Clippinator is an AI-powered code assistant designed to help users plan, write, debug, and test software projects autonomously or with user feedback. It targets developers seeking to accelerate their workflow, offering a multi-agent system that collaborates to achieve project goals, from high-level guidance to low-level function implementation.

How It Works

Clippinator employs a multi-agent architecture, with a central "Taskmaster" agent orchestrating specialized "minion" agents (e.g., Architect, Writer, QA). These agents, powered by GPT-4, leverage a shared understanding of the project's architecture, file structure, and linting status. They interact with various tools, including file I/O, bash commands, Selenium for browser automation, and HTTP requests, to execute tasks. The system aims for efficiency by summarizing history and allowing human intervention via ^C for feedback or manual adjustments to the project plan.

Quick Start & Requirements

• Install dependencies: poetry install
• Run: poetry run clippinator PROJECT_PATH
• Prerequisites: OpenAI API key (required), SerpAPI key (optional), ctags, pylint, pylint-venv.
• Setup involves cloning the repo, configuring .env with API keys, and installing Python dependencies via Poetry.

Highlighted Details

• Utilizes GPT-4 for agent capabilities, potentially leading to high OpenAI API costs.
• Agents can manage background processes (e.g., starting servers) via BashBackground.
• Integrates Selenium for browser automation, enabling page inspection and interaction.
• Supports manual editing of project architecture and objectives after initial planning.

Maintenance & Community

Created by Lev Chizhov and Timofey Fedoseev, with contributions from Sergei Bogdanov. Further community engagement details are not provided in the README.

Licensing & Compatibility

The README does not explicitly state the project's license. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The system relies on GPT-4, which can be expensive due to long execution times. While designed for autonomy, it can make mistakes and requires human feedback for complex tasks or to ensure accuracy. The README notes that subagent execution can be aborted with ^C, but the Architect agent has specific handling for feedback.