Files
LocalAI/core/http/routes/anthropic.go
Richard Palethorpe 3fa7b2955c feat(pii): NER tier engine — privacy-filter.cpp backend + NER-centric PII filter (#10360)
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>
2026-06-18 11:45:22 +01:00

143 lines
5.2 KiB
Go

package routes
import (
"context"
"fmt"
"net/http"
"github.com/google/uuid"
"github.com/labstack/echo/v4"
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/endpoints/anthropic"
mcpTools "github.com/mudler/LocalAI/core/http/endpoints/mcp"
"github.com/mudler/LocalAI/core/http/middleware"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/routing/pii"
"github.com/mudler/LocalAI/core/services/routing/piiadapter"
"github.com/mudler/LocalAI/core/services/routing/router"
"github.com/mudler/LocalAI/pkg/distributedhdr"
"github.com/mudler/xlog"
)
func RegisterAnthropicRoutes(app *echo.Echo,
re *middleware.RequestExtractor,
application *application.Application,
) {
// Anthropic Messages API endpoint
var natsClient mcpTools.MCPNATSClient
if d := application.Distributed(); d != nil {
natsClient = d.Nats
}
messagesHandler := anthropic.MessagesEndpoint(
application.ModelConfigLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
natsClient,
)
messagesMiddleware := []echo.MiddlewareFunc{
middleware.ExposeNodeHeader(application.ApplicationConfig()),
middleware.UsageMiddleware(application.StatsRecorder(), application.FallbackUser()),
middleware.TraceMiddleware(application),
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_CHAT)),
re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.AnthropicRequest) }),
setAnthropicRequestContext(application.ApplicationConfig()),
// RouteModel runs after the request is parsed but before the
// PII filter — see the OpenAI route for why this order matters
// (per-model PII configs apply to the routed target).
middleware.RouteModel(
application.ModelConfigLoader(),
application.ApplicationConfig(),
application.RouterDecisions(),
application.FallbackUser(),
middleware.AnthropicProbe,
router.SourceAnthropic,
middleware.ClassifierDeps{
Scorer: application.Scorer,
TokenCounter: application.TokenCounter,
Embedder: application.Embedder,
VectorStore: application.VectorStore,
Reranker: application.Reranker,
ModelLookup: application.ModelConfigLookup(),
Registry: application.RouterClassifierRegistry(),
Evaluator: application.TemplatesEvaluator(),
},
),
middleware.AdmissionControl(application.AdmissionLimiter(), application.PIIEvents()),
pii.RequestMiddleware(application.PIIRedactor(), application.PIIEvents(), piiadapter.Anthropic(), application.FallbackUser(), pii.WithNERResolver(application.PIINERResolver()), pii.WithPolicyResolver(application.PIIPolicyResolver())),
}
// Main Anthropic endpoint
app.POST("/v1/messages", messagesHandler, messagesMiddleware...)
// Also support without version prefix for compatibility
app.POST("/messages", messagesHandler, messagesMiddleware...)
}
// setAnthropicRequestContext sets up the context and cancel function for Anthropic requests
func setAnthropicRequestContext(appConfig *config.ApplicationConfig) echo.MiddlewareFunc {
return func(next echo.HandlerFunc) echo.HandlerFunc {
return func(c echo.Context) error {
input, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.AnthropicRequest)
if !ok || input.Model == "" {
return echo.NewHTTPError(http.StatusBadRequest, "model is required")
}
cfg, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
if !ok || cfg == nil {
return echo.NewHTTPError(http.StatusBadRequest, "model configuration not found")
}
// Extract or generate the correlation ID
// Anthropic uses x-request-id header
correlationID := c.Request().Header.Get("x-request-id")
if correlationID == "" {
correlationID = uuid.New().String()
}
c.Response().Header().Set("x-request-id", correlationID)
// Set up context with cancellation
reqCtx := c.Request().Context()
c1, cancel := context.WithCancel(appConfig.Context)
// Bridge request cancellation to c1 without spawning a goroutine.
stop := context.AfterFunc(reqCtx, cancel)
defer func() {
stop() // deregister callback if it hasn't fired
cancel() // release c1 resources (idempotent)
}()
// Add the correlation ID to the new context
ctxWithCorrelationID := context.WithValue(c1, middleware.CorrelationIDKey, correlationID)
ctxWithCorrelationID = distributedhdr.Inherit(ctxWithCorrelationID, reqCtx)
input.Context = ctxWithCorrelationID
input.Cancel = cancel
if cfg.Model == "" {
xlog.Debug("replacing empty cfg.Model with input value", "input.Model", input.Model)
cfg.Model = input.Model
}
c.Set(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST, input)
c.Set(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG, cfg)
// Log the Anthropic API version if provided
anthropicVersion := c.Request().Header.Get("anthropic-version")
if anthropicVersion != "" {
xlog.Debug("Anthropic API version", "version", anthropicVersion)
}
// Validate max_tokens is provided
if input.MaxTokens <= 0 {
return echo.NewHTTPError(http.StatusBadRequest, fmt.Sprintf("max_tokens is required and must be greater than 0"))
}
return next(c)
}
}
}