* feat(distributed): add per-request node ID context holder
Introduce pkg/distributedhdr, a leaf package carrying a per-request
*atomic.Value holder for the picked worker node ID from the
SmartRouter (core/services/nodes) up to the HTTP response writer
wrapper (core/http/middleware). Avoids the import cycle that a shared
key in either consumer would create.
Exposes NewHolder, WithHolder, Holder, Stamp, Load, Inherit. The
holder is atomic.Value so cross-goroutine publish from the router to
the response writer wrapper is race-clean.
Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(distributed): add ExposeNodeHeader middleware + response writer wrapper
New ApplicationConfig.ExposeNodeHeader bool + --expose-node-header CLI
flag / LOCALAI_EXPOSE_NODE_HEADER env var (default off; the node ID
reveals internal topology and is opt-in).
The middleware creates a per-request *atomic.Value holder, attaches it
to c.Request().Context() via distributedhdr.WithHolder, and wraps
c.Response().Writer with a custom http.ResponseWriter that sets the
X-LocalAI-Node header on first Write / WriteHeader / Flush by reading
the holder. Implements http.Flusher, http.Hijacker, Unwrap so it
composes cleanly with Echo and http.NewResponseController.
request.go propagates the holder onto derived contexts via
distributedhdr.Inherit so the holder survives the correlation-ID
context replacement.
Unit + race-clean concurrency + integration specs.
Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(distributed): stamp node ID in router and wire middleware to inference routes
ModelRouterAdapter.Route stamps the picked node ID into the
per-request holder via distributedhdr.Stamp(ctx, result.Node.ID) right
after replica selection.
Wire ExposeNodeHeader middleware to:
- OpenAI chat/completion/embeddings + audio transcriptions/speech + image generations/inpainting
- Anthropic /v1/messages
- Ollama /api/chat, /api/generate, /api/embed, /api/embeddings
- Jina /v1/rerank
- LocalAI /v1/vad
The middleware's wrapper reads the holder on first byte and sets the
X-LocalAI-Node response header before delegating to the underlying
writer. Per-request scope means no race under concurrent multi-replica
routing.
Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): thread request context through backend Load + cover ctx propagation
Five non-OpenAI backend helpers were silently using app.Context instead
of the request context for the gRPC backend call: transcription, TTS,
image generation, rerank, VAD. Effect: distributedhdr.Stamp in the
router callback was a silent no-op for these paths, AND client
cancellation didn't propagate to in-flight inference.
Thread c.Request().Context() (or the equivalent input.Context after
the request middleware has installed the correlation-ID derived
context) through each helper and into ModelOptions via
model.WithContext(ctx). ImageGeneration's signature gains a leading
ctx parameter; in-tree callers (openai image, openai inpainting,
openai inpainting_test) are updated to match.
ModelEmbedding gains a leading ctx parameter for the same reason; the
openai and ollama embedding handlers pass the request context through.
chat_stream_workers.go defers the initial role=assistant chunk
emission until the first token callback so the wrapper's lazy
X-LocalAI-Node lookup against the loader runs AFTER ml.Load has
stamped the per-modelID node ID; semantically identical for clients
(role still arrives before any text).
Regression test core/backend/ctx_propagation_test.go pins ctx
propagation for all five helpers.
Docs updated to enumerate the full endpoint coverage of the
--expose-node-header flag.
Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* 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>
* feat(gallery): Switch to expandable box instead of pop-over and display model files
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(ui, backends): Add individual backend logging
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ui): Set the context settings from the model config
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore: drop mode from image generation(unused)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(UI): improve image generation front-end
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(UI): only ref images. files is to be deprecated
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not override default steps
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(loader): refactor single active backend support to LRU
This changeset introduces LRU management of loaded backends. Users can
set now a maximum number of models to be loaded concurrently, and, when
setting LocalAI in single active backend mode we set LRU to 1 for
backward compatibility.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: add tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Update docs
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
- Add a system backend path
- Refactor and consolidate system information in system state
- Use system state in all the components to figure out the system paths
to used whenever needed
- Refactor BackendConfig -> ModelConfig. This was otherway misleading as
now we do have a backend configuration which is not the model config.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(stablediffusion-ggml): add support to ref images
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add it to the model gallery
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(refactor): track internally started models by ID
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Just extend options, no need to copy
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Improve debugging for rerankers failures
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Simplify model loading with rerankers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Be more consistent when generating model options
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Uncommitted code
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Make deleteProcess more idiomatic
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt CLI for sound generation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixup threads definition
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Handle corner case where c.Seed is nil
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Consistently use ModelOptions
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt new code to refactoring
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Dave <dave@gray101.com>
* fix(defaults): set better defaults for inferencing
This changeset aim to have better defaults and to properly detect when
no inference settings are provided with the model.
If not specified, we defaults to mirostat sampling, and offload all the
GPU layers (if a GPU is detected).
Related to https://github.com/mudler/LocalAI/issues/1373 and https://github.com/mudler/LocalAI/issues/1723
* Adapt tests
* Also pre-initialize default seed
* feat(intel): add diffusers support
* try to consume upstream container image
* Debug
* Manually install deps
* Map transformers/hf cache dir to modelpath if not specified
* fix(compel): update initialization, pass by all gRPC options
* fix: add dependencies, implement transformers for xpu
* base it from the oneapi image
* Add pillow
* set threads if specified when launching the API
* Skip conda install if intel
* defaults to non-intel
* ci: add to pipelines
* prepare compel only if enabled
* Skip conda install if intel
* fix cleanup
* Disable compel by default
* Install torch 2.1.0 with Intel
* Skip conda on some setups
* Detect python
* Quiet output
* Do not override system python with conda
* Prefer python3
* Fixups
* exllama2: do not install without conda (overrides pytorch version)
* exllama/exllama2: do not install if not using cuda
* Add missing dataset dependency
* Small fixups, symlink to python, add requirements
* Add neural_speed to the deps
* correctly handle model offloading
* fix: device_map == xpu
* go back at calling python, fixed at dockerfile level
* Exllama2 restricted to only nvidia gpus
* Tokenizer to xpu
* core 1
* api/openai/files fix
* core 2 - core/config
* move over core api.go and tests to the start of core/http
* move over localai specific endpoints to core/http, begin the service/endpoint split there
* refactor big chunk on the plane
* refactor chunk 2 on plane, next step: port and modify changes to request.go
* easy fixes for request.go, major changes not done yet
* lintfix
* json tag lintfix?
* gitignore and .keep files
* strange fix attempt: rename the config dir?
This PR specifically introduces a `core` folder and moves the following packages over, without any other changes:
- `api/backend`
- `api/config`
- `api/options`
- `api/schema`
Once this is merged and we confirm there's no regressions, I can migrate over the remaining changes piece by piece to split up application startup, backend services, http, and mqtt as was the goal of the earlier PRs!
