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3a8e9de dcb463f 3a8e9de 9895fb8 3a8e9de 9895fb8 3a8e9de fe84bea 3a8e9de 9895fb8 3a8e9de 9895fb8 3a8e9de | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | 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
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