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- Skill optimization framework with training loop analogy - 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen) - WebUI for browser-based training control - Pluggable architecture for extending benchmarks and backends
8 lines
372 B
Python
8 lines
372 B
Python
"""ReflACT Evaluation -- candidate skill validation and model selection.
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Analogous to validation-based early stopping and model selection in neural
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network training: evaluates candidate skills on held-out selection sets and
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decides whether to accept or reject proposed updates.
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"""
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from skillopt.evaluation.gate import evaluate_gate, GateAction, GateResult # noqa: F401
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