requirements.txt

# Dependencies for GemmaFischer - Chess LLM Engine + Tutor
# Mac-only (M3 Pro) with MPS acceleration - no CUDA/CPU fallbacks
#
# When updating dependencies, install the desired versions and regenerate
# pins with:
#   pip freeze > requirements.txt

# Core ML dependencies (MPS-optimized)
transformers>=4.45.0,<4.48.0  # Compatible with MPS and LoRA
datasets>=2.14.0
accelerate>=0.24.0
peft>=0.5.0
trl>=0.7.0  # Updated for better LoRA support
huggingface_hub>=0.17.0

# PyTorch stack (MPS-optimized)
torch>=2.1.0,<2.3.0  # Stable MPS version
torchvision>=0.16.0,<0.19.0
torchaudio>=2.1.0,<2.3.0

# Chess and UCI support
python-chess>=1.999
stockfish>=3.28.0  # Updated for better UCI support

# Web interface
flask>=3.0.0,<3.1.0
flask-cors>=4.0.0

# Data processing and embeddings (MPS-compatible)
sentence-transformers>=2.2.0  # For embedding generation
faiss-cpu>=1.7.0  # CPU-only vector search
pandas>=2.0.0,<2.2.0  # Stable pandas version
numpy>=1.24.0,<2.0.0  # Avoid numpy 2.0 breaking changes

# PGN processing and chess data
pgnparser>=1.0.0  # For PGN file parsing

# Evaluation and testing
pytest>=7.4.0
pytest-asyncio>=0.21.0  # For async tests
mlflow>=2.8.0  # For experiment tracking
scipy>=1.11.0  # For statistical analysis

# Utilities and validation
pyyaml>=6.0.0
psutil>=5.9.0
pydantic>=2.4.0  # For configuration validation
pydantic-settings>=2.0.0  # For config management

# Mac-specific optimizations
# Note: All ML operations use MPS acceleration on M3 Pro
# No CUDA dependencies or CPU fallbacks needed