# D-MOE-EVAL: Dynamic Mixture-of-Experts Framework for LLM Evaluation
# Core Dependencies

# Data Processing and Analysis
numpy>=1.21.0
pandas>=1.3.0
scipy>=1.7.0
scikit-learn>=1.0.0

# Machine Learning and NLP
torch>=1.12.0
transformers>=4.20.0
datasets>=2.0.0
tokenizers>=0.12.0

# API and HTTP Requests
requests>=2.28.0
httpx>=0.23.0
openai>=1.0.0

# Configuration and Environment
python-dotenv>=0.19.0
pydantic>=1.10.0
pyyaml>=6.0

# Logging and Monitoring
loguru>=0.6.0
tqdm>=4.64.0
rich>=12.0.0

# Data Visualization
matplotlib>=3.5.0
seaborn>=0.11.0
plotly>=5.10.0

# File I/O and Serialization
jsonlines>=3.0.0
pickle5>=0.0.11
h5py>=3.7.0

# Testing and Development
pytest>=7.0.0
pytest-cov>=4.0.0
black>=22.0.0
flake8>=5.0.0
mypy>=0.950

# Jupyter and Documentation
jupyter>=1.0.0
notebook>=6.4.0
sphinx>=5.0.0
