# tinyMARS — minimum requirements for training, eval, corpus generation
# Tested on Python 3.10+, CUDA 12.x

# Core ML
torch>=2.4.0
transformers>=4.45.0
datasets>=2.21.0
sentencepiece>=0.2.0
tokenizers>=0.20.0

# Embeddings (BGE-M3 for memory/identity/continuity channels)
FlagEmbedding>=1.3.0

# Corpus + data plumbing
pyarrow>=17.0.0
pandas>=2.2.0
numpy>=1.26.0
zstandard>=0.23.0

# Inference client (corpus generation via teacher LLM)
requests>=2.32.0
aiohttp>=3.9.0

# Eval / scoring
scikit-learn>=1.5.0

# Dev / utilities
tqdm>=4.66.0
python-dotenv>=1.0.0

# Optional: rendering final report PDF
markdown2>=2.5.0
weasyprint>=63.0
