infrastructure/machines/krz01/_configuration.nix

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Nix
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{
config,
lib,
pkgs,
...
}:
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lib.extra.mkConfig {
enabledModules = [
# INFO: This list needs to stay sorted alphabetically
];
enabledServices = [
# INFO: This list needs to stay sorted alphabetically
# Machine learning API machine
"microvm-ml01"
"microvm-router01"
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"nvidia-tesla-k80"
"proxmox"
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];
extraConfig = {
microvm = {
host.enable = true;
};
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dgn-hardware = {
useZfs = true;
zfsPools = [
"dpool"
"ppool0"
];
};
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services.netbird.enable = true;
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# We are going to use CUDA here.
nixpkgs.config.cudaSupport = true;
hardware.graphics.enable = true;
environment.systemPackages = [
((pkgs.openai-whisper-cpp.override { cudaPackages = pkgs.cudaPackages_11; }).overrideAttrs (old: {
src = pkgs.fetchFromGitHub {
owner = "ggerganov";
repo = "whisper.cpp";
rev = "v1.7.1";
hash = "sha256-EDFUVjud79ZRCzGbOh9L9NcXfN3ikvsqkVSOME9F9oo=";
};
env = {
WHISPER_CUBLAS = "";
GGML_CUDA = "1";
};
# We only need Compute Capability 3.7.
CUDA_ARCH_FLAGS = [ "sm_37" ];
# We are GPU-only anyway.
patches = (old.patches or [ ]) ++ [
./no-weird-microarch.patch
./all-nvcc-arch.patch
];
}))
];
services = {
nginx = {
enable = true;
recommendedProxySettings = true;
virtualHosts."ollama01.beta.dgnum.eu" = {
enableACME = true;
forceSSL = true;
locations."/" = {
proxyPass = "http://${config.services.ollama.host}:${toString config.services.ollama.port}";
basicAuthFile = pkgs.writeText "ollama-htpasswd" ''
raito:$y$j9T$UDEHpLtM52hRGK0I4qT6M0$N75AhENLqgtJnTGaPzq51imhjZvuPr.ow81Co1ZTcX2
'';
};
};
};
ollama = {
enable = true;
package = pkgs.callPackage ./ollama.nix {
cudaPackages = pkgs.cudaPackages_11;
# We need to thread our nvidia x11 driver for CUDA.
extraLibraries = [ config.hardware.nvidia.package ];
};
};
};
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};
root = ./.;
}