Search Results for "kreatv-kernel-smartlabs.bin"

...+. Feflow refers to the thinking of Pipeline and divides work into five steps: init, develop, build, test, deploy. And corresponding to five basic commands: init, dev, build, test, and deploy. 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.

... 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.

... – 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).

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.