# MLatelier runtime dependencies
# Install with: python -m pip install -r requirements.txt
#
# This mirrors [project.dependencies] in pyproject.toml — keep the two in step.
# `pip install mlatelier` reads pyproject.toml, not this file.
#
# There are no user-facing optional extras: MLatelier is driven from a browser,
# so every feature must work on a single install. Contributors additionally want
#   pip install "mlatelier[dev]"   pytest, coverage, build, onnxruntime

# Web app
streamlit>=1.33.0
requests>=2.31.0

# Data handling and plotting
pandas>=2.0.0
numpy>=1.26.0
matplotlib>=3.8.0
seaborn>=0.13.0
scipy>=1.12.0
tabulate>=0.9.0
pillow>=10.0.0

# Excel readers used by pandas.read_excel (not pulled in by pandas itself)
openpyxl>=3.1.0
xlrd>=2.0.1

# Tabular ML core
scikit-learn>=1.4.0
scikit-optimize>=0.10.0
joblib>=1.3.0

# Tabular ML extras
imbalanced-learn>=0.12.0
xgboost>=2.0.0
lightgbm>=4.0.0
catboost>=1.2.0

# Explainability
shap>=0.44.0
lime>=0.2.0.1

# Vision / deep learning
torch>=2.2.0
torchvision>=0.17.0

# NLP
nltk>=3.8.0
sentence-transformers>=2.6.0
transformers>=4.40.0
wordcloud>=1.9.0

# Gemini AI assistant
google-genai>=0.4.0

# ONNX export (skl2onnx converts sklearn; onnxmltools adds XGBoost/LightGBM)
skl2onnx>=1.16.0
onnxmltools>=1.12.0

# Counterfactual explanations
dice-ml>=0.11
