Jupyter AI - AI SDKs and Libraries Tool

Overview

Jupyter AI is an open-source JupyterLab extension that brings generative AI capabilities directly into notebooks. It provides a %%ai cell magic and a native chat sidebar so users can iterate with language models in-place, ask for code generation, explanations, or natural-language transformations without leaving the notebook environment. The project is designed to be provider-agnostic: it ships with adapters so you can connect hosted LLM providers or run models locally via projects such as GPT4All and Ollama. Designed for data scientists, researchers, and educators, Jupyter AI captures notebook context (cells and variables) to produce context-aware responses and code suggestions. Its architecture separates a frontend JupyterLab extension (UI/chat) from a server-side component and provider plugins, enabling contributors to add new model backends, authentication flows, or local runtime integrations. According to the GitHub repository, the project is actively maintained and community-backed (4,066 stars, 473 forks, 59 contributors as of the repository metadata).

GitHub Statistics

• Stars: 4,066
• Forks: 473
• Contributors: 59
• License: BSD-3-Clause
• Primary Language: Python
• Last Updated: 2026-01-06T17:37:43Z
• Latest Release: v2.31.7

Repository activity and community health appear strong: the project is under a permissive BSD-3-Clause license and has 4,066 stars, 473 forks, and 59 contributors (per the GitHub repository metadata). The repository shows recent commits (last commit recorded 2026-01-06), indicating ongoing maintenance. The contributor count and number of forks suggest active community interest and contributions focused on provider adapters, UX improvements, and local model integrations.

Installation

Install via pip:

pip install jupyter-ai

jupyter server extension enable --py jupyter_ai --sys-prefix

jupyter lab build

Key Features

• %%ai cell magic for running generative prompts directly inside notebook cells
• Native chat sidebar for conversational interactions with models within JupyterLab
• Provider-agnostic architecture supporting hosted and local models (e.g., GPT4All, Ollama)
• Context-aware prompts that can include notebook cells and variable state
• Extensible provider plugin system for adding new model backends and auth flows
• Helpers for code generation, explanation, and refactoring driven by LLM responses
• Open-source BSD-3-Clause license enabling commercial and academic use

Community

The project has an active open-source community (4,066 stars, 473 forks, 59 contributors). Discussions and pull requests focus on provider adapters, local model support, and UX refinements. The repository receives regular commits and community contributions; issues and PRs are the primary channels for feedback and feature requests (see the project's GitHub page for ongoing discussions).

Key Information

• Category: SDKs and Libraries
• Type: AI SDKs and Libraries Tool