ModelPreferences extension type
The server's preferences for model selection, requested of the client during sampling.
Because LLMs can vary along multiple dimensions, choosing the "best" model is rarely straightforward. Different models excel in different areas—some are faster but less capable, others are more capable but more expensive, and so on. This interface allows servers to express their priorities across multiple dimensions to help clients make an appropriate selection for their use case.
These preferences are always advisory. The client MAY ignore them. It is also up to the client to decide how to interpret these preferences and how to balance them against other considerations.
Constructors
-
ModelPreferences({List<
ModelHint> ? hints, double? costPriority, double? speedPriority, double? intelligencePriority}) -
factory
-
ModelPreferences.fromMap(Map<
String, Object?> _value)
Properties
- costPriority → double?
-
How much to prioritize cost when selecting a model.
no setter
-
hints
→ List<
ModelHint> ? -
Optional hints to use for model selection.
no setter
- intelligencePriority → double?
-
How much to prioritize intelligence and capabilities when selecting a
model.
no setter
- speedPriority → double?
-
How much to prioritize sampling speed (latency) when selecting a model.
no setter