mirror of
https://github.com/invoke-ai/InvokeAI
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Merge remote-tracking branch 'origin/main' into refactor/model_manager_instantiate
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commit
e3519052ae
25
flake.lock
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flake.lock
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{
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"nodes": {
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"nixpkgs": {
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"locked": {
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"lastModified": 1690630721,
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"narHash": "sha256-Y04onHyBQT4Erfr2fc82dbJTfXGYrf4V0ysLUYnPOP8=",
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"owner": "NixOS",
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"repo": "nixpkgs",
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"rev": "d2b52322f35597c62abf56de91b0236746b2a03d",
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"type": "github"
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},
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"original": {
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"id": "nixpkgs",
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"type": "indirect"
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}
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},
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"root": {
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"inputs": {
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"nixpkgs": "nixpkgs"
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}
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}
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},
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"root": "root",
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"version": 7
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}
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81
flake.nix
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flake.nix
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# Important note: this flake does not attempt to create a fully isolated, 'pure'
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# Python environment for InvokeAI. Instead, it depends on local invocations of
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# virtualenv/pip to install the required (binary) packages, most importantly the
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# prebuilt binary pytorch packages with CUDA support.
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# ML Python packages with CUDA support, like pytorch, are notoriously expensive
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# to compile so it's purposefuly not what this flake does.
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{
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description = "An (impure) flake to develop on InvokeAI.";
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outputs = { self, nixpkgs }:
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let
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system = "x86_64-linux";
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pkgs = import nixpkgs {
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inherit system;
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config.allowUnfree = true;
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};
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python = pkgs.python310;
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mkShell = { dir, install }:
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let
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setupScript = pkgs.writeScript "setup-invokai" ''
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# This must be sourced using 'source', not executed.
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${python}/bin/python -m venv ${dir}
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${dir}/bin/python -m pip install ${install}
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# ${dir}/bin/python -c 'import torch; assert(torch.cuda.is_available())'
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source ${dir}/bin/activate
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'';
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in
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pkgs.mkShell rec {
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buildInputs = with pkgs; [
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# Backend: graphics, CUDA.
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cudaPackages.cudnn
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cudaPackages.cuda_nvrtc
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cudatoolkit
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freeglut
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glib
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gperf
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procps
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libGL
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libGLU
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linuxPackages.nvidia_x11
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python
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stdenv.cc
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stdenv.cc.cc.lib
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xorg.libX11
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xorg.libXext
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xorg.libXi
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xorg.libXmu
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xorg.libXrandr
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xorg.libXv
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zlib
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# Pre-commit hooks.
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black
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# Frontend.
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yarn
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nodejs
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];
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LD_LIBRARY_PATH = pkgs.lib.makeLibraryPath buildInputs;
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CUDA_PATH = pkgs.cudatoolkit;
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EXTRA_LDFLAGS = "-L${pkgs.linuxPackages.nvidia_x11}/lib";
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shellHook = ''
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if [[ -f "${dir}/bin/activate" ]]; then
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source "${dir}/bin/activate"
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echo "Using Python: $(which python)"
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else
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echo "Use 'source ${setupScript}' to set up the environment."
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fi
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'';
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};
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in
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{
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devShells.${system} = rec {
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develop = mkShell { dir = "venv"; install = "-e '.[xformers]' --extra-index-url https://download.pytorch.org/whl/cu118"; };
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default = develop;
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};
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};
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}
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@ -274,7 +274,7 @@ class InvokeAISettings(BaseSettings):
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@classmethod
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def _excluded(self) -> List[str]:
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# internal fields that shouldn't be exposed as command line options
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return ["type", "initconf"]
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return ["type", "initconf", "cached_root"]
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@classmethod
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def _excluded_from_yaml(self) -> List[str]:
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@ -290,6 +290,7 @@ class InvokeAISettings(BaseSettings):
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"restore",
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"root",
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"nsfw_checker",
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"cached_root",
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]
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class Config:
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@ -423,6 +424,7 @@ class InvokeAIAppConfig(InvokeAISettings):
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log_level : Literal[tuple(["debug","info","warning","error","critical"])] = Field(default="info", description="Emit logging messages at this level or higher", category="Logging")
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version : bool = Field(default=False, description="Show InvokeAI version and exit", category="Other")
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cached_root : Path = Field(default=None, description="internal use only", category="DEPRECATED")
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# fmt: on
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def parse_args(self, argv: List[str] = None, conf: DictConfig = None, clobber=False):
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@ -470,10 +472,15 @@ class InvokeAIAppConfig(InvokeAISettings):
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"""
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Path to the runtime root directory
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"""
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if self.root:
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return Path(self.root).expanduser().absolute()
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# we cache value of root to protect against it being '.' and the cwd changing
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if self.cached_root:
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root = self.cached_root
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elif self.root:
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root = Path(self.root).expanduser().absolute()
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else:
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return self.find_root()
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root = self.find_root()
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self.cached_root = root
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return self.cached_root
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@property
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def root_dir(self) -> Path:
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@ -320,7 +320,7 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
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def get_model_names(self, base_model: BaseModelType = None) -> List[str]:
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model_names = [
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info["name"]
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info["model_name"]
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for info in self.model_manager.list_models(model_type=ModelType.Main, base_model=base_model)
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if info["model_format"] == "diffusers"
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]
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