Model Selection Orchestrator

Choose an Ollama model based on task intent and emit a consistent tuning preset.

Workflow

1. List local models with ollama list.
2. Map the task to a preference list and pick the first available model.
3. Emit a recommended model, a backup, and a tuning preset.
4. Fall back to the fastest available model when none match.

Scripts

• Run: python skills/tuning/model-selection-orchestrator/scripts/recommend_model.py --task reasoning

References

• references/presets.json