# Core dependencies
# IMPORTANT: Install PyTorch with CUDA 12.8 support first using:
# pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
# Then install remaining dependencies with: pip install -r requirements.txt

# PyTorch - version will be satisfied by pre-installed nightly build
# Minimum version for CUDA 12.8 support (will use nightly/2.3.0+ in practice)
torch>=2.2.0
torchvision>=0.17.0
torchaudio>=2.2.0
# HuggingFace Transformers
transformers>=4.38.0
# HuggingFace Datasets
datasets>=2.14.0
# HuggingFace Tokenizers
tokenizers>=0.15.0
numpy>=1.23.0
scipy>=1.10.0
scikit-learn>=1.3.0
pandas>=1.5.0
FlagEmbedding>=1.2.0
# For CPU use faiss-cpu
faiss-gpu>=1.7.4
psutil>=5.9.0
omegaconf>=2.3.0
toml>=0.10.2
tqdm>=4.64.0
pyyaml>=6.0
jsonlines>=3.1.0
huggingface-hub>=0.19.0
jieba>=0.42.1
requests>=2.28.0
# Optional/dev dependencies
# For Huawei Ascend NPU support (install only if needed)
# torch-npu>=1.11.0.post1; platform_system=="Linux" and platform_machine=="aarch64"
# ascend-compiler; platform_system=="Linux" and platform_machine=="aarch64"
# For experiment tracking (optional)
wandb  # optional, for Weights & Biases logging
# For visualization (optional)
tensorboard  # optional, for TensorBoard logging
# For testing and development
pytest  # optional, for running tests
# For ModelScope support (optional)
modelscope  # optional, for ModelScope model hub
sentence-transformers>=2.2.2
accelerate>=0.25.0
rank-bm25>=0.2.2
# For logging and distributed
loguru>=0.7.0