environment.yml

name: py310
channels:
  - conda-forge
  - pytorch
  - defaults
dependencies:
  - python=3.10
  - pip>=23.0

  # Core dependencies (conda)
  - numpy>=1.24.0
  - pandas>=2.0.0

  # PyTorch (conda for better CUDA integration)
  - pytorch>=2.0.0
  - pytorch-cuda=11.8  # For CUDA 11.8 (adjust for your GPU)
  - cudatoolkit=11.8   # For CUDA 11.8

  # pip dependencies
  - pip:
    # ML/DL
    - lightning>=2.0.0
    - pytorch-forecasting>=1.0.0

    # Data processing
    - pyarrow>=12.0.0

    # Visualization & Dashboard
    - streamlit>=1.28.0
    - plotly>=5.17.0
    - matplotlib>=3.7.0

    # API & Networking
    - requests>=2.31.0
    - websockets>=11.0

    # Model serialization
    - safetensors>=0.4.0

    # Utilities
    - python-dateutil>=2.8.0

# Platform-specific notes:
#
# For CPU-only (no GPU):
#   Remove pytorch-cuda and cudatoolkit lines
#   Use: conda env create -f environment.yml
#
# For different CUDA versions:
#   CUDA 12.1: pytorch-cuda=12.1, cudatoolkit=12.1
#   CUDA 11.7: pytorch-cuda=11.7, cudatoolkit=11.7
#
# Alternative creation method:
#   conda create -n py310 python=3.10
#   conda activate py310
#   pip install -r requirements.txt