notebooks

Jupyter Notebook Examples

This directory contains interactive Jupyter notebooks demonstrating various Mellea features.

Notebooks

example.ipynb

General introduction to Mellea with basic examples.

compositionality_with_generative_stubs.ipynb

Interactive tutorial on composing generative functions.

context_example.ipynb

Working with contexts and context management.

document_mobject.ipynb

Using document MObjects for text processing.

georgia_tech.ipynb

Domain-specific example (possibly academic/research use case).

instruct_validate_repair.ipynb

Interactive walkthrough of the instruct-validate-repair paradigm.

m_serve_example.ipynb

Deploying Mellea programs as services.

mcp_example.ipynb

Model Context Protocol integration examples.

model_options_example.ipynb

Configuring model options and parameters.

sentiment_classifier.ipynb

Building a sentiment classification system.

simple_email.ipynb

Email generation with requirements.

table_mobject.ipynb

Working with table data structures.

Running the Notebooks

# Install Jupyter if needed
uv pip install jupyter

# Start Jupyter
jupyter notebook docs/examples/notebooks/

# Or use JupyterLab
jupyter lab docs/examples/notebooks/

Benefits of Notebooks

• Interactive Learning: Experiment with code in real-time
• Visualization: See results immediately
• Documentation: Combine code, output, and explanations
• Experimentation: Try different parameters and approaches
• Sharing: Easy to share complete examples with outputs

Corresponding Python Files

Most notebooks have corresponding Python files in the tutorial/ directory for non-interactive use.

Tips

• Run cells in order for proper context building
• Restart kernel if you encounter state issues
• Use Shift+Enter to run cells
• Check cell outputs for errors before proceeding

Related Documentation

• See tutorial/ for Python script versions
• See individual example directories for more details on each topic