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{
lib,
buildPythonPackage,
fetchFromGitHub,
setuptools,
aiohttp,
fastapi,
httpx,
markdown2,
nh3,
numpy,
prompt-toolkit,
pydantic,
requests,
rich,
shortuuid,
tiktoken,
uvicorn,
anthropic,
openai,
ray,
wandb,
einops,
gradio,
accelerate,
peft,
sentencepiece,
torch,
transformers,
protobuf,
}:
let
version = "0.2.36";
in
buildPythonPackage {
pname = "fschat";
inherit version;
format = "pyproject";
src = fetchFromGitHub {
owner = "lm-sys";
repo = "FastChat";
rev = "refs/tags/v${version}";
hash = "sha256-tQuvQXzQbQjU16DfS1o55VHW6eklngEvIigzZGgrKB8=";
};
nativeBuildInputs = [ setuptools ];
propagatedBuildInputs = [
aiohttp
fastapi
httpx
markdown2
nh3
numpy
prompt-toolkit
pydantic
requests
rich
shortuuid
tiktoken
uvicorn
# ] ++ markdown2.optional-dependencies.all;
];
passthru.optional-dependencies = {
llm_judge = [
anthropic
openai
ray
];
train = [
# flash-attn
wandb
einops
];
webui = [ gradio ];
model_worker = [
accelerate
peft
sentencepiece
torch
transformers
protobuf
];
};
pythonImportsCheck = [ "fastchat" ];
# tests require networking
doCheck = false;
meta = with lib; {
description = "Open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena";
homepage = "https://github.com/lm-sys/FastChat";
license = licenses.asl20;
maintainers = with maintainers; [ happysalada ];
};
}
|
