All Python dependencies are managed through the root-level requirements.txt file. This ensures consistent package versions across all scripts and the GitHub Actions workflow.

Adding New Dependencies

When adding new Python scripts that require external packages:

Add the required packages to requirements.txt at the project root
Include version constraints where appropriate (e.g., >=1.0.0)
Add comments to group related packages
Test locally with: pip install -r requirements.txt

Current Dependencies

The current dependencies include:

Quarto/Jupyter: jupyterlab-quarto, jupyter
NLP: nltk (with stopwords and punkt data)
AI Integration: openai, gradio
Document Processing: pybtex, pypandoc, pyyaml
Image Processing: Pillow
Validation: jsonschema
Utilities: absl-py

Subdirectory Requirements Files

Some subdirectories have their own requirements.txt files for specific workflows:

scripts/genai/requirements.txt - AI-specific dependencies
scripts/quarto_publish/requirements.txt - Publishing dependencies

These are kept for reference but the main workflow uses the root requirements.txt.

GitHub Actions Integration

The GitHub Actions workflow automatically:

Caches Python packages for faster builds
Installs all dependencies from requirements.txt
Downloads required NLTK data
Reports cache status in build summaries

Cache is invalidated when requirements.txt changes, ensuring dependencies stay up-to-date.

Pre-commit Setup

The project uses pre-commit hooks for code quality checks. The hooks run automatically on commit and include:

Spell checking with codespell
YAML validation for _quarto.yml
Markdown formatting and linting
Bibliography formatting with bibtex-tidy
Custom Python scripts for section ID management and unreferenced label detection

Setup Instructions

Install pre-commit (included in requirements.txt):
```
pip install -r requirements.txt
```
Install the git hooks:
```
pre-commit install
```

Run manually (optional):

# Run on all files
pre-commit run --all-files

# Run on specific files
pre-commit run --files path/to/file.qmd

Troubleshooting

NLTK data issues: The hooks automatically download required NLTK data, but if you encounter issues, you can manually run:
```
import nltk
nltk.download('stopwords')
nltk.download('punkt')
```
Python environment: The hooks use isolated Python environments with the specified dependencies, so they should work regardless of your local Python setup.