ALTK‑Evolve trains agents in real‑time, achieving a 30% faster adaptation rate compared to baseline methods. The Hugging Face lab demonstrates the system on a suite of dialogue tasks, showing agents can refine policies while interacting with users. Practitioners can integrate the framework into existing pipelines to accelerate deployment. The open‑source release includes a lightweight inference engine and a training script.