Rust Framework Unifies LLM Gateway and Multi-Agent Orchestration in One Runtime

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A developer building multi-agent systems in Rust identified two recurring architectural problems: redundant infrastructure from running separate model gateways and agent orchestrators, and brittle multi-turn reasoning caused by agents reinitializing context from scratch each turn. To address this, a unified Tokio-based runtime was designed that supports two operational modes — one for multi-agent orchestration using dynamic task graphs, and another acting as a standard LLM inference gateway with OpenAI-compatible endpoints. Both modes share the same connection pooling, authentication, and telemetry layers, eliminating duplicated infrastructure. The system also introduces an opt-in four-tier context engine that gives agents persistent conversational memory across turns while maintaining backward compatibility with simpler stateless setups.

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