tox==3.24.5
numpy>=2.0.0, <3.0
build[virtualenv]==1.2.1
flake8==7.1.2
pytest==6.2.5
pytest-cov==3.0.0
pytest-rerunfailures==10.2
pytest-timeout==2.1.0
pytest-xdist==2.4.0
coverage>=5.2, <6.2
mock==4.0.3
contextlib2==21.6.0
awslogs==0.14.0
black==24.3.0
stopit==1.1.2
# Update tox.ini to have correct version of airflow constraints file
apache-airflow==2.10.4
apache-airflow-providers-amazon==7.2.1
Flask-Limiter==3.11
attrs>=24,<26
fabric==3.2.2
requests==2.32.2
sagemaker-experiments==0.1.35
Jinja2==3.1.6
pyvis==0.2.1
pandas>=2.3.0
scikit-learn==1.6.1
cloudpickle==2.2.1
jsonpickle<4.0.0
PyYAML>=6.0.1
# TODO find workaround
xgboost>=1.6.2,<=1.7.6
pillow>=10.0.1,<=11
opentelemetry-proto==1.27.0
opentelemetry_exporter_otlp==1.27.0
protobuf==4.25.8
tensorboard>=2.16.2,<=2.18.0
transformers==4.48.0
sentencepiece==0.1.99
# https://github.com/triton-inference-server/server/issues/6246
tritonclient[http]<2.37.0
onnx==1.17.0
# tf2onnx==1.15.1
nbformat>=5.9,<6
accelerate>=0.24.1,<=0.27.0
schema==0.7.5
tensorflow>=2.16.2,<=2.19.0
mlflow>=2.14.2,<3
huggingface_hub==0.26.2
uvicorn>=0.30.1
fastapi==0.115.4
nest-asyncio
sagemaker-mlflow>=0.1.0
deepdiff>=8.0.0
orderly-set<5.4.0
lexicon
networkx==3.2.1
mypy-boto3-appflow==1.35.39
mypy-boto3-rds==1.35.72
mypy-boto3-redshift-data==1.35.51
mypy-boto3-s3==1.35.76
mypy-extensions==1.0.0
mypy==1.9.0
