ARES (Agent Runtime & Evolution System)
What it is
ARES is a multi-agent runtime and framework for building resilient AI agents in Go. It features a self-evolving DAG workflow, chaos engineering for self-healing, and an experimental LLM-free knowledge graph (AKG) that uses rule-based extraction and hybrid search.
The problem it solves
Addresses the fragility of AI agent workflows (lack of recovery/robustness) and the high cost/unreliability of using LLMs for knowledge graph construction.
What you could use it for
- Building multi-agent systems with automated failover and self-healing capabilities.
- Developing AI agents that evolve their own workflow DAGs and recovery strategies in production.
- Creating knowledge-heavy agents that require high-precision, low-cost fact retrieval without LLM-based extraction costs.
- Orchestrating complex tasks using a unified SDK that supports Model Context Protocol (MCP) for tools.
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.