Files
LocalAI/core/backend/options.go
LocalAI [bot] 1198d10b58 fix(traces): cap backend trace Data to keep admin UI responsive (#9960)
* fix(traces): cap backend trace Data field so the admin UI stays responsive

The previous fix (#9946) capped API trace bodies but missed backend traces,
which carry the same blast radius:

  - LLM backend traces store the full chat messages JSON, full response, and
    full streaming deltas. Every agent-pool reasoning step ships the full
    RAG-augmented history (50-500 KiB per trace, often 100+ traces queued).
  - TTS / audio_transform / transcript traces embed a 30s audio snippet as
    base64, around 1.3 MiB per trace.

Both blow the /api/backend-traces JSON past tens of MiB. The admin Traces
page then keeps re-downloading and re-parsing the buffer faster than the
5s auto-refresh and stays in the loading state forever, the same symptom
the API-side fix addressed.

Apply two complementary caps, both honoring LOCALAI_TRACING_MAX_BODY_BYTES:

Option A (safety net in core/trace): RecordBackendTrace walks the Data map
recursively and replaces any string value larger than the cap with
"<truncated: N bytes>". Catches anything a future producer forgets.

Option B (head-preserving at the producer):
  - core/backend/llm.go: TruncateToBytes on messages, response, and
    chat_deltas content/reasoning_content so the leading content stays
    readable in the UI.
  - core/trace/audio_snippet.go: omit audio_wav_base64 when the encoded
    blob would exceed the cap (truncated base64 is undecodable). The
    quality metrics still ship and the UI's WaveformPlayer simply skips
    when the field is absent.

TruncateToBytes is bounded to <= maxBytes so Option A leaves the producer's
head-preserving output alone instead of replacing it with the bare marker.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* fix(react-ui): expose tracing_max_body_bytes in Settings and Traces panels

The setting was already plumbed through env (LOCALAI_TRACING_MAX_BODY_BYTES),
CLI flag, and the runtime_settings.json GET/PUT schema, but neither the main
Settings page nor the inline Traces panel offered an input for it. Admins
hitting the "Traces UI stuck loading" symptom had to know to set an env var
or PUT raw JSON to /api/settings to dial the cap.

Add a "Max Body Bytes" row next to "Max Items" in both places. Same input
type, same disabled-when-tracing-off semantics, placeholder shows the 65536
default so users see what they're inheriting.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* test(react-ui): disambiguate Max Items locator after adding Max Body Bytes

The Tracing settings panel now has two number inputs. The previous spec
matched 'input[type="number"]' which became ambiguous and triggered a
Playwright strict-mode violation in CI. Switch to getByPlaceholder('100')
for Max Items and add a parallel spec for the new Max Body Bytes field
using getByPlaceholder('65536').

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-23 14:50:40 +02:00

324 lines
9.1 KiB
Go

package backend
import (
"encoding/json"
"fmt"
"math/rand/v2"
"os"
"path/filepath"
"strings"
"time"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/trace"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/xlog"
)
// recordModelLoadFailure records a backend trace when model loading fails.
func recordModelLoadFailure(appConfig *config.ApplicationConfig, modelName, backend string, err error, data map[string]any) {
if !appConfig.EnableTracing {
return
}
trace.InitBackendTracingIfEnabled(appConfig.TracingMaxItems, appConfig.TracingMaxBodyBytes)
trace.RecordBackendTrace(trace.BackendTrace{
Timestamp: time.Now(),
Type: trace.BackendTraceModelLoad,
ModelName: modelName,
Backend: backend,
Summary: "Model load failed",
Error: err.Error(),
Data: data,
})
}
func ModelOptions(c config.ModelConfig, so *config.ApplicationConfig, opts ...model.Option) []model.Option {
name := c.Name
if name == "" {
name = c.Model
}
defOpts := []model.Option{
model.WithBackendString(c.Backend),
model.WithModel(c.Model),
model.WithContext(so.Context),
model.WithModelID(name),
}
threads := 1
if c.Threads != nil {
threads = *c.Threads
}
if so.Threads != 0 {
threads = so.Threads
}
c.Threads = &threads
grpcOpts := grpcModelOpts(c, so.SystemState.Model.ModelsPath)
defOpts = append(defOpts, model.WithLoadGRPCLoadModelOpts(grpcOpts))
defOpts = append(defOpts, model.EnableParallelRequests)
if c.GRPC.Attempts != 0 {
defOpts = append(defOpts, model.WithGRPCAttempts(c.GRPC.Attempts))
}
if c.GRPC.AttemptsSleepTime != 0 {
defOpts = append(defOpts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
}
for k, v := range so.ExternalGRPCBackends {
defOpts = append(defOpts, model.WithExternalBackend(k, v))
}
return append(defOpts, opts...)
}
func getSeed(c config.ModelConfig) int32 {
var seed int32 = config.RAND_SEED
if c.Seed != nil {
seed = int32(*c.Seed)
}
if seed == config.RAND_SEED {
seed = rand.Int32()
}
return seed
}
func grpcModelOpts(c config.ModelConfig, modelPath string) *pb.ModelOptions {
b := 512
if c.Batch != 0 {
b = c.Batch
}
flashAttention := "auto"
if c.FlashAttention != nil {
flashAttention = *c.FlashAttention
}
f16 := false
if c.F16 != nil {
f16 = *c.F16
}
embeddings := false
if c.Embeddings != nil {
embeddings = *c.Embeddings
}
lowVRAM := false
if c.LowVRAM != nil {
lowVRAM = *c.LowVRAM
}
reranking := false
if c.Reranking != nil {
reranking = *c.Reranking
}
mmap := false
if c.MMap != nil {
mmap = *c.MMap
}
// Intel SYCL backend has issues with mmap enabled
// See: https://github.com/mudler/LocalAI/issues/9012
// Automatically disable mmap for Intel SYCL backends
if c.Backend != "" {
if strings.Contains(strings.ToLower(c.Backend), "intel") || strings.Contains(strings.ToLower(c.Backend), "sycl") {
mmap = false
xlog.Info("Auto-disabling mmap for Intel SYCL backend", "backend", c.Backend)
}
}
ctxSize := 4096
if c.ContextSize != nil {
ctxSize = *c.ContextSize
}
mmlock := false
if c.MMlock != nil {
mmlock = *c.MMlock
}
nGPULayers := 9999999
if c.NGPULayers != nil {
nGPULayers = *c.NGPULayers
}
triggers := make([]*pb.GrammarTrigger, 0)
for _, t := range c.FunctionsConfig.GrammarConfig.GrammarTriggers {
triggers = append(triggers, &pb.GrammarTrigger{
Word: t.Word,
})
}
engineArgsJSON := ""
if len(c.EngineArgs) > 0 {
buf, err := json.Marshal(c.EngineArgs)
if err != nil {
// ModelConfig.Validate() rejects unmarshalable engine_args at
// config load, so reaching here means the validator was bypassed.
// Silently dropping user-set options would change runtime behaviour
// without warning — fail loud instead.
panic(fmt.Sprintf("engine_args marshal failed for model %q: %v (Validate() should have caught this)", c.Model, err))
}
engineArgsJSON = string(buf)
}
opts := &pb.ModelOptions{
CUDA: c.CUDA || c.Diffusers.CUDA,
SchedulerType: c.Diffusers.SchedulerType,
GrammarTriggers: triggers,
PipelineType: c.Diffusers.PipelineType,
CFGScale: c.CFGScale,
LoraAdapter: c.LoraAdapter,
LoraScale: c.LoraScale,
LoraAdapters: c.LoraAdapters,
LoraScales: c.LoraScales,
F16Memory: f16,
LoraBase: c.LoraBase,
IMG2IMG: c.Diffusers.IMG2IMG,
CLIPModel: c.Diffusers.ClipModel,
CLIPSubfolder: c.Diffusers.ClipSubFolder,
Options: c.Options,
Overrides: c.Overrides,
EngineArgs: engineArgsJSON,
CLIPSkip: int32(c.Diffusers.ClipSkip),
ControlNet: c.Diffusers.ControlNet,
ContextSize: int32(ctxSize),
Seed: getSeed(c),
NBatch: int32(b),
NoMulMatQ: c.NoMulMatQ,
DraftModel: c.DraftModel,
AudioPath: c.AudioPath,
Quantization: c.Quantization,
LoadFormat: c.LoadFormat,
GPUMemoryUtilization: c.GPUMemoryUtilization,
TrustRemoteCode: c.TrustRemoteCode,
EnforceEager: c.EnforceEager,
SwapSpace: int32(c.SwapSpace),
MaxModelLen: int32(c.MaxModelLen),
TensorParallelSize: int32(c.TensorParallelSize),
DisableLogStatus: c.DisableLogStatus,
DType: c.DType,
// LimitMMPerPrompt vLLM
LimitImagePerPrompt: int32(c.LimitMMPerPrompt.LimitImagePerPrompt),
LimitVideoPerPrompt: int32(c.LimitMMPerPrompt.LimitVideoPerPrompt),
LimitAudioPerPrompt: int32(c.LimitMMPerPrompt.LimitAudioPerPrompt),
FlashAttention: flashAttention,
CacheTypeKey: c.CacheTypeK,
CacheTypeValue: c.CacheTypeV,
NoKVOffload: c.NoKVOffloading,
YarnExtFactor: c.YarnExtFactor,
YarnAttnFactor: c.YarnAttnFactor,
YarnBetaFast: c.YarnBetaFast,
YarnBetaSlow: c.YarnBetaSlow,
NGQA: c.NGQA,
RMSNormEps: c.RMSNormEps,
MLock: mmlock,
RopeFreqBase: c.RopeFreqBase,
RopeScaling: c.RopeScaling,
Type: c.ModelType,
RopeFreqScale: c.RopeFreqScale,
NUMA: c.NUMA,
Embeddings: embeddings,
Reranking: reranking,
LowVRAM: lowVRAM,
NGPULayers: int32(nGPULayers),
MMap: mmap,
MainGPU: c.MainGPU,
Threads: int32(*c.Threads),
TensorSplit: c.TensorSplit,
// RWKV
Tokenizer: c.Tokenizer,
}
if c.MMProj != "" {
opts.MMProj = filepath.Join(modelPath, c.MMProj)
}
// Resolve draft_model against the models directory, mirroring the
// handling of parameters.model and mmproj. Always joining (without an
// IsAbs shortcut) prevents user-supplied configs from pointing the
// backend at arbitrary host files via an absolute path.
if c.DraftModel != "" {
opts.DraftModel = filepath.Join(modelPath, c.DraftModel)
}
return opts
}
func gRPCPredictOpts(c config.ModelConfig, modelPath string) *pb.PredictOptions {
promptCachePath := ""
if c.PromptCachePath != "" {
p := filepath.Join(modelPath, c.PromptCachePath)
err := os.MkdirAll(filepath.Dir(p), 0750)
if err == nil {
promptCachePath = p
} else {
xlog.Error("error creating prompt cache folder", "error", err, "promptCachePath", promptCachePath)
}
}
pbOpts := &pb.PredictOptions{
Temperature: float32(*c.Temperature),
TopP: float32(*c.TopP),
NDraft: c.NDraft,
TopK: int32(*c.TopK),
MinP: float32(*c.MinP),
Tokens: int32(*c.Maxtokens),
Threads: int32(*c.Threads),
PromptCacheAll: *c.PromptCacheAll,
PromptCacheRO: c.PromptCacheRO,
PromptCachePath: promptCachePath,
F16KV: *c.F16,
DebugMode: *c.Debug,
Grammar: c.Grammar,
NegativePromptScale: c.NegativePromptScale,
RopeFreqBase: c.RopeFreqBase,
RopeFreqScale: c.RopeFreqScale,
NegativePrompt: c.NegativePrompt,
Mirostat: int32(*c.LLMConfig.Mirostat),
MirostatETA: float32(*c.LLMConfig.MirostatETA),
MirostatTAU: float32(*c.LLMConfig.MirostatTAU),
Debug: *c.Debug,
StopPrompts: c.StopWords,
Repeat: int32(c.RepeatLastN),
FrequencyPenalty: float32(c.FrequencyPenalty),
PresencePenalty: float32(c.PresencePenalty),
Penalty: float32(c.RepeatPenalty),
NKeep: int32(c.Keep),
Batch: int32(c.Batch),
IgnoreEOS: c.IgnoreEOS,
Seed: getSeed(c),
MLock: *c.MMlock,
MMap: *c.MMap,
MainGPU: c.MainGPU,
TensorSplit: c.TensorSplit,
TailFreeSamplingZ: float32(*c.TFZ),
TypicalP: float32(*c.TypicalP),
}
metadata := map[string]string{}
if c.ReasoningConfig.DisableReasoning != nil {
if *c.ReasoningConfig.DisableReasoning {
metadata["enable_thinking"] = "false"
} else {
metadata["enable_thinking"] = "true"
}
}
pbOpts.Metadata = metadata
// Logprobs and TopLogprobs are set by the caller if provided
return pbOpts
}