numpy
networkx
openai
z3-solver<=4.15.4.0
aiohttp
flask
torch
# Cap below 5.13: transformers 5.13.0 tightened AutoTokenizer.register() to require
# a class, which breaks mlx-lm (it registers a tokenizer by string name). Lift the
# cap once mlx-lm ships a transformers-5.13-compatible release. See mlx_lm
# tokenizer_utils.register("NewlineTokenizer", ...).
transformers>=5.0.0,<5.13.0
azure.identity
tiktoken
scikit-learn
litellm
google-cloud-aiplatform
requests
beautifulsoup4
lxml
selenium
webdriver-manager
presidio_analyzer
presidio_anonymizer
nbformat
nbconvert
ipython
ipykernel
peft
bitsandbytes
gradio<5.16.0
spacy>=3.7.0
cerebras_cloud_sdk
outlines[transformers]>=1.2.3
sentencepiece
adaptive-classifier
datasets
mcp>=2,<3
# MLX support for Apple Silicon optimization
mlx-lm>=0.24.0; platform_machine=="arm64" and sys_platform=="darwin"
math-verify