- Added tier boundary descriptions (fast/standard/heavy) to the classifier
system prompt so gpt-5.4-nano understands what each complexity band means
- Added signal keywords for higher/lower ratings to reduce misclassification
of simple requests as complex and vice versa
Upgrades the routing engine to support tag, token limit, multimodal, reasoning, and tool calling conditions. Adds unit tests for the new routing features.
Classifier: When complexity_threshold is set (e.g. 10), uses it as the
rating scale and maps ratings proportionally to target buckets instead
of 1:1. Formula: idx = rating * len(targets) / (threshold + 1).
With threshold=10 and 3 targets: 1-3→target[0], 4-7→target[1], 8-10→target[2].
Seed: Added 'dispatcher' group (classifier, threshold=10, selector=deepseek-v4-flash)
that auto-routes to fast-flow/standard-pro/heavy-logic by complexity score.
Combined with hierarchical routing, this enables two-level dispatch:
dispatcher scores 1-10 → routes to tier group → tier picks concrete model.
RouteToConcrete() recursively resolves group chains until a concrete
model is reached, with cycle detection and max depth (10) guard.
Example: all-purpose -> fast-flow -> deepseek-v4-flash
The dashboard log shows the full chain: 'deepseek-v4-flash (hierarchical:
fast-flow (default (first target)) -> deepseek-v4-flash (default (first target)))'
Add Groups() method to Router so handleListModels can append model
group IDs (e.g. 'deepseek-auto', 'openai-auto') to the model list,
marked with owned_by: 'gophergate'. This lets clients discover and
use groups via the standard OpenAI /v1/models endpoint.
newkirk
hobokenchicken