Files
LocalAI/core/backend/stores.go
Richard Palethorpe 6a80e23733 feat(middleware): Model routing, PII filtering, Cloud model proxies (#9802)
Add a routing middleware stack and a cloud-proxy backend.

* cloud-proxy: a Go gRPC backend that forwards OpenAI- and
  Anthropic-shaped chat requests to upstream providers, with an
  optional translate mode (OpenAI request -> Anthropic /v1/messages
  -> OpenAI response) and full tool-calling support.

* routing: admission control, content-aware model routing
  (embedding cache + classifier + rerank + Arch-Router score),
  PII detection/redaction (regex + NER) with streaming filter and
  OpenAI/Anthropic adapters, and a per-user/per-key billing recorder
  backed by GORM or in-memory storage.

* middleware: UsageMiddleware records usage via the billing recorder,
  plus admission, route-model, usage-stamp and trace middlewares.

* observability: BackendTrace ring buffer stores full request bodies
  (capped), MITM proxy emits structured trace events, and router
  classifier decisions surface at /api/router/decide.

* gallery: Arch-Router-1.5B (Q4_K_M and Q8_0).

* UI: cloud-proxy model-editor fields, classifier system-prompt and
  score-normalization config, and a Traces page rendering request
  bodies.

Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-25 09:28:27 +02:00

92 lines
3.1 KiB
Go

package backend
import (
"context"
"fmt"
"strings"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/pkg/grpc"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/store"
)
// VectorStore is the narrowed KNN store used by the router's embedding
// cache. Search returns the top-1 match (cosine similarity in [-1, 1])
// and the serialised payload, or ok=false on a clean miss.
type VectorStore interface {
Search(ctx context.Context, vec []float32) (similarity float64, payload []byte, ok bool, err error)
Insert(ctx context.Context, vec []float32, payload []byte) error
}
// NewVectorStore returns a VectorStore backed by the local-store
// gRPC backend, namespaced by storeName so two routers don't collide.
func NewVectorStore(loader *model.ModelLoader, appConfig *config.ApplicationConfig, storeName string) VectorStore {
if storeName == "" {
return nil
}
return &localVectorStore{loader: loader, appConfig: appConfig, storeName: storeName}
}
type localVectorStore struct {
loader *model.ModelLoader
appConfig *config.ApplicationConfig
storeName string
}
func (s *localVectorStore) backend(_ context.Context) (grpc.Backend, error) {
return StoreBackend(s.loader, s.appConfig, s.storeName, "")
}
func (s *localVectorStore) Search(ctx context.Context, vec []float32) (float64, []byte, bool, error) {
be, err := s.backend(ctx)
if err != nil {
return 0, nil, false, fmt.Errorf("vector store load: %w", err)
}
_, values, similarities, err := store.Find(ctx, be, vec, 1)
if err != nil {
// local-store's Find returns "existing length is -1" before
// any keys are inserted. Surface that as a clean miss so the
// cache layer treats it as an empty store and proceeds to
// Insert rather than skipping.
if strings.Contains(err.Error(), "existing length is -1") {
return 0, nil, false, nil
}
return 0, nil, false, fmt.Errorf("vector store find: %w", err)
}
if len(values) == 0 || len(similarities) == 0 {
return 0, nil, false, nil
}
return float64(similarities[0]), values[0], true, nil
}
func (s *localVectorStore) Insert(ctx context.Context, vec []float32, payload []byte) error {
be, err := s.backend(ctx)
if err != nil {
return fmt.Errorf("vector store load: %w", err)
}
return store.SetSingle(ctx, be, vec, payload)
}
func StoreBackend(sl *model.ModelLoader, appConfig *config.ApplicationConfig, storeName string, backend string) (grpc.Backend, error) {
if backend == "" {
backend = model.LocalStoreBackend
}
// ModelLoader caches backend processes by `modelID`, not by the `model`
// passed via WithModel. Without a distinct modelID, every StoreBackend
// call collapses to the same `modelID=""` cache slot — face (512-D) and
// voice (192-D) biometrics would then share the same local-store process
// and the second enrollment would fail with
// Try to add key with length N when existing length is M
// Use the store namespace as modelID so each namespace gets its own
// process instance and its own in-memory Store{}.
sc := []model.Option{
model.WithBackendString(backend),
model.WithModelID(storeName),
model.WithModel(storeName),
}
return sl.Load(sc...)
}