AI tools for zsh_codex
Related Tools:
How2
How2 is an AI tool designed for the Command-Line interface, utilizing AI models to suggest shell commands directly from the Unix Terminal. It offers up to 5 free queries per day and aims to enhance the Command Line experience by providing quick Bash script creation and StackOverflow search capabilities. The tool is focused on improving AI models retrained on Bash/Zsh commands to cater to user needs effectively and safely.
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.
shellChatGPT
ShellChatGPT is a shell wrapper for OpenAI's ChatGPT, DALL-E, Whisper, and TTS, featuring integration with LocalAI, Ollama, Gemini, Mistral, Groq, and GitHub Models. It provides text and chat completions, vision, reasoning, and audio models, voice-in and voice-out chatting mode, text editor interface, markdown rendering support, session management, instruction prompt manager, integration with various service providers, command line completion, file picker dialogs, color scheme personalization, stdin and text file input support, and compatibility with Linux, FreeBSD, MacOS, and Termux for a responsive experience.
hof
Hof is a CLI tool that unifies data models, schemas, code generation, and a task engine. It allows users to augment data, config, and schemas with CUE to improve consistency, generate multiple Yaml and JSON files, explore data or config with a TUI, and run workflows with automatic task dependency inference. The tool uses CUE to power the DX and implementation, providing a language for specifying schemas, configuration, and writing declarative code. Hof offers core features like code generation, data model management, task engine, CUE cmds, creators, modules, TUI, and chat for better, scalable results.
gp.nvim
Gp.nvim (GPT prompt) Neovim AI plugin provides a seamless integration of GPT models into Neovim, offering features like streaming responses, extensibility via hook functions, minimal dependencies, ChatGPT-like sessions, instructable text/code operations, speech-to-text support, and image generation directly within Neovim. The plugin aims to enhance the Neovim experience by leveraging the power of AI models in a user-friendly and native way.
llm.nvim
llm.nvim is a universal plugin for a large language model (LLM) designed to enable users to interact with LLM within neovim. Users can customize various LLMs such as gpt, glm, kimi, and local LLM. The plugin provides tools for optimizing code, comparing code, translating text, and more. It also supports integration with free models from Cloudflare, Github models, siliconflow, and others. Users can customize tools, chat with LLM, quickly translate text, and explain code snippets. The plugin offers a flexible window interface for easy interaction and customization.
shell_gpt
ShellGPT is a command-line productivity tool powered by AI large language models (LLMs). This command-line tool offers streamlined generation of shell commands, code snippets, documentation, eliminating the need for external resources (like Google search). Supports Linux, macOS, Windows and compatible with all major Shells like PowerShell, CMD, Bash, Zsh, etc.
amazon-q-developer-cli
The `amazon-q-developer-cli` monorepo houses core code for the Amazon Q Developer desktop app and CLI. It includes projects like autocomplete, dashboard, figterm, q CLI, fig_desktop, fig_input_method, VSCode plugin, and JetBrains plugin. The repo also contains build scripts, internal rust crates, internal npm packages, protocol buffer message specification, and integration tests. The architecture involves different components communicating via IPC.
prompty
Prompty is an asset class and format for LLM prompts designed to enhance observability, understandability, and portability for developers. The primary goal is to accelerate the developer inner loop. This repository contains the Prompty Language Specification and a documentation site. The Visual Studio Code extension offers a prompt playground to streamline the prompt engineering process.
fasttrackml
FastTrackML is an experiment tracking server focused on speed and scalability, fully compatible with MLFlow. It provides a user-friendly interface to track and visualize your machine learning experiments, making it easy to compare different models and identify the best performing ones. FastTrackML is open source and can be easily installed and run with pip or Docker. It is also compatible with the MLFlow Python package, making it easy to integrate with your existing MLFlow workflows.
aiodocker
Aiodocker is a simple Docker HTTP API wrapper written with asyncio and aiohttp. It provides asynchronous bindings for interacting with Docker containers and images. Users can easily manage Docker resources using async functions and methods. The library offers features such as listing images and containers, creating and running containers, and accessing container logs. Aiodocker is designed to work seamlessly with Python's asyncio framework, making it suitable for building asynchronous Docker management applications.
yoyak
Yoyak is a small CLI tool powered by LLM for summarizing and translating web pages. It provides shell completion scripts for bash, fish, and zsh. Users can set the model they want to use and summarize web pages with the 'yoyak summary' command. Additionally, translation to other languages is supported using the '-l' option with ISO 639-1 language codes. Yoyak supports various models for summarization and translation tasks.
air
Air is a live-reloading command line utility for developing Go applications. It provides colorful log output, allows customization of build or any command, supports excluding subdirectories, and allows watching new directories after Air has started. Air can be installed via `go install`, `install.sh`, `goblin.run`, or Docker/Podman. To use Air, simply run `air` in your project root directory and leave it alone to focus on your code. Air has nothing to do with hot-deploy for production.
unsloth
Unsloth is a tool that allows users to fine-tune large language models (LLMs) 2-5x faster with 80% less memory. It is a free and open-source tool that can be used to fine-tune LLMs such as Gemma, Mistral, Llama 2-5, TinyLlama, and CodeLlama 34b. Unsloth supports 4-bit and 16-bit QLoRA / LoRA fine-tuning via bitsandbytes. It also supports DPO (Direct Preference Optimization), PPO, and Reward Modelling. Unsloth is compatible with Hugging Face's TRL, Trainer, Seq2SeqTrainer, and Pytorch code. It is also compatible with NVIDIA GPUs since 2018+ (minimum CUDA Capability 7.0).
obs-cleanstream
CleanStream is an OBS plugin that utilizes AI to clean live audio streams by removing unwanted words and utterances, such as 'uh's and 'um's, and configurable words like profanity. It uses a neural network (OpenAI Whisper) in real-time to predict speech and eliminate unwanted words. The plugin is still experimental and not recommended for live production use, but it is functional for testing purposes. Users can adjust settings and configure the plugin to enhance audio quality during live streams.
client-python
The Mistral Python Client is a tool inspired by cohere-python that allows users to interact with the Mistral AI API. It provides functionalities to access and utilize the AI capabilities offered by Mistral. Users can easily install the client using pip and manage dependencies using poetry. The client includes examples demonstrating how to use the API for various tasks, such as chat interactions. To get started, users need to obtain a Mistral API Key and set it as an environment variable. Overall, the Mistral Python Client simplifies the integration of Mistral AI services into Python applications.
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.