Overview
ROMA (Recursive Open Meta-Agents) is an open-source meta-agent framework that recursively decomposes complex tasks into parallelizable subtasks. It supports multi-agent collaboration, transparent development, and high-performance reasoning, making it ideal for building scalable, extensible AI agent systems.
Key Features
- Recursive task decomposition and aggregation for efficient problem solving.
- Multi-agent parallel execution for faster reasoning and improved performance.
- Fully open-source, extensible by the community for custom agent development.
- Transparent, traceable execution for easy debugging and optimization.
Use Cases
- Automating research and academic reasoning workflows.
- Multi-dimensional analytics in finance, blockchain, and data science.
- Building reusable, high-performance AI agent systems.
- Scenarios requiring transparent, traceable task decomposition and execution.
Technical Highlights
- Python 3.12+ backend (FastAPI/Flask), React + TypeScript frontend.
- Supports multiple LLM backends and multimodal tool integration.
- Enterprise-grade S3 mounting, security validation, and E2B sandbox execution.