Showing 4 open source projects for "mystic-kernel"

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  • 1
    JupyterLab LSP

    JupyterLab LSP

    Coding assistance for JupyterLab (code navigation + hover suggestions

    ...Use the context menu entry, or Alt + 🖱️ to jump to definitions/references (you can change it to Ctrl/⌘ in settings); use Alt + o to jump back. Place your cursor on a variable, function, etc and all the usages will be highlighted. When a kernel is available the suggestions from the kernel (such as keys of a dict and columns of a DataFrame) are merged with the suggestions from the Language Server (in notebook). If the kernel is too slow to respond promptly only the Language Server suggestions will be shown (default threshold: 0.6s). You can configure the completer to not attempt to fetch the kernel completions if the kernel is busy.
    Downloads: 2 This Week
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  • 2
    GPT-Code UI

    GPT-Code UI

    An open source implementation of OpenAI's ChatGPT Code interpreter

    An open source implementation of OpenAI's ChatGPT Code interpreter. Simply ask the OpenAI model to do something and it will generate & execute the code for you. You can put a .env in the working directory to load the OPENAI_API_KEY environment variable. For Azure OpenAI Services, there are also other configurable variables like deployment name. See .env.azure-example for more information. Note that model selection on the UI is currently not supported for Azure OpenAI Services.
    Downloads: 0 This Week
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  • 3
    Cross Platform Node Guide

    Cross Platform Node Guide

    Improve front-end engineer workflow & standard, powered by TypeScript

    ...In addition to serving basic development workflows and specifications, Feflow provides an easy-to-expand plug-in mechanism for creating a team-wide toolchain ecosystem. Feflow only provides a CLI and kernel. The CLI is responsible for interacting with the command line terminal.
    Downloads: 0 This Week
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  • 4
    Hydrogen

    Hydrogen

    Run code interactively, inspect data, and plot

    ...You also may be interested in our latest project – interact – a desktop application that wraps up the best of the web-based Jupyter notebook. Watch expressions let you keep track of variables and re-run snippets after every change. Completions from the running kernel, just like autocomplete in the Chrome dev tools. Code can be inspected to show useful information provided by the running kernel. One kernel per language (so you can run snippets from several files, all in the same namespace).
    Downloads: 0 This Week
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