# elyra-ai/elyra

Elyra extends JupyterLab with an AI centric approach.

Repository: https://github.com/elyra-ai/elyra
Canonical: https://ross.abutalabs.com/products/elyra
Homepage: https://elyra.readthedocs.io/en/stable/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: notebooks, notebook-jupyter, jupyterlab, jupyterlab-extensions, ai, machine-learning, pipelines, kubeflow-pipelines, python, elyra, binder, jupyterlab-notebooks, kubeflow, hacktoberfest, jupyterlab-extension, anaconda, pypi, docker, apache-airflow, airflow
Last push: 2026-08-19T16:36:12+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 11, longevity 100
- inputs: {"age_days": 2507, "days_push": 14, "days_rel": 382, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1996, forks 368 (observed 2026-08-28T04:06:03.528659+00:00)

## What it is
Elyra is a set of AI-centric extensions for JupyterLab, including a visual pipeline editor for building and executing notebook-based pipelines on Kubeflow Pipelines or Apache Airflow. It also adds batch job execution for notebooks and scripts, reusable code snippets, script editors, and AI assistant integration.

## Use cases
- build and run notebook pipelines visually on kubeflow or airflow
- run a jupyter notebook as a batch job
- execute python or r scripts remotely from jupyterlab
- manage reusable code snippets in jupyterlab
- add ai code assistance to notebook cells
- orchestrate notebooks into machine learning workflows

## When to choose
- you orchestrate notebooks and scripts into ML pipelines on Kubeflow or Airflow
- you want a drag-and-drop visual pipeline editor inside JupyterLab
- you need to run notebooks or scripts as scheduled batch jobs

## When to avoid
- you need a general-purpose workflow orchestrator outside Jupyter
- you don't use JupyterLab or notebook-based workflows
- you need fully code-defined pipelines rather than visual ones

## Facets
- artifact type: plugin
- maturity: active
- function: machine-learning, workflow-automation, developer-tools, gui
- domain: machine-learning, data-science, developer-tools
- platform: python, cross-platform
- tags: jupyterlab-extension, visual-pipeline-editor, kubeflow-pipelines, apache-airflow, notebooks, batch-jobs, code-snippets, web-server, docker, kubernetes

## Member repositories
- elyra-ai/elyra (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:03.528659+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:02:29.184346+00:00, confidence not recorded.
  - readme: https://github.com/elyra-ai/elyra (fetched 2026-08-28T04:06:03.528659+00:00, sha 665e7159f008)
  - registry_pypi: https://pypi.org/pypi/elyra/json (fetched 2026-08-29T10:42:36.274689+00:00, sha 76f1cfa173d9)
- Data as of 2026-08-30T08:39:29.467469+00:00.