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Static

Overview​

static provides deterministic model choice without metrics or learned state. It selects the first entry in a decision's modelRefs by default. A matched domain can supply fixed model_scores; the selector uses the highest score when it differs from the default score sentinel of 1.0.

Key Advantages​

  • Deterministic and easy to audit.
  • Has no selector model, metrics, or storage dependency.
  • Provides a stable baseline for other selection policies.

What Problem Does It Solve?​

Some routes already have an intentional model order or fixed per-domain scores and do not need an online ranking policy. Static makes that choice explicit.

When to Use​

Use Static for deterministic routing, as a baseline when comparing selectors, or when an external process owns candidate ordering. If a decision has only one candidate, you can usually omit the algorithm entirely.

Configuration​

algorithm:
  type: static

Place the intended fallback winner first in modelRefs. To rank with domain model_scores, score every candidate and avoid 1.0, which is reserved by the selector's first-candidate fallback. See a complete example: config/fragments/algorithm/selection/static.yaml.

Dependencies and Limitations​

  • No external dependencies and no request-content processing beyond ordinary decision matching.
  • It does not fail over to later candidates, react to load, or learn from outcomes. Backend availability remains the responsibility of the normal provider path.