environment.yaml

# reasons you might want to use `environment.yaml` instead of `requirements.txt`:
# - pip installs packages in a loop, without ensuring dependencies across all packages
#   are fulfilled simultaneously, but conda achieves proper dependency control across
#   all packages
# - conda allows for installing packages without requiring certain compilers or
#   libraries to be available in the system, since it installs precompiled binaries

name: characters11

channels:
  - nvidia
  - pytorch
  - conda-forge
  - defaults

# it is strongly recommended to specify versions of packages installed through conda
# to avoid situation when version-unspecified packages install their latest major
# versions which can sometimes break things

# current approach below keeps the dependencies in the same major versions across all
# users, but allows for different minor and patch versions of packages where backwards
# compatibility is usually guaranteed

dependencies:
  - mamba=1.*
  - pytorch=2.*
  - torchvision=0.*
  - pytorch-cuda=11.8.*
  - lightning=2.*
  - torchmetrics=0.*
  - hydra-core=1.*
  - rich=13.*
  - pre-commit=3.*
  - pytest=7.*
  - pytest-xdist=3.*

  # --------- loggers --------- #
  - wandb=0.*
  # - neptune-client
  # - mlflow
  # - comet-ml

  # --------- code health --------- #
  - black=23.*
  - icontract=2.*
  - mypy=1.*
  - rope=1.*

  # --------- libraries --------- #
  - openai=0.*
  - pandas=2.*
  - seaborn=0.*
  - spacy=3.*
  - transformers=4.*
  - textstat==0.*
  - tqdm=4.*

  - pip>=23
  - pip:
      - bitsandbytes==0.*
      - farrow-and-ball==0.*
      - fschat==0.2.23
      - google-cloud-aiplatform>=1.26.1
      - hydra-optuna-sweeper==1.*
      - hydra-colorlog==1.*
      - hydra-submitit-launcher==1.*
      - git+https://github.com/Lightning-AI/lit-llama.git
      - langchain==0.*
      - pyrootutils==1.*
      - sentence_transformers==2.*
      - slurm-gpustat==0.*
      - gymnasium==0.*