Livebook

Livebook is a web application for creating interactive and collaborative notebooks that evaluate Elixir code on demand. Notebooks are stored as .livemd (a Markdown subset) and combine prose, executable cells, and rich output for data visualization and automation.

Key Features

• Executable Elixir code cells with sequential evaluation and state tracking (stale cell annotation).
• Rich editor experience (autocompletion, inline docs, formatting) powered by a web code editor integration.
• Interactive visualizations via Kino and supported libraries (Vega-Lite, MapLibre) for charts, tables, and maps.
• Smart cells: high-level, UI-driven cells that generate and run code for common tasks (databases, ML models, plotting).
• Multiple runtimes: launch a fresh Elixir instance, connect to an existing node, or run inside an existing Elixir project with access to its modules and deps.
• Multiple deployment options including a desktop app, Docker images, and running inside platforms such as Hugging Face Spaces for GPU-backed ML workloads.

Use Cases

• Teaching and documentation: interactive Elixir tutorials and reproducible technical walkthroughs stored in versionable .livemd files.
• Data exploration and ML prototyping: query databases, visualize data, and run Hugging Face models via Smart cells or deployed Spaces.
• Internal tools and automation: convert notebooks into multi-session Livebook Apps to run shared workflows and lightweight internal UIs.

Limitations and Considerations

• Language scope: Livebook is Elixir-centric; capabilities for other languages are limited compared to multi-language notebook platforms.
• Cloud Smart cell caveats: some Smart cell features and integrations (e.g., running models) depend on external services or platform settings (Hugging Face Spaces visibility and secrets), which may affect reproducibility or feature availability in hosted environments.

Livebook provides a focused, production-ready notebook experience for Elixir developers and teams that need interactive documentation, data exploration, and workflow automation. Its integrations, runtime flexibility, and collaboration features make it suitable for teaching, prototyping, and building internal apps.