ralph-orchestrator
A hat-based orchestration framework that keeps AI agents in a loop until a task is complete, supporting multiple backends and human interaction.
What is ralph-orchestrator?
Ralph Orchestrator is an open-source framework for autonomous AI agent orchestration that implements the Ralph Wiggum technique. It provides a structured system for task completion through continuous iteration, enabling developers to automate complex coding and planning workflows with persistent learning and runtime tracking. The framework keeps AI agents in a loop until a task is done, integrating quality checks and human oversight.
Developers and engineers building automated AI agent workflows for software development, planning, and research tasks, particularly those who need persistent, iterative agents with multi-model support and human-in-the-loop capabilities.
Developers choose Ralph Orchestrator for its implementation of the Ralph Wiggum technique that ensures autonomous task completion through relentless iteration, combined with practical features like multi-backend AI model support, a specialized hat system for persona coordination, and built-in human-in-the-loop integration via Telegram. It offers a comprehensive framework with persistent memory, quality gates, and monitoring tools not found in simpler agent implementations.
Overview
An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration
Use Cases
Best For
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
