ARES
ARES — a Go-native, multi-agent runtime with an adaptive knowledge graph
ARES is a Go-native multi-agent runtime. It provides a unified SDK for building LLM-powered agents with built-in memory, tool calling, an adaptive knowledge graph (AKG), strategy evolution, and MCP integration.
Key features
- Unified Runtime — one entry point (
sdk.NewRuntime) wires the LLM client, tool registry, memory, knowledge fabric, and evolution system. - Adaptive Knowledge Graph (AKG) — distills conversations into fact-level KnowledgeObjects with quality gating and hybrid retrieval (vector + lexical), no LLM required in the build/retrieve loop.
- Multi-provider LLM — OpenAI, Ollama, Anthropic, OpenRouter, plus automatic failover across fallback providers.
- Tool calling — built-in tools, custom tools, MCP-discovered tools, and a capability planner for intent-based tool resolution.
- Agent OS kernel — agents are scheduled processes, not workflow nodes.
Work is durable
Taskintent (checkpoint + lease + epoch fencing); the kernel scheduler drivesSchedule → Acquire → RunQuantum → finalize, so an agent dying does not kill the task (lease expiry requeues it). - Dynamic graphs — the live topology is a
MutableDAG(internal/fabric/task/workflow/engine): session L2 graphs grow per quantum (plan/tool/answer nodes) and compile incrementally into the task fabric viaplanprojection; evolution structure patches mutate DAG objects in place. See the workflow module page. - Strategy evolution — GA over instruction/LLM-parameter strategies: population scoring, lifecycle gates (shadow/eval/rollback) and a coordinator applying patches from multiple sources. Verified gate semantics documented on the ares_evolution module page.
- Bilingual documentation — every module page is available in English and Chinese. Pages are audited against the source tree; where a page lags, the source is authoritative.
Explore
Start with the Architecture overview, then browse the Module reference for per-package details, or read the Guides for deployment and extension walkthroughs.