ibrahimiq-qcmd 1.0.4

AI-powered Command Generator using Local LLMs

qcmd - AI-powered Command Generator

A simple command-line tool that generates shell commands using local AI models via Ollama.

Version 1.0.3

Overview

qcmd is a powerful command-line tool that generates shell commands using AI language models via Ollama. Simply describe what you want to do in natural language, and qcmd will generate the appropriate command.

Key Features

• Natural Language Inputs: Describe what you want to do in plain English
• Auto-fix Mode: Automatically fixes failed commands and retries
• AI Error Analysis: Explains errors and suggests solutions
• Interactive Shell: Continuous operation with command history
• Multiple Models: Works with any Ollama model (default: qwen2.5-coder:0.5b)
• Safety First: Always asks for confirmation before executing any command
• Log Analysis: Find and analyze system log files with real-time monitoring

Installation

Prerequisites

• Python 3.6 or higher
• Ollama installed and running
• At least one language model pulled (e.g., qwen2.5-coder:0.5b)

Install from PyPI

pip install ibrahimiq-qcmd

Make sure Ollama is running before using qcmd:

ollama serve

Basic Usage

# Generate and confirm a command
qcmd "list all files in the current directory"

# Auto-execute mode
qcmd -e "find large log files"

# Smart auto-fix mode
qcmd -A "find Python files modified today"

# Interactive shell
qcmd -s

What's New in 1.0.3

• Implemented improved release automation workflow
• Enhanced package publishing process
• Updated GitHub Actions configuration
• Streamlined deployment process
• Documentation improvements for contributors

What's New in 1.0.2

• Fixed undefined variable errors in interactive shell and auto mode
• Improved error handling and command detection for dangerous operations
• Streamlined GitHub Actions workflow for Python 3.10 and 3.11
• Enhanced compatibility with continuous integration systems
• Fixed tab completion issues in interactive shell

What's New in 1.0.1

• Updated documentation with improved installation instructions
• Fixed package structure for better compatibility
• Added PyPI integration for easier installation

Full Documentation

For full documentation and source code, visit the GitHub repository.