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wehub-resource-sync 1b8708893a
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chore: import upstream snapshot with attribution
2026-07-13 13:12:26 +08:00

82 lines
3.0 KiB
Go

package piidetector
import (
"context"
"time"
"github.com/mudler/LocalAI/core/backend"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/services/routing/pii"
"github.com/mudler/LocalAI/core/services/routing/piipattern"
"github.com/mudler/LocalAI/core/trace"
)
// NewPattern builds a pii.NERDetector that matches secrets with the restricted
// regex tier (built-ins + operator-defined patterns) instead of a neural model.
// It runs entirely in-process — no backend, GGUF, or VRAM — and the patterns
// compile once here, so an invalid pattern is reported now (the resolver fails
// closed) rather than per request. Matches are reported under their group with
// a deterministic Score of 1.0.
func NewPattern(modelConfig config.ModelConfig, appConfig *config.ApplicationConfig) (pii.NERDetector, error) {
custom := make([]piipattern.Pattern, 0, len(modelConfig.PIIDetection.Patterns))
for _, p := range modelConfig.PIIDetection.Patterns {
custom = append(custom, piipattern.Pattern{Group: p.Name, Pattern: p.Match, MinLen: p.MinLen})
}
m, err := piipattern.NewMatcher(modelConfig.PIIDetection.Builtins, custom)
if err != nil {
return nil, err
}
return &patternDetector{matcher: m, modelName: modelConfig.Name, appConfig: appConfig}, nil
}
type patternDetector struct {
matcher *piipattern.Matcher
modelName string
appConfig *config.ApplicationConfig
}
// Detect runs the compiled patterns and maps each match onto a pii.NEREntity.
// When tracing is enabled it records a pattern_pii BackendTrace so the matches
// (group, byte range, text) show in the Traces UI alongside NER detections.
func (d *patternDetector) Detect(_ context.Context, text string) ([]pii.NEREntity, error) {
tracing := d.appConfig != nil && d.appConfig.EnableTracing
var start time.Time
if tracing {
trace.InitBackendTracingIfEnabled(d.appConfig.TracingMaxItems, d.appConfig.TracingMaxBodyBytes)
start = time.Now()
}
matches := d.matcher.Find(text)
out := make([]pii.NEREntity, 0, len(matches))
var traceEnts []backend.TokenEntity
for _, mt := range matches {
out = append(out, pii.NEREntity{Group: mt.Group, Start: mt.Start, End: mt.End, Score: 1.0, Text: mt.Text})
if tracing {
traceEnts = append(traceEnts, backend.TokenEntity{Group: mt.Group, Start: mt.Start, End: mt.End, Score: 1.0, Text: mt.Text})
}
}
if tracing {
trace.RecordBackendTrace(patternPIITrace(d.modelName, text, traceEnts, start))
}
return out, nil
}
// patternPIITrace assembles the Traces-UI row for one pattern-detector run.
// Split out so the Data assembly is unit-testable without a request.
func patternPIITrace(modelName, text string, entities []backend.TokenEntity, start time.Time) trace.BackendTrace {
return trace.BackendTrace{
Timestamp: start,
Duration: time.Since(start),
Type: trace.BackendTracePatternPII,
ModelName: modelName,
Backend: "pattern",
Summary: trace.TruncateString(text, 200),
Data: map[string]any{
"input_chars": len(text),
"matches": len(entities),
"entities": entities,
},
}
}