Simple Installer for Unified Directory Structure, Initial Implementation (invoke-ai#1819)

* partially working simple installer

* works on linux

* fix linux requirements files

* read root environment variable in right place

* fix cat invokeai.init in test workflows

* fix classical cp error in test-invoke-pip.yml

* respect --root argument now

* untested bat installers added

* windows install.bat now working

fix logic to find frontend files

* rename simple_install to "installer"

1. simple_install => 'installer'
2. source and binary install directories are removed

* enable update scripts to update requirements

- Also pin requirements to known working commits.
- This may be a breaking change; exercise with caution
- No functional testing performed yet!

* update docs and installation requirements

NOTE: This may be a breaking commit! Due to the way the installer
works, I have to push to a public branch in order to do full end-to-end
testing.

- Updated installation docs, removing binary and source installers and
  substituting the "simple" unified installer.
- Pin requirements for the "http:" downloads to known working commits.
- Removed as much as possible the invoke-ai forks of others' repos.

* fix directory path for installer

* correct requirement/environment errors

* exclude zip files in .gitignore

* possible fix for dockerbuild

* ready for torture testing

- final Windows bat file tweaks
- copy environments-and-requirements to the runtime directory so that
  the `update.sh` script can run.

  This is not ideal, since we lose control over the
  requirements. Better for the update script to pull the proper
  updated requirements script from the repository.

* allow update.sh/update.bat to install arbitrary InvokeAI versions

- Can pass the zip file path to any InvokeAI release, branch, commit or tag,
  and the installer will try to install it.
- Updated documentation
- Added Linux Python install hints.

* use binary installer's :err_exit function

* user diffusers 0.10.0

* added logic for CPPFLAGS on mac

* improve windows install documentation

- added information on a couple of gotchas I experienced during
  windows installation, including DLL loading errors experienced
  when Visual Studio C++ Redistributable was not present.

* tagged to pull from 2.2.4-rc1

- also fix error of shell window closing immediately if suitable
  python not found

Co-authored-by: mauwii <[email protected]>

Author: lstein

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

@@ -114,9 +114,9 @@ jobs:
         run: |
           python scripts/configure_invokeai.py --no-interactive --yes
 
-      - name: cat ~/.invokeai
+      - name: cat invokeai.init
         id: cat-invokeai
-        run: cat ~/.invokeai
+        run: cat ${{ env.INVOKEAI_ROOT }}/invokeai.init
 
       - name: Run the tests
         id: run-tests

.gitignore

@@ -222,12 +222,11 @@ environment.yml
 requirements.txt
 
 # source installer files
-source_installer/*zip
-source_installer/invokeAI
-install.bat
-install.sh
-update.bat
-update.sh
+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

backend/invoke_ai_web_server.py

@@ -246,14 +246,16 @@ def upload():
 
     def find_frontend(self):
         my_dir = os.path.dirname(__file__)
-        for candidate in (os.path.join(my_dir,'..','frontend','dist'),         # pip install -e .
-                          os.path.join(my_dir,'../../../../frontend','dist')   # pip install .
+        # LS: setup.py seems to put the frontend in different places on different systems, so
+        # this is fragile and needs to be replaced with a better way of finding the front end.
+        for candidate in (os.path.join(my_dir,'..','frontend','dist'),          # pip install -e .
+                          os.path.join(my_dir,'../../../../frontend','dist'),   # pip install . (Linux, Mac)
+                          os.path.join(my_dir,'../../../frontend','dist'),      # pip install . (Windows)
         ):
             if os.path.exists(candidate):
                 return candidate
         assert "Frontend files cannot be found. Cannot continue"
 
-
     def setup_app(self):
         self.result_url = "outputs/"
         self.init_image_url = "outputs/init-images/"

binary_installer/create_installers.sh

@@ -2,10 +2,6 @@
 
 set -eu
 
-# ensure we're in the correct folder in case user's CWD is somewhere else
-scriptdir=$(dirname "$0")
-cd "$scriptdir"
-
 . .venv/bin/activate
 
 # set required env var for torch on mac MPS

binary_installer/invoke.sh.in

@@ -36,7 +36,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 
 COPY . .
 RUN --mount=type=cache,target=/root/.cache/pip \
-    cp binary_installer/py3.10-linux-x86_64-cuda-reqs.txt requirements.txt && \
+    cp environments-and-requirements/requirements-lin-cuda.txt requirements.txt && \
     pip install -r requirements.txt &&\
     pip install -e .
 

docker-build/Dockerfile.cloud

@@ -82,13 +82,18 @@ Mac and Linux machines, and runs on GPU cards with as little as 4 GB or RAM.
 
 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/)
+AMD card (using the ROCm driver).
+
+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).
+module. Instructions can be found at [Installing
+PyPatchMatch](installation/INSTALL_PATCHMATCH.md).
 
 ## :fontawesome-solid-computer: Hardware Requirements
 
@@ -100,26 +105,25 @@ You wil need one of the following:
 - :simple-amd: An AMD-based graphics card with 4 GB or more VRAM memory (Linux only)
 - :fontawesome-brands-apple: An Apple computer with an M1 chip.
 
-We do not recommend the GTX 1650 or 1660 series video cards. They are
-unable to run in half-precision mode and do not come with sufficient VRAM
-to render 512x512 images.
+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 12 GB of free disk space for the machine learning model, Python, and
+- At least 18 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: