calibrate.go

@@ -2,6 +2,7 @@ package i18n
 
 import (
 	"context"
+	"errors"
 	"fmt"
 	"time"
 
@@ -48,7 +49,7 @@ func CalibrateDomains(ctx context.Context, modelA, modelB inference.TextModel,
 	samples []CalibrationSample, opts ...ClassifyOption) (*CalibrationStats, error) {
 
 	if len(samples) == 0 {
-		return nil, fmt.Errorf("calibrate: empty sample set")
+		return nil, errors.New("calibrate: empty sample set")
 	}
 
 	cfg := defaultClassifyConfig()

reversal/reference.go

@@ -1,9 +1,10 @@
 package reversal
 
 import (
-	"fmt"
+	"errors"
+	"maps"
 	"math"
-	"sort"
+	"slices"
 )
 
 // ClassifiedText is a text sample with a domain label (from 1B model or ground truth).
@@ -45,7 +46,7 @@ type ImprintClassification struct {
 // per unique domain label.
 func BuildReferences(tokeniser *Tokeniser, samples []ClassifiedText) (*ReferenceSet, error) {
 	if len(samples) == 0 {
-		return nil, fmt.Errorf("empty sample set")
+		return nil, errors.New("empty sample set")
 	}
 
 	// Group imprints by domain.
@@ -60,7 +61,7 @@ func BuildReferences(tokeniser *Tokeniser, samples []ClassifiedText) (*Reference
 	}
 
 	if len(grouped) == 0 {
-		return nil, fmt.Errorf("no samples with domain labels")
+		return nil, errors.New("no samples with domain labels")
 	}
 
 	rs := &ReferenceSet{Domains: make(map[string]*ReferenceDistribution)}
@@ -105,7 +106,15 @@ func (rs *ReferenceSet) Classify(imprint GrammarImprint) ImprintClassification {
 	for d, m := range distances {
 		ranked = append(ranked, scored{d, m.CosineSimilarity})
 	}
-	sort.Slice(ranked, func(i, j int) bool { return ranked[i].sim > ranked[j].sim })
+	slices.SortFunc(ranked, func(a, b scored) int {
+		if a.sim > b.sim {
+			return -1
+		}
+		if a.sim < b.sim {
+			return 1
+		}
+		return 0
+	})
 
 	result := ImprintClassification{Distances: distances}
 	if len(ranked) > 0 {
@@ -121,12 +130,7 @@ func (rs *ReferenceSet) Classify(imprint GrammarImprint) ImprintClassification {
 
 // DomainNames returns sorted domain names in the reference set.
 func (rs *ReferenceSet) DomainNames() []string {
-	names := make([]string, 0, len(rs.Domains))
-	for d := range rs.Domains {
-		names = append(names, d)
-	}
-	sort.Strings(names)
-	return names
+	return slices.Sorted(maps.Keys(rs.Domains))
 }
 
 // computeCentroid averages imprints into a single centroid.

service.go

@@ -3,6 +3,7 @@ package i18n
 import (
 	"embed"
 	"encoding/json"
+	"errors"
 	"fmt"
 	"io/fs"
 	"maps"
@@ -97,7 +98,7 @@ func NewWithLoader(loader Loader, opts ...Option) (*Service, error) {
 
 	langs := loader.Languages()
 	if len(langs) == 0 {
-		return nil, fmt.Errorf("no languages available from loader")
+		return nil, errors.New("no languages available from loader")
 	}
 
 	for _, lang := range langs {
@@ -181,7 +182,7 @@ func (s *Service) SetLanguage(lang string) error {
 		return fmt.Errorf("invalid language tag %q: %w", lang, err)
 	}
 	if len(s.availableLangs) == 0 {
-		return fmt.Errorf("no languages available")
+		return errors.New("no languages available")
 	}
 	matcher := language.NewMatcher(s.availableLangs)
 	bestMatch, _, confidence := matcher.Match(requestedLang)