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Squashed feat/pii-ner-tier-engine rebased onto master (was 45 commits; see backup/pii-ner-tier-engine-prerebase). Net change: - privacy-filter.cpp: standalone GGML engine for the openai-privacy-filter PII/NER token classifier, wired as a LocalAI gRPC backend (CPU/CUDA/Vulkan). TokenClassify moves off the patched llama.cpp path onto this backend. - PII filter reworked to be NER-centric (encoder/NER detection tier scanning whole conversations as one document), with a recreated bounded restricted- regex secret-matching pattern detector tier alongside it (per-model pii_detection.builtins / .patterns + core/services/routing/piipattern). - Detection labelled by source (ner vs pattern); backend trace / confidence / debug observability; analyze/redact exposed as a synchronous API. - Instance-wide default detector policy + per-usecase default-on; request filtering extended to completions, embeddings, edits & Ollama. - React UI: NER-centric PII editor, detector-models table, pattern/builtins editor, middleware default-policy UI. - Gallery: privacy-filter-multilingual token-classify model + NER install filter; token_classify known_usecase; batch sized to context for NER models. privacy-filter backend registered in the backend gallery (cpu/vulkan/cuda-13 meta + image entries with a capabilities map) matching its CI matrix jobs, and an /import-model auto-detect importer (PrivacyFilterImporter, narrow privacy-filter GGUF detection) replacing the prior pref-only registration. Reconciled against master's independent evolution: - Dropped master's PIIPatternOverrides feature (global-pattern runtime overrides + /api/pii/patterns API + runtime_settings.json persistence). The per-model NER + pattern-detector design supersedes it; it was built on the global redactor pattern set this branch replaced. - Reverted the llama.cpp Score carry-patch (0006-server-task-type-score): removed the patch and restored master's grpc-server.cpp Score RPC (direct llama_decode, slot-loop bypass) and LLAMA_VERSION pin, plus master's model_config validation forbidding score + chat/completion/embeddings on llama-cpp. token_classify is unaffected (it runs on the privacy-filter backend, not llama-cpp). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com>
84 lines
3.5 KiB
Go
84 lines
3.5 KiB
Go
package routes
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import (
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"net/http"
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"strconv"
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"github.com/labstack/echo/v4"
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"github.com/mudler/LocalAI/core/application"
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"github.com/mudler/LocalAI/core/http/auth"
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"github.com/mudler/LocalAI/core/http/endpoints/localai"
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"github.com/mudler/LocalAI/core/services/routing/pii"
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)
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// RegisterPIIRoutes wires the read-only PII audit endpoint. The
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// detection itself runs request-side from the chat middleware
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// (routes/openai.go) and the MITM input path, driven by per-model NER
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// detectors; this endpoint is observation-side only.
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//
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// The legacy regex tier (pattern catalogue + per-pattern action editor
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// + dry-run/decide oracles) was removed — policy now lives on each
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// detector model's pii_detection block, so there is nothing global to
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// list or mutate here.
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func RegisterPIIRoutes(e *echo.Echo, app *application.Application) {
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if app.PIIEvents() == nil {
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e.GET("/api/pii/events", func(c echo.Context) error {
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return c.JSON(http.StatusServiceUnavailable, map[string]string{
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"error": "PII subsystem unavailable",
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})
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})
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return
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}
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// GetPIIEventsEndpoint godoc
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// @Summary List recent middleware events
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// @Description The event log is shared between the PII filter and the MITM proxy: PII redactions, proxy_connect (intercept decisions), and proxy_traffic (per-request byte counts) all flow through the same store. Filter by kind to narrow the view. Admin-only when auth is on; available to the local user in single-user mode.
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// @Tags pii
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// @Produce json
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// @Param correlation_id query string false "Correlation ID join key"
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// @Param user_id query string false "User id"
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// @Param pattern_id query string false "Detector group id (e.g. ner:EMAIL, pattern:ANTHROPIC_KEY)"
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// @Param kind query string false "Event kind: pii | proxy_connect | proxy_traffic"
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// @Param origin query string false "Redaction origin: middleware | proxy | pii_analyze | pii_redact"
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// @Param limit query int false "Max events" default(100)
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// @Success 200 {object} map[string]interface{}
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// @Router /api/pii/events [get]
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e.GET("/api/pii/events", func(c echo.Context) error {
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viewer := resolveUsageUser(c, app)
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if viewer == nil {
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return c.JSON(http.StatusUnauthorized, map[string]string{"error": "not authenticated"})
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}
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// Admin-only when auth is enabled. Local user has Role: admin.
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if viewer.Role != auth.RoleAdmin {
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return c.JSON(http.StatusForbidden, map[string]string{"error": "admin access required"})
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}
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limit := 100
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if v := c.QueryParam("limit"); v != "" {
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if n, err := strconv.Atoi(v); err == nil && n > 0 {
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limit = n
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}
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}
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events, err := app.PIIEvents().List(c.Request().Context(), pii.ListQuery{
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CorrelationID: c.QueryParam("correlation_id"),
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UserID: c.QueryParam("user_id"),
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PatternID: c.QueryParam("pattern_id"),
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Kind: pii.EventKind(c.QueryParam("kind")),
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Origin: c.QueryParam("origin"),
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Limit: limit,
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})
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if err != nil {
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return c.JSON(http.StatusInternalServerError, map[string]string{"error": "failed to list events"})
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}
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return c.JSON(http.StatusOK, map[string]any{"events": events})
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})
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// Synchronous redaction service: scan a string and either report the
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// detected entities (analyze) or apply the policy (redact). Unlike the
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// admin-only events log above, these are an inference-tier service gated
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// by the pii_filter feature (any authenticated user), so a client can use
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// LocalAI's PII engine without routing a full chat request through it.
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e.POST("/api/pii/analyze", localai.PIIAnalyzeEndpoint(app))
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e.POST("/api/pii/redact", localai.PIIRedactEndpoint(app))
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}
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