}
-dockerfile=${INVOKE_DOCKERFILE:-docker-build/Dockerfile}
+invokeai_conda_version=${INVOKEAI_CONDA_VERSION:-py39_4.12.0-${platform/\//-}}
+invokeai_conda_prefix=${INVOKEAI_CONDA_PREFIX:-\/opt\/conda}
+invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment-lin-cuda.yml}
+invokeai_git=${INVOKEAI_GIT:-invoke-ai/InvokeAI}
+invokeai_branch=${INVOKEAI_BRANCH:-main}
+huggingface_token=${HUGGINGFACE_TOKEN?}
 
 # print the settings
-echo -e "You are using these values:\n"
-echo -e "Dockerfile:\t ${dockerfile}"
-echo -e "requirements:\t ${pip_requirements}"
-echo -e "volumename:\t ${volumename}"
-echo -e "arch:\t\t ${arch}"
-echo -e "platform:\t ${platform}"
-echo -e "invokeai_tag:\t ${invokeai_tag}\n"
+echo "You are using these values:"
+echo -e "project_name:\t\t ${project_name}"
+echo -e "volumename:\t\t ${volumename}"
+echo -e "arch:\t\t\t ${arch}"
+echo -e "platform:\t\t ${platform}"
+echo -e "invokeai_conda_version:\t ${invokeai_conda_version}"
+echo -e "invokeai_conda_prefix:\t ${invokeai_conda_prefix}"
+echo -e "invokeai_conda_env_file: ${invokeai_conda_env_file}"
+echo -e "invokeai_git:\t\t ${invokeai_git}"
+echo -e "invokeai_tag:\t\t ${invokeai_tag}\n"
+
+_runAlpine() {
+  docker run \
+    --rm \
+    --interactive \
+    --tty \
+    --mount source="$volumename",target=/data \
+    --workdir /data \
+    alpine "$@"
+}
+
+_copyCheckpoints() {
+  echo "creating subfolders for models and outputs"
+  _runAlpine mkdir models
+  _runAlpine mkdir outputs
+  echo "downloading v1-5-pruned-emaonly.ckpt"
+  _runAlpine wget \
+    --header="Authorization: Bearer ${huggingface_token}" \
+    -O models/v1-5-pruned-emaonly.ckpt \
+    https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
+  echo "done"
+}
+
+_checkVolumeContent() {
+  _runAlpine ls -lhA /data/models
+}
+
+_getModelMd5s() {
+  _runAlpine  \
+    alpine sh -c "md5sum /data/models/*.ckpt"
+}
 
 if [[ -n "$(docker volume ls -f name="${volumename}" -q)" ]]; then
   echo "Volume already exists"
-  echo
+  if [[ -z "$(_checkVolumeContent)" ]]; then
+    echo "looks empty, copying checkpoint"
+    _copyCheckpoints
+  fi
+  echo "Models in ${volumename}:"
+  _checkVolumeContent
 else
   echo -n "createing docker volume "
   docker volume create "${volumename}"
+  _copyCheckpoints
 fi
 
 # Build Container
 docker build \
   --platform="${platform}" \
-  --tag="${invokeai_tag}" \
-  --build-arg="PIP_REQUIREMENTS=${pip_requirements}" \
-  --file="${dockerfile}" \
+  --tag "${invokeai_tag}" \
+  --build-arg project_name="${project_name}" \
+  --build-arg conda_version="${invokeai_conda_version}" \
+  --build-arg conda_prefix="${invokeai_conda_prefix}" \
+  --build-arg conda_env_file="${invokeai_conda_env_file}" \
+  --build-arg invokeai_git="${invokeai_git}" \
+  --build-arg invokeai_branch="${invokeai_branch}" \
+  --file ./docker-build/Dockerfile \
   .
-
-docker run \
-  --rm \
-  --platform="$platform" \
-  --name="$project_name" \
-  --hostname="$project_name" \
-  --mount="source=$volumename,target=/data" \
-  --mount="type=bind,source=$HOME/.huggingface,target=/root/.huggingface" \
-  --env="HUGGINGFACE_TOKEN=${HUGGINGFACE_TOKEN}" \
-  --entrypoint="python3" \
-  "${invokeai_tag}" \
-  scripts/configure_invokeai.py --yes

docker-build/entrypoint.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+set -e
+
+source "${CONDA_PREFIX}/etc/profile.d/conda.sh"
+conda activate "${PROJECT_NAME}"
+
+python scripts/invoke.py \
+  ${@:---web --host=0.0.0.0}

docker-build/env.sh

@@ -4,7 +4,7 @@ project_name=${PROJECT_NAME:-invokeai}
 volumename=${VOLUMENAME:-${project_name}_data}
 arch=${ARCH:-x86_64}
 platform=${PLATFORM:-Linux/${arch}}
-invokeai_tag=${INVOKEAI_TAG:-${project_name}:${arch}}
+invokeai_tag=${INVOKEAI_TAG:-${project_name}-${arch}}
 
 export project_name
 export volumename

docker-build/run.sh

@@ -3,17 +3,13 @@ set -e
 
 source ./docker-build/env.sh || echo "please run from repository root" || exit 1
 
-echo -e "You are using these values:\n"
-echo -e "volumename:\t ${volumename}"
-echo -e "invokeai_tag:\t ${invokeai_tag}\n"
-
 docker run \
   --interactive \
   --tty \
   --rm \
-  --platform="$platform" \
-  --name="$project_name" \
-  --hostname="$project_name" \
-  --mount="source=$volumename,target=/data" \
-  --publish=9090:9090 \
+  --platform "$platform" \
+  --name "$project_name" \
+  --hostname "$project_name" \
+  --mount source="$volumename",target=/data \
+  --publish 9090:9090 \
   "$invokeai_tag" ${1:+$@}

docs/CHANGELOG.md

@@ -171,12 +171,12 @@ title: Changelog
 - Integrate sd-v1-5 model into test matrix (easily expandable), remove
   unecesarry caches by @mauwii in
   https://github.com/invoke-ai/InvokeAI/pull/1293
-- add --no-interactive to configure_invokeai step by @mauwii in
+- add --no-interactive to preload_models step by @mauwii in
   https://github.com/invoke-ai/InvokeAI/pull/1302
 - 1-click installer and updater. Uses micromamba to install git and conda into a
   contained environment (if necessary) before running the normal installation
   script by @cmdr2 in https://github.com/invoke-ai/InvokeAI/pull/1253
-- configure_invokeai.py script downloads the weight files by @lstein in
+- preload_models.py script downloads the weight files by @lstein in
   https://github.com/invoke-ai/InvokeAI/pull/1290
 
 ## v2.0.1 <small>(13 October 2022)</small>

docs/features/CLI.md

@@ -99,7 +99,8 @@ overridden on a per-prompt basis (see
 | `--sampler <sampler>`                     | `-A<sampler>`                             | `k_lms`                                        | Sampler to use. Use `-h` to get list of available samplers.                                          |
 | `--seamless`                              |                                           | `False`                                        | Create interesting effects by tiling elements of the image.                                          |
 | `--embedding_path <path>`                 |                                           | `None`                                         | Path to pre-trained embedding manager checkpoints, for custom models                                 |
-| `--gfpgan_model_path`                     |                                           | `experiments/pretrained_models/GFPGANv1.4.pth` | Path to GFPGAN model file.                                              |
+| `--gfpgan_dir`                            |                                           | `src/gfpgan`                                   | Path to where GFPGAN is installed.                                                                   |
+| `--gfpgan_model_path`                     |                                           | `experiments/pretrained_models/GFPGANv1.4.pth` | Path to GFPGAN model file, relative to `--gfpgan_dir`.                                               |
 | `--free_gpu_mem`                          |                                           | `False`                                        | Free GPU memory after sampling, to allow image decoding and saving in low VRAM conditions            |
 | `--precision`                             |                                           | `auto`                                         | Set model precision, default is selected by device. Options: auto, float32, float16, autocast        |
 
@@ -130,34 +131,20 @@ 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 "my unmodified initialization file"
+!!! example ""
 
-    ```bash title="~/.invokeai" linenums="1"
-    # InvokeAI initialization file
-    # This is the InvokeAI initialization file, which contains command-line default values.
-    # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
-    # 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
+    ```bash
+    --web
+    --steps=28
+    --grid
+    -f 0.6 -C 11.0 -A k_euler_a
     ```
 
-!!! note
-
-    The  initialization file only accepts the command line arguments.
-    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.
-    Also be alert for empty blank lines at the end of the file, which will cause
-    an arguments error at startup time.
+Note that the initialization file only accepts the command line arguments.
+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.
+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
 
@@ -209,17 +196,15 @@ 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
+Note that 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.
 
-    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.
+### This is an example of img2img:
 
-!!! example "This is a example of img2img"
-
-    ```bash
-    invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
-    ```
+```
+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
@@ -269,7 +254,7 @@ 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
 ```
 
@@ -281,26 +266,20 @@ 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
 ```
 
-### Custom Styles and Subjects
-
-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`
@@ -327,19 +306,19 @@ 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
@@ -352,7 +331,7 @@ 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,
@@ -377,7 +356,7 @@ 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
 
@@ -397,7 +376,7 @@ 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
@@ -444,10 +423,10 @@ 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
@@ -484,12 +463,12 @@ 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
@@ -501,22 +480,20 @@ 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:
 
-!!! example ""
+```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
+```
 
-    ```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`
+### !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
@@ -526,36 +503,33 @@ 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.
 
-!!! example "load the generation command for a single png file"
+This example loads the generation command for a single png file:
 
-    ```bash
-    invoke> !fetch 0000015.8929913.png
-    # 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
-    ```
+```bash
+invoke> !fetch 0000015.8929913.png
+# 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
+```
 
-!!! example "fetch the generation commands from a batch of files and store them into `selected.txt`"
+This one fetches the generation commands from a batch of files and stores them
+into `selected.txt`:
 
-    ```bash
-    invoke> !fetch outputs\selected-imgs\*.png selected.txt
-    ```
+```bash
+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
+```
 
-    ```bash
-    invoke> !replay outputs\selected-imgs\selected.txt
-    ```
+Note that these commands may behave unexpectedly if given a PNG file that was
+not generated by InvokeAI.
 
-!!! note
-
-    These commands may behave unexpectedly if given a PNG file that was
-    not generated by InvokeAI.
-
-#### `!search <search string>`
+### !search <search string>
 
 This is similar to !history but it only returns lines that contain
 `search string`. For example:
@@ -565,7 +539,7 @@ 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

@@ -1,112 +0,0 @@
----
-title: 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 specialized subjects
-and artistic styles. They are also known as "embeds" in the machine learning
-world.
-
-Each TI file introduces one or more vocabulary terms to the SD model. These are
-known in InvokeAI as "triggers." Triggers are often, but not always, denoted
-using angle brackets as in "<trigger-phrase>". The two most common type of
-TI files that you'll encounter are `.pt` and `.bin` files, which are produced by
-different TI training packages. InvokeAI supports both formats, but its
-[built-in TI training system](TEXTUAL_INVERSION.md) produces `.pt`.
-
-The [Hugging Face company](https://huggingface.co/sd-concepts-library) has
-amassed a large ligrary of >800 community-contributed TI files covering a
-broad range of subjects and styles. InvokeAI has built-in support for this
-library which downloads and merges TI files automatically upon request. You can
-also install your own or others' TI files by placing them in a designated
-directory.
-
-### An Example
-
-Here are a few examples to illustrate how it works. All these images were
-generated using the command-line client and the Stable Diffusion 1.5 model:
-
-|         Japanese gardener          | Japanese gardener <ghibli-face> | Japanese gardener <hoi4-leaders> | Japanese gardener <cartoona-animals> |
-| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
-| ![](../assets/concepts/image1.png) |  ![](../assets/concepts/image2.png)   |   ![](../assets/concepts/image3.png)   |     ![](../assets/concepts/image4.png)     |
-
-You can also combine styles and concepts:
-
-<figure markdown>
-  ![](../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 you
-require them. This requires your machine to be connected to the Internet. To
-find out what each concept is for, you can browse the
-[Hugging Face concepts library](https://huggingface.co/sd-concepts-library) and
-look at examples of what each concept produces.
-
-When you have an idea of a concept you wish to try, go to the command-line
-client (CLI) and type a "&lt;" character and the beginning of the Hugging Face
-concept name you wish to load. Press the Tab key, and the CLI will show you all
-matching concepts. You can also type "&lt;" and Tab to get a listing of all ~800
-concepts, but be prepared to scroll up to see them all! If there is more than
-one match you can 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:
-
-```
-<xatu2>        <xatu>         <xbh>          <xi>           <xidiversity>  <xioboma>      <xuna>         <xyz>
-```
-
-Now type "id" and press Tab. It will be autocompleted to "&lt;xidiversity&gt;"
-because this is a unique match.
-
-Finish your prompt and generate as usual. You may include multiple concept terms
-in the prompt.
-
-If you have never used this concept before, you will see a message that the TI
-model is being downloaded and installed. After this, the concept will be saved
-locally (in the `models/sd-concepts-library` directory) for future use.
-
-Several steps happen during downloading and installation, including a scan of
-the file for malicious code. Should any errors occur, you will be warned and the
-concept will fail to load. Generation will then continue treating the trigger
-term as a normal string of characters (e.g. as literal "&lt;ghibli-face&gt;").
-
-Currently auto-installation of concepts is a feature only available on the
-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 them into
-the `embeddings` directory of the InvokeAI runtime directory (usually `invokeai`
-in your home directory). You may create subdirectories in order to organize the
-files in any way you wish. Be careful not to overwrite one file with another.
-For example, TI files generated by the Hugging Face toolkit share the named
-`learned_embedding.bin`. You can use subdirectories to keep them distinct.
-
-At startup time, InvokeAI will scan the `embeddings` directory and load any TI
-files it finds there. At startup you will see a message 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 TI
-tutorials taught people to use rather than a more descriptive term.
-Unfortunately, if you have multiple TI files that all use this term, only the
-first one loaded will be triggered by use of the term.
-
-To avoid this problem, you can use the `merge_embeddings.py` script to merge two
-or more TI files together. If it encounters a collision of terms, the script
-will prompt you to select new terms that do not collide. See
-[Textual Inversion](TEXTUAL_INVERSION.md) for details.
-
-## Further Reading
-
-Please see [the repository](https://github.com/rinongal/textual_inversion) and
-associated paper for details and limitations.

docs/features/EMBIGGEN.md

@@ -85,7 +85,7 @@ increasing size, every tile after the first in a row or column
 effectively only covers an extra `1 - overlap_ratio` on each axis. If
 the input/`--init_img` is same size as a tile, the ideal (for time)
 scaling factors with the default overlap (0.25) are 1.75, 2.5, 3.25,
-4.0, etc.
+4.0 etc..
 
 `-embiggen_tiles <spaced list of tiles>`
 
@@ -100,15 +100,6 @@ Tiles are numbered starting with one, and left-to-right,
 top-to-bottom.  So, if you are generating a 3x3 tiled image, the
 middle row would be `4 5 6`.
 
-`-embiggen_strength <strength>`
-
-Another advanced option if you want to experiment with the strength parameter
-that embiggen uses when it calls Img2Img. Values range from 0.0 to 1.0
-and lower values preserve more of the character of the initial image.
-Values that are too high will result in a completely different end image,
-while values that are too low will result in an image not dissimilar to one
-you would get with ESRGAN upscaling alone. The default value is 0.4.
-
 ### Examples
 
 !!! example ""

docs/features/IMG2IMG.md

@@ -12,19 +12,21 @@ 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:
 
-!!! example ""
+```commandline
+tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
+```
 
-    ```commandline
-    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:
 
-    <figure markdown>
+<figure markdown>
+![](https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png)
+</figure>
 
-    | 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 } |
+and generate a new image based on it as shown here:
 
-    </figure>
+<figure markdown>
+![](https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png)
+</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
@@ -43,16 +45,15 @@ Note that the prompt makes a big difference. For example, this slight variation
 on the prompt produces a very different image:
 
 <figure markdown>
-![](https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png){ width=320 }
+![](https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png)
 <caption markdown>photograph of a tree on a hill with a river</caption>
 </figure>
 
 !!! tip
 
-    When designing prompts, think about how the images scraped from the internet were
-    captioned. Very few photographs will be labeled "photograph" or "photorealistic."
-    They will, however, be captioned with the publication, photographer, camera model,
-    or film settings.
+    When designing prompts, think about how the images scraped from the internet were captioned. Very few photographs will
+    be labeled "photograph" or "photorealistic." They will, however, be captioned with the publication, photographer, camera
+    model, or film settings.
 
 If the initial image contains transparent regions, then Stable Diffusion will
 only draw within the transparent regions, a process called
@@ -60,17 +61,17 @@ only draw within the transparent regions, a process called
 However, for this to work correctly, the color information underneath the
 transparent needs to be preserved, not erased.
 
-!!! warning "**IMPORTANT ISSUE** "
+!!! warning
 
-    `img2img` does not work properly on initial images smaller
-    than 512x512. Please scale your image to at least 512x512 before using it.
-    Larger images are not a problem, but may run out of VRAM on your GPU card. To
-    fix this, use the --fit option, which downscales the initial image to fit within
-    the box specified by width x height:
+**IMPORTANT ISSUE** `img2img` does not work properly on initial images smaller
+than 512x512. Please scale your image to at least 512x512 before using it.
+Larger images are not a problem, but may run out of VRAM on your GPU card. To
+fix this, use the --fit option, which downscales the initial image to fit within
+the box specified by width x height:
 
-    ```
-    tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
-    ```
+```
+tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
+```
 
 ## How does it actually work, though?
 
@@ -86,15 +87,13 @@ 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:
 
-!!! example ""
+```commandline
+invoke> "fire" -s10 -W384 -H384 -S1592514025
+```
 
-    ```bash
-    invoke> "fire" -s10 -W384 -H384 -S1592514025
-    ```
-
-    <figure markdown>
-    ![latent steps](../assets/img2img/000019.steps.png){ width=720 }
-    </figure>
+<figure markdown>
+![latent steps](../assets/img2img/000019.steps.png)
+</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,
@@ -109,32 +108,34 @@ into the sequence at the appropriate point, with just the right amount of noise.
 
 ### A concrete example
 
-!!! example "I want SD to draw a fire based on this hand-drawn image"
+I want SD to draw a fire based on this hand-drawn image:
 
-    ![drawing of a fireplace](../assets/img2img/fire-drawing.png){ align=left }
+<figure markdown>
+![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
-    is `0.7`, this is what the internal steps the algorithm has to take will look
-    like:
+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
+like:
 
-    <figure markdown>
-    ![gravity32](../assets/img2img/000032.steps.gravity.png)
-    </figure>
+<figure markdown>
+![gravity32](../assets/img2img/000032.steps.gravity.png)
+</figure>
 
-    With strength `0.4`, the steps look more like this:
+With strength `0.4`, the steps look more like this:
 
-    <figure markdown>
-    ![gravity30](../assets/img2img/000030.steps.gravity.png)
-    </figure>
+<figure markdown>
+![gravity30](../assets/img2img/000030.steps.gravity.png)
+</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`:
 
 |                             | strength = 0.7                                                | strength = 0.4                                                |
 | --------------------------- | ------------------------------------------------------------- | ------------------------------------------------------------- |
-| initial image that SD sees  | ![step-0](../assets/img2img/000032.step-0.png)                | ![step-0](../assets/img2img/000030.step-0.png)                |
+| initial image that SD sees  | ![](../assets/img2img/000032.step-0.png)                      | ![](../assets/img2img/000030.step-0.png)                      |
 | steps argument to `invoke>` | `-S10`                                                        | `-S10`                                                        |
-| steps actually taken        | `7`                                                           | `4`                                                           |
+| steps actually taken        | 7                                                             | 4                                                             |
 | latent space at each step   | ![gravity32](../assets/img2img/000032.steps.gravity.png)      | ![gravity30](../assets/img2img/000030.steps.gravity.png)      |
 | output                      | ![000032.1592514025](../assets/img2img/000032.1592514025.png) | ![000030.1592514025](../assets/img2img/000030.1592514025.png) |
 
@@ -149,7 +150,7 @@ If you want to try this out yourself, all of these are using a seed of
 `1592514025` with a width/height of `384`, step count `10`, the default sampler
 (`k_lms`), and the single-word prompt `"fire"`:
 
-```bash
+```commandline
 invoke> "fire" -s10 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png --strength 0.7
 ```
 
@@ -169,7 +170,7 @@ give each generation 20 steps.
 Here's strength `0.4` (note step count `50`, which is `20 ÷ 0.4` to make sure SD
 does `20` steps from my image):
 
-```bash
+```commandline
 invoke> "fire" -s50 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.4
 ```
 

docs/features/NSFW.md

@@ -1,89 +0,0 @@
----
-title: The NSFW Checker
----
-
-# :material-image-off: NSFW Checker
-
-## The NSFW ("Safety") Checker
-
-The Stable Diffusion image generation models will produce sexual
-imagery if deliberately prompted, and will occasionally produce such
-images when this is not intended. Such images are colloquially known
-as "Not Safe for Work" (NSFW). This behavior is due to the nature of
-the training set that Stable Diffusion was trained on, which culled
-millions of "aesthetic" images from the Internet.
-
-You may not wish to be exposed to these images, and in some
-jurisdictions it may be illegal to publicly distribute such imagery,
-including mounting a publicly-available server that provides
-unfiltered images to the public. Furthermore, the [Stable Diffusion
-weights
-License](https://github.com/invoke-ai/InvokeAI/blob/main/LICENSE-ModelWeights.txt)
-forbids the model from being used to "exploit any of the
-vulnerabilities of a specific group of persons."
-
-For these reasons Stable Diffusion offers a "safety checker," a
-machine learning model trained to recognize potentially disturbing
-imagery. When a potentially NSFW image is detected, the checker will
-blur the image and paste a warning icon on top. The checker can be
-turned on and off on the command line using `--nsfw_checker` and
-`--no-nsfw_checker`.
-
-At installation time, InvokeAI will ask whether the checker should be
-activated by default (neither argument given on the command line). The
-response is stored in the InvokeAI initialization file (usually
-`.invokeai` in your home directory). You can change the default at any
-time by opening this file in a text editor and commenting or
-uncommenting the line `--nsfw_checker`.
-
-## Caveats
-
-There are a number of caveats that you need to be aware of.
-
-### Accuracy
-
-The checker is [not perfect](https://arxiv.org/abs/2210.04610).It will
-occasionally flag innocuous images (false positives), and will
-frequently miss violent and gory imagery (false negatives). It rarely
-fails to flag sexual imagery, but this has been known to happen. For
-these reasons, the InvokeAI team prefers to refer to the software as a
-"NSFW Checker" rather than "safety checker."
-
-### Memory Usage and Performance
-
-The NSFW checker consumes an additional 1.2G of GPU VRAM on top of the
-3.4G of VRAM used by Stable Diffusion v1.5 (this is with
-half-precision arithmetic). This means that the checker will not run
-successfully on GPU cards with less than 6GB VRAM, and will reduce the
-size of the images that you can produce.
-
-The checker also introduces a slight performance penalty. Images will
-take ~1 second longer to generate when the checker is
-activated. Generally this is not noticeable.
-
-### Intermediate Images in the Web UI
-
-The checker only operates on the final image produced by the Stable
-Diffusion algorithm. If you are using the Web UI and have enabled the
-display of intermediate images, you will briefly be exposed to a
-low-resolution (mosaicized) version of the final image before it is
-flagged by the checker and replaced by a fully blurred version. You
-are encouraged to turn **off** intermediate image rendering when you
-are using the checker. Future versions of InvokeAI will apply
-additional blurring to intermediate images when the checker is active.
-
-### Watermarking
-
-InvokeAI does not apply any sort of watermark to images it
-generates. However, it does write metadata into the PNG data area,
-including the prompt used to generate the image and relevant parameter
-settings. These fields can be examined using the `sd-metadata.py`
-script that comes with the InvokeAI package.
-
-Note that several other Stable Diffusion distributions offer
-wavelet-based "invisible" watermarking. We have experimented with the
-library used to generate these watermarks and have reached the
-conclusion that while the watermarking library may be adding
-watermarks to PNG images, the currently available version is unable to
-retrieve them successfully. If and when a functioning version of the
-library becomes available, we will offer this feature as well.

docs/features/OTHER.md

@@ -133,6 +133,29 @@ outputs = g.txt2img("a unicorn in manhattan")
 
 Outputs is a list of lists in the format [filename1,seed1],[filename2,seed2]...].
 
-Please see the documentation in ldm/generate.py for more information.
+Please see ldm/generate.py for more information. A set of example scripts is coming RSN.
 
 ---
+
+## **Preload Models**
+
+In situations where you have limited internet connectivity or are blocked behind a firewall, you can
+use the preload script to preload the required files for Stable Diffusion to run.
+
+The preload script `scripts/preload_models.py` needs to be run once at least while connected to the
+internet. In the following runs, it will load up the cached versions of the required files from the
+`.cache` directory of the system.
+
+```bash
+(invokeai) ~/stable-diffusion$ python3 ./scripts/preload_models.py
+preloading bert tokenizer...
+Downloading: 100%|██████████████████████████████████| 28.0/28.0 [00:00<00:00, 49.3kB/s]
+Downloading: 100%|██████████████████████████████████| 226k/226k [00:00<00:00, 2.79MB/s]
+Downloading: 100%|██████████████████████████████████| 455k/455k [00:00<00:00, 4.36MB/s]
+Downloading: 100%|██████████████████████████████████| 570/570 [00:00<00:00, 477kB/s]
+...success
+preloading kornia requirements...
+Downloading: "https://github.com/DagnyT/hardnet/raw/master/pretrained/train_liberty_with_aug/checkpoint_liberty_with_aug.pth" to /u/lstein/.cache/torch/hub/checkpoints/checkpoint_liberty_with_aug.pth
+100%|███████████████████████████████████████████████| 5.10M/5.10M [00:00<00:00, 101MB/s]
+...success
+```

docs/features/OUTPAINTING.md

@@ -92,21 +92,6 @@ The new image is larger than the original (576x704) because 64 pixels were added
 to the top and right sides. You will need enough VRAM to process an image of
 this size.
 
-#### Outcropping non-InvokeAI images
-
-You can outcrop an arbitrary image that was not generated by InvokeAI,
-but your results will vary. The `inpainting-1.5` model is highly
-recommended, but if not feasible, then you may be able to improve the
-output by conditioning the outcropping with a text prompt that
-describes the scene using the `--new_prompt` argument:
-
-```bash
-invoke> !fix images/vacation.png --outcrop top 128 --new_prompt "family vacation"
-```
-
-You may also provide a different seed for outcropping to use by passing
-`-S<seed>`. A negative seed will generate a new random seed.
-
 A number of caveats:
 
 1. Although you can specify any pixel values, they will be rounded up to the
@@ -120,7 +105,7 @@ A number of caveats:
    (`--iterations`) argument.
 
 3. Your results will be _much_ better if you use the `inpaint-1.5` model
-   released by runwayML and installed by default by `scripts/configure_invokeai.py`.
+   released by runwayML and installed by default by `scripts/preload_models.py`.
    This model was trained specifically to harmoniously fill in image gaps. The
    standard model will work as well, but you may notice color discontinuities at
    the border.

docs/features/POSTPROCESS.md

@@ -6,39 +6,53 @@ title: Postprocessing
 
 ## Intro
 
-This extension provides the ability to restore faces and upscale images.
+This extension provides the ability to restore faces and upscale
+images.
 
-Face restoration and upscaling can be applied at the time you generate the
-images, or at any later time against a previously-generated PNG file, using the
-[!fix](#fixing-previously-generated-images) command.
-[Outpainting and outcropping](OUTPAINTING.md) can only be applied after the
-fact.
+Face restoration and upscaling can be applied at the time you generate
+the images, or at any later time against a previously-generated PNG
+file, using the [!fix](#fixing-previously-generated-images)
+command. [Outpainting and outcropping](OUTPAINTING.md) can only be
+applied after the fact.
 
 ## Face Fixing
 
 The default face restoration module is GFPGAN. The default upscale is
-Real-ESRGAN. For an alternative face restoration module, see
-[CodeFormer Support](#codeformer-support) below.
+Real-ESRGAN. For an alternative face restoration module, see [CodeFormer
+Support](#codeformer-support) below.
 
-As of version 1.14, environment.yaml will install the Real-ESRGAN package into
-the standard install location for python packages, and will put GFPGAN into a
-subdirectory of "src" in the InvokeAI directory. Upscaling with Real-ESRGAN
-should "just work" without further intervention. Simply pass the `--upscale`
-(`-U`) option on the `invoke>` command line, or indicate the desired scale on
-the popup in the Web GUI.
+As of version 1.14, environment.yaml will install the Real-ESRGAN
+package into the standard install location for python packages, and
+will put GFPGAN into a subdirectory of "src" in the InvokeAI
+directory. Upscaling with Real-ESRGAN should "just work" without
+further intervention. Simply pass the `--upscale` (`-U`) option on the
+`invoke>` command line, or indicate the desired scale on the popup in
+the Web GUI.
 
-**GFPGAN** requires a series of downloadable model files to work. These are
-loaded when you run `scripts/configure_invokeai.py`. If GFPAN is failing with an
-error, please run the following from the InvokeAI directory:
+**GFPGAN** requires a series of downloadable model files to
+work. These are loaded when you run `scripts/preload_models.py`. If
+GFPAN is failing with an error, please run the following from the
+InvokeAI directory:
 
 ```bash
-python scripts/configure_invokeai.py
+python scripts/preload_models.py
 ```
 
-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
+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.
 
+Alternatively, if you have GFPGAN installed elsewhere, or if you are
+using an earlier version of this package which asked you to install
+GFPGAN in a sibling directory, you may use the `--gfpgan_dir` argument
+with `invoke.py` to set a custom path to your GFPGAN directory. _There
+are other GFPGAN related boot arguments if you wish to customize
+further._
+
+## Usage
+
+You will now have access to two new prompt arguments.
+
 ### Upscaling
 
 `-U : <upscaling_factor> <upscaling_strength>`
@@ -105,17 +119,17 @@ actions.
 This repo also allows you to perform face restoration using
 [CodeFormer](https://github.com/sczhou/CodeFormer).
 
-In order to setup CodeFormer to work, you need to download the models like with
-GFPGAN. You can do this either by running `configure_invokeai.py` or by manually
-downloading the
-[model file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth)
+In order to setup CodeFormer to work, you need to download the models
+like with GFPGAN. You can do this either by running
+`preload_models.py` or by manually downloading the [model
+file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth)
 and saving it to `ldm/invoke/restoration/codeformer/weights` folder.
 
-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.
+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.
 
-### CodeFormer Usage
+### Usage
 
 The following command will perform face restoration with CodeFormer instead of
 the default gfpgan.
@@ -143,9 +157,9 @@ situations when there is very little facial data to work with.
 ## Fixing Previously-Generated Images
 
 It is easy to apply face restoration and/or upscaling to any
-previously-generated file. Just use the syntax
-`!fix path/to/file.png <options>`. For example, to apply GFPGAN at strength 0.8
-and upscale 2X for a file named `./outputs/img-samples/000044.2945021133.png`,
+previously-generated file. Just use the syntax `!fix path/to/file.png
+<options>`. For example, to apply GFPGAN at strength 0.8 and upscale
+2X for a file named `./outputs/img-samples/000044.2945021133.png`,
 just run:
 
 ```bash
@@ -156,7 +170,7 @@ 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.
 
-## How to disable
+### Disabling
 
 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/UNIFIED_CANVAS.md

@@ -1,117 +0,0 @@
-The Unified Canvas is a tool designed to streamline and simplify the process of composing an image using Stable Diffusion. It offers artists all of the available Stable Diffusion generation modes (Text To Image, Image To Image, Inpainting, and Outpainting) as a single unified workflow. The flexibility of the tool allows you to tweak and edit image generations, extend images beyond their initial size, and to create new content in a freeform way both inside and outside of existing images. 
-
-This document explains the basics of using the Unified Canvas, introducing you to its features and tools one by one. It also describes some of the more advanced tools available to power users of the Canvas.
-
-# Basics
-The Unified Canvas consists of two layers: the **Base Layer** and the **Mask Layer**. You can swap from one layer to the other by selecting the layer you want in the drop-down menu on the top left corner of the Unified Canvas, or by pressing the (Q) hotkey.
-
-### Base Layer
-The **Base Layer** is the image content currently managed by the Canvas, and can be exported at any time to the gallery by using the **Save to Gallery** option. When the Base Layer is selected, the Brush (B) and Eraser (E) tools will directly manipulate the base layer. Any images uploaded to the Canvas, or sent to the Unified Canvas from the gallery, will clear out all existing content and set the Base layer to the new image.
-
-### Staging Area
-When you generate images, they will display in the Canvas's **Staging Area**, alongside the Staging Area toolbar buttons. While the Staging Area is active, you cannot interact with the Canvas itself.
-
-<figure markdown>
-![staging area](../assets/canvas/staging_area.png)
-</figure>
-
-Accepting generations will commit the new generation to the **Base Layer**. You can review all generated images using the Prev/Next arrows, save any individual generations to your gallery (without committing to the Base layer) or discard generations. While you can Undo a discard in an individual Canvas session, any generations that are not saved will be lost when the Canvas resets.
-
-### Mask Layer
-The **Mask Layer** consists of any masked sections that have been created to inform Inpainting generations. You can paint a new mask, or edit an existing mask, using the Brush tool and the Eraser with the Mask layer set as your Active layer. Any masked areas will only affect generation inside of the current bounding box.
-
-### Bounding Box
-When generating a new image, Invoke will process and apply new images within the area denoted by the **Bounding Box**. The Width & Height settings of the Bounding Box, as well as its location within the Unified Canvas and pixels or empty space that it encloses, determine how new invocations are generated - see [Inpainting & Outpainting](#inpainting-and-outpainting) below. The Bounding Box can be moved and resized using the Move (V) tool. It can also be resized using the Bounding Box options in the Options Panel. By using these controls you can generate larger or smaller images, control which sections of the image are being processed, as well as control Bounding Box tools like the Bounding Box fill/erase. 
-
-### <a name="inpainting-and-outpainting"></a> Inpainting & Outpainting
-"Inpainting" means asking the AI to refine part of an image while leaving the rest alone. For example, updating a portrait of your grandmother to have her wear a biker's jacket.
-
-<figure markdown>
-![granny with a mask applied](../assets/canvas/mask_granny.png)
-</figure>
-
-<figure markdown>
-![just like magic, granny with a biker's jacket](../assets/canvas/biker_jacket_granny.png)
-</figure>
-
-"Outpainting" means asking the AI to expand the original image beyond its original borders, making a bigger image that's still based on the original. For example, extending the above image of your Grandmother in a biker's jacket to include her wearing jeans (and while we're at it, a motorcycle!)
-
-<figure markdown>
-![more magic - granny with a tattooed arm, denim pants, and an obscured motorcycle](../assets/canvas/biker_jacket_granny.png)
-</figure>
-
-When you are using the Unified Canvas, Invoke decides automatically whether to do Inpainting, Outpainting, ImageToImage, or TextToImage by looking inside the area enclosed by the Bounding Box. It chooses the appropriate type of generation based on whether the Bounding Box contains empty (transparent) areas on the Base layer, or whether it contains colored areas from previous generations (or from painted brushstrokes) on the Base layer, and/or whether the Mask layer contains any brushstrokes. See [Generation Methods](#generation-methods) below for more information.
-
-# Getting Started
-
-To get started with the Unified Canvas, you will want to generate a new base layer using Txt2Img or importing an initial image. We'll refer to either of these methods as the "initial image" in the below guide.
-
-From there, you can consider the following techniques to augment your image:
-* **New Images**: Move the bounding box to an empty area of the Canvas, type in your prompt, and Invoke, to generate a new image using the Text to Image function.
-* **Image Correction**: Use the color picker and brush tool to paint corrections on the image, switch to the Mask layer, and brush a mask over your painted area to use **Inpainting**. You can also use the **ImageToImage** generation method to invoke new interpretations of the image. 
-* **Image Expansion**: Move the bounding box to include a portion of your initial image, and a portion of transparent/empty pixels, then Invoke using a prompt that describes what you'd like to see in that area. This will Outpaint the image. You'll typically find more coherent results if you keep about 50-60% of the original image in the bounding box. Make sure that the Image To Image Strength slider is set to a high value - you may need to set it higher than you are used to.
-* **New Content on Existing Images**: If you want to add new details or objects into your image, use the brush tool to paint a sketch of what you'd like to see on the image, switch to the Mask layer, and brush a mask over your painted area to use **Inpainting**. If the masked area is small, consider using a smaller bounding box to take advantage of Invoke's automatic Scaling features, which can help to produce better details. 
-* **And more**: There are a number of creative ways to use the Canvas, and the above are just starting points. We're excited to see what you come up with!
-
-
-# <a name="generation-methods"></a> Generation Methods
-The Canvas can use all generation methods available (Txt2Img, Img2Img, Inpainting, and Outpainting), and these will be automatically selected and used based on the current selection area within the Bounding Box.
-
-## Text to Image
-If the Bounding Box is placed over an area of Canvas with an **empty Base Layer**, invoking a new image will use **TextToImage**. This generates an entirely new image based on your prompt.
-
-## Image to Image
-If the Bounding Box is placed over an area of Canvas with an **existing Base Layer area with no transparent pixels or masks**, invoking a new image will use **ImageToImage**. This uses the image within the bounding box and your prompt to interpret a new image. The image will be closer to your original image at lower Image to Image strengths.
-
-## Inpainting
-If the Bounding Box is placed over an area of Canvas with an **existing Base Layer and any pixels selected using the Mask layer**, invoking a new image will use **Inpainting**. Inpainting uses the existing colors/forms in the masked area in order to generate a new image for the masked area only. The unmasked portion of the image will remain the same. Image to Image strength applies to the inpainted area.
-
-If you desire something completely different from the original image in your new generation (i.e., if you want Invoke to ignore existing colors/forms), consider toggling the Inpaint Replace setting on, and use high values for both Inpaint Replace and Image To Image Strength.
-
-> Note: By default, the **Scale Before Processing** option &mdash; which inpaints more coherent details by generating at a larger resolution and then scaling &mdash; is only activated when the Bounding Box is relatively small. To get the best inpainting results you should therefore resize your Bounding Box to the smallest area that contains your mask and enough surrounding detail to help Stable Diffusion understand the context of what you want it to draw. You should also update your prompt so that it describes *just* the area within the Bounding Box.
-
-## Outpainting
-If the Bounding Box is placed over an area of Canvas partially filled by an existing Base Layer area and partially by transparent pixels or masks, invoking a new image will use **Outpainting**, as well as **Inpainting** any masked areas.
-
-____
-
-# Advanced Features
-
-Features with non-obvious behavior are detailed below, in order to provide clarity on the intent and common use cases we expect for utilizing them.
-
-## Toolbar
-
-### Mask Options
-* **Enable Mask** - This flag can be used to Enable or Disable the currently painted mask. If you have painted a mask, but you don't want it affect the next invocation, but you *also* don't want to delete it, then you can set this option to Disable. When you want the mask back, set this back to Enable. 
-* **Preserve Masked Area** - When enabled, Preserve Masked Area inverts the effect of the Mask on the Inpainting process. Pixels in masked areas will be kept unchanged, and unmasked areas will be regenerated.
-
-### Creative Tools
-* **Brush - Base/Mask Modes** - The Brush tool switches automatically between different modes of operation for the Base and Mask layers respectively. 
-  * On the Base layer, the brush will directly paint on the Canvas using the color selected on the Brush Options menu. 
-  * On the Mask layer, the brush will create a new mask. If you're finding the mask difficult to see over the existing content of the Unified Canvas, you can change the color it is drawn with using the color selector on the Mask Options dropdown.
-* **Erase Bounding Box** - On the Base layer, erases all pixels within the Bounding Box.
-* **Fill Bounding Box** - On the Base layer, fills all pixels within the Bounding Box with the currently selected color.
-
-### Canvas Tools
-* **Move Tool** - Allows for manipulation of the Canvas view (by dragging on the Canvas, outside the bounding box), the Bounding Box (by dragging the edges of the box), or the Width/Height of the Bounding Box (by dragging one of the 9 directional handles).
-* **Reset View** - Click to re-orients the view to the center of the Bounding Box. 
-* **Merge Visible** - If your browser is having performance problems drawing the image in the Unified Canvas, click this to consolidate all of the information currently being rendered by your browser into a merged copy of the image. This lowers the resource requirements and should improve performance.
-
-## Seam Correction
-When doing Inpainting or Outpainting, Invoke needs to merge the pixels generated by Stable Diffusion into your existing image. To do this, the area around the `seam` at the boundary between your image and the new generation is automatically blended to produce a seamless output. In a fully automatic process, a mask is generated to cover the seam, and then the area of the seam is Inpainted. 
-
-Although the default options should work well most of the time, sometimes it can help to alter the parameters that control the seam Inpainting. A wider seam and a blur setting of about 1/3 of the seam have been noted as producing consistently strong results (e.g. 96 wide and 16 blur - adds up to 32 blur with both sides). Seam strength of 0.7 is best for reducing hard seams.
-* **Seam Size** - The size of the seam masked area. Set higher to make a larger mask around the seam.
-* **Seam Blur** - The size of the blur that is applied on *each* side of the masked area. 
-* **Seam Strength** - The Image To Image Strength parameter used for the Inpainting generation that is applied to the seam area.
-* **Seam Steps** - The number of generation steps that should be used to Inpaint the seam.
-
-## Infill & Scaling
-* **Scale Before Processing & W/H**: When generating images with a bounding box smaller than the optimized W/H of the model (e.g., 512x512 for SD1.5), this feature first generates at a larger size with the same aspect ratio, and then scales that image down to fill the selected area. This is particularly useful when inpainting very small details. Scaling is optional but is enabled by default.
-* **Inpaint Replace**: When Inpainting, the default method is to utilize the existing RGB values of the Base layer to inform the generation process. If Inpaint Replace is enabled, noise is generated and blended with the existing pixels (completely replacing the original RGB values at an Inpaint Replace value of 1). This can help generate more variation from the pixels on the Base layers.
-  * > When using Inpaint Replace you should use a higher Image To Image Strength value, especially at higher Inpaint Replace values
-* **Infill Method**: Invoke currently supports two methods for producing RGB values for use in the Outpainting process: Patchmatch and Tile. We believe that Patchmatch is the superior method, however we provide support for Tile in case Patchmatch cannot be installed or is unavailable on your computer.
-  * **Tile Size**: The Tile method for Outpainting sources small portions of the original image and randomly place these into the areas being Outpainted. This value sets the size of those tiles.
-
-# Hot Keys
-The Unified Canvas is a tool that excels when you use hotkeys. You can view the full list of keyboard shortcuts, updated with all new features, by clicking the Keyboard Shortcuts icon at the top right of the InvokeAI WebUI.

docs/features/WEB.md

@@ -303,8 +303,6 @@ The WebGUI is only rapid development. Check back regularly for updates!
 | `--cors [CORS ...]`                     | Additional allowed origins, comma-separated                                                                                                |
 | `--host HOST`                           | Web server: Host or IP to listen on. Set to 0.0.0.0 to accept traffic from other devices on your network.                                  |
 | `--port PORT`                           | Web server: Port to listen on                                                                                                              |
-| `--certfile CERTFILE`                   | Web server: Path to certificate file to use for SSL. Use together with --keyfile                                                           |
-| `--keyfile KEYFILE`                     | Web server: Path to private key file to use for SSL. Use together with --certfile'                                                         |
 | `--gui`                                 | Start InvokeAI GUI - This is the "desktop mode" version of the web app. It uses Flask to create a desktop app experience of the webserver. |
 
 ### Web Specific Features

docs/features/index.md

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

docs/index.md

@@ -80,20 +80,12 @@ Mac and Linux machines, and runs on GPU cards with as little as 4 GB or RAM.
 
 ## :octicons-package-dependencies-24: Installation
 
-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).
+This fork is supported across multiple platforms. You can find individual
+installation instructions below.
 
-First time users, please see [Automated
-Installer](installation/INSTALL_AUTOMATED.md) for a walkthrough of
-getting InvokeAI up and running on your system. For alternative
-installation and upgrade instructions, please see: [InvokeAI
-Installation Overview](installation/)
-
-Linux users who wish to make use of the PyPatchMatch inpainting
-functions will need to perform a bit of extra work to enable this
-module. Instructions can be found at [Installing
-PyPatchMatch](installation/INSTALL_PATCHMATCH.md).
+- :fontawesome-brands-linux: [Linux](installation/INSTALL_LINUX.md)
+- :fontawesome-brands-windows: [Windows](installation/INSTALL_WINDOWS.md)
+- :fontawesome-brands-apple: [Macintosh](installation/INSTALL_MAC.md)
 
 ## :fontawesome-solid-computer: Hardware Requirements
 
@@ -105,25 +97,22 @@ 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 following video cards due to issues with
-their running in half-precision mode and having insufficient VRAM to
-render 512x512 images in full-precision mode:
-
-- NVIDIA 10xx series cards such as the 1080ti
-- GTX 1650 series cards
-- GTX 1660 series cards
-
 ### :fontawesome-solid-memory: Memory
 
 - At least 12 GB Main Memory RAM.
 
 ### :fontawesome-regular-hard-drive: Disk
 
-- At least 18 GB of free disk space for the machine learning model, Python, and
+- At least 12 GB of free disk space for the machine learning model, Python, and
   all its dependencies.
 
 !!! info
 
+    If you are have a Nvidia 10xx series card (e.g. the 1080ti), please run the invoke script in
+    full-precision mode as shown below.
+
+    Similarly, specify full-precision mode on Apple M1 hardware.
+
     Precision is auto configured based on the device. If however you encounter errors like
     `expected type Float but found Half` or `not implemented for Half` you can try starting
     `invoke.py` with the `--precision=float32` flag:
@@ -131,38 +120,9 @@ render 512x512 images in full-precision mode:
     ```bash
     (invokeai) ~/InvokeAI$ python scripts/invoke.py --full_precision
     ```
-## :octicons-gift-24: InvokeAI Features
-
-- [The InvokeAI Web Interface](features/WEB.md)
-    - [WebGUI hotkey reference guide](features/WEBUIHOTKEYS.md)
-    - [WebGUI Unified Canvas for Img2Img, inpainting and outpainting](features/UNIFIED_CANVAS.md)
-<!-- seperator -->
-- [The Command Line Interace](features/CLI.md)
-    - [Image2Image](features/IMG2IMG.md)
-    - [Inpainting](features/INPAINTING.md)
-    - [Outpainting](features/OUTPAINTING.md)
-    - [Adding custom styles and subjects](features/CONCEPTS.md)
-    - [Upscaling and Face Reconstruction](features/POSTPROCESS.md)
-<!-- seperator -->
-- [Generating Variations](features/VARIATIONS.md)
-<!-- seperator -->
-- [Prompt Engineering](features/PROMPTS.md)
-<!-- seperator -->
-- Miscellaneous
-    - [NSFW Checker](features/NSFW.md)
-    - [Embiggen upscaling](features/EMBIGGEN.md)
-    - [Other](features/OTHER.md)
 
 ## :octicons-log-16: Latest Changes
 
-### v2.1.3 <small>(13 November 2022)</small>
-
-- A choice of installer scripts that automate installation and configuration. See [Installation](https://github.com/invoke-ai/InvokeAI/blob/2.1.3-rc6/docs/installation/INSTALL.md).
-- A streamlined manual installation process that works for both Conda and PIP-only installs. See [Manual Installation](https://github.com/invoke-ai/InvokeAI/blob/2.1.3-rc6/docs/installation/INSTALL_MANUAL.md).
-- The ability to save frequently-used startup options (model to load, steps, sampler, etc) in a `.invokeai` file. See [Client](https://github.com/invoke-ai/InvokeAI/blob/2.1.3-rc6/docs/features/CLI.md)
-- Support for AMD GPU cards (non-CUDA) on Linux machines.
-- Multiple bugs and edge cases squashed.
-
 ### v2.1.0 <small>(2 November 2022)</small>
 
 - [Inpainting](https://invoke-ai.github.io/InvokeAI/features/INPAINTING/)
@@ -174,7 +134,7 @@ render 512x512 images in full-precision mode:
 - You can now load
   [multiple models and switch among them quickly](https://docs.google.com/presentation/d/1WywGA1rny7bpFh7CLSdTr4nNpVKdlUeT0Bj0jCsILyU/edit?usp=sharing)
   without leaving the CLI.
-- The installation process (via `scripts/configure_invokeai.py`) now lets you select
+- The installation process (via `scripts/preload_models.py`) now lets you select
   among several popular
   [Stable Diffusion models](https://invoke-ai.github.io/InvokeAI/installation/INSTALLING_MODELS/)
   and downloads and installs them on your behalf. Among other models, this

docs/installation/BUILDING_BINARY_INSTALLERS.md

@@ -1,89 +0,0 @@
----
-title: build binary installers
----
-
-# :simple-buildkite: How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
-
-## 1. Ensure `installers/requirements.in` is correct
-
-and up to date on the branch to be installed.
-
-## <a name="step-2"></a> 2. Run `pip-compile` on each platform.
-
-On each target platform, in the branch that is to be installed, and
-inside the InvokeAI git root folder, run the following commands:
-
-```commandline
-conda activate invokeai # or however you activate python
-pip install pip-tools
-pip-compile --allow-unsafe --generate-hashes --output-file=binary_installer/<reqsfile>.txt binary_installer/requirements.in
-```
-where `<reqsfile>.txt` is whichever of
-```commandline
-py3.10-darwin-arm64-mps-reqs.txt
-py3.10-darwin-x86_64-reqs.txt
-py3.10-linux-x86_64-cuda-reqs.txt
-py3.10-windows-x86_64-cuda-reqs.txt
-```
-matches the current OS and architecture.
-> There is no way to cross-compile these. They must be done on a system matching the target OS and arch.
-
-## <a name="step-3"></a> 3. Set github repository and branch
-
-Once all reqs files have been collected and committed **to the branch
-to be installed**, edit `binary_installer/install.sh.in` and `binary_installer/install.bat.in` so that `RELEASE_URL`
-and `RELEASE_SOURCEBALL` point to the github repo and branch that is
-to be installed.
-
-For example, to install `main` branch of `InvokeAI`, they should be
-set as follows:
-
-`install.sh.in`:
-```commandline
-RELEASE_URL=https://github.com/invoke-ai/InvokeAI
-RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
-```
-
-`install.bat.in`:
-```commandline
-set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
-set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
-```
-
-Or, to install `damians-cool-feature` branch of `damian0815`, set them
-as follows:
-
-`install.sh.in`:
-```commandline
-RELEASE_URL=https://github.com/damian0815/InvokeAI
-RELEASE_SOURCEBALL=/archive/refs/heads/damians-cool-feature.tar.gz
-```
-
-`install.bat.in`:
-```commandline
-set RELEASE_URL=https://github.com/damian0815/InvokeAI
-set RELEASE_SOURCEBALL=/archive/refs/heads/damians-cool-feature.tar.gz
-```
-
-The branch and repo specified here **must** contain the correct reqs
-files. The installer zip files **do not** contain requirements files,
-they are pulled from the specified branch during the installation
-process.
-
-## 4. Create zip files.
-
-cd into the `installers/` folder and run
-`./create_installers.sh`. This will create
-`InvokeAI-mac_on_<branch>.zip`,
-`InvokeAI-windows_on_<branch>.zip` and
-`InvokeAI-linux_on_<branch>.zip`. These files can be distributed to end users.
-
-These zips will continue to function as installers for all future
-pushes to those branches, as long as necessary changes to
-`requirements.in` are propagated in a timely manner to the
-`py3.10-*-reqs.txt` files using pip-compile as outlined in [step
-2](#step-2).
-
-To actually install, users should unzip the appropriate zip file into an empty
-folder and run `install.sh` on macOS/Linux or `install.bat` on
-Windows.

docs/installation/INSTALL.md

@@ -0,0 +1,57 @@
+---
+title: Installation Overview
+---
+
+## Installation
+
+We offer several ways to install InvokeAI, each one suited to your
+experience and preferences.
+
+1. [1-click installer](INSTALL_1CLICK.md)
+
+    This is an automated shell script that will handle installation of
+    all dependencies for you, and is recommended for those who have
+    limited or no experience with the Python programming language, are
+    not currently interested in contributing to the project, and just want
+    the thing to install and run. In this version, you interact with the
+    web server and command-line clients through a shell script named
+    `invoke.sh` (Linux/Mac) or `invoke.bat` (Windows), and perform
+    updates using `update.sh` and `update.bat`.
+
+2. [Pre-compiled PIP installer](INSTALL_PCP.md)
+
+    This is a series of installer files for which all the requirements
+    for InvokeAI have been precompiled, thereby preventing the conflicts
+    that sometimes occur when an external library is changed unexpectedly.
+    It will leave you with an environment in which you interact directly
+    with the scripts for running the web and command line clients, and
+    you will update to new versions using standard developer commands.
+
+    This method is recommended for users with a bit of experience using
+    the `git` and `pip` tools.
+
+3. [Manual Installation](INSTALL_MANUAL.md)
+
+    In this method you will manually run the commands needed to install
+    InvokeAI and its dependencies. We offer two recipes: one suited to
+    those who prefer the `conda` tool, and one suited to those who prefer
+    `pip` and Python virtual environments.
+
+    This method is recommended for users who have previously used `conda`
+    or `pip` in the past, developers, and anyone who wishes to remain on
+    the cutting edge of future InvokeAI development and is willing to put
+    up with occasional glitches and breakage.
+
+4. [Docker Installation](INSTALL_DOCKER.md)
+
+    We also offer a method for creating Docker containers containing
+    InvokeAI and its dependencies. This method is recommended for
+    individuals with experience with Docker containers and understand
+    the pluses and minuses of a container-based install.
+
+5. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)
+
+    This method is suitable for running InvokeAI on a Google Colab
+    account. It is recommended for individuals who have previously
+    worked on the Colab and are comfortable with the Jupyter notebook
+    environment.

docs/installation/INSTALLING_MODELS.md

@@ -56,7 +56,7 @@ unofficial Stable Diffusion models and where they can be obtained.
 
 There are three ways to install weights files:
 
-1. During InvokeAI installation, the `configure_invokeai.py` script can download
+1. During InvokeAI installation, the `preload_models.py` script can download
    them for you.
 
 2. You can use the command-line interface (CLI) to import, configure and modify
@@ -65,13 +65,13 @@ There are three ways to install weights files:
 3. You can download the files manually and add the appropriate entries to
    `models.yaml`.
 
-### Installation via `configure_invokeai.py`
+### Installation via `preload_models.py`
 
-This is the most automatic way. Run `scripts/configure_invokeai.py` from the
+This is the most automatic way. Run `scripts/preload_models.py` from the
 console. It will ask you to select which models to download and lead you through
 the steps of setting up a Hugging Face account if you haven't done so already.
 
-To start, run `python scripts/configure_invokeai.py` from within the InvokeAI:
+To start, run `python scripts/preload_models.py` from within the InvokeAI:
 directory
 
 !!! example ""
@@ -162,12 +162,6 @@ 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:
 
@@ -244,7 +238,7 @@ arabian-nights-1.0:
 | arabian-nights-1.0 | This is the name of the model that you will refer to from within the CLI and the WebGUI when you need to load and use the model.                                                                                                                                                                                                                                                                                                                                                                                                  |
 | description        | Any description that you want to add to the model to remind you what it is.                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
 | weights            | Relative path to the .ckpt weights file for this model.                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
-| config             | This is the confusingly-named configuration file for the model itself. Use `./configs/stable-diffusion/v1-inference.yaml` unless the model happens to need a custom configuration, in which case the place you downloaded it from will tell you what to use instead. For example, the runwayML custom inpainting model requires the file `configs/stable-diffusion/v1-inpainting-inference.yaml`. This is already inclued in the InvokeAI distribution and is configured automatically for you by the `configure_invokeai.py` script. |
+| config             | This is the confusingly-named configuration file for the model itself. Use `./configs/stable-diffusion/v1-inference.yaml` unless the model happens to need a custom configuration, in which case the place you downloaded it from will tell you what to use instead. For example, the runwayML custom inpainting model requires the file `configs/stable-diffusion/v1-inpainting-inference.yaml`. This is already inclued in the InvokeAI distribution and is configured automatically for you by the `preload_models.py` script. |
 | vae                | If you want to add a VAE file to the model, then enter its path here.                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
 | width, height      | This is the width and height of the images used to train the model. Currently they are always 512 and 512.                                                                                                                                                                                                                                                                                                                                                                                                                        |
 

docs/installation/INSTALL_1CLICK.md

@@ -0,0 +1,164 @@
+---
+title: The "One-Click" Installer
+---
+
+## Introduction
+
+The one-click 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, MacOSX or Windows.
+
+Before you begin, make sure that you meet the [hardware
+requirements](index.md#Hardware_Requirements) and has the appropriate
+GPU drivers installed. In particular, if you are a Linux user with an
+AMD GPU installed, you may need to install the [ROCm
+driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
+
+Installation requires roughly 18G of free disk space to load the
+libraries and recommended model weights files.
+
+## Walk through
+
+Though there are multiple steps, there really is only one click
+involved to kick off the process.
+
+1. The 1-click installer is distributed in ZIP files. Download the one
+that is appropriate for your operating system:
+
+  !!! todo "Change the URLs after release"
+  
+    - [invokeAI-mac.zip](https://github.com/invoke-ai/InvokeAI/releases/download/2.1.3-rc1/invokeAI-mac.zip)
+    - [invokeAI-linux.zip](https://github.com/invoke-ai/InvokeAI/releases/download/2.1.3-rc1/invokeAI-linux.zip)
+    - [invokeAI-windows.zip](https://github.com/invoke-ai/InvokeAI/releases/download/2.1.3-rc1/invokeAI-windows.zip)
+
+2. Unpack the zip file into a directory that has at least 18G of free
+   space. Do *not* unpack into a directory that has an earlier version of
+   InvokeAI.
+
+   This will create a new directory named "InvokeAI". This example
+   shows how this would look using the `unzip` command-line tool,
+   but you may use any graphical or command-line Zip extractor:
+   
+   ```bash
+   C:\Documents\Linco> unzip invokeAI-windows.zip
+   Archive:  C: \Linco\Downloads\invokeAI-linux.zip
+   creating: invokeAI\
+   inflating: invokeAI\install.bat
+   inflating: invokeAI\readme.txt     
+   ```
+
+3. 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, form the command line, run the shell script or .bat
+   file:
+
+   ```bash
+   C:\Documents\Linco> cd invokeAI
+   C:\Documents\Linco> install.bat
+   ```
+
+5. 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.
+
+6. After installation completes, the installer will launch a script
+   called `preload_models.py`, which will guide you through the
+   first-time process of selecting one or more Stable Diffusion model
+   weights files, downloading and configuring them.
+
+   Note that the main Stable Diffusion weights file is protected by a
+   license agreement that you must agree to in order to use. The
+   script will list the steps you need to take to create an account on
+   the official site that hosts the weights files, accept the
+   agreement, and provide an access token that allows InvokeAI to
+   legally download and install the weights files.
+
+   If you have already downloaded the weights file(s) for another
+   Stable Diffusion distribution, you may skip this step (by selecting
+   "skip" when prompted) and configure InvokeAI to use the
+   previously-downloaded files. The process for this is described in
+   [INSTALLING_MODELS.md].
+
+ 7. 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:
+
+   ```bash
+   C:\Documents\Linco\invokeAI> cd invokeAI
+   C:\Documents\Linco\invokeAI> invoke.bat
+   ```
+
+   The `invoke.bat` (`invoke.sh`) script will give you the choice of
+   starting (1) the command-line interface, or (2) the web GUI. If you
+   start the latter, you can load the user interface by pointing your
+   browser at http://localhost:9090.
+
+   The `invoke` script also offers you a third option labeled "open
+   the developer console". If you choose this option, you will be
+   dropped into a command-line interface in which you can run python
+   commands directly, access developer tools, and launch InvokeAI
+   with customized options. To do the latter, you would launch the
+   script `scripts/invoke.py` as shown in this example:
+
+   ```bash
+   python scripts\invoke.py --web --max_load_models=3 \
+       --model=waifu-1.3 --steps=30 --outdir=C:/Documents/AIPhotos
+   ```
+
+   These options are described in detail in the [Command-Line
+   Interface](../features/CLI.md) documentation.
+
+## Updating to newer versions
+
+This section describes how to update InvokeAI to new versions of the
+software.
+
+### Updating the stable version
+
+This distribution is changing rapidly, and we add new features on a
+daily basis. To update to the latest released version (recommended),
+run the `update.sh` (Linux/Mac) or `update.bat` (Windows)
+scripts. This will fetch the latest release and re-run the
+`preload_models` script to download any updated models files that may
+be needed. You can also use this to add additional models that you did
+not select at installation time.
+
+### Updating to the development version
+
+There may be times that there is a feature in the `development` branch
+of InvokeAI that you'd like to take advantage of. Or perhaps there is
+a branch that corrects an annoying bug. To do this, you will use the
+developer's console.
+
+From within the invokeAI directory, run the command `invoke.sh`
+(Linux/Mac) or `invoke.bat` (Windows) and selection option (3) to open
+the developers console. Then run the following command to get the
+`development branch`:
+
+```bash
+git checkout development
+git pull
+conda env update
+```
+
+You can now close the developer console and run `invoke` as before.
+If you get complaints about missing models, then you may need to do
+the additional step of running `preload_models.py`. This happens
+relatively infrequently. To do this, simply open up the developer's
+console again and type `python scripts/preload_models.py`.
+
+## Troubleshooting
+
+If you run into problems during or after installation, the InvokeAI
+team is available to help you. Either create an
+[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub
+site, or make a request for help on the "bugs-and-support" channel of
+our [Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100%
+volunteer organization, but typically somebody will be available to
+help you within 24 hours, and often much sooner.
+

docs/installation/INSTALL_AUTOMATED.md

@@ -1,315 +0,0 @@
----
-title: InvokeAI Automated Installation
----
-
-# InvokeAI Automated Installation
-
-## Introduction
-
-The automated 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.
-
-## Walk through
-
-1.  Make sure that your system meets the
-    [hardware requirements](../index.md#hardware-requirements) and has the
-    appropriate GPU drivers installed. In particular, if you are a Linux user
-    with an AMD GPU installed, you may need to install the
-    [ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
-
-    !!! info "Required Space"
-
-        Installation requires roughly 18G of free disk space to load the libraries and
-        recommended model weights files.
-
-2.  Check that your system has an up-to-date Python installed. To do this, open
-    up a command-line window ("Terminal" on Linux and Macintosh, "Command" or
-    "Powershell" on Windows) and type `python --version`. If Python is
-    installed, it will print out the version number. If it is version `3.9.1` or
-    higher, you meet requirements.
-
-    !!! warning "If you see an older version, or get a command not found error"
-
-        Go to [Python Downloads](https://www.python.org/downloads/) and
-        download the appropriate installer package for your platform. We recommend
-        [Version 3.10.9](https://www.python.org/downloads/release/python-3109/),
-        which has been extensively tested with InvokeAI.
-
-    !!! warning "At this time we do not recommend Python 3.11"
-
-    === "Windows users"
-
-        - During the Python configuration process,
-        Please look out for a checkbox to add Python to your PATH
-        and select it. If the install script complains that it can't
-        find python, then open the Python installer again and choose
-        "Modify" existing installation.
-
-        - There is a slight possibility that you will encountered
-        DLL load errors at the very end of the installation process. This is caused
-        by not having up to date Visual C++ redistributable libraries. If this
-        happens to you, you can install the C++ libraries from this site:
-        https://learn.microsoft.com/en-us/cpp/windows/deploying-native-desktop-applications-visual-cpp?view=msvc-170
-
-    === "Mac users"
-
-        - After installing Python, you may need to run the
-        following command from the Terminal in order to install the Web
-        certificates needed to download model data from https sites. If
-        you see lots of CERTIFICATE ERRORS during the last part of the
-        install, this is the problem, and you can fix it with this command:
-
-            `/Applications/Python\ 3.10/Install\ Certificates.command`
-
-        -  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/
-
-    === "Linux users"
-
-        - See [Installing Python in Ubuntu](#installing-python-in-ubuntu) for some
-        platform-specific tips.
-
-3.  The source installer is distributed in ZIP files. Go to the
-    [latest release](https://github.com/invoke-ai/InvokeAI/releases/latest), and
-    look for a series of files named:
-
-    - [InvokeAI-installer-2.2.4-mac.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/InvokeAI-installer-2.2.4-mac.zip)
-    - [InvokeAI-installer-2.2.4-windows.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/InvokeAI-installer-2.2.4-windows.zip)
-    - [InvokeAI-installer-2.2.4-linux.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/InvokeAI-installer-2.2.4-linux.zip)
-
-    Download the one that is appropriate for your operating system.
-
-4.  Unpack the zip file into a convenient directory. This will create a new
-    directory named "InvokeAI-Installer". This example shows how this would look
-    using the `unzip` command-line tool, but you may use any graphical or
-    command-line Zip extractor:
-
-    ```cmd
-    C:\Documents\Linco> unzip InvokeAI-installer-2.2.4-windows.zip
-    Archive:  C: \Linco\Downloads\InvokeAI-installer-2.2.4-windows.zip
-    creating: InvokeAI-Installer\
-    inflating: InvokeAI-Installer\install.bat
-    inflating: InvokeAI-Installer\readme.txt
-    ...
-    ```
-
-    After successful installation, you can delete the `InvokeAI-Installer`
-    directory.
-
-5.  **Windows only** Please double-click on the file WinLongPathsEnabled.reg and
-    accept the dialog box that asks you if you wish to modify your registry.
-    This activates long filename support on your system and will prevent
-    mysterious errors during installation.
-
-6.  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.
-
-    On Windows systems you will probably get an "Untrusted Publisher" warning.
-    Click on "More Info" and select "Run Anyway." You trust us, right?
-
-7.  Alternatively, from the command line, run the shell script or .bat file:
-
-    ```cmd
-    C:\Documents\Linco> cd InvokeAI-Installer
-    C:\Documents\Linco\invokeAI> install.bat
-    ```
-
-8.  The script will ask you to choose where to install InvokeAI. Select a
-    directory with at least 18G of free space for a full install. InvokeAI and
-    all its support files will be installed into a new directory named
-    `invokeai` located at the location you specify.
-
-    - The default is to install the `invokeai` directory in your home directory,
-      usually `C:\Users\YourName\invokeai` on Windows systems,
-      `/home/YourName/invokeai` on Linux systems, and `/Users/YourName/invokeai`
-      on Macintoshes, where "YourName" is your login name.
-
-    - The script uses tab autocompletion to suggest directory path completions.
-      Type part of the path (e.g. "C:\Users") and press ++tab++ repeatedly
-      to suggest completions.
-
-9.  Sit back and let the install script work. It will install the third-party
-    libraries needed by InvokeAI, then download the current InvokeAI release and
-    install it.
-
-    Be aware that some of the library download and install steps take a long
-    time. In particular, the `pytorch` package is quite large and often appears
-    to get "stuck" at 99.9%. Have patience and the installation step will
-    eventually resume. However, there are occasions when the library install
-    does legitimately get stuck. If you have been waiting for more than ten
-    minutes and nothing is happening, you can interrupt the script with ^C. You
-    may restart it and it will pick up where it left off.
-
-10. 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. We provide a list of popular models that InvokeAI
-    performs well with. However, you can add more weight files later on using
-    the command-line client or the Web UI. See
-    [Installing Models](INSTALLING_MODELS.md) for details.
-
-    Note that the main Stable Diffusion weights file is protected by a license
-    agreement that you must agree to in order to use. The script will list the
-    steps you need to take to create an account on the official site that hosts
-    the weights files, accept the agreement, and provide an access token that
-    allows InvokeAI to legally download and install the weights files.
-
-    If you have already downloaded the weights file(s) for another Stable
-    Diffusion distribution, you may skip this step (by selecting "skip" when
-    prompted) and configure InvokeAI to use the previously-downloaded files. The
-    process for this is described in [Installing Models](INSTALLING_MODELS.md).
-
-11. The script will now exit and you'll be ready to generate some images. Look
-    for the directory `invokeai` installed in the location you chose at the
-    beginning of the install session. 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:
-
-    ```cmd
-    C:\Documents\Linco> cd invokeai
-    C:\Documents\Linco\invokeAI> invoke.bat
-    ```
-
-    - The `invoke.bat` (`invoke.sh`) script will give you the choice of starting
-      (1) the command-line interface, or (2) the web GUI. If you start the
-      latter, you can load the user interface by pointing your browser at
-      http://localhost:9090.
-
-    - The script also offers you a third option labeled "open the developer
-      console". If you choose this option, you will be dropped into a
-      command-line interface in which you can run python commands directly,
-      access developer tools, and launch InvokeAI with customized options.
-
-12. You can launch InvokeAI with several different command-line arguments that
-    customize its behavior. For example, you can change the location of the
-    inage output directory, or select your favorite sampler. See the
-    [Command-Line Interface](../features/CLI.md) for a full list of the options.
-
-        - To set defaults that will take effect every time you launch InvokeAI,
-        use a text editor (e.g. Notepad) to exit the file
-        `invokeai\invokeai.init`. It contains a variety of examples that you can
-        follow to add and modify launch options.
-
-!!! warning "The `invokeai` directory contains the `invoke` application, its
-configuration files, the model weight files, and outputs of image generation.
-Once InvokeAI is installed, do not move or remove this directory."
-
-## Troubleshooting
-
-### _Package dependency conflicts_
-
-If you have previously installed InvokeAI or another Stable Diffusion package,
-the installer may occasionally pick up outdated libraries and either the
-installer or `invoke` will fail with complaints about library conflicts. You can
-address this by entering the `invokeai` directory and running `update.sh`, which
-will bring InvokeAI up to date with the latest libraries.
-
-### ldm from pypi
-
-!!! warning
-
-    Some users have tried to correct dependency problems by installing
-    the `ldm` package from PyPi.org. Unfortunately this is an unrelated package that
-    has nothing to do with the 'latent diffusion model' used by InvokeAI. Installing
-    ldm will make matters worse. If you've installed ldm, uninstall it with
-    `pip uninstall ldm`.
-
-### Corrupted configuration file
-
-Everything seems to install ok, but `invoke` complains of a corrupted
-configuration file and goes back into the configuration process (asking you to
-download models, etc), but this doesn't fix the problem.
-
-This issue is often caused by a misconfigured configuration directive in the
-`invokeai\invokeai.init` initialization file that contains startup settings. The
-easiest way to fix the problem is to move the file out of the way and re-run
-`configure_invokeai.py`. Enter the developer's console (option 3 of the launcher
-script) and run this command:
-
-```cmd
-configure_invokeai.py --root=.
-```
-
-Note the dot (.) after `--root`. It is part of the command.
-
-_If none of these maneuvers fixes the problem_ then please report the problem to
-the [InvokeAI Issues](https://github.com/invoke-ai/InvokeAI/issues) section, or
-visit our [Discord Server](https://discord.gg/ZmtBAhwWhy) for interactive
-assistance.
-
-### other problems
-
-If you run into problems during or after installation, the InvokeAI team is
-available to help you. Either create an
-[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
-make a request for help on the "bugs-and-support" channel of our
-[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
-organization, but typically somebody will be available to help you within 24
-hours, and often much sooner.
-
-## Updating to newer versions
-
-This distribution is changing rapidly, and we add new features on a daily basis.
-To update to the latest released version (recommended), run the `update.sh`
-(Linux/Mac) or `update.bat` (Windows) scripts. This will fetch the latest
-release and re-run the `configure_invokeai` script to download any updated
-models files that may be needed. You can also use this to add additional models
-that you did not select at installation time.
-
-You can now close the developer console and run `invoke` as before. If you get
-complaints about missing models, then you may need to do the additional step of
-running `configure_invokeai.py`. This happens relatively infrequently. To do
-this, simply open up the developer's console again and type
-`python scripts/configure_invokeai.py`.
-
-You may also use the `update` script to install any selected version of
-InvokeAI. From https://github.com/invoke-ai/InvokeAI, navigate to the zip file
-link of the version you wish to install. You can find the zip links by going to
-the one of the release pages and looking for the **Assets** section at the
-bottom. Alternatively, you can browse "branches" and "tags" at the top of the
-big code directory on the InvokeAI welcome page. When you find the version you
-want to install, go to the green "<> Code" button at the top, and copy the
-"Download ZIP" link.
-
-Now run `update.sh` (or `update.bat`) with the URL of the desired InvokeAI
-version as its argument. For example, this will install the old 2.2.0 release.
-
-```cmd
-update.sh https://github.com/invoke-ai/InvokeAI/archive/refs/tags/v2.2.0.zip
-```
-
-## Installing Python in Ubuntu
-
-For reasons that are not entirely clear, installing the correct version of
-Python can be a bit of a challenge on Ubuntu, Linux Mint, and other
-Ubuntu-derived distributions.
-
-In particular, Ubuntu version 20.04 LTS comes with an old version of Python,
-does not come with the PIP package manager installed, and to make matters worse,
-the `python` command points to Python2, not Python3.
-
-Here is the quick recipe for bringing your system up to date:
-
-```
-sudo apt update
-sudo apt install python3.9
-sudo apt install python3-pip
-cd /usr/bin
-sudo ln -sf python3.9 python3
-sudo ln -sf python3 python
-```
-
-You can still access older versions of Python by calling `python2`, `python3.8`,
-etc.

docs/installation/INSTALL_DOCKER.md

@@ -4,21 +4,12 @@ title: Docker
 
 # :fontawesome-brands-docker: Docker
 
-!!! warning "For end users"
+## Before you begin
 
-    We highly recommend to Install InvokeAI locally using [these instructions](index.md)
-
-!!! tip "For developers"
-
-    For container-related development tasks or for enabling easy
-    deployment to other environments (on-premises or cloud), follow these
-    instructions.
-
-    For general use, install locally to leverage your machine's GPU.
-
-!!! tip "For running on a cloud instance/service"
-
-    Check out the [Running InvokeAI in the cloud with Docker](#running-invokeai-in-the-cloud-with-docker) section below
+- For end users: Install InvokeAI locally using the instructions for your OS.
+- For developers: For container-related development tasks or for enabling easy
+  deployment to other environments (on-premises or cloud), follow these
+  instructions. For general use, install locally to leverage your machine's GPU.
 
 ## Why containers?
 
@@ -40,25 +31,22 @@ development purposes it's fine. Once you're done with development tasks on your
 laptop you can build for the target platform and architecture and deploy to
 another environment with NVIDIA GPUs on-premises or in the cloud.
 
-## Installation in a Linux container (desktop)
+## Installation on a Linux container
 
 ### Prerequisites
 
 #### Install [Docker](https://github.com/santisbon/guides#docker)
 
-On the [Docker Desktop app](https://docs.docker.com/get-docker/), go to
-Preferences, Resources, Advanced. Increase the CPUs and Memory to avoid this
+On the Docker Desktop app, go to Preferences, Resources, Advanced. Increase the
+CPUs and Memory to avoid this
 [Issue](https://github.com/invoke-ai/InvokeAI/issues/342). You may need to
 increase Swap and Disk image size too.
 
 #### Get a Huggingface-Token
 
-Besides the Docker Agent you will need an Account on
-[huggingface.co](https://huggingface.co/join).
-
-After you succesfully registered your account, go to
-[huggingface.co/settings/tokens](https://huggingface.co/settings/tokens), create
-a token and copy it, since you will need in for the next step.
+Go to [Hugging Face](https://huggingface.co/settings/tokens), create a token and
+temporary place it somewhere like a open texteditor window (but dont save it!,
+only keep it open, we need it in the next step)
 
 ### Setup
 
@@ -76,19 +64,14 @@ created in the last step.
 
 Some Suggestions of variables you may want to change besides the Token:
 
-<figure markdown>
-
-| Environment-Variable | Default value                 | Description                                                                                  |
-| -------------------- | ----------------------------- | -------------------------------------------------------------------------------------------- |
-| `HUGGINGFACE_TOKEN`  | No default, but **required**! | This is the only **required** variable, without it you can't download the huggingface models |
-| `PROJECT_NAME`       | `invokeai`                    | affects the project folder, tag- and volume name                                             |
-| `VOLUMENAME`         | `${PROJECT_NAME}_data`        | Name of the Docker Volume where model files will be stored                                   |
-| `ARCH`               | `x86_64`                      | can be changed to f.e. aarch64 if you are using a ARM based CPU                              |
-| `INVOKEAI_TAG`       | `${PROJECT_NAME}:${ARCH}`     | the Container Repository / Tag which will be used                                            |
-| `PIP_REQUIREMENTS`   | `requirements-lin-cuda.txt`   | the requirements file to use (from `environments-and-requirements`)                          |
-| `INVOKE_DOCKERFILE`  | `docker-build/Dockerfile`     | the Dockerfile which should be built, handy for development                                  |
-
-</figure>
+| Environment-Variable      | Default value                 | Description                                                                  |
+| ------------------------- | ----------------------------- | ---------------------------------------------------------------------------- |
+| `HUGGINGFACE_TOKEN`       | No default, but **required**! | This is the only **required** variable, without you can't get the checkpoint |
+| `ARCH`                    | x86_64                        | if you are using a ARM based CPU                                             |
+| `INVOKEAI_TAG`            | invokeai-x86_64               | the Container Repository / Tag which will be used                            |
+| `INVOKEAI_CONDA_ENV_FILE` | environment-lin-cuda.yml      | since environment.yml wouldn't work with aarch                               |
+| `INVOKEAI_GIT`            | invoke-ai/InvokeAI            | the repository to use                                                        |
+| `INVOKEAI_BRANCH`         | main                          | the branch to checkout                                                       |
 
 #### Build the Image
 
@@ -111,104 +94,25 @@ After the build process is done, you can run the container via the provided
 ./docker-build/run.sh
 ```
 
-When used without arguments, the container will start the webserver and provide
+When used without arguments, the container will start the website and provide
 you the link to open it. But if you want to use some other parameters you can
 also do so.
 
-!!! example "run script example"
+!!! example
 
     ```bash
-    ./docker-build/run.sh "banana sushi" -Ak_lms -S42 -s10
+    docker-build/run.sh --from_file tests/validate_pr_prompt.txt
     ```
 
-    This would generate the legendary "banana sushi" with Seed 42, k_lms Sampler and 10 steps.
+    The output folder is located on the volume which is also used to store the model.
 
-    Find out more about available CLI-Parameters at [features/CLI.md](../../features/CLI/#arguments)
-
----
-
-## Running InvokeAI in the cloud with Docker
-
-We offer an optimized Ubuntu-based image that has been well-tested in cloud deployments. Note: it also works well locally on Linux x86_64 systems with an Nvidia GPU. It *may* also work on Windows under WSL2 and on Intel Mac (not tested).
-
-An advantage of this method is that it does not need any local setup or additional dependencies.
-
-See the `docker-build/Dockerfile.cloud` file to familizarize yourself with the image's content.
-
-### Prerequisites
-
-- a `docker` runtime
-- `make` (optional but helps for convenience)
-- Huggingface token to download models, or an existing InvokeAI runtime directory from a previous installation
-
- Neither local Python nor any dependencies are required. If you don't have `make` (part of `build-essentials` on Ubuntu), or do not wish to install it, the commands from the `docker-build/Makefile` are readily adaptable to be executed directly.
-
-### Building and running the image locally
-
-1. Clone this repo and `cd docker-build`
-1. `make build` - this will build the image. (This does *not* require a GPU-capable system).
-1. _(skip this step if you already have a complete InvokeAI runtime directory)_
-    - `make configure` (This does *not* require a GPU-capable system)
-    - this will create a local cache of models and configs (a.k.a the _runtime dir_)
-    - enter your Huggingface token when prompted
-1. `make web`
-1. Open the `http://localhost:9090` URL in your browser, and enjoy the banana sushi!
-
-To use InvokeAI on the cli, run `make cli`. To open a Bash shell in the container for arbitraty advanced use, `make shell`.
-
-#### Building and running without `make`
-
-(Feel free to adapt paths such as `${HOME}/invokeai` to your liking, and modify the CLI arguments as necessary).
-
-!!! example "Build the image and configure the runtime directory"
-    ```Shell
-    cd docker-build
-
-    DOCKER_BUILDKIT=1 docker build -t local/invokeai:latest -f Dockerfile.cloud ..
-
-    docker run --rm -it -v ${HOME}/invokeai:/mnt/invokeai local/invokeai:latest -c "python scripts/configure_invokeai.py"
-    ```
-
-!!! example "Run the web server"
-    ```Shell
-    docker run --runtime=nvidia --gpus=all --rm -it -v ${HOME}/invokeai:/mnt/invokeai -p9090:9090 local/invokeai:latest
-    ```
-
-    Access the Web UI at http://localhost:9090
-
-!!! example "Run the InvokeAI interactive CLI"
-    ```
-    docker run --runtime=nvidia --gpus=all --rm -it -v ${HOME}/invokeai:/mnt/invokeai local/invokeai:latest -c "python scripts/invoke.py"
-    ```
-
-### Running the image in the cloud
-
-This image works anywhere you can run a container with a mounted Docker volume. You may either build this image on a cloud instance, or build and push it to your Docker registry. To manually run this on a cloud instance (such as AWS EC2, GCP or Azure VM):
-
-1. build this image either in the cloud (you'll need to pull the repo), or locally
-1. `docker tag` it as `your-registry/invokeai` and push to your registry (i.e. Dockerhub)
-1. `docker pull` it on your cloud instance
-1. configure the runtime directory as per above example, using `docker run ... configure_invokeai.py` script
-1. use either one of the `docker run` commands above, substituting the image name for your own image.
-
-To run this on Runpod, please refer to the following Runpod template: https://www.runpod.io/console/gpu-secure-cloud?template=vm19ukkycf (you need a Runpod subscription). When launching the template, feel free to set the image to pull your own build.
-
-The template's `README` provides ample detail, but at a high level, the process is as follows:
-
-1. create a pod using this Docker image
-1. ensure the pod has an `INVOKEAI_ROOT=<path_to_your_persistent_volume>` environment variable, and that it corresponds to the path to your pod's persistent volume mount
-1. Run the pod with `sleep infinity` as the Docker command
-1. Use Runpod basic SSH to connect to the pod, and run `python scripts/configure_invokeai.py` script
-1. Stop the pod, and change the Docker command to `python scripts/invoke.py --web --host 0.0.0.0`
-1. Run the pod again, connect to your pod on HTTP port 9090, and enjoy the banana sushi!
-
-Running on other cloud providers such as Vast.ai will likely work in a similar fashion.
+    Find out more about available CLI-Parameter at [features/CLI.md](../features/CLI.md)
 
 ---
 
 !!! warning "Deprecated"
 
-    From here on you will find the the previous Docker-Docs, which will still
+    From here on you will find the rest of the previous Docker-Docs, which will still
     provide some usefull informations.
 
 ## Usage (time to have fun)
@@ -218,12 +122,12 @@ Running on other cloud providers such as Vast.ai will likely work in a similar f
 If you're on a **Linux container** the `invoke` script is **automatically
 started** and the output dir set to the Docker volume you created earlier.
 
-If you're **directly on macOS follow these startup instructions**.
+If you're **directly on macOS follow these startup instructions**.  
 With the Conda environment activated (`conda activate ldm`), run the interactive
 interface that combines the functionality of the original scripts `txt2img` and
-`img2img`:
+`img2img`:  
 Use the more accurate but VRAM-intensive full precision math because
-half-precision requires autocast and won't work.
+half-precision requires autocast and won't work.  
 By default the images are saved in `outputs/img-samples/`.
 
 ```Shell
@@ -240,8 +144,8 @@ invoke> q
 ### Text to Image
 
 For quick (but bad) image results test with 5 steps (default 50) and 1 sample
-image. This will let you know that everything is set up correctly.
-Then increase steps to 100 or more for good (but slower) results.
+image. This will let you know that everything is set up correctly.  
+Then increase steps to 100 or more for good (but slower) results.  
 The prompt can be in quotes or not.
 
 ```Shell
@@ -255,8 +159,8 @@ You'll need to experiment to see if face restoration is making it better or
 worse for your specific prompt.
 
 If you're on a container the output is set to the Docker volume. You can copy it
-wherever you want.
-You can download it from the Docker Desktop app, Volumes, my-vol, data.
+wherever you want.  
+You can download it from the Docker Desktop app, Volumes, my-vol, data.  
 Or you can copy it from your Mac terminal. Keep in mind `docker cp` can't expand
 `*.png` so you'll need to specify the image file name.
 

docs/installation/INSTALL_INVOKE.md

@@ -1,64 +0,0 @@
----
-title: InvokeAI Binary Installer
----
-
-The InvokeAI binary installer is a shell script that will install InvokeAI onto a stock
-computer running recent versions of Linux, MacOSX or Windows. It will leave you
-with a version that runs a stable version of InvokeAI. When a new version of
-InvokeAI is released, you will download and reinstall the new version.
-
-If you wish to tinker with unreleased versions of InvokeAI that introduce
-potentially unstable new features, you should consider using the
-[source installer](INSTALL_SOURCE.md) or one of the
-[manual install](INSTALL_MANUAL.md) methods.
-
-**Important Caveats**
-  - This script does not support AMD GPUs. For Linux AMD support,
-    please use the manual or source code installer methods.
-
-  - This script has difficulty on some Macintosh machines
-    that have previously been used for Python development due to
-    conflicting development tools versions. Mac developers may wish
-    to try the source code installer or one of the manual methods instead.
-
-!!! todo
-
-    Before you begin, make sure that you meet
-    the[hardware requirements](/#hardware-requirements) and has the
-    appropriate GPU drivers installed. In particular, if you are a Linux user with
-    an AMD GPU installed, you may need to install the
-    [ROCm-driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
-
-Installation requires roughly 18G of free disk space to load the libraries and
-recommended model weights files.
-
-## Steps to Install
-
-1. Download the
-   [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,
-   and have full permissions (i.e. `~/` on Lin/Mac; your home folder on Windows)
-
-3. Extract the 'InvokeAI' folder from the downloaded package
-
-4. Open the extracted 'InvokeAI' folder
-
-5. Double-click 'install.bat' (Windows), or 'install.sh' (Lin/Mac) (or run from
-   a terminal)
-
-6. Follow the prompts
-
-7. After installation, please run the 'invoke.bat' file (on Windows) or
-   'invoke.sh' file (on Linux/Mac) to start InvokeAI.
-
-## Troubleshooting
-
-If you run into problems during or after installation, the InvokeAI team is
-available to help you. Either create an
-[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
-make a request for help on the "bugs-and-support" channel of our
-[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
-organization, but typically somebody will be available to help you within 24
-hours, and often much sooner.

docs/installation/INSTALL_JUPYTER.md

@@ -2,31 +2,27 @@
 title: Running InvokeAI on Google Colab using a Jupyter Notebook
 ---
 
+# THIS NEEDS TO BE FLESHED OUT
+
 ## Introduction
 
 We have a [Jupyter
-notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
+notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable-Diffusion-local-Windows.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 installed)/Jupyter/JupyterLab and
 start running the cells one-by-one.
 
-!!! Note "you will need NVIDIA drivers, Python 3.10, and Git installed beforehand"
+Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehand.
 
-## Running Online On Google Colabotary
-[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
 
-## Running Locally (Cloning)
+## Walkthrough
 
-1. Install the Jupyter Notebook python library (one-time):
-pip install jupyter
+## Updating to newer versions
 
-2. Clone the InvokeAI repository:
-git clone https://github.com/invoke-ai/InvokeAI.git
-cd invoke-ai
-3. Create a virtual environment using conda:
-conda create -n invoke jupyter
-4. Activate the environment and start the Jupyter notebook:
-conda activate invoke
-jupyter notebook
+### Updating the stable version
+
+### Updating to the development version
+
+## Troubleshooting

docs/installation/INSTALL_MANUAL.md

@@ -2,54 +2,51 @@
 title: Manual Installation
 ---
 
-<figure markdown>
-# :fontawesome-brands-linux: Linux | :fontawesome-brands-apple: macOS | :fontawesome-brands-windows: Windows
-</figure>
-
-!!! warning "This is for advanced Users"
-
-    who are already experienced with using conda or pip
+# :fontawesome-brands-linux: Linux
+# :fontawesome-brands-apple: macOS
+# :fontawesome-brands-windows: Windows
 
 ## Introduction
 
-You have two choices for manual installation, the [first one](#Conda_method)
-based on the Anaconda3 package manager (`conda`), and
-[a second one](#PIP_method) which uses basic Python virtual environment (`venv`)
-commands and the PIP package manager. Both methods require you to enter commands
-on the terminal, also known as the "console".
+You have two choices for manual installation, the [first
+one](#Conda_method) based on the Anaconda3 package manager (`conda`),
+and [a second one](#PIP_method) which uses basic Python virtual
+environment (`venv`) commands and the PIP package manager. Both
+methods require you to enter commands on the command-line shell, also
+known as the "console".
 
 On Windows systems you are encouraged to install and use the
 [Powershell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell-on-windows?view=powershell-7.3),
-which provides compatibility with Linux and Mac shells and nice features such as
-command-line completion.
+which provides compatibility with Linux and Mac shells and nice
+features such as command-line completion.
 
 ### Conda method
 
-1.  Check that your system meets the
-    [hardware requirements](index.md#Hardware_Requirements) and has the
-    appropriate GPU drivers installed. In particular, if you are a Linux user
-    with an AMD GPU installed, you may need to install the
-    [ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
+1. Check that your system meets the [hardware
+requirements](index.md#Hardware_Requirements) and has the appropriate
+GPU drivers installed. In particular, if you are a Linux user with an
+AMD GPU installed, you may need to install the [ROCm
+driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
 
-    InvokeAI does not yet support Windows machines with AMD GPUs due to the lack
-    of ROCm driver support on this platform.
+InvokeAI does not yet support Windows machines with AMD GPUs due to
+the lack of ROCm driver support on this platform.
 
-    To confirm that the appropriate drivers are installed, run `nvidia-smi` on
-    NVIDIA/CUDA systems, and `rocm-smi` on AMD systems. These should return
-    information about the installed video card.
+To confirm that the appropriate drivers are installed, run
+`nvidia-smi` on NVIDIA/CUDA systems, and `rocm-smi` on AMD
+systems. These should return information about the installed video
+card.
 
-    Macintosh users with MPS acceleration, or anybody with a CPU-only system,
-    can skip this step.
+Macintosh users with MPS acceleration, or anybody with a CPU-only
+system, can skip this step.
 
-2.  You will need to install Anaconda3 and Git if they are not already
-    available. Use your operating system's preferred package manager, or
-    download the installers manually. You can find them here:
+2. You will need to install Anaconda3 and Git if they are not already
+available. Use your operating system's preferred installer, or
+download installers from the following URLs
 
-    - [Anaconda3](https://www.anaconda.com/)
-    - [git](https://git-scm.com/downloads)
+    - Anaconda3 (https://www.anaconda.com/)
+    - git (https://git-scm.com/downloads)
 
-3.  Clone the [InvokeAI](https://github.com/invoke-ai/InvokeAI) source code from
-    GitHub:
+3.  Copy the InvokeAI source code from GitHub using `git`:
 
     ```bash
     git clone https://github.com/invoke-ai/InvokeAI.git
@@ -58,158 +55,122 @@ command-line completion.
     This will create InvokeAI folder where you will follow the rest of the
     steps.
 
-4.  Enter the newly-created InvokeAI folder:
+3.  Enter the newly-created InvokeAI folder. From this step forward make sure
+    that you are working in the InvokeAI directory!
 
     ```bash
     cd InvokeAI
     ```
+4.  Select the appropriate environment file:
 
-    From this step forward make sure that you are working in the InvokeAI
-    directory!
-
-5.  Select the appropriate environment file:
-
-    We have created a series of environment files suited for different operating
-    systems and GPU hardware. They are located in the
+    We have created a series of environment files suited for different
+    operating systems and GPU hardware. They are located in the
     `environments-and-requirements` directory:
 
-    <figure markdown>
+    ```bash
+    environment-lin-amd.yml     # Linux with an AMD (ROCm) GPU
+    environment-lin-cuda.yml    # Linux with an NVIDIA CUDA GPU
+    environment-mac.yml         # Macintoshes with MPS acceleration
+    environment-win-cuda.yml    # Windows with an NVIDA CUDA GPU
+    ```
 
-    |         filename         |               OS               |
-    | :----------------------: | :----------------------------: |
-    | environment-lin-amd.yml  |  Linux with an AMD (ROCm) GPU  |
-    | environment-lin-cuda.yml | Linux with an NVIDIA CUDA GPU  |
-    | environment-mac.yml    |   Macintosh            |
-    | environment-win-cuda.yml | Windows with an NVIDA CUDA GPU |
+    Select the appropriate environment file, and make a link to it
+    from `environment.yml` in the top-level InvokeAI directory. The
+    command to do this from the top-level directory is:
 
-    </figure>
-
-    Choose the appropriate environment file for your system and link or copy it
-    to `environment.yml` in InvokeAI's top-level directory. To do so, run
-    following command from the repository-root:
-
-    !!! Example ""
-
-        === "Macintosh and Linux"
-
-            !!! todo "Replace `xxx` and `yyy` with the appropriate OS and GPU codes as seen in the table above"
-
-            ```bash
-            ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
-            ```
-
-            When this is done, confirm that a file `environment.yml` has been linked in
-            the InvokeAI root directory and that it points to the correct file in the
-            `environments-and-requirements`.
-
-            ```bash
-            ls -la
-            ```
-
-        === "Windows"
-
-            !!! todo " Since it requires admin privileges to create links, we will use the copy command to create your `environment.yml`"
-
-            ```cmd
-            copy environments-and-requirements\environment-win-cuda.yml environment.yml
-            ```
-
-            Afterwards verify that the file `environment.yml` has been created, either via the
-            explorer or by using the command `dir` from the terminal
-
-            ```cmd
-            dir
-            ```
-
-    !!! warning "Do not try to run conda on directly on the subdirectory environments file. This won't work. Instead, copy or link it to the top-level directory as shown."    
+    !!! todo "Macintosh and Linux"
     
-6.  Create the conda environment:
+       ```bash
+       ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
+       ```
 
-    ```bash
-    conda env update
-    ```
+       Replace `xxx` and `yyy` with the appropriate OS and GPU codes.
 
-    This will create a new environment named `invokeai` and install all InvokeAI
-    dependencies into it. If something goes wrong you should take a look at
-    [troubleshooting](#troubleshooting).
+    !!! todo "Windows requires admin privileges to make links, so we use the copy (cp) command"
+    
+       ```bash
+       cp environments-and-requirements\environment-win-cuda.yml environment.yml 
+       ```
 
-7.  Activate the `invokeai` environment:
+    When this is done, confirm that a file `environment.yml` has been created in
+    the InvokeAI root directory and that it points to the correct file in the
+    `environments-and-requirements`.
 
-    In order to use the newly created environment you will first need to
-    activate it
+4. Run conda:
 
-    ```bash
-    conda activate invokeai
-    ```
+   ```bash
+   conda env update
+   ```
 
-    Your command-line prompt should change to indicate that `invokeai` is active
-    by prepending `(invokeai)`.
+   This will create a new environment named `invokeai` and install all
+   InvokeAI dependencies into it.
 
-8.  Pre-Load the model weights files:
+   If something goes wrong at this point, see
+   [troubleshooting](#Troubleshooting).
 
-    !!! tip
+5. Activate the `invokeai` environment:
 
-        If you have already downloaded the weights file(s) for another Stable
-        Diffusion distribution, you may skip this step (by selecting "skip" when
-        prompted) and configure InvokeAI to use the previously-downloaded files. The
-        process for this is described in [here](INSTALLING_MODELS.md).
+   ```bash
+   conda activate invokeai
+   ```
 
-    ```bash
-    python scripts/configure_invokeai.py
-    ```
+   Your command-line prompt should change to indicate that `invokeai` is active.
 
-    The script `configure_invokeai.py` will interactively guide you through the
-    process of downloading and installing the weights files needed for InvokeAI.
-    Note that the main Stable Diffusion weights file is protected by a license
-    agreement that you have to agree to. The script will list the steps you need
-    to take to create an account on the site that hosts the weights files,
-    accept the agreement, and provide an access token that allows InvokeAI to
-    legally download and install the weights files.
+6. Load the model weights files:
 
-    If you get an error message about a module not being installed, check that
-    the `invokeai` environment is active and if not, repeat step 5.
+   ```bash
+   python scripts/preload_models.py
+   ```
 
-9.  Run the command-line- or the web- interface:
+   (Windows users should use the backslash instead of the slash)
 
-    !!! example ""
+   The script `preload_models.py` will interactively guide you through
+   downloading and installing the weights files needed for
+   InvokeAI. Note that the main Stable Diffusion weights file is
+   protected by a license agreement that you have to agree to. The
+   script will list the steps you need to take to create an account on
+   the site that hosts the weights files, accept the agreement, and
+   provide an access token that allows InvokeAI to legally download
+   and install the weights files.
 
-        !!! warning "Make sure that the conda environment is activated, which should create `(invokeai)` in front of your prompt!"
+   If you have already downloaded the weights file(s) for another
+   Stable Diffusion distribution, you may skip this step (by selecting
+   "skip" when prompted) and configure InvokeAI to use the
+   previously-downloaded files. The process for this is described in
+   [INSTALLING_MODELS.md].
 
-        === "CLI"
+   If you get an error message about a module not being installed,
+   check that the `invokeai` environment is active and if not, repeat
+   step 5.
 
-            ```bash
-            python scripts/invoke.py
-            ```
+7. Run the command-line interface or the web interface:
 
-        === "local Webserver"
+   ```bash
+   python scripts/invoke.py         # command line
+   python scripts/invoke.py --web   # web interface
+   ```
 
-            ```bash
-            python scripts/invoke.py --web
-            ```
+   (Windows users replace backslash with forward slash)
+   
+   If you choose the run the web interface, point your browser at
+   http://localhost:9090 in order to load the GUI.
 
-        === "Public Webserver"
+8. Render away!
 
-            ```bash
-            python scripts/invoke.py --web --host 0.0.0.0
-            ```
+   Browse the features listed in the [Stable Diffusion Toolkit
+   Docs](https://invoke-ai.git) to learn about all the things you can
+   do with InvokeAI.
 
-        If you choose the run the web interface, point your browser at
-        http://localhost:9090 in order to load the GUI.
+   Note that some GPUs are slow to warm up. In particular, when using
+   an AMD card with the ROCm driver, you may have to wait for over a
+   minute the first time you try to generate an image. Fortunately, after
+   the warm up period rendering will be fast.
 
-10. Render away!
-
-    Browse the [features](../features/CLI.md) section to learn about all the things you
-    can do with InvokeAI.
-
-    Note that some GPUs are slow to warm up. In particular, when using an AMD
-    card with the ROCm driver, you may have to wait for over a minute the first
-    time you try to generate an image. Fortunately, after the warm up period
-    rendering will be fast.
-
-11. Subsequently, to relaunch the script, be sure to run "conda activate
-    invokeai", enter the `InvokeAI` directory, and then launch the invoke
-    script. If you forget to activate the 'invokeai' environment, the script
-    will fail with multiple `ModuleNotFound` errors.
+9. Subsequently, to relaunch the script, be sure to run "conda
+   activate invokeai", enter the `InvokeAI` directory, and then launch
+   the invoke script. If you forget to activate the 'invokeai'
+   environment, the script will fail with multiple `ModuleNotFound`
+   errors.
 
 ## Updating to newer versions of the script
 
@@ -220,210 +181,188 @@ greatest version, launch the Anaconda window, enter `InvokeAI` and type:
 ```bash
 git pull
 conda env update
-python scripts/configure_invokeai.py --no-interactive  #optional
+python scripts/preload_models.py --no-interactive  #optional
 ```
 
-This will bring your local copy into sync with the remote one. The last step may
-be needed to take advantage of new features or released models. The
-`--no-interactive` flag will prevent the script from prompting you to download
-the big Stable Diffusion weights files.
+This will bring your local copy into sync with the remote one. The
+last step may be needed to take advantage of new features or released
+models. The `--no-interactive` flag will prevent the script from
+prompting you to download the big Stable Diffusion weights files.
 
 ## pip Install
 
-To install InvokeAI with only the PIP package manager, please follow these
-steps:
+To install InvokeAI with only the PIP package manager, please follow
+these steps:
 
-1.  Make sure you are using Python 3.9 or higher. The rest of the install
-    procedure depends on this:
+1. Make sure you are using Python 3.9 or higher. The rest of the install
+   procedure depends on this:
 
-    ```bash
-    python -V
-    ```
+   ```bash
+   python -V
+   ```
 
-2.  Install the `virtualenv` tool if you don't have it already:
+2. Install the `virtualenv` tool if you don't have it already:
+   ```bash
+   pip install virtualenv
+   ```
 
-    ```bash
-    pip install virtualenv
-    ```
+3. From within the InvokeAI top-level directory, create and activate a
+   virtual environment named `invokeai`:
 
-3.  From within the InvokeAI top-level directory, create and activate a virtual
-    environment named `invokeai`:
+   ```bash
+   virtualenv invokeai
+   source invokeai/bin/activate
+   ```
 
-    ```bash
-    virtualenv invokeai
-    source invokeai/bin/activate
-    ```
+4. Pick the correct `requirements*.txt` file for your hardware and
+operating system.
 
-4.  Pick the correct `requirements*.txt` file for your hardware and operating
-    system.
-
-    We have created a series of environment files suited for different operating
-    systems and GPU hardware. They are located in the
+    We have created a series of environment files suited for different
+    operating systems and GPU hardware. They are located in the
     `environments-and-requirements` directory:
 
-    <figure markdown>
-
-    |              filename               |                               OS                                |
-    | :---------------------------------: | :-------------------------------------------------------------: |
-    |      requirements-lin-amd.txt       |                  Linux with an AMD (ROCm) GPU                   |
-    |     requirements-lin-arm64.txt      |                 Linux running on arm64 systems                  |
-    |      requirements-lin-cuda.txt      |                 Linux with an NVIDIA (CUDA) GPU                 |
-    |    requirements-mac-mps-cpu.txt     |                Macintoshes with MPS acceleration                |
-    | requirements-lin-win-colab-cuda.txt | Windows with an NVIDA (CUDA) GPU<br>(supports Google Colab too) |
-
-    </figure>
-
-    Select the appropriate requirements file, and make a link to it from
-    `requirements.txt` in the top-level InvokeAI directory. The command to do
-    this from the top-level directory is:
-
-    !!! example ""
-
-        === "Macintosh and Linux"
-
-            !!! info "Replace `xxx` and `yyy` with the appropriate OS and GPU codes."
-
-            ```bash
-            ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
-            ```
-
-        === "Windows"
-
-            !!! info "on Windows, admin privileges are required to make links, so we use the copy command instead"
-
-            ```cmd
-            copy environments-and-requirements\requirements-lin-win-colab-cuda.txt requirements.txt
-            ```
-
-        !!! warning
-
-            Please do not link or copy `environments-and-requirements/requirements-base.txt`.
-            This is a base requirements file that does not have the platform-specific
-            libraries. Also, be sure to link or copy the platform-specific file to
-	    a top-level file named `requirements.txt` as shown here. Running pip on
-	    a requirements file in a subdirectory will not work as expected.
-
-    When this is done, confirm that a file named `requirements.txt` has been
-    created in the InvokeAI root directory and that it points to the correct
-    file in `environments-and-requirements`.
-
-5.  Run PIP
-
-    Be sure that the `invokeai` environment is active before doing this:
-
     ```bash
-    pip install --prefer-binary -r requirements.txt
+    requirements-lin-amd.txt                # Linux with an AMD (ROCm) GPU
+    requirements-lin-arm64.txt              # Linux running on arm64 systems
+    requirements-lin-cuda.txt               # Linux with an NVIDIA (CUDA) GPU
+    requirements-mac-mps-cpu.txt            # Macintoshes with MPS acceleration
+    requirements-lin-win-colab-cuda.txt     # Windows with an NVIDA (CUDA) GPU
+                                            #    (supports Google Colab too)
     ```
 
----
+    Select the appropriate requirements file, and make a link to it
+    from `environment.txt` in the top-level InvokeAI directory. The
+    command to do this from the top-level directory is:
+
+    !!! todo "Macintosh and Linux"
+    
+       ```bash
+       ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
+       ```
+
+    Replace `xxx` and `yyy` with the appropriate OS and GPU codes.
+
+    !!! todo "Windows requires admin privileges to make links, so we use the copy (cp) command instead"
+    
+       ```bash
+       cp environments-and-requirements\requirements-lin-win-colab-cuda.txt requirements.txt
+       ```
+
+    Note that the order of arguments is reversed between the Linux/Mac and Windows
+    commands!
+
+    Please do not link directly to the file
+    `environments-and-requirements/requirements.txt`. This is a base requirements
+    file that does not have the platform-specific libraries.
+
+    When this is done, confirm that a file `requirements.txt` has been
+    created in the InvokeAI root directory and that it points to the
+    correct file in the `environments-and-requirements`.
+
+5. Run PIP
+
+   Be sure that the `invokeai` environment is active before doing
+   this:
+
+   ```bash
+   pip install --prefer-binary -r requirements.txt
+   ```
 
 ## Troubleshooting
 
 Here are some common issues and their suggested solutions.
 
-### Conda
+### Conda install
 
-#### Conda fails before completing `conda update`
+1. Conda fails before completing `conda update`:
 
-The usual source of these errors is a package incompatibility. While we have
-tried to minimize these, over time packages get updated and sometimes introduce
-incompatibilities.
+   The usual source of these errors is a package
+   incompatibility. While we have tried to minimize these, over time
+   packages get updated and sometimes introduce incompatibilities.
 
-We suggest that you search
-[Issues](https://github.com/invoke-ai/InvokeAI/issues) or the "bugs-and-support"
-channel of the [InvokeAI Discord](https://discord.gg/ZmtBAhwWhy).
+   We suggest that you search
+   [Issues](https://github.com/invoke-ai/InvokeAI/issues) or the
+   "bugs-and-support" channel of the [InvokeAI
+   Discord](https://discord.gg/ZmtBAhwWhy).
 
-You may also try to install the broken packages manually using PIP. To do this,
-activate the `invokeai` environment, and run `pip install` with the name and
-version of the package that is causing the incompatibility. For example:
+   You may also try to install the broken packages manually using PIP. To do this, activate
+   the `invokeai` environment, and run `pip install` with the name and version of the
+   package that is causing the incompatibility. For example:
 
-```bash
-pip install test-tube==0.7.5
-```
+   ```bash
+   pip install test-tube==0.7.5
+   ```
 
-You can keep doing this until all requirements are satisfied and the `invoke.py`
-script runs without errors. Please report to
-[Issues](https://github.com/invoke-ai/InvokeAI/issues) what you were able to do
-to work around the problem so that others can benefit from your investigation.
+   You can keep doing this until all requirements are satisfied and
+   the `invoke.py` script runs without errors. Please report to
+   [Issues](https://github.com/invoke-ai/InvokeAI/issues) what you
+   were able to do to work around the problem so that others can
+   benefit from your investigation.
 
-### Create Conda Environment fails on MacOS
+2. `preload_models.py` or `invoke.py` crashes at an early stage
 
-If conda create environment fails with lmdb error, this is most likely caused by Clang.
-Run brew config to see which Clang is installed on your Mac. If Clang isn't installed, that's causing the error.
-Start by installing additional XCode command line tools, followed by brew install llvm.
+   This is usually due to an incomplete or corrupted Conda install.
+   Make sure you have linked to the correct environment file and run
+   `conda update` again.
 
-```bash
-xcode-select --install
-brew install llvm
-```
+   If the problem persists, a more extreme measure is to clear Conda's
+   caches and remove the `invokeai` environment:
 
-If brew config has Clang installed, update to the latest llvm and try creating the environment again.
+   ```bash
+   conda deactivate
+   conda env remove -n invokeai
+   conda clean -a
+   conda update
+   ```
 
-#### `configure_invokeai.py` or `invoke.py` crashes at an early stage
+   This removes all cached library files, including ones that may have
+   been corrupted somehow. (This is not supposed to happen, but does
+   anyway).
+   
+3. `invoke.py` crashes at a later stage.
 
-This is usually due to an incomplete or corrupted Conda install. Make sure you
-have linked to the correct environment file and run `conda update` again.
+   If the CLI or web site had been working ok, but something
+   unexpected happens later on during the session, you've encountered
+   a code bug that is probably unrelated to an install issue. Please
+   search [Issues](https://github.com/invoke-ai/InvokeAI/issues), file
+   a bug report, or ask for help on [Discord](https://discord.gg/ZmtBAhwWhy)
 
-If the problem persists, a more extreme measure is to clear Conda's caches and
-remove the `invokeai` environment:
+4. My renders are running very slowly!
 
-```bash
-conda deactivate
-conda env remove -n invokeai
-conda clean -a
-conda update
-```
+   You may have installed the wrong torch (machine learning) package,
+   and the system is running on CPU rather than the GPU. To check,
+   look at the log messages that appear when `invoke.py` is first
+   starting up. One of the earlier lines should say `Using device type
+   cuda`. On AMD systems, it will also say "cuda", and on Macintoshes,
+   it should say "mps". If instead the message says it is running on
+   "cpu", then you may need to install the correct torch library.
 
-This removes all cached library files, including ones that may have been
-corrupted somehow. (This is not supposed to happen, but does anyway).
+   You may be able to fix this by installing a different torch
+   library. Here are the magic incantations for Conda and PIP.
 
-#### `invoke.py` crashes at a later stage
+   !!! todo "For CUDA systems"
 
-If the CLI or web site had been working ok, but something unexpected happens
-later on during the session, you've encountered a code bug that is probably
-unrelated to an install issue. Please search
-[Issues](https://github.com/invoke-ai/InvokeAI/issues), file a bug report, or
-ask for help on [Discord](https://discord.gg/ZmtBAhwWhy)
+   (conda)
+   ```bash
+   conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
+   ```
 
-#### My renders are running very slowly
+   (pip)
+   ```bash
+   pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
+   ```
 
-You may have installed the wrong torch (machine learning) package, and the
-system is running on CPU rather than the GPU. To check, look at the log messages
-that appear when `invoke.py` is first starting up. One of the earlier lines
-should say `Using device type cuda`. On AMD systems, it will also say "cuda",
-and on Macintoshes, it should say "mps". If instead the message says it is
-running on "cpu", then you may need to install the correct torch library.
+   !!! todo "For AMD systems"
 
-You may be able to fix this by installing a different torch library. Here are
-the magic incantations for Conda and PIP.
+   (conda)
+   ```bash
+   conda activate invokeai
+   pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
+   ```
 
-!!! todo "For CUDA systems"
+   (pip)
+   ```bash
+   pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
+   ```
 
-    - conda
-
-      ```bash
-      conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
-      ```
-
-    - pip
-
-      ```bash
-      pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
-      ```
-
-!!! todo "For AMD systems"
-
-    - conda
-
-      ```bash
-      conda activate invokeai
-      pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
-      ```
-
-    - pip
-
-      ```bash
-      pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
-      ```
-
-More information and troubleshooting tips can be found at https://pytorch.org.
+   More information and troubleshooting tips can be found at https://pytorch.org.

docs/installation/INSTALL_PATCHMATCH.md

@@ -1,115 +0,0 @@
----
-title: Installing PyPatchMatch
----
-
-# :octicons-paintbrush-16: Installing PyPatchMatch
-
-pypatchmatch is a Python module for inpainting images. It is not
-needed to run InvokeAI, but it greatly improves the quality of
-inpainting and outpainting and is recommended.
-
-Unfortunately, it is a C++ optimized module and installation
-can be somewhat challenging. This guide leads you through the steps.
-
-## Windows
-
-You're in luck! On Windows platforms PyPatchMatch will install
-automatically on Windows systems with no extra intervention.
-
-## Macintosh
-
-PyPatchMatch is not currently supported, but the team is working on
-it.
-
-## Linux
-
-Prior to installing PyPatchMatch, you need to take the following
-steps:
-
-### Debian Based Distros
-
-
-1. Install the `build-essential` tools:
-
-   ```
-   sudo apt update
-   sudo apt install build-essential
-   ```
-
-2. Install `opencv`:
-
-   ```
-   sudo apt install python3-opencv libopencv-dev
-   ```
-
-3. Fix the naming of the `opencv` package configuration file:
-
-   ```
-   cd /usr/lib/x86_64-linux-gnu/pkgconfig/
-   ln -sf opencv4.pc opencv.pc
-   ```
-
-4. Activate the environment you use for invokeai, either with
-`conda` or with a virtual environment.
-
-5. Do a "develop" install of pypatchmatch:
-
-   ```
-   pip install "git+https://github.com/invoke-ai/PyPatchMatch@0.1.3#egg=pypatchmatch"
-   ```
-
-6. Confirm that pypatchmatch is installed.
-   At the command-line prompt enter `python`, and
-   then at the `>>>` line type `from patchmatch import patch_match`:
-   It should look like the follwing:
-
-   ```
-   Python 3.9.5 (default, Nov 23 2021, 15:27:38) 
-   [GCC 9.3.0] on linux
-   Type "help", "copyright", "credits" or "license" for more information.
-   >>> from patchmatch import patch_match
-   Compiling and loading c extensions from "/home/lstein/Projects/InvokeAI/.invokeai-env/src/pypatchmatch/patchmatch".
-   rm -rf build/obj libpatchmatch.so
-   mkdir: created directory 'build/obj'
-   mkdir: created directory 'build/obj/csrc/'
-   [dep] csrc/masked_image.cpp ...
-   [dep] csrc/nnf.cpp ...
-   [dep] csrc/inpaint.cpp ...
-   [dep] csrc/pyinterface.cpp ...
-   [CC] csrc/pyinterface.cpp ...
-   [CC] csrc/inpaint.cpp ...
-   [CC] csrc/nnf.cpp ...
-   [CC] csrc/masked_image.cpp ...
-   [link] libpatchmatch.so ...
-   ```
-
-
-### Arch Based Distros
-
-1. Install the `base-devel` package:
-   ```
-   sudo pacman -Syu
-   sudo pacman -S --needed base-devel
-   ```
-
-2. Install `opencv`:
-   ```
-   sudo pacman -S opencv
-   ```
-   or for CUDA support
-   ```
-   sudo pacman -S opencv-cuda
-   ```
-
-3. Fix the naming of the `opencv` package configuration file:
-   ```
-   cd /usr/lib/pkgconfig/
-   ln -sf opencv4.pc opencv.pc
-   ```
-
-**Next, Follow Steps 4-6 from the Debian Section above**
-
-
-If you see no errors, then you're ready to go!
-
-

docs/installation/INSTALL_SOURCE.md

@@ -1,225 +0,0 @@
----
-title: Source Installer
----
-
-# The InvokeAI Source Installer
-
-## Introduction
-
-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.
-
-Before you begin, make sure that you meet the
-[hardware requirements](index.md#Hardware_Requirements) and has the appropriate
-GPU drivers installed. In particular, if you are a Linux user with an AMD GPU
-installed, you may need to install the
-[ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
-
-Installation requires roughly 18G of free disk space to load the libraries and
-recommended model weights files.
-
-## Walk through
-
-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/latest), and
-    look for a series of files named:
-
-    - [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-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-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.
-
-2.  Unpack the zip file into a directory that has at least 18G of free space. Do
-    _not_ unpack into a directory that has an earlier version of InvokeAI.
-
-    This will create a new directory named "InvokeAI". This example shows how
-    this would look using the `unzip` command-line tool, but you may use any
-    graphical or command-line Zip extractor:
-
-    ```cmd
-    C:\Documents\Linco> unzip invokeAI-windows.zip
-    Archive:  C: \Linco\Downloads\invokeAI-linux.zip
-    creating: invokeAI\
-    inflating: invokeAI\install.bat
-    inflating: invokeAI\readme.txt
-    ```
-
-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.
-
-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
-    ```
-
-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.
-
-    Be aware that some of the library download and install steps take a long time.
-    In particular, the `pytorch` package is quite large and often appears to get
-    "stuck" at 99.9%. Similarly, the `pip installing requirements` step may
-    appear to hang. Have patience and the installation step will eventually
-    resume. However, there are occasions when the library install does
-    legitimately get stuck. If you have been waiting for more than ten minutes
-    and nothing is happening, you can interrupt the script with ^C. You may restart
-    it and it will pick up where it left off.
-
-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.
-
-    Note that the main Stable Diffusion weights file is protected by a license
-    agreement that you must agree to in order to use. The script will list the
-    steps you need to take to create an account on the official site that hosts
-    the weights files, accept the agreement, and provide an access token that
-    allows InvokeAI to legally download and install the weights files.
-
-    If you have already downloaded the weights file(s) for another Stable
-    Diffusion distribution, you may skip this step (by selecting "skip" when
-    prompted) and configure InvokeAI to use the previously-downloaded files. The
-    process for this is described in [Installing Models](INSTALLING_MODELS.md).
-
-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:
-
-    ```cmd
-    C:\Documents\Linco> cd invokeAI
-    C:\Documents\Linco\invokeAI> invoke.bat
-    ```
-
-The `invoke.bat` (`invoke.sh`) script will give you the choice of starting (1)
-the command-line interface, or (2) the web GUI. If you start the latter, you can
-load the user interface by pointing your browser at http://localhost:9090.
-
-The `invoke` script also offers you a third option labeled "open the developer
-console". If you choose this option, you will be dropped into a command-line
-interface in which you can run python commands directly, access developer tools,
-and launch InvokeAI with customized options. To do the latter, you would launch
-the script `scripts/invoke.py` as shown in this example:
-
-```cmd
-python scripts/invoke.py --web --max_load_models=3 \
-    --model=waifu-1.3 --steps=30 --outdir=C:/Documents/AIPhotos
-```
-
-These options are described in detail in the
-[Command-Line Interface](../features/CLI.md) documentation.
-
-## Troubleshooting
-
-_Package dependency conflicts_ If you have previously installed
-InvokeAI or another Stable Diffusion package, the installer may
-occasionally pick up outdated libraries and either the installer or
-`invoke` will fail with complaints out library conflicts. There are
-two steps you can take to clear this problem. Both of these are done
-from within the "developer's console", which you can get to by
-launching `invoke.sh` (or `invoke.bat`) and selecting launch option
-#3:
-
-1. Remove the previous `invokeai` environment completely. From within
-   the developer's console, give the command `conda env remove -n
-   invokeai`. This will delete previous files installed by `invoke`.
-
-   Then exit from the developer's console and launch the script
-   `update.sh` (or `update.bat`). This will download the most recent
-   InvokeAI (including bug fixes) and reinstall the environment.
-   You should then be able to run `invoke.sh`/`invoke.bat`.
-
-2. If this doesn't work, you can try cleaning your system's conda
-   cache. This is slightly more extreme, but won't interfere with
-   any other python-based programs installed on your computer.
-   From the developer's console, run the command `conda clean -a`
-   and answer "yes" to all prompts.
-
-   After this is done, run `update.sh` and try again as before.
-
-_"Corrupted configuration file."__ Everything seems to install ok, but
-`invoke` complains of a corrupted configuration file and goes calls
-`configure_invokeai.py` to fix, but this doesn't fix the problem.
-
-This issue is often caused by a misconfigured configuration directive
-in the `.invokeai` initialization file that contains startup settings.
-This can be corrected by fixing the offending line.
-
-First find `.invokeai`. It is a small text file located in your home
-directory, `~/.invokeai` on Mac and Linux systems, and `C:\Users\*your
-name*\.invokeai` on Windows systems. Open it with a text editor
-(e.g. Notepad on Windows, TextEdit on Macs, or `nano` on Linux)
-and look for the lines starting with `--root` and `--outdir`.
-
-An example is here:
-
-```cmd
---root="/home/lstein/invokeai"
---outdir="/home/lstein/invokeai/outputs"
-```
-
-There should not be whitespace before or after the directory paths,
-and the paths should not end with slashes:
-
-```cmd
---root="/home/lstein/invokeai "     # wrong! no whitespace here
---root="/home\lstein\invokeai\"     # wrong! shouldn't end in a slash
-```
-
-Fix the problem with your text editor and save as a **plain text**
-file. This should clear the issue.
-
-_If none of these maneuvers fixes the problem_ then please report the
-problem to the [InvokeAI
-Issues](https://github.com/invoke-ai/InvokeAI/issues) section, or
-visit our [Discord Server](https://discord.gg/ZmtBAhwWhy) for interactive assistance.
-
-## Updating to newer versions
-
-This section describes how to update InvokeAI to new versions of the software.
-
-### Updating the stable version
-
-This distribution is changing rapidly, and we add new features on a daily basis.
-To update to the latest released version (recommended), run the `update.sh`
-(Linux/Mac) or `update.bat` (Windows) scripts. This will fetch the latest
-release and re-run the `configure_invokeai` script to download any updated models
-files that may be needed. You can also use this to add additional models that
-you did not select at installation time.
-
-You can now close the developer console and run `invoke` as before. If you get
-complaints about missing models, then you may need to do the additional step of
-running `configure_invokeai.py`. This happens relatively infrequently. To do this,
-simply open up the developer's console again and type
-`python scripts/configure_invokeai.py`.
-
-## Troubleshooting
-
-If you run into problems during or after installation, the InvokeAI team is
-available to help you. Either create an
-[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
-make a request for help on the "bugs-and-support" channel of our
-[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
-organization, but typically somebody will be available to help you within 24
-hours, and often much sooner.

docs/installation/index.md

@@ -1,34 +0,0 @@
----
-title: Overview
----
-
-We offer several ways to install InvokeAI, each one suited to your
-experience and preferences.
-
-1.  [Automated Installer](INSTALL_AUTOMATED.md)
-
-    This is a script that will install all of InvokeAI's essential
-    third party libraries and InvokeAI itself. It includes access to a
-    "developer console" which will help us debug problems with you and
-    give you to access experimental features.
-
-2. [Manual Installation](INSTALL_MANUAL.md)
-
-    In this method you will manually run the commands needed to install
-    InvokeAI and its dependencies. We offer two recipes: one suited to
-    those who prefer the `conda` tool, and one suited to those who prefer
-    `pip` and Python virtual environments. In our hands the pip install
-    is faster and more reliable, but your mileage may vary.
-
-    This method is recommended for users who have previously used `conda`
-    or `pip` in the past, developers, and anyone who wishes to remain on
-    the cutting edge of future InvokeAI development and is willing to put
-    up with occasional glitches and breakage.
-
-3. [Docker Installation](INSTALL_DOCKER.md)
-
-    We also offer a method for creating Docker containers containing
-    InvokeAI and its dependencies. This method is recommended for
-    individuals with experience with Docker containers and understand
-    the pluses and minuses of a container-based install.
-

docs/installation/older_docs_to_be_removed/INSTALL_LINUX.md

@@ -69,7 +69,7 @@ title: Manual Installation, Linux
     machine-learning models:
 
     ```bash
-    (invokeai) ~/InvokeAI$ python3 scripts/configure_invokeai.py
+    (invokeai) ~/InvokeAI$ python3 scripts/preload_models.py
     ```
 
     !!! note
@@ -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](../INSTALL_MANUAL.md) for a manual process for doing
+        Please look [here](INSTALLING_MODELS.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

@@ -111,7 +111,7 @@ will do our best to help.
 
 !!! todo "Download the model weight files"
 
-    The `configure_invokeai.py` script downloads and installs the model weight
+    The `preload_models.py` script downloads and installs the model weight
     files for you. It will lead you through the process of getting a Hugging Face
     account, accepting the Stable Diffusion model weight license agreement, and
     creating a download token:
@@ -119,7 +119,7 @@ will do our best to help.
     ```bash
     # This will take some time, depending on the speed of your internet connection
     # and will consume about 10GB of space
-    python scripts/configure_invokeai.py
+    python scripts/preload_models.py
     ```
 
 !!! todo "Run InvokeAI!"
@@ -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`.
 
 ---
@@ -220,8 +220,8 @@ There are several causes of these errors:
    with "(invokeai)" then you activated it. If it begins with "(base)" or
    something else you haven't.
 
-2. You might've run `./scripts/configure_invokeai.py` or `./scripts/invoke.py`
-   instead of `python ./scripts/configure_invokeai.py` or
+2. You might've run `./scripts/preload_models.py` or `./scripts/invoke.py`
+   instead of `python ./scripts/preload_models.py` or
    `python ./scripts/invoke.py`. The cause of this error is long so it's below.
 
     <!-- I could not find out where the error is, otherwise would have marked it as a footnote -->
@@ -359,7 +359,7 @@ python ./scripts/txt2img.py \
 ### OSError: Can't load tokenizer for 'openai/clip-vit-large-patch14'
 
 ```bash
-python scripts/configure_invokeai.py
+python scripts/preload_models.py
 ```
 
 ---

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_AI_Notebook.ipynb)
+[Jupyter notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable-Diffusion-local-Windows.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
@@ -65,7 +65,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
 7. Load the big stable diffusion weights files and a couple of smaller machine-learning models:
 
     ```bash
-    python scripts/configure_invokeai.py
+    python scripts/preload_models.py
     ```
 
     !!! note
@@ -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](../INSTALL_MANUAL.md) for a manual process for doing the
+          Please look [here](INSTALLING_MODELS.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

@@ -13,19 +13,6 @@ We thank them for all of their time and hard work.
 
 - [Lincoln D. Stein](mailto:lincoln.stein@gmail.com)
 
-## **Current core team**
-
-* @lstein (Lincoln Stein) - Co-maintainer
-* @blessedcoolant - Co-maintainer
-* @hipsterusername (Kent Keirsey) - Product Manager
-* @psychedelicious - Web Team Leader
-* @Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
-* @damian0815 - Attention Systems and Gameplay Engineer
-* @mauwii (Matthias Wild) - Continuous integration and product maintenance engineer
-* @Netsvetaev (Artur Netsvetaev) - UI/UX Developer
-* @tildebyte - general gadfly and resident (self-appointed) know-it-all
-* @keturn - Lead for Diffusers port
-
 ## **Contributions by**
 
 - [Sean McLellan](https://github.com/Oceanswave)

environments-and-requirements/environment-lin-aarch64.yml

@@ -2,7 +2,6 @@ name: invokeai
 channels:
   - pytorch
   - conda-forge
-  - defaults
 dependencies:
   - albumentations=0.4.3
   - cudatoolkit
@@ -32,15 +31,15 @@ dependencies:
   - pip:
       - dependency_injector==4.40.0
       - getpass_asterisk
+      - gfpgan
       - omegaconf==2.1.1
-      - picklescan
       - pyreadline3
       - realesrgan
       - taming-transformers-rom1504
       - test-tube>=0.7.5
       - git+https://github.com/openai/CLIP.git@main#egg=clip
       - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
-      - git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
-      - git+https://github.com/invoke-ai/GFPGAN@basicsr-1.4.2#egg=gfpgan
-      - git+https://github.com/invoke-ai/PyPatchMatch@0.1.4#egg=pypatchmatch
+      - git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
       - -e .
+variables:
+  PYTORCH_ENABLE_MPS_FALLBACK: 1

environments-and-requirements/environment-lin-amd.yml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=3.9.*
+  - python>=3.9
   - pip=22.2.2
   - numpy=1.23.3
   - pip:
@@ -18,12 +18,12 @@ dependencies:
     - flask_cors==3.0.10
     - flask_socketio==5.3.0
     - getpass_asterisk
+    - gfpgan
     - imageio-ffmpeg==0.4.2
     - imageio==2.9.0
     - kornia==0.6.0
     - omegaconf==2.2.3
     - opencv-python==4.5.5.64
-    - picklescan
     - pillow==9.2.0
     - pudb==2019.2
     - pyreadline3
@@ -33,7 +33,6 @@ dependencies:
     - streamlit==1.12.0
     - taming-transformers-rom1504
     - test-tube>=0.7.5
-    - tqdm
     - torch
     - torch-fidelity==0.3.0
     - torchaudio
@@ -41,8 +40,6 @@ dependencies:
     - torchvision
     - transformers==4.21.3
     - git+https://github.com/openai/CLIP.git@main#egg=clip
-    - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion
+    - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
     - git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
-    - git+https://github.com/invoke-ai/GFPGAN@basicsr-1.4.2#egg=gfpgan
-    - git+https://github.com/invoke-ai/PyPatchMatch@0.1.4#egg=pypatchmatch
     - -e .

environments-and-requirements/environment-lin-cuda.yml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=3.9.*
+  - python>=3.9
   - pip=22.2.2
   - numpy=1.23.3
   - torchvision=0.13.1
@@ -21,12 +21,12 @@ dependencies:
     - flask_cors==3.0.10
     - flask_socketio==5.3.0
     - getpass_asterisk
+    - gfpgan
     - imageio-ffmpeg==0.4.2
     - imageio==2.9.0
     - kornia==0.6.0
     - omegaconf==2.2.3
     - opencv-python==4.5.5.64
-    - picklescan
     - pillow==9.2.0
     - pudb==2019.2
     - pyreadline3
@@ -40,8 +40,6 @@ dependencies:
     - torchmetrics==0.7.0
     - transformers==4.21.3
     - git+https://github.com/openai/CLIP.git@main#egg=clip
-    - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion
-    - git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
-    - git+https://github.com/invoke-ai/GFPGAN@basicsr-1.4.2#egg=gfpgan
-    - git+https://github.com/invoke-ai/PyPatchMatch@0.1.4#egg=pypatchmatch
+    - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
+    - git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
     - -e .

environments-and-requirements/environment-mac.yml

@@ -2,64 +2,55 @@ name: invokeai
 channels:
   - pytorch
   - conda-forge
-  - defaults
 dependencies:
-  - python=3.10
-  - pip>=22.2
-  - pytorch=1.12
-  - pytorch-lightning=1.7
-  - torchvision=0.13
-  - torchmetrics=0.10
-  - torch-fidelity=0.3
+  - python=3.9.13
+  - pip=22.2.2
+  - pytorch=1.12.1
+  - torchvision=0.13.1
 
-  # I suggest to keep the other deps sorted for convenience.
-  # To determine what the latest versions should be, run:
-  #
-  # ```shell
-  # sed -E 's/invokeai/invokeai-updated/;20,99s/- ([^=]+)==.+/- \1/' environment-mac.yml > environment-mac-updated.yml
-  # CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac-updated.yml && conda list -n invokeai-updated | awk ' {print "  - " $1 "==" $2;} '
-  # ```
-
-  - albumentations=1.2
-  - coloredlogs=15.0
-  - diffusers=0.6
-  - einops=0.3
-  - eventlet
-  - grpcio=1.46
-  - flask=2.1
-  - flask-socketio=5.3
-  - flask-cors=3.0
+  - albumentations=1.2.1
+  - coloredlogs=15.0.1
+  - diffusers=0.6.0
+  - einops=0.4.1
+  - grpcio=1.46.4
   - humanfriendly=10.0
-  - imageio=2.21
-  - imageio-ffmpeg=0.4
-  - imgaug=0.4
-  - kornia=0.6
-  - mpmath=1.2
-  - nomkl=3
-  - numpy=1.23
-  - omegaconf=2.1
-  - openh264=2.3
-  - onnx=1.12
-  - onnxruntime=1.12
-  - pudb=2019.2
-  - protobuf=3.20
-  - py-opencv=4.6
-  - scipy=1.9
-  - streamlit=1.12
-  - sympy=1.10
-  - send2trash=1.8
-  - tensorboard=2.10
-  - transformers=4.23
+  - imageio=2.21.2
+  - imageio-ffmpeg=0.4.7
+  - imgaug=0.4.0
+  - kornia=0.6.7
+  - mpmath=1.2.1
+  - nomkl # arm64 has only 1.0 while x64 needs 3.0
+  - numpy=1.23.4
+  - omegaconf=2.1.1
+  - openh264=2.3.0
+  - onnx=1.12.0
+  - onnxruntime=1.12.1
+  - pudb=2022.1
+  - pytorch-lightning=1.7.7
+  - scipy=1.9.3
+  - streamlit=1.12.2
+  - sympy=1.10.1
+  - tensorboard=2.10.0
+  - torchmetrics=0.10.1
+  - py-opencv=4.6.0
+  - flask=2.1.3
+  - flask-socketio=5.3.0
+  - flask-cors=3.0.10
+  - eventlet=0.33.1
+  - protobuf=3.20.1
+  - send2trash=1.8.0
+  - transformers=4.23.1
+  - torch-fidelity=0.3.0
   - pip:
       - getpass_asterisk
-      - picklescan
+      - dependency_injector==4.40.0
+      - realesrgan==0.2.5.0
       - taming-transformers-rom1504
       - test-tube==0.7.5
       - git+https://github.com/openai/CLIP.git@main#egg=clip
-      - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion
-      - git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
-      - git+https://github.com/invoke-ai/GFPGAN@basicsr-1.4.2#egg=gfpgan
-      - git+https://github.com/invoke-ai/PyPatchMatch@0.1.4#egg=pypatchmatch
+      - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
+      - git+https://github.com/TencentARC/GFPGAN.git#egg=gfpgan
+      - git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg
       - -e .
 variables:
   PYTORCH_ENABLE_MPS_FALLBACK: 1

environments-and-requirements/environment-win-cuda.yml

@@ -4,7 +4,7 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=3.10.*
+  - python>=3.9
   - pip=22.2.2
   - numpy=1.23.3
   - torchvision=0.13.1
@@ -21,12 +21,12 @@ dependencies:
     - flask_cors==3.0.10
     - flask_socketio==5.3.0
     - getpass_asterisk
+    - gfpgan
     - imageio-ffmpeg==0.4.2
     - imageio==2.9.0
     - kornia==0.6.0
     - omegaconf==2.2.3
     - opencv-python==4.5.5.64
-    - picklescan
     - pillow==9.2.0
     - pudb==2019.2
     - pyreadline3
@@ -42,6 +42,4 @@ dependencies:
     - git+https://github.com/openai/CLIP.git@main#egg=clip
     - git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
     - git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg
-    - git+https://github.com/invoke-ai/GFPGAN@basicsr-1.4.1#egg=gfpgan
-    - git+https://github.com/invoke-ai/PyPatchMatch@0.1.4#egg=pypatchmatch
     - -e .

environments-and-requirements/requirements-base.txt

@@ -1,16 +1,15 @@
 # pip will resolve the version which matches torch
 albumentations
 dependency_injector==4.40.0
-diffusers==0.10.*
+diffusers
 einops
 eventlet
-facexlib
 flask==2.1.3
 flask_cors==3.0.10
 flask_socketio==5.3.0
-flaskwebgui==1.0.3
+flaskwebgui==0.3.7
 getpass_asterisk
-gfpgan==1.3.8
+gfpgan
 huggingface-hub
 imageio
 imageio-ffmpeg
@@ -18,23 +17,20 @@ kornia
 numpy
 omegaconf
 opencv-python
-picklescan
 pillow
 pip>=22
 pudb
 pyreadline3
 pytorch-lightning==1.7.7
 realesrgan
-requests==2.25.1
 scikit-image>=0.19
 send2trash
 streamlit
 taming-transformers-rom1504
-test-tube>=0.7.5
+test-tube
 torch-fidelity
 torchmetrics
-transformers==4.25.*
-https://github.com/Birch-san/k-diffusion/archive/refs/heads/mps.zip#egg=k-diffusion
-https://github.com/invoke-ai/PyPatchMatch/archive/refs/tags/0.1.4.zip#egg=pypatchmatch
-https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip#egg=clip
-https://github.com/invoke-ai/clipseg/archive/relaxed-python-requirement.zip#egg=clipseg
+transformers==4.21.*
+git+https://github.com/openai/CLIP.git@main#egg=clip
+git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion
+git+https://github.com/invoke-ai/clipseg.git@models-rename#egg=clipseg

environments-and-requirements/requirements-lin-amd.txt

@@ -1,5 +1,6 @@
 -r environments-and-requirements/requirements-base.txt
-# Get hardware-appropriate torch/torchvision
+
+# Get hardware-appropriate torch/torchvision 
 --extra-index-url https://download.pytorch.org/whl/rocm5.1.1 --trusted-host https://download.pytorch.org
 torch
 torchvision

environments-and-requirements/requirements-lin-cuda.txt

@@ -1,5 +1,2 @@
---extra-index-url https://download.pytorch.org/whl/cu116 --trusted-host https://download.pytorch.org
 -r environments-and-requirements/requirements-base.txt
-torch
-torchvision
 -e .

environments-and-requirements/requirements-mac-mps-cpu.txt

@@ -1,5 +1,5 @@
 -r environments-and-requirements/requirements-base.txt
-grpcio<1.51.0
+
 protobuf==3.19.6
 torch<1.13.0
 torchvision<0.14.0

environments-and-requirements/requirements-win-colab-cuda.txt

@@ -1,5 +1,6 @@
 -r environments-and-requirements/requirements-base.txt
-# Get hardware-appropriate torch/torchvision
+
+# Get hardware-appropriate torch/torchvision 
 --extra-index-url https://download.pytorch.org/whl/cu116 --trusted-host https://download.pytorch.org
 torch==1.12.1
 torchvision==0.13.1