ShellGPT is a powerful command-line productivity tool driven by large language models like GPT-4. It is designed to streamline the development workflow by generating shell commands, code snippets, and documentation directly within the terminal, reducing the need for external searches. The tool supports multiple operating systems including Linux, macOS, and Windows, and is compatible with various shells such as Bash, Zsh, and PowerShell. Beyond simple queries, it offers advanced features like shell integration for automated command execution, a REPL mode for interactive chatting, and the ability to implement custom function calls. Users can also leverage local LLM backends like Ollama for a free, privacy-focused alternative to OpenAI's API.
This Gist details a solution for reclaiming control over a macOS system when using older versions of Bash and the sandboxed App Store version of WireGuard cause issues. The core problem is that macOS's system Bash is outdated (version 3.2), which breaks modern scripts. Additionally, the App Store WireGuard client stores configurations in the Keychain, making them inaccessible to the command-line interface.
The solution involves installing a modern Bash and WireGuard tools via Homebrew, fixing terminal issues with terminfo, configuring the root environment's PATH, and rescuing WireGuard configurations from the Keychain. By following these steps, users can establish a functional WireGuard CLI setup on their macOS systems, bypassing the limitations imposed by the system's default configuration.
The solution involves installing a modern Bash and WireGuard tools via Homebrew, fixing terminal issues with terminfo, configuring the root environment's PATH, and rescuing WireGuard configurations from the Keychain. By following these steps, users can establish a functional WireGuard CLI setup on their macOS systems, bypassing the limitations imposed by the system's default configuration.
Milad Alizadeh introduces 'kitcat', a new matplotlib backend designed for plotting directly within compatible terminals. Frustrated with Jupyter notebooks as a development environment, the author sought a leaner, script-based workflow for matplotlib plotting. Kitcat leverages the graphic protocol popularized by Kitty, allowing image data to be sent via escape codes to terminals supporting this functionality, such as Yazi.
The backend encodes PNG pixel data into base64 and transmits it, supporting chunked data for larger images. While acknowledging the existence of 'matplotlib-backend-kitty', kitcat aims for broader compatibility across terminals supporting the protocol. Future development may include support for iTerm2 animations and the Sixel graphics standard.
The backend encodes PNG pixel data into base64 and transmits it, supporting chunked data for larger images. While acknowledging the existence of 'matplotlib-backend-kitty', kitcat aims for broader compatibility across terminals supporting the protocol. Future development may include support for iTerm2 animations and the Sixel graphics standard.
This article advocates for wider adoption of Claude Code, an AI tool from Anthropic designed to write, edit, and fix code. Initially an internal tool for Anthropic developers, it's now publicly available as a command-line tool that operates within your terminal. It can understand natural language instructions to modify codebases, and even assists with non-programming tasks like file organization and research. While the terminal interface can be intimidating, the author suggests using it within an IDE or utilizing the Claude Desktop app's integrated Cowork interface, highlighting its potential for both developers and non-developers.
This article details how to set up a local AI assistant within a Linux terminal using Ollama and Llama 3.2. It explains the installation process, necessary shell configurations, and practical applications for troubleshooting and understanding system logs and processes. The author demonstrates how to use the AI to explain command outputs, interpret journal logs, and gain insights into disk usage and running processes, improving efficiency and understanding for both beginners and advanced Linux users. It also discusses the benefits and limitations of this approach.
OpenCode is an open source agent that helps you write code in your terminal, IDE, or desktop.
It features LSP enabled, multi-session support, shareable links, GitHub Copilot and ChatGPT Plus/Pro integration, support for 75+ LLM providers, and availability as a terminal interface, desktop app, and IDE extension.
With over 120,000 GitHub stars, 800 contributors, and over 5,000,000 monthly developers, OpenCode prioritizes privacy by not storing user code or context data.
It also offers Zen, a curated set of AI models optimized for coding agents.
It features LSP enabled, multi-session support, shareable links, GitHub Copilot and ChatGPT Plus/Pro integration, support for 75+ LLM providers, and availability as a terminal interface, desktop app, and IDE extension.
With over 120,000 GitHub stars, 800 contributors, and over 5,000,000 monthly developers, OpenCode prioritizes privacy by not storing user code or context data.
It also offers Zen, a curated set of AI models optimized for coding agents.
This page provides an overview of the 'Missing Semester' course, focusing on the importance of the shell as a powerful tool for computer scientists. It covers motivation, class structure, the basics of navigating and using the shell, and exercises to reinforce learning. The course aims to equip students with practical skills beyond rote memorization of commands, enabling them to automate tasks and solve complex problems efficiently.
This article details seven terminal-based tools – Gonzo, Lazyjournal, Toolong, Humanlog, GoAccess, Logrotate, and Logwatch – that can significantly improve the experience of working with logs for debugging, analysis, and management. It highlights how these tools offer interactive visualization, efficient navigation, and automated management to make log analysis more manageable and even enjoyable.
This article details the author's experience with Nushell, a terminal shell that presents data in a spreadsheet-like format, improving usability and productivity compared to traditional command-line interfaces. It covers installation, core concepts, benefits for everyday tasks, customization options, and limitations.
This guide explains how to use tool calling with local LLMs, including examples with mathematical, story, Python code, and terminal functions, using llama.cpp, llama-server, and OpenAI endpoints.
