24 Simultaneous Claude Code agents on local hardware (github.com)

A new orchestrator, tokio-prompt-orchestrator, has been announced that enables the management of 24 simultaneous Claude Code agents on local hardware for AI model inference. This production-ready system optimizes costs and enhances reliability with a comprehensive 5-stage pipeline handling requests through RAG, assembly, inference, post-processing, and response, integrating features like request deduplication to save 60-80% on inference costs and a circuit breaker to prevent cascading failures. This development is significant for the AI/ML community as it highlights a push toward more efficient, scalable local inference solutions that combine multiple models and backends, such as OpenAI's GPT-4 and Claude 3.5. With support for REST APIs and WebSockets, along with enterprise-grade observability through Prometheus and Grafana integration, it promises high reliability, low latency, and real-time monitoring capabilities. The architecture facilitates hot-swapping of models and settings, enabling flexible configurations to suit production needs while helping organizations reduce costs significantly, potentially saving up to $273,600 annually with improved success rates and reduced user-visible errors.