zsh-github-copilot
🧠 GitHub Copilot for your command line
Stars: 66
zsh-github-copilot is a `zsh` plugin that enhances the GitHub Copilot experience by providing keybinds to quickly access command explanations and get Copilot suggestions. It integrates seamlessly with GitHub CLI and offers a smooth setup process. Users can easily install the plugin using popular zsh plugin managers like antigen, oh-my-zsh, zinit, zplug, and zpm. By binding specific keys, users can access the 'suggest' and 'explain' functionalities to improve their coding workflow with GitHub Copilot. This plugin is designed to streamline the usage of GitHub Copilot within the zsh shell environment.
README:
A
zsh
plugin for GitHub Copilot
Requires the GitHub CLI with the Copilot extension installed and configured.
The plugin will check for the extension and other dependencies at source time, to disable this check, set the
ZSH_GH_COPILOT_NO_CHECK
environment variable to1
.
Add the following to your .zshrc
:
antigen bundle loiccoyle/zsh-github-copilot
Clone this repository into $ZSH_CUSTOM/plugins
(by default ~/.oh-my-zsh/custom/plugins
):
git clone https://github.com/loiccoyle/zsh-github-copilot ${ZSH_CUSTOM:-~/.oh-my-zsh/custom}/plugins/zsh-github-copilot
Add the plugin to the list of plugins for Oh My Zsh to load (inside ~/.zshrc
):
plugins=(
# other plugins...
zsh-github-copilot
)
Add the following to your .zshrc
:
zinit light loiccoyle/zsh-github-copilot
Add the following to your .zshrc
:
zplug "loiccoyle/zsh-github-copilot"
Add the following to your .zshrc
:
zpm load loiccoyle/zsh-github-copilot
Bind the suggest and/or explain widgets:
bindkey '^[|' zsh_gh_copilot_explain # bind Alt+shift+\ to explain
bindkey '^[\' zsh_gh_copilot_suggest # bind Alt+\ to suggest
bindkey '»' zsh_gh_copilot_explain # bind Option+shift+\ to explain
bindkey '«' zsh_gh_copilot_suggest # bind Option+\ to suggest
To get command explanations, write out the command in your prompt and hit your keybind.
To get Copilot to suggest a command to fulfill a query, type out the query in your prompt and hit your suggest keybind.
This plugin draws from stefanheule/zsh-llm-suggestions
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for zsh-github-copilot
Similar Open Source Tools
zsh-github-copilot
zsh-github-copilot is a `zsh` plugin that enhances the GitHub Copilot experience by providing keybinds to quickly access command explanations and get Copilot suggestions. It integrates seamlessly with GitHub CLI and offers a smooth setup process. Users can easily install the plugin using popular zsh plugin managers like antigen, oh-my-zsh, zinit, zplug, and zpm. By binding specific keys, users can access the 'suggest' and 'explain' functionalities to improve their coding workflow with GitHub Copilot. This plugin is designed to streamline the usage of GitHub Copilot within the zsh shell environment.
Discord-AI-Chatbot
Discord AI Chatbot is a versatile tool that seamlessly integrates into your Discord server, offering a wide range of capabilities to enhance your communication and engagement. With its advanced language model, the bot excels at imaginative generation, providing endless possibilities for creative expression. Additionally, it offers secure credential management, ensuring the privacy of your data. The bot's hybrid command system combines the best of slash and normal commands, providing flexibility and ease of use. It also features mention recognition, ensuring prompt responses whenever you mention it or use its name. The bot's message handling capabilities prevent confusion by recognizing when you're replying to others. You can customize the bot's behavior by selecting from a range of pre-existing personalities or creating your own. The bot's web access feature unlocks a new level of convenience, allowing you to interact with it from anywhere. With its open-source nature, you have the freedom to modify and adapt the bot to your specific needs.
pacha
Pacha is an AI tool designed for retrieving context for natural language queries using a SQL interface and Python programming environment. It is optimized for working with Hasura DDN for multi-source querying. Pacha is used in conjunction with language models to produce informed responses in AI applications, agents, and chatbots.
AMD-AI
AMD-AI is a repository containing detailed instructions for installing, setting up, and configuring ROCm on Ubuntu systems with AMD GPUs. The repository includes information on installing various tools like Stable Diffusion, ComfyUI, and Oobabooga for tasks like text generation and performance tuning. It provides guidance on adding AMD GPU package sources, installing ROCm-related packages, updating system packages, and finding graphics devices. The instructions are aimed at users with AMD hardware looking to set up their Linux systems for AI-related tasks.
files-to-prompt
files-to-prompt is a tool that concatenates a directory full of files into a single prompt for use with Language Models (LLMs). It allows users to provide the path to one or more files or directories for processing, outputting the contents of each file with relative paths and separators. The tool offers options to include hidden files, ignore specific patterns, and exclude files specified in .gitignore. It is designed to streamline the process of preparing text data for LLMs by simplifying file concatenation and customization.
shortest
Shortest is a project for local development that helps set up environment variables and services for a web application. It provides a guide for setting up Node.js and pnpm dependencies, configuring services like Clerk, Vercel Postgres, Anthropic, Stripe, and GitHub OAuth, and running the application and tests locally.
llm-functions
LLM Functions is a project that enables the enhancement of large language models (LLMs) with custom tools and agents developed in bash, javascript, and python. Users can create tools for their LLM to execute system commands, access web APIs, or perform other complex tasks triggered by natural language prompts. The project provides a framework for building tools and agents, with tools being functions written in the user's preferred language and automatically generating JSON declarations based on comments. Agents combine prompts, function callings, and knowledge (RAG) to create conversational AI agents. The project is designed to be user-friendly and allows users to easily extend the capabilities of their language models.
rlhf-book
RLHF Book is a work-in-progress textbook covering the fundamentals of Reinforcement Learning from Human Feedback (RLHF). It is built on the Pandoc book template and is meant for people with a basic ML and/or software background. The content for the book is licensed under the Creative Commons Non-Commercial Attribution License, CC BY-NC 4.0. The repository contains a simple template for building Pandoc documents, allowing users to compile markdown files into readable files such as PDF, EPUB, and HTML.
tiledesk-dashboard
Tiledesk is an open-source live chat platform with integrated chatbots written in Node.js and Express. It is designed to be a multi-channel platform for web, Android, and iOS, and it can be used to increase sales or provide post-sales customer service. Tiledesk's chatbot technology allows for automation of conversations, and it also provides APIs and webhooks for connecting external applications. Additionally, it offers a marketplace for apps and features such as CRM, ticketing, and data export.
ethereum-etl-airflow
This repository contains Airflow DAGs for extracting, transforming, and loading (ETL) data from the Ethereum blockchain into BigQuery. The DAGs use the Google Cloud Platform (GCP) services, including BigQuery, Cloud Storage, and Cloud Composer, to automate the ETL process. The repository also includes scripts for setting up the GCP environment and running the DAGs locally.
clickclickclick
ClickClickClick is a framework designed to enable autonomous Android and computer use using various LLM models, both locally and remotely. It supports tasks such as drafting emails, opening browsers, and starting games, with current support for local models via Ollama, Gemini, and GPT 4o. The tool is highly experimental and evolving, with the best results achieved using specific model combinations. Users need prerequisites like `adb` installation and USB debugging enabled on Android phones. The tool can be installed via cloning the repository, setting up a virtual environment, and installing dependencies. It can be used as a CLI tool or script, allowing users to configure planner and finder models for different tasks. Additionally, it can be used as an API to execute tasks based on provided prompts, platform, and models.
TalkWithGemini
Talk With Gemini is a web application that allows users to deploy their private Gemini application for free with one click. It supports Gemini Pro and Gemini Pro Vision models. The application features talk mode for direct communication with Gemini, visual recognition for understanding picture content, full Markdown support, automatic compression of chat records, privacy and security with local data storage, well-designed UI with responsive design, fast loading speed, and multi-language support. The tool is designed to be user-friendly and versatile for various deployment options and language preferences.
tenere
Tenere is a TUI interface for Language Model Libraries (LLMs) written in Rust. It provides syntax highlighting, chat history, saving chats to files, Vim keybindings, copying text from/to clipboard, and supports multiple backends. Users can configure Tenere using a TOML configuration file, set key bindings, and use different LLMs such as ChatGPT, llama.cpp, and ollama. Tenere offers default key bindings for global and prompt modes, with features like starting a new chat, saving chats, scrolling, showing chat history, and quitting the app. Users can interact with the prompt in different modes like Normal, Visual, and Insert, with various key bindings for navigation, editing, and text manipulation.
docker-cups-airprint
This repository provides a Docker image that acts as an AirPrint bridge for local printers, allowing them to be exposed to iOS/macOS devices. It runs a container with CUPS and Avahi to facilitate this functionality. Users must have CUPS drivers available for their printers. The tool requires a Linux host and a dedicated IP for the container to avoid interference with other services. It supports setting up printers through environment variables and offers options for automated configuration via command line, web interface, or files. The repository includes detailed instructions on setting up and testing the AirPrint bridge.
air
Air is a live-reloading command line utility for developing Go applications. It provides colorful log output, customizable build or any command, support for excluding subdirectories, and allows watching new directories after Air started. Users can overwrite specific configuration from arguments and pass runtime arguments for running the built binary. Air can be installed via `go install`, `install.sh`, or `goblin.run`, and can also be used with Docker/Podman. It supports debugging, Docker Compose, and provides a Q&A section for common issues. The tool requires Go 1.16+ for development and welcomes pull requests. Air is released under the GNU General Public License v3.0.
For similar tasks
zsh-github-copilot
zsh-github-copilot is a `zsh` plugin that enhances the GitHub Copilot experience by providing keybinds to quickly access command explanations and get Copilot suggestions. It integrates seamlessly with GitHub CLI and offers a smooth setup process. Users can easily install the plugin using popular zsh plugin managers like antigen, oh-my-zsh, zinit, zplug, and zpm. By binding specific keys, users can access the 'suggest' and 'explain' functionalities to improve their coding workflow with GitHub Copilot. This plugin is designed to streamline the usage of GitHub Copilot within the zsh shell environment.
zsh_codex
Zsh Codex is a ZSH plugin that enables AI-powered code completion in the command line. It supports both OpenAI's Codex and Google's Generative AI (Gemini), providing advanced language model capabilities for coding tasks directly in the terminal. Users can easily install the plugin and configure it to enhance their coding experience with AI assistance.
wtf.nvim
wtf.nvim is a Neovim plugin that enhances diagnostic debugging by providing explanations and solutions for code issues using ChatGPT. It allows users to search the web for answers directly from Neovim, making the debugging process faster and more efficient. The plugin works with any language that has LSP support in Neovim, offering AI-powered diagnostic assistance and seamless integration with various resources for resolving coding problems.
pearai-submodule
PearAI Submodule / Extension is the source code for the bulk of PearAI's functionality, bundled as a VSCode / PearAI extension. It allows users to easily understand code sections, refactor functions, and ask questions by mentioning a file. The tool aims to enhance coding experience and productivity within the VSCode environment.
GPThemes
GPThemes is a GitHub repository that provides a collection of customizable themes for various programming languages and text editors. It offers a wide range of color schemes and styling options to enhance the visual appearance of code editors and terminals. Users can easily browse through the available themes and apply them to their preferred development environment to personalize the coding experience. With GPThemes, developers can quickly switch between different themes to find the one that best suits their preferences and workflow, making coding more enjoyable and visually appealing.
For similar jobs
weave
Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.
agentcloud
AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.
oss-fuzz-gen
This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.
LLMStack
LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.
VisionCraft
The VisionCraft API is a free API for using over 100 different AI models. From images to sound.
kaito
Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.
PyRIT
PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.
Azure-Analytics-and-AI-Engagement
The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.