142 lines
5.5 KiB
Nix

{ pkgs, lib, ... }:
let
models = [
# {
# name = "Qwen2.5-14B-Instruct-Q4_K_S.gguf";
# context_length = "32768";
# gen_length = "8192";
# source = pkgs.fetchurl {
# url = "https://huggingface.co/bartowski/Qwen2.5-14B-Instruct-GGUF/resolve/main/Qwen2.5-14B-Instruct-Q4_K_S.gguf?download=true";
# sha256 = "E1CmWUhMMbTXEjIRczzA3rSrVuR8qOL8BLagw7LiyZk=";
# };
# }
{
name = "Replete-LLM-V2.5-Qwen-14b-Q4_K_S.gguf";
context_length = "32768";
gen_length = "8192";
source = pkgs.fetchurl {
url = "https://huggingface.co/bartowski/Replete-LLM-V2.5-Qwen-14b-GGUF/resolve/main/Replete-LLM-V2.5-Qwen-14b-Q4_K_S.gguf?download=true";
sha256 = "/Oa1y4WVRGQkLEt5Sxxyt5plN5+tDFblLShPhMtzs7k=";
};
}
# {
# name = "Qwen2.5-7B-Instruct-Q6_K_L.gguf";
# context_length = "32768";
# gen_length = "8192";
# source = pkgs.fetchurl {
# url = "https://huggingface.co/bartowski/Qwen2.5-7B-Instruct-GGUF/resolve/main/Qwen2.5-7B-Instruct-Q6_K_L.gguf?download=true";
# sha256 = "thEXN06T/UVGfzdB83jlgpG7kuTzZtz1ZUAdupAnErM=";
# };
# }
# {
# name = "Replete-LLM-V2.5-Qwen-7b-Q6_K_L.gguf";
# context_length = "32768";
# gen_length = "8192";
# source = pkgs.fetchurl {
# url = "https://huggingface.co/bartowski/Replete-LLM-V2.5-Qwen-7b-GGUF/resolve/main/Replete-LLM-V2.5-Qwen-7b-Q6_K_L.gguf?download=true";
# sha256 = "dR7M5GKfGdiPI9mqBSH6naVr8XzuCjLLv514VYXSikg=";
# };
# }
];
# stolen from: https://stackoverflow.com/a/42398526
optimizeWithFlags =
pkg: flags:
pkgs.lib.overrideDerivation pkg (
old:
let
newflags = pkgs.lib.foldl' (acc: x: "${acc} ${x}") "" flags;
oldflags = if (pkgs.lib.hasAttr "NIX_CFLAGS_COMPILE" old) then "${old.NIX_CFLAGS_COMPILE}" else "";
in
{
NIX_CFLAGS_COMPILE = "${oldflags} ${newflags}";
stdenv = pkgs.clangStdenv;
}
);
model_files = builtins.listToAttrs (
map (f: {
name = ".local/share/nomic.ai/GPT4All/${f.name}";
value.source = f.source;
}) models
);
gpt4all_package = (
optimizeWithFlags
(pkgs.gpt4all.overrideAttrs (old: {
version = "3.4.0-dev0";
src = pkgs.fetchFromGitHub {
fetchSubmodules = true;
owner = "nomic-ai";
repo = "gpt4all";
rev = "HEAD";
sha256 = "/w1VAfLYlhB5y08cVG2u9RT2kajtFtyTPziQXSwVFcE=";
};
patches = old.patches ++ [
./gpt4all-HEAD-disable-settings-err.patch
];
}))
# compile flags
[
"-Ofast"
"-march=native"
"-mtune=native"
"-fno-protect-parens"
"-fno-finite-math-only" # https://github.com/ggerganov/llama.cpp/pull/7154#issuecomment-2143844461
]
);
in
{
home.packages = [
gpt4all_package
];
home.file = lib.recursiveUpdate {
".config/nomic.ai/GPT4All.ini".text =
let
system_prompt = "You are an expert AI assistant who is thoughtful and works step-by-step from first principles derive an answer to the user's prompt. For each step, provide a title that describes what you're doing in that step, along with the content. Decide if you need another step or if you're ready to provide your answer to the user, make sure to exhaust ALL POSSIBILITIES before providing a response to the user. While your reasoning is not shown to the user, it is under high levels of scrutiny to ensure high-quality reasoning. WHEN YOU DETERMINE THAT YOU ARE READY TO GIVE A FINAL ANSWER TO THE USER GIVEN YOUR REASONING AND STEP-BY-STEP WORK. ONLY TEXT WRITTEN AFTER A SECTION NAMED \"Final Answer\" WILL BE SHOWN TO THE USER. ASSUME THAT NO REASONING STEPS ARE SHOWN TO THE USER. DO NOT THINK THAT THE USER CAN SEE YOUR INTERNAL REASONING STEPS.
USE AS MANY REASONING STEPS AS POSSIBLE. AT LEAST 3. BE AWARE OF YOUR LIMITATIONS AS AN LLM AND WHAT YOU CAN AND CANNOT DO. EXPLORE ALTERNATE ANSWERS AND CONSIDER THAT YOUR ANSWER MAY BE WRONG. IDENTIFY POSSIBLE ERRORS IN YOUR REASONING AND WHERE SUCH ERRORS MAY BE. FULLY TEST ALL OTHER POSSIBILITIES. YOU CAN BE WRONG. WHEN YOU SAY YOU ARE RE-EXAMINING, ACTUALLY RE-EXAMINE, AND USE ANOTHER APPROACH TO DO SO. DO NOT JUST SAY YOU ARE RE-EXAMINING. SHOW ALL YOUR WORK. USE AT LEAST 3 METHODS TO DERIVE THE ANSWER. USE BEST PRACTICES. WORK FROM FIRST PRINCIPLES TO CREATE YOUR ANSWER.";
in
''
[General]
chatTheme=Dark
height=940
suggestionMode=Off
threadCount=8
uniqueId=7096f2d2-448d-4272-a132-d37e77f8a781
userDefaultModel=${
# select the first element of `models` to be the default model
(builtins.elemAt models 0).name
}
width=1472
x=0
y=0
[download]
lastVersionStarted=${gpt4all_package.version}
''
+ (lib.concatStrings (
map (model: ''
[model-${model.name}]
contextLength=${model.context_length}
filename=${model.name}
maxLength=${model.gen_length}
promptBatchSize=256
promptTemplate=<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n
systemPrompt="<|im_start|>system\n${
# replace newlines with the string "\n" for gpt4all to properly parse
builtins.replaceStrings [ "\n" ] [ "\\n" ] system_prompt
}<|im_end|>
\n"
'') models
))
+ ''
[network]
isActive=true
usageStatsActive=true
'';
} model_files;
}