Adding Mistral Codestral and GPT-4o to Jupyter Notebooks
Hey HN! We’ve forked Jupyter Lab and added AI code generation features that feel native and have all the context about your notebook. You can see a demo video (2 min) here: https://www.tella.tv/video/clxt7ei4v00rr09i5gt1laop6/view Try a hosted version here: https://pretzelai.app Jupyter is by far the most used Data Science tool. Despite its popularity, it still lacks good code-generation extensions. The flagship AI extension jupyter-ai lags far behind in features and UX compared to modern AI code generation and understanding tools (like…
In plain words
Pretzel is a modified version of Jupyter Lab that integrates AI code generation directly into notebooks using Mistral Codestral and GPT-4o. Built for data scientists and developers who work in Jupyter, it provides native AI assistance with full notebook context, addressing the gap left by existing extensions. The tool is available as a free, open-source fork that can be installed locally or accessed through a hosted version.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN! We’ve forked Jupyter Lab and added AI code generation features that feel native and have all the context about your notebook. You can see a demo video (2 min) here: https://www.tella.tv/video/clxt7ei4v00rr09i5gt1laop6/view Try a hosted version here: https://pretzelai.app Jupyter is by far the most used Data Science tool. Despite its popularity, it still lacks good code-generation extensions. The flagship AI extension jupyter-ai lags far behind in features and UX compared to modern AI code generation and understanding tools (like https://www.continue.dev and https://www.cursor.com). Also, GitHub Copilot still isn’t supported in Jupyter, more than 2 years after its launch. We’re solving this with Pretzel. Pretzel is a free and open-source fork of Jupyter. You can install it locally with “pip install pretzelai” and launch it with “pretzel lab”. We recommend creating a new python environment if you already have jupyter lab installed. Our GitHub README has more information: https://github.com/pretzelai/pretzelai For our first iteration, we’ve shipped 3 features: 1. Inline Tab autocomplete: This works similar to GitHub Copilot. You can choose between Mistral Codestral or GPT-4o in the settings 2. Cell level code generation: Click Ask AI or press Cmd+K / Ctrl+K to instruct AI to generate code in the active Jupyter Cell. We provide relevant context from the current notebook to the LLM with RAG. You can refer to existing variables in the notebook using the @variable syntax (for dataframes, it will pass the column names to the LLM) 3. Sidebar chat: Clicking the blue Pretzel Icon on the right sidebar opens this chat (Ctrl+Cmd+B / Ctrl+Alt+B). This chat always has context of your current cell or any selected text. Here too, we use RAG to send any relevant context from the current notebook to the LLM All of these features work out-of-the-box via our “AI Server” but you have the option of using your own OpenAI API Key. This can be configured in the settings (Menu Bar > Settings > Settings Editor > Search for Pretzel). If you use your own OpenAI API Key but don’t have a Mistral API key, be sure to select OpenAI as the inline code completion model in the settings. These features are just a start. We're building a modern version of Jupyter. Our roadmap includes frictionless, realtime collaboration (think pair-programming, comments, version history), full-fledged SQL support (both in code cells and as a standalone SQL IDE), a visual analysis builder, a VSCode-like coding experience powered by Monaco, and 1-click dashboard creation and sharing straight from your notebooks. We’d love for you to try Pretzel and send us any feedback, no matter how minor (see my bio for contact info, or file a GitHub issue here: https://github.com/pretzelai/pretzelai/issues)
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