{
  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 ];
  };
}