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#10970 gave the four PredictOptions RPCs a model-identity check so a backend reached through a stale distributed route rejects the request instead of answering from whatever model it holds (#10952). Every other modality shares that exposure: the route is cached by host:port, a worker can recycle a stopped backend's port for another model's backend, and a liveness-only probe cannot tell a stale row from a valid one. Extends the same mechanism to the 21 remaining request messages that reach a backend through the router, using the pattern #10970 established rather than a parallel one: - proto: ModelIdentity on each modality request message. - controller: populated from ModelConfig.Model at the call site that also builds ModelOptions, so load-time and request-time values are equal by construction. - backends: one generic guard in pkg/grpc/server.go (27 Go backends), the method set in backend/python/common (36 Python backends), llama-cpp (AudioTranscription/Stream, Rerank, Score) and privacy-filter (TokenClassify). - reconcile already drops the stale row on IsModelMismatch; no change. TTSRequest and SoundGenerationRequest get a SEPARATE ModelIdentity field rather than reusing their existing `model`: FileStagingClient rewrites `model` to a worker-local path, so comparing it would reject valid requests in exactly the configuration this guards. AudioEncode/AudioDecode are deliberately left unguarded: the opus codec backend is loaded from a literal rather than a ModelConfig, so no value carries the equality guarantee the comparison depends on. The four bidirectional stream RPCs are out of scope; they bypass reconcile. Empty means skip on both sides, so an old controller, an old backend, and the bare request structs in tests/e2e-backends all keep working. Assisted-by: Claude Code:claude-opus-4-8 [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
73 lines
1.6 KiB
Go
73 lines
1.6 KiB
Go
package backend
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import (
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"context"
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"fmt"
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"time"
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/core/trace"
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"github.com/mudler/LocalAI/pkg/grpc/proto"
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"github.com/mudler/LocalAI/pkg/model"
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)
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func Detection(
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ctx context.Context,
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sourceFile string,
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prompt string,
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points []float32,
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boxes []float32,
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threshold float32,
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loader *model.ModelLoader,
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appConfig *config.ApplicationConfig,
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modelConfig config.ModelConfig,
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) (*proto.DetectResponse, error) {
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opts := ModelOptions(modelConfig, appConfig)
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detectionModel, err := loader.Load(opts...)
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if err != nil {
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recordModelLoadFailure(appConfig, modelConfig.Name, modelConfig.Backend, err, nil)
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return nil, err
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}
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if detectionModel == nil {
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return nil, fmt.Errorf("could not load detection model")
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}
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var startTime time.Time
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if appConfig.EnableTracing {
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trace.InitBackendTracingIfEnabled(appConfig.TracingMaxItems, appConfig.TracingMaxBodyBytes)
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startTime = time.Now()
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}
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res, err := detectionModel.Detect(ctx, &proto.DetectOptions{
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ModelIdentity: modelConfig.Model,
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Src: sourceFile,
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Prompt: prompt,
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Points: points,
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Boxes: boxes,
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Threshold: threshold,
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})
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if appConfig.EnableTracing {
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errStr := ""
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if err != nil {
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errStr = err.Error()
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}
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trace.RecordBackendTrace(trace.BackendTrace{
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Timestamp: startTime,
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Duration: time.Since(startTime),
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Type: trace.BackendTraceDetection,
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ModelName: modelConfig.Name,
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Backend: modelConfig.Backend,
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Summary: trace.TruncateString(sourceFile, 200),
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Error: errStr,
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Data: map[string]any{
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"source_file": sourceFile,
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},
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})
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}
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return res, err
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}
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