elyra-ai/elyra

Elyra extends JupyterLab with an AI centric approach.

Elyra – AI‑centric extensions for JupyterLab

Elyra is an open‑source add‑on for JupyterLab that bundles a set of tools aimed at data‑science and AI workflows. It lives as a collection of JupyterLab extensions (both front‑end and server‑side) and can be installed via pip or conda.

What it does

Feature What you get
Visual Pipeline Editor Drag‑and‑drop UI to compose notebooks, Python or R scripts into reusable AI pipelines.
Batch job execution Run a notebook, Python or R script as a remote batch job (e.g., on Kubernetes, Spark, Airflow) directly from the UI.
Reusable code snippets Library of saved code blocks that can be inserted into cells with a click.
AI Assistant integration Hooks into the Jupyter‑AI extension to provide LLM‑powered code suggestions inside notebook cells.
Hybrid runtime support Works with Jupyter Enterprise Gateway, letting you run code on local kernels or remote clusters transparently.
Python & R script editors Full‑featured editors with Table‑of‑Contents navigation, experimental debugger, and LSP‑based language features.
Git integration Basic version‑control actions (commit, push, pull) from within JupyterLab.
Theme & UI extensions Additional UI polish (theme, metadata panels) to make the experience cohesive.

Who might use it

  • Data scientists who want to turn a series of notebooks into a repeatable pipeline without leaving JupyterLab.
  • ML engineers needing to submit training or inference jobs to remote clusters while staying in a familiar notebook environment.
  • Teams that want a unified UI for code snippets, debugging, and version control inside Jupyter.
  • Educators looking for a richer notebook interface that includes outlines, TOC, and AI‑assisted coding.

Getting started (quick‑start)

  1. Install – either pip install "elyra[all]" or conda install -c conda-forge "elyra[all]" (requires Python 3.10+ and Node 22 for the lab extensions).
  2. Verify – run jupyter server extension list and jupyter labextension list to see that the Elyra extensions are enabled.
  3. Launch – start JupyterLab with jupyter lab. The new Elyra panels (pipeline editor, code‑snippet sidebar, etc.) appear automatically.
  4. Optional container – pull the pre‑built Docker image elyra/elyra:latest (or a specific tag) and run docker run -it -p 8888:8888 elyra/elyra:dev jupyter lab --debug to try it without a local install.

Documentation & help

Why it matters

Elyra bridges the gap between the interactive notebook world and production‑grade AI pipelines. By embedding pipeline authoring, remote execution, and LLM‑assisted coding directly into JupyterLab, it lets teams prototype and scale models without switching tools, which speeds up experimentation and reduces context‑switch overhead.

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