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Algorithm

Overview

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Algorithm

Overview​

Latest algorithm tutorials mirror the fragment catalog under config/algorithm/.

Algorithms only matter after a decision matches and exposes multiple candidate models in modelRefs. The router then uses decision.algorithm to choose or coordinate those candidates.

Key Advantages​

  • Separates route eligibility from model selection policy.
  • Lets one decision keep several candidate models without inlining ranking logic.
  • Supports both one-model ranking and multi-model orchestration.
  • Mirrors the repo fragment tree exactly: one tutorial page per algorithm under config/algorithm/selection/ and config/algorithm/looper/.

What Problem Does It Solve?​

Once a route matches, the router still needs a principled way to choose among candidate models. Without an algorithm layer, teams either hard-code one winner or duplicate ranking logic across routes.

Algorithms solve that by making the post-match selection policy explicit and reusable.

When to Use​

Use algorithm/ when:

  • modelRefs contains more than one candidate
  • route policy depends on latency, feedback, semantic fit, or online exploration
  • one decision should orchestrate several models instead of choosing exactly one
  • you want model choice to evolve without changing the decision rule itself

Configuration​

In canonical v0.3 YAML, algorithms live inside each matched decision:

routing:
  decisions:
    - name: computer-science-reasoning
      rules:
        operator: AND
        conditions:
          - type: domain
            name: "computer science"
      modelRefs:
        - model: qwen2.5:7b
        - model: qwen3:14b
      algorithm:
        type: router_dc
        router_dc:
          temperature: 0.07

The repo now keeps one tutorial page per algorithm.

Selection Algorithms​

Looper Algorithms​