Kolosal CLI is a super lightweight, AI-powered command-line tool designed to enhance developer workflows by providing advanced code understanding, automated task execution, and intelligent assistance. It serves as an alternative to Ollama and Qwen Code for running various large language models, aiming to streamline complex coding tasks and boost developer productivity.

How It Works

The tool is built upon Qwen Code models, featuring an enhanced parser optimized for code-centric LLMs. This allows it to query and edit large codebases beyond typical context window limitations. Kolosal CLI automates operational tasks like handling pull requests and rebasing, supports multimodal analysis of images, and integrates flexibly with OpenAI-compatible APIs and Hugging Face models.

Quick Start & Requirements

• Installation: Recommended quick install via curl -fsSL https://raw.githubusercontent.com/KolosalAI/kolosal-cli/main/install.sh | bash. Alternatives include npm install -g @kolosal-ai/kolosal-ai@latest (requires Node.js >= 20), manual .pkg (macOS) or .deb (Linux) downloads, or building from source.
• Prerequisites: Node.js version 20+ for npm installation.
• Links: Installation details, Contributing. Homebrew support is planned.

Highlighted Details

• Processes codebases exceeding traditional context window limits.
• Automates complex development workflows (e.g., PR handling, rebasing).
• Features automatic image detection and multimodal analysis.
• Supports flexible model integration via OpenAI-compatible APIs and Hugging Face.
• Includes an experimental embedded API for programmatic interaction.

Maintenance & Community

The project provides a CONTRIBUTING.md file, indicating a pathway for community involvement. No explicit links to community channels (e.g., Discord, Slack) or a public roadmap are present in the README.

Licensing & Compatibility

Licensed under the Apache License, Version 2.0. Compatible with OpenAI-compatible APIs and Hugging Face models, facilitating integration with various LLM backends.

Limitations & Caveats

The embedded API is experimental. The tool may incur higher token usage due to multiple API calls per cycle, with ongoing optimization efforts. The Linux package version (0.1.2) suggests a potentially early-stage release.