Stricter data-sovereignty mandates often require public institutions to run on-premise agents against live government APIs, where open-weight models frequently struggle with multi-step reasoning. To address this shortfall, researchers introduced KOPA-Bench—a suite of 145 real-world tasks—and EDGE, a data synthesis framework that maps API input-output compatibilities and retains only chains verified through live execution. Trained on these grounded trajectories using GRPO, a 9B model achieved tool-calling accuracy comparable to an untuned 27B counterpart across both local public endpoints and the standard BFCL benchmark.
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