name: protein-conformal
channels:
  - pytorch
  - conda-forge
  - huggingface
  - defaults

dependencies:
  # Python version
  - python=3.10

  # Core scientific computing
  - numpy>=1.24.0
  - pandas>=2.0.0
  - scipy>=1.10.0
  - scikit-learn>=1.0.0

  # Machine Learning & Deep Learning
  - pytorch>=2.1.0
  - cpuonly  # CPU-only PyTorch for Windows compatibility
  - transformers>=4.30.0
  - pytorch-lightning>=2.0.0
  - h5py>=3.7.0

  # FAISS for similarity search
  - faiss-cpu>=1.7.4  # Use faiss-gpu if you have GPU support

  # Bioinformatics
  - biopython>=1.81

  # Web frameworks and APIs
  - fastapi>=0.90.0
  - uvicorn>=0.18.0
  - jinja2>=3.1.0
  - pydantic>=1.10.0
  - python-multipart>=0.0.5

  # Visualization and plotting
  - matplotlib>=3.5.0
  - seaborn>=0.12.0
  - plotly>=5.9.0
  - networkx>=2.8.0

  # Development and debugging tools
  - tqdm
  - ipdb
  - jupyter
  - notebook
  - jupyterlab

  # Utilities
  - requests>=2.27.1

  # Pip dependencies (packages not available via conda)
  - pip
  - pip:
    - gradio>=4.0.0  # Install from PyPI with prebuilt frontend assets
    - py3Dmol>=1.8.0  # 3D molecular visualization for Gradio
    - sentencepiece>=0.1.99
    - huggingface_hub>=0.34.0,<1.0

# Installation instructions:
# conda env update -f environment.yaml --prune  # Update existing 'cpr' environment
# conda activate cpr
#
# Alternative: Create new environment
# conda env create -f environment.yaml
# conda activate protein-conformal
#
# For GPU support on Linux/properly configured CUDA systems:
# 1. Replace 'cpuonly' with 'pytorch-cuda=11.8'
# 2. Change 'faiss-cpu' to 'faiss-gpu'
# 3. Add nvidia channel: conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia