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Elyra AI Toolkit, an open source project that extends the JupyterLab user interface to simplify the development of data science and AI models, has hit version 1.0.

The release is said to bring usability enhancements and bug fixes for existing features, such as enhanced inline user documentation and validation capabilities for the Pipeline Editor, improved performance for pipeline submission to Kubeflow Pipelines runtime.

Elyra 1.0.0 also features a new reusable Code Snippets extension and the ability to configure runtimes directly on the JupyterLab user interface.

On the platform side, Elyra 1.0.0 is now based on JupyterLab 2.x. It can easily be integrated into a JupyterHub deployment or other containerized environments such as Kubernetes and OpenShift or even be run in standalone mode using local docker deployment.

Elyra’s Notebook Pipeline Editor is said to simplify the conversion of multiple notebooks into batch jobs or workflows. By leveraging cloud-based resources to run their experiments faster, the data scientists, machine learning engineers, and AI developers are then more productive, and therefore able to spend more of their time focusing on their technical skills.

With the new code snippets extension, you can expect easy discovery, creation and insertion of reusable snippets of code into your Notebooks, Python Scripts or even Markdown files used for documentation directly from the JupyterLab workspace. This makes the process of writing code more efficient and accessible.

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