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Reef is an open-source infrastructure for continual learning in self-improving agents. It connects inference, feedback, and versioned delivery to allow training via Slime and SGLang or optimizing agent harnesses like prompts and rules. It acts as middleware between inference engines and RL frameworks to manage live updates without downtime.

It is worth exploring if you need an agent that improves from interaction logs rather than static retraining. The catch is that model weight training requires a trainable model and a supported GPU stack, which is a significant hardware commitment. It is not a drop-in replacement for simple API wrappers but a full deployment layer for evolving systems.

more: https://github.com/Human-Agent-Society/reef