Files
LocalAI/core/backend/stores_test.go
Richard Palethorpe 085fc53bbc fix(router): production-ready request router + auto-size batch for embedding/rerank (#10104)
* fix(router): score classifier production-readiness

Conversation trimming runs through the classifier model's chat template
and trims by exact token count, sized to the model's n_batch which is
now scaled to context so long probes can't crash the backend. Missing
chat_message templates are a hard error at router build time. Router-
facing factories (Embedder/Scorer/Reranker/TokenCounter) re-resolve
ModelConfig per call so a model installed post-startup doesn't bind a
stub Backend="" config and silently fall into the loader's auto-
iterate path.

New 'vector_store' backend trace recorded inside localVectorStore on
every Search/Insert — including the backend-load-failure path that
previously vanished into an xlog.Warn — with outcome tagging
(hit/miss/empty_store/backend_load_error/find_error/insert_error/ok).
Companion cleanup drops misleading similarity:0 and input_tokens_count:0
from non-hit and text-mode traces.

Gallery local-store-development aliases to 'local-store' so the master
image satisfies pkg/model.LocalStoreBackend lookups from the embedding
cache.

Misc: llama-cpp TokenizeString reads the correct 'prompt' JSON key
(the original bug); ModelTokenize nil-guard; non-fatal mitm proxy
startup; PII 'route_local' renamed to 'allow' with docs/UI in sync;
model-editor footer no longer eats the edit area on small screens;
several config-editor template/dropdown/section fixes.

Tests: e2e router specs (casual/code-hint + long-conversation trim),
vector_store trace specs, lazy-factory specs, gallery dev-alias
resolution, Playwright trace badge + scroll regression.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(backend): auto-size batch to context for embedding and rerank models

Embedding and rerank models pool over the whole input in a single physical batch (n_ubatch). With batch left at the 512 default, the backend rejects longer inputs with "input is too large to process", silently capping a large-context embedder (e.g. 8k/32k) at 512 tokens. Size n_batch to the context for these single-pass usecases, mirroring the existing FLAG_SCORE behaviour; an explicit batch: still wins.

Extracts EffectiveContextSize/EffectiveBatchSize from grpcModelOpts so the effective decode window has one home for other callers to reuse.

Adds an e2e-aio regression test that embeds a >512-token input. The AIO embedding model is switched to nomic-embed-text-v1.5 (2048 context) because the previous granite model was capped at 512 tokens and could not exercise the larger batch.

Assisted-by: claude-code:claude-opus-4-8 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(gallery): raise arch-router scoring output cap via parallel:64

Scoring decodes the whole prompt+candidate in a single llama_decode and
reads one logit row per candidate token. The vendored llama.cpp server
caps causal output rows at n_parallel, so the default of 1 aborts with
GGML_ASSERT(n_outputs_max <= cparams.n_outputs_max) on multi-token route
labels. Set options: [parallel:64] on both arch-router quant entries to
lift the cap; kv_unified (the grpc-server default) keeps the full context
per sequence, so this does not split the KV cache.

Assisted-by: claude-code:claude-opus-4-8 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-06-12 16:21:15 +02:00

89 lines
3.1 KiB
Go

package backend
import (
"context"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/trace"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/system"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
// findVectorStoreTrace returns the most recent vector_store trace whose
// model_name matches storeName, or nil if none was recorded. Used by
// the specs below to assert the trace landed without relying on
// ring-buffer ordering across other tests in the suite.
func findVectorStoreTrace(storeName string) *trace.BackendTrace {
traces := trace.GetBackendTraces()
for i := range traces {
bt := &traces[i]
if bt.Type == trace.BackendTraceVectorStore && bt.ModelName == storeName {
return bt
}
}
return nil
}
var _ = Describe("localVectorStore tracing", func() {
// Pin the trace surface admins read from /api/backend-traces.
// The original failure mode that motivated these specs — the
// local-store backend not installed — was silent on every surface
// except a per-call xlog.Warn. With tracing wired in, the row
// appears next to the embedder/score traces for the same request.
BeforeEach(func() {
trace.ClearBackendTraces()
})
It("records a vector_store trace with outcome=backend_load_error when the backend can't be loaded", func() {
// nil ModelLoader → s.backend → StoreBackend → panics on load.
// Use a real-but-empty loader so the failure surfaces as an
// error instead, exercising the load-failure trace path the
// admin would hit when local-store isn't installed.
appCfg := &config.ApplicationConfig{
EnableTracing: true,
TracingMaxItems: 16,
TracingMaxBodyBytes: 1024,
}
s := &localVectorStore{
loader: model.NewModelLoader(&system.SystemState{}),
appConfig: appCfg,
storeName: "router-cache-test",
}
// Search must surface the error AND record a trace describing it.
_, _, _, err := s.Search(context.Background(), []float32{0.1, 0.2, 0.3})
Expect(err).To(HaveOccurred())
Eventually(func() *trace.BackendTrace {
return findVectorStoreTrace("router-cache-test")
}).ShouldNot(BeNil())
bt := findVectorStoreTrace("router-cache-test")
Expect(bt.Backend).To(Equal(model.LocalStoreBackend))
Expect(bt.Data["op"]).To(Equal("search"))
Expect(bt.Data["outcome"]).To(Equal("backend_load_error"))
Expect(bt.Data["vector_dim"]).To(Equal(3))
// Error is the wrapped "vector store load: …" surfaced to the caller.
Expect(bt.Error).To(ContainSubstring("vector store load"))
})
It("does not record a trace when tracing is disabled", func() {
// Opt-out path: appConfig.EnableTracing=false must short-circuit
// before InitBackendTracingIfEnabled, so a workload with tracing
// turned off doesn't pay the channel-send cost per cache call.
appCfg := &config.ApplicationConfig{EnableTracing: false}
s := &localVectorStore{
loader: model.NewModelLoader(&system.SystemState{}),
appConfig: appCfg,
storeName: "router-cache-disabled",
}
_, _, _, _ = s.Search(context.Background(), []float32{1})
Consistently(func() *trace.BackendTrace {
return findVectorStoreTrace("router-cache-disabled")
}).Should(BeNil())
})
})