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Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 LocalAI [bot]andEttore Di Giacinto
|
c1a891662c |
refactor(settings): single declarative registry for runtime settings (fixes the #10845 bug class) (#10864)
* feat(settings): add declarative runtime-settings field registry One fieldSpec row per RuntimeSettings field, with a reflection completeness spec so a field added without a registry row is a red test instead of a silently-dropped setting (the #10845 bug class). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * refactor(settings): drive ToRuntimeSettings/ApplyRuntimeSettings from the field registry Behavior-preserving: ~350 hand-written per-field lines become two loops over runtimeSettingsFields, gated by a To->Apply->To round-trip spec. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * feat(settings): baseline-driven startup merge for persisted runtime settings ApplyRuntimeSettingsAtStartup compares the live config against DefaultRuntimeBaseline (option-less-run defaults incl. kong-injected flag defaults) instead of per-field == 0 guards. Fixes persisted lru_eviction_max_retries, tracing_max_items, agent_job_retention_days, memory_reclaimer_threshold, galleries and autoload flags being silently ignored at boot. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * fix(settings): registry-driven startup merge, applied before consumers loadRuntimeSettingsFromFile becomes a thin wrapper over ApplyRuntimeSettingsAtStartup and runs at the top of New(), before model configs capture app-level defaults. WithThreads stops eagerly resolving 0 so a persisted thread count survives restart while LOCALAI_THREADS still wins (#10845); the physical-core fallback moves after the merge. Also: run.go now injects the memory-reclaimer threshold unconditionally so the option-less boot matches DefaultRuntimeBaseline and a UI-saved threshold survives restart. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * refactor(settings): file watcher delegates to the registry merge; shared API-key merge Manual edits to runtime_settings.json now behave like a boot-time load (env still wins) instead of the inverted diverged-from-startup guard that ignored most manual edits. MergeAPIKeys dedups env keys in one place for the endpoint and the watcher. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * docs(settings): document unified runtime-settings precedence Document the single env/CLI > runtime_settings.json > defaults rule, applied identically at boot, on POST /api/settings, and on manual file edits, plus the two known limitations (default-valued env vars are indistinguishable from unset; API-changed fields hot-apply on the next restart only). Also add a completion debug log when the watcher applies runtime_settings.json. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * test(settings): reset the global VRAM cap leaked by the round-trip spec The round-trip spec applies vram_budget=12GiB, whose post-loop hook installs a process-global default cap; without a reset every spec ordered after it runs under that phantom budget. Also drop a stale enumeration in the ApplyRuntimeSettings doc comment. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Tai AnandAnai-Guo
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dc2cc4da43 |
fix(audio-transform): serialize WebSocket writes to avoid concurrent-write panic (#10857)
* fix(audio-transform): serialize WebSocket writes to avoid concurrent-write panic AudioTransformStreamEndpoint writes to the same Gorilla WebSocket connection from two goroutines: the backend-forwarding goroutine emits binary PCM frames (and can call sendWSError on a backend recv error), while the read loop calls sendWSError for malformed mid-stream JSON or a backend send failure. Gorilla WebSocket permits only one concurrent writer, so these writers race and can panic with "concurrent write to websocket connection", resetting the client session; a -race build reports the data race directly. Wrap the connection in a lockedConn that serializes WriteMessage behind a mutex, mirroring the existing lockedConn used by the openresponses WebSocket endpoint. Reads stay on the single read loop, so only writes need the lock. Fixes #10844 Signed-off-by: Tai An <antai12232931@outlook.com> * chore: empty commit to re-trigger checks Signed-off-by: Anai-Guo <antai12232931@anaiguo.com> --------- Signed-off-by: Tai An <antai12232931@outlook.com> Signed-off-by: Anai-Guo <antai12232931@anaiguo.com> Co-authored-by: Anai-Guo <antai12232931@anaiguo.com> |
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LocalAI [bot]andEttore Di Giacinto
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8cec22c3b7 |
feat(vram): per-node VRAM allocation budget (LOCALAI_VRAM_BUDGET) (#10833)
* feat(vram): add vrambudget primitive for per-node VRAM caps Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): apply default VRAM budget in xsysinfo aggregate getters Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): wire LOCALAI_VRAM_BUDGET flag to xsysinfo default budget Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): persist VRAM budget via runtime settings with live apply Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(vram): reset process-global VRAM budget after runtime-settings spec Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): add VRAM budget field to Settings page Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): store and enforce per-node VRAM budget in the node registry Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): apply per-node VRAM budget in router hardware defaults Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): report worker VRAM budget in node registration The distributed worker now reports its operator-set VRAM budget string (LOCALAI_VRAM_BUDGET) to the server on registration. The worker keeps reporting RAW total/available VRAM and never sets the xsysinfo process-global budget (that stays standalone-only); the server resolves and enforces the budget uniformly (Task 6). Also closes a Task 6 gap: on re-registration, a struct Updates zero-skips an empty budget, so a worker that dropped LOCALAI_VRAM_BUDGET left the stale cap in place. For non-admin-override nodes the budget columns are now force-written (map Updates) even when empty, so removing the env var clears the cap; admin overrides are preserved unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(vram): drop em dash from worker-clear comment Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): add node VRAM budget admin endpoints Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): add node VRAM budget control to the node UI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): expose set_node_vram_budget MCP admin tool Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(vram): document LOCALAI_VRAM_BUDGET and node VRAM budget UI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vram): avoid double-applying VRAM budget in GetResourceAggregateInfo The GPU-branch aggregate returned by GetResourceInfo is sourced from GetGPUAggregateInfo, which already caps total/free/used against the process-wide VRAM budget. GetResourceAggregateInfo then applied the budget a second time. For an absolute budget this is idempotent, but for a percentage budget b.Apply resolves the ceiling as a fraction of its input total, so a second pass yields P*(P*T) instead of P*T and distorts UsagePercent (read by the memory reclaimer in pkg/model/watchdog.go). Remove the redundant second application so the budget is applied exactly once, against the raw physical totals, upstream in GetGPUAggregateInfo. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vram): implement SetNodeVRAMBudget on mcp assistant test stub The LocalAIClient interface gained SetNodeVRAMBudget; the stubClient in core/http/endpoints/mcp used by the assistant tests is a separate implementer and needs the method too (broke golangci-lint typecheck and both test jobs). 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> |
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LocalAI [bot]andEttore Di Giacinto
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3601174ce0 |
fix(distributed): make per-node backend upgrade actually upgrade (#10838)
* test(core/http): make the suite's HTTP port overridable app_test.go and openresponses_test.go hardcoded 127.0.0.1:9090. When another service already listens on 9090 the suite does not fail fast: the server goroutine logs the bind error and the specs then poll whatever is squatting the port until Eventually times out. On machines where 9090 is permanently taken this makes the pre-commit coverage gate impossible to pass. Introduce testHTTPAddr, defaulting to 127.0.0.1:9090 (what CI has always used) and overridable via LOCALAI_TEST_HTTP_PORT for local runs. Assisted-by: Claude:claude-fable-5 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): make per-node backend upgrade actually upgrade The node detail page's Upgrade button reused the node-scoped install path (POST /api/nodes/:id/backends/install). That fires NATS backend.install with force=false, and the worker's install handler is deliberately "ensure installed": when the backend binary already exists on disk it short-circuits without touching the gallery. Since only an installed backend can be upgraded, the whole chain was a guaranteed successful no-op - the UI then toasted "backend upgraded" without even waiting for the async job. Route upgrades through the real force-reinstall path instead: - BackendManager.UpgradeBackend now receives the ManagementOp (like InstallBackend already did) so implementations can honor op.TargetNodeID. - DistributedBackendManager.UpgradeBackend scopes the backend.upgrade fan-out to op.TargetNodeID when set, and errors when the target node does not report the backend as installed. - New POST /api/nodes/:id/backends/upgrade endpoint enqueues an Upgrade=true node-scoped op (async 202 + jobID, mirroring install). - NodeDetail UI calls the new endpoint and reports the dispatch ("Upgrading ... on this node...") instead of claiming success; the Operations panel tracks the actual job. Verified against a live local cluster (NATS + Postgres + two workers): the target worker stops the running process, force-reinstalls from the gallery and re-downloads the OCI image; the second worker receives no backend.upgrade event; upgrading a backend missing from the target node fails the job with a clear error. Assisted-by: Claude:claude-fable-5 golangci-lint 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> |
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LocalAI [bot]andEttore Di Giacinto
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bcc41219f7 |
feat: materialize Hugging Face model artifacts (#10825)
* feat(config): add model artifact source contract Assisted-by: Codex:GPT-5 [Codex] * feat(downloader): add authenticated raw-byte progress Assisted-by: Codex:GPT-5 [Codex] * feat(huggingface): resolve immutable snapshot manifests Assisted-by: Codex:GPT-5 [Codex] * feat(models): add artifact storage primitives Assisted-by: Codex:GPT-5 [Codex] * feat(models): materialize pinned Hugging Face snapshots Assisted-by: Codex:GPT-5 [Codex] * feat(models): bind managed snapshots at runtime Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): materialize model artifacts during install Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): declare managed Hugging Face artifacts Assisted-by: Codex:GPT-5 [Codex] * feat(models): preload managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * fix(gallery): retain shared artifact caches on delete Assisted-by: Codex:GPT-5 [Codex] * feat(models): report artifact acquisition progress Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load managed models from ModelFile Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load staged speech model snapshots Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): use staged snapshots in engine backends Assisted-by: Codex:GPT-5 [Codex] * test(distributed): cover staged artifact snapshots Assisted-by: Codex:GPT-5 [Codex] * docs: explain managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * docs: add product design context Assisted-by: Codex:GPT-5 [Codex] * feat(ui): show model artifact download progress Assisted-by: Codex:GPT-5 [Codex] * Eagerly materialize Hugging Face artifacts Materialize HF-backed model references as managed GGUF artifacts during load, with lazy download retained only as fallback. Assisted-by: Codex:GPT-5 [shell] * Refactor HF downloads through a shared executor Assisted-by: Codex:GPT-5 [shell] * drop 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> |
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Ijasandajuijas
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a5aa56db81 |
fix: preserve uploaded file content when regenerating a non-last answer (#10819)
handleRegenerate rebuilt the outbound message from the display-only
message.files metadata ({name, type: 'file'|'image'|..., content}),
which doesn't carry the base64/textContent payload sendMessage's
file-building loop expects. As a result, regenerating any answer whose
own question had an attachment silently dropped that attachment from
the resent message. This wasn't fork-specific, but forking a chat and
then regenerating an earlier (now non-last) answer is the natural way
to hit it.
Fix by reusing the original message's already-assembled `content`
verbatim (it already has the file text / image_url / audio_url /
video_url parts embedded from the first send) instead of trying to
reconstruct it from lossy display metadata.
Fixes #10806
Assisted-by: Claude:claude-sonnet-5
Signed-off-by: ajuijas <189517297+ajuijas@users.noreply.github.com>
Co-authored-by: ajuijas <189517297+ajuijas@users.noreply.github.com>
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Dedy F. Setyawan
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b10e330590 |
feat(react-ui): localize MediaHistory, AudioTransform, and Sound components (#10802)
- Replace hardcoded text with useTranslation hook in UI components - Add localization support for both English (en) and Indonesian (id) locales Signed-off-by: Dedy F. Setyawan <dedyfajars@gmail.com> |
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LocalAI [bot]andEttore Di Giacinto
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4056283aa4 |
[voice] feat: add managed voice cloning profiles (#10799)
* feat(ui): add voice library workflow Give administrators a production-ready flow to record or upload consented reference audio, manage reusable profiles, inspect API usage, discover compatible models, and hand a saved voice directly to text-to-speech. Assisted-by: Codex:gpt-5 * feat(voice): add managed voice cloning profiles Make reusable reference voices manageable through the admin API instead of requiring model-directory and YAML edits. Discover compatible installed and gallery models from server-side backend capabilities, retain explicit model configuration controls, and stage saved references for supported backends. Expose profile management through REST and MCP, document backend-specific behavior, and cover the workflow from profile creation through real Qwen3-TTS synthesis. Harden the agent-job HTTP test against completion racing cancellation. Assisted-by: Codex:gpt-5 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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b00422e45f |
feat(backends): add LongCat video and avatar generation (#10792)
* feat(backends): add LongCat video and avatar generation Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] [web] * refactor(config): declare model I/O modalities Make model configs declare input and output modalities so capability discovery no longer branches on backend or checkpoint names. Complete the LongCat gallery and user documentation, make the SDPA patch apply to the pinned upstream revision, and stabilize the Agent Jobs race exposed by the required hook. Assisted-by: Codex:GPT-5 [web] --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Dedy F. Setyawan
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294487eb61 |
fix(ui): prevent table container from breaking flexbox layout (#10754)
Signed-off-by: Dedy F. Setyawan <dedyfajars@gmail.com> |
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LocalAI [bot]andEttore Di Giacinto
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40dae953f4 |
feat: interleaved thinking with tool calls (reasoning_content alias + Anthropic thinking blocks) (#10744)
* feat(schema): accept reasoning_content as inbound alias for reasoning Interleaved-thinking clients (cogito, vLLM/DeepSeek-style) emit reasoning_content on assistant turns. Accept it as an inbound alias so reasoning survives the tool-result loop; canonical reasoning wins when both are present. Emission is unchanged (still reasoning). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(schema): pin interleaved reasoning+tool_calls round-trip Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(openai): pin reachedTokenBudget truncation detection Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(anthropic): add thinking and signature fields to content blocks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(anthropic): parse inbound thinking blocks into reasoning Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(anthropic): emit thinking blocks with synthetic signature on tool turns Extract buildAnthropicContentBlocks so non-streaming content assembly is unit-testable, and prepend a thinking block (with an opaque synthetic signature) before text/tool_use blocks when the request opts into thinking. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(anthropic): stream thinking_delta and signature_delta before tool_use Extract anthropicStreamSequence so the streaming block order is unit-testable, and emit content_block_start(thinking) -> thinking_delta -> signature_delta -> content_block_stop before the tool_use block sequence when thinking is enabled. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: add interleaved thinking with tool calls guide Add a features guide describing interleaved thinking: an assistant turn carrying reasoning and tool_calls together, the reasoning-round-trip contract (including the reasoning_content inbound alias and Anthropic thinking blocks with a synthetic signature), per-backend enablement (reasoning_format for llama.cpp, reasoning_parser/tool_call_parser for vLLM/SGLang plus the vLLM auto-config hook), a worked request/response example, and known limitations. Cross-link from model-configuration, text-generation, and openai-functions. 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> |
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LocalAI [bot]andEttore Di Giacinto
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a0ed395cf9 |
fix(auth): accept EC/PS/EdDSA-signed OIDC ID tokens, not just RS256 (#10736)
The OIDC verifier was built with a bare oidc.Config{ClientID: ...}, so
go-oidc applied its default of accepting RS256-signed ID tokens only. An
identity provider configured with an EC signing key (e.g. Authentik) issues
ES256-signed tokens, and the callback failed verification with:
failed to verify ID token: oidc: malformed jwt: unexpected signature
algorithm "HS256"; expected ["RS256"]
surfacing to the user as HTTP 500 "failed to fetch user info" (#10677; the
underlying cause became visible after the logging fix in #10679).
Set SupportedSigningAlgs to the standard asymmetric algorithms
(RS256/384/512, ES256/384/512, PS256/384/512, EdDSA). All are verified
against the provider's published JWKS. HS256 is intentionally excluded: it
is symmetric and would validate against the client secret, a different and
security-sensitive trust model.
Tested with a functional spec that signs an ES256 ID token and confirms it
verifies with the configured algorithms and is rejected under go-oidc's
RS256-only default (using oidc.StaticKeySet, no network).
Closes #10677
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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LocalAI [bot]andEttore Di Giacinto
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cd65a1f645 |
fix(transcription): honor model-config language/translate + OpenAI language form field (#10731)
fix(transcription): honor model-config language/translate, add language form field The /v1/audio/transcriptions endpoint read only input.Language / input.Translate from the parsed request, and the request middleware never populates those from a multipart upload -- nor did it read a `language` form field. As a result the model config's parameters.language / parameters.translate (a valid PredictionOptions field under `parameters:`) were silently ignored, and multilingual models like canary defaulted to translating into English even when the YAML set language: ru, translate: false (#10655). Resolve both with clear precedence: the request form field wins, then any language on the parsed request, then the model config default. This also makes the endpoint honor OpenAI's `language` form parameter, which was not read before. Applies to both the streaming and non-streaming paths (the resolved values are built into the shared TranscriptionRequest). Note this ensures the language/translate flags reach the backend; whether a given engine acts on them is up to the backend. Closes #10655 Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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97175f4b5a |
feat(model): debounce model loads after a failure to stop retry-storms (#10728)
A client that keeps polling a model whose load fails (e.g. a backend that crashes deterministically on init) triggered a fresh backend start on every request: request -> load -> crash in ~10s -> 500, repeat on the next poll. Each attempt could leak GPU/CUDA state, and under LOCALAI_SINGLE_ACTIVE_BACKEND it kept stealing the active slot from healthy models. The existing loading-coalesce map only dedups *concurrent* loads, so sequential polls were never covered. Track load failures per modelID in ModelLoader. After a load fails, refuse fresh load triggers for that model until a cooldown elapses, returning a typed ModelLoadCooldownError that the HTTP layer maps to 503 with a Retry-After header. The cooldown grows exponentially per consecutive failure (base, doubling, capped at 5m) and resets on a successful load. The coalesced follower-retry of an in-flight burst bypasses the gate, so a genuinely concurrent burst still gets its one retry -- only new, independent triggers are refused, matching the report's "refuse new load-triggers" wording. Configurable via --model-load-failure-cooldown / LOCALAI_MODEL_LOAD_FAILURE_COOLDOWN (default 10s, 0 disables), plumbed through ApplicationConfig and applied unconditionally at startup. Closes #10719 Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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bd3f2588fd |
fix(ui): center the home empty-state wizard (#10691)
The no-models getting-started wizard (`.home-wizard`) rendered left-aligned instead of centered. `.home-page` is a column flexbox with the default `align-items: stretch`; a child with `max-width: 48rem` cannot be stretched past its max-width, so it falls back to the cross-start (left) edge. The populated home branch never exposed this because its children are full-width. Add `margin: 0 auto` to `.home-wizard` so the max-width block centers horizontally, for both the admin getting-started wizard and the non-admin no-models hero. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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b0959d4756 |
feat(api): add GET /v1/models/capabilities endpoint (#10687)
Additive superset of /v1/models that enriches each model entry with the capabilities it supports plus its input/output modalities (text / image / audio / video). Clients that only understand /v1/models are unaffected -- they simply never call the new route. Audio and video *input* are derived from the model's multimodal limits (vLLM limit_mm_per_prompt), which no single usecase FLAG expresses. That gap is exactly why a plain capability list is insufficient and this enriched endpoint exists: an attachment router can now decide whether an image/audio/video file can go to the active model directly, or must be converted/transcribed first. Capability derivation lives in core/config as the single source of truth (ModelConfig.Capabilities / InputModalities / OutputModalities / VisionSupported / ...); the Ollama capability surface now delegates to it instead of keeping a parallel copy. Vision is gated on chat/completion capability so a MediaMarker hydrated onto a non-chat model (e.g. a pure ASR/TTS backend) no longer reports a false vision capability. Read-only listing: no new FLAG_* flag, reuses the existing `models` swagger tag, and intentionally exposes no MCP admin tool (there is nothing to manage conversationally). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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9e41be4bfb |
fix(auth): log the real cause of OIDC/OAuth user-info failures (#10679)
The OAuth callback discarded the error returned by user-info resolution before sending the generic 500, so real failures were completely opaque in the logs: ID-token verification errors (e.g. issuer/audience mismatch behind a reverse proxy), a missing id_token, claim-parse errors, or a rejecting GitHub userinfo endpoint all collapsed into "failed to fetch user info" with nothing logged. Log the wrapped cause with xlog.Error (provider + error), matching the code-exchange step just above it. The client-facing message is unchanged, so no internal detail leaks to the browser. Refs #10677 Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Richard Palethorpe
|
eb32cd9073 |
feat(realtime): eager blocking pipeline warm-up + /backend/load API (#10662)
Realtime sessions previously lazy-loaded each pipeline sub-model (VAD,
transcription, LLM, TTS) on first use, so every cold session paid a
per-request model-load stall and load errors only surfaced mid-stream.
Warm the whole pipeline eagerly and blockingly at session start
(including the voice-gate speaker-recognition model, which an enforced
gate blocks each utterance on; compaction's summary_model stays lazy
since it only runs off the response path):
- Add backend.PreloadModel / PreloadModelByName as the single load path
for every modality (no transcription special-case; backend-omitted
configs are deprecated).
- The realtime session blocks on Model.Warmup and returns a
model_load_error to the client if any stage fails to load;
updateSession warms in the background. Opt out per pipeline with
pipeline.disable_warmup, exposed as a UI toggle via the
config-metadata registry.
Add a LocalAI-native POST /backend/load (and /v1/backend/load) that
pre-loads a model -- expanding realtime pipelines into their sub-models
-- as the inverse of /backend/shutdown. There is one preload engine
(backend.PreloadStages): the realtime Warmup methods, /backend/load and
the --load-to-memory startup flag all use it, so --load-to-memory now
also expands pipeline models and records load-failure traces. Pipeline
sub-model alias resolution is likewise shared
(ModelConfigLoader.LoadResolvedModelConfig). Surface the endpoint
everywhere an admin manages models:
- MCP admin tool load_model (httpapi + inproc clients, safety/catalog
prompts, catalog/dispatch tests).
- "Load into memory" action in the React models UI.
- Swagger regenerated; docs moved to the general backend-monitor page
since it is not realtime-specific.
Fix a Traces UI crash ("json: unsupported value: -Inf"): audio-snippet
RMS/peak now floor at a finite dBFS, and backend-trace data is sanitized
to drop non-finite floats before marshaling. The sanitizer is
copy-on-write -- it runs on every RecordBackendTrace, so containers are
only re-allocated on the paths that actually changed.
Migrate core/http/openresponses_test.go onto the prebuilt mock-backend
the rest of the http suite already uses -- it was the last spec still
pointing at a real HuggingFace model, so it 404'd wherever no vision
backend was built -- and fix its item_reference specs to send the
spec's "id" field instead of "item_id", which the handler never
accepted.
Assisted-by: Claude:claude-opus-4-8 Claude Code
Signed-off-by: Richard Palethorpe <io@richiejp.com>
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LocalAI [bot]andEttore Di Giacinto
|
237bce48e8 |
feat(ui): forking chat - retry any answer, copy, duplicate, branch (#10645) (#10654)
* feat(ui): clone a chat into a new conversation (#10645) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): retry any assistant answer, not just the last (#10645) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): copy an entire chat to the clipboard (#10645) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): branch a new chat from any assistant answer (#10645) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ui): send truncated history on mid-conversation retry (#10645) Mid-conversation retry regenerated an answer with the downstream turns still in the model's context. handleRegenerate truncated the DOM history via updateChatSettings (a scheduled state update), but the synchronous sendMessage that followed read the stale, pre-truncation history from its closure to build the outbound API payload. Thread the intended base history explicitly through sendMessage's options.baseHistory so the request body matches the truncated view. Backward compatible: the normal send path (no baseHistory) is unchanged. Also guard two minor issues in Chat.jsx: the "Branch from here" button now renders under !isStreaming to match the retry button, and the duplicate toast only fires when forkChat returns a chat (not on a null result). Assisted-by: Claude:claude-opus-4-8 [Claude Code] 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> |
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LocalAI [bot]andEttore Di Giacinto
|
6eea3ef2ac |
fix(backends): make backend install ops idempotent unless forced (#10643)
* fix(backends): make backend install ops idempotent unless forced POST /backends/apply hardcoded force=true through LocalBackendManager.InstallBackend, so applying an already-installed backend re-downloaded and re-extracted the whole artifact every time. API clients that ensure a backend exists at startup paid a full OCI image pull on every boot. Backend install ops now default to non-forced — an installed, runnable backend short-circuits (the orphaned-meta reinstall path in InstallBackendFromGallery is preserved) — and reinstall stays available: - ManagementOp gains a Force field; the local manager passes it through instead of hardcoding true. - /backends/apply accepts an optional "force" boolean in the body. - The React UI install route keeps forcing, since its button doubles as the explicit "Reinstall backend" action. Distributed installs already behaved this way (workers skip when the binary exists unless force is set); this aligns single-node behavior. Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(backends): don't force-reinstall LOCALAI_EXTERNAL_BACKENDS on boot The startup loop for LOCALAI_EXTERNAL_BACKENDS runs InstallExternalBackend for each listed backend on every boot, and its gallery-name path hardcoded force=true — so every start re-downloaded and re-extracted each listed backend's OCI image even when it was installed and runnable. Supervising apps that list several backends paid several full OCI pulls per launch. Give InstallExternalBackend an explicit force parameter (it only affects the gallery-name fallback; URI installs always write) and pass: - false from the boot loop and `local-ai backends install` (idempotent ensure — `backends upgrade` is the refresh path), - op.Force from the local manager's external-URI op, - the request's force on the worker install path and true on its upgrade path (behavior unchanged). Assisted-by: Claude:claude-fable-5 [Claude Code] 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> |
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LocalAI [bot]andEttore Di Giacinto
|
d74f88357e |
fix(tests): align openresponses test model name with GGUF-derived naming (#10589) (#10609)
PR #10589 changed repo-root HuggingFace URI imports to name the model after
the selected GGUF file rather than the repository. The Open Responses API
integration test still requested the old repo-derived name
("Qwen3-VL-2B-Instruct-GGUF"), so every request 404'd on an unknown model and
the suite has failed on master since
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Adira
|
28d7397743 |
fix(openai): stop max_tokens streaming retry loop on reasoning models (#9716) (#10448)
fix(openai): stop max_tokens streaming retry loop on reasoning models When a thinking model spends its entire max_tokens budget on the reasoning block, the C++ autoparser clears the raw Response and delivers reasoning-only ChatDeltas (no content, no tool calls). ComputeChoices' empty-response retry then fires and regenerates from scratch up to maxRetries times, each re-consuming the whole budget, instead of terminating with finish_reason "length" (issue #9716). Add a reachedTokenBudget helper and suppress both the built-in and caller-driven retries when the completion count has reached the configured max_tokens ceiling. Report finish_reason "length" instead of "stop" in the streaming and non-streaming chat paths when the budget was exhausted. Adds a deterministic regression test that counts backend invocations (previously 6, now 1) plus boundary tests for the helper. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Dennisadira <dennisadira@gmail.com> |
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Richard Palethorpe
|
5d0c43ec6e |
feat(realtime): Semantic VAD EOU token (#10444)
* feat(realtime): EOU-driven semantic_vad turn detection Add a `semantic_vad` turn-detection mode to the realtime API that feeds the transcription model live and decides "the user finished speaking" from the `<EOU>` end-of-utterance token rather than from silence alone. When EOU fires the turn commits immediately (~0.3s); otherwise it falls back to an eagerness-scaled silence threshold (low/med/high = 8/4/2s). Plumbing, bottom to top: - proto: `AudioTranscriptionLive` bidirectional RPC (config-first oneof, mono float PCM @16k, ready-ack / Unimplemented degrade signal) plus `TranscriptResult.eou` for the unary retranscribe gate. - pkg/grpc: client/server/base/embed scaffolding for the bidi stream, modeled on AudioTransformStream; release stream conns on terminal Recv. - parakeet-cpp: live transcription RPC with per-C-call engine locking (one live stream per turn, finalize+free at commit); bump parakeet.cpp to ABI v5 — incremental StreamingMel (no more quadratic per-feed mel recompute that delayed EOU on long turns) and the <EOU>/<EOB> split; strip the literal <EOU>/<EOB> from offline text and set Eou. - core/backend: LiveTranscriptionSession wrapper + pipeline `turn_detection:` config block (type/eagerness/retranscribe). - realtime: semantic_vad integration — live input captions streamed as transcription deltas while the user speaks, EOU-immediate commit with eagerness fallback, optional retranscribe gate (batch re-decode must also end in <EOU> to confirm), clause synthesis off the LLM token callback, and per-turn live-transcription / model_load telemetry. - UI: show the realtime pipeline components as a vertical list. Docs and tests included; opt-in via the pipeline YAML or per-session `session.update`. Non-streaming STT backends degrade to silence-only. Assisted-by: Claude Code:claude-opus-4-8 [Read] [Edit] [Write] [Bash] Assisted-by: Claude Code:claude-fable-5 [Read] [Edit] [Bash] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): explicit formally-verified state machines + parakeet streaming driver The realtime API had several implicit state machines whose state was inferred from scattered booleans, channels, and five separate mutexes, leaving illegal/inconsistent states reachable. Make them explicit and keep the implementation in step with a formal design; rework the parakeet streaming backend along the same lines. Realtime state machines (M1-M5). Each is a sealed sum-type State/Event/Effect with a total, pure Next(state,event)->(state,[]effect) behind a single-writer Coordinator: M1 conncoord connection lifecycle: VAD toggle + once-only teardown (replaces vadServerStarted + a `done` channel closed from two sites). M2 turncoord turn detection: collapses speechStarted and the live-stream "turn open" flag into one state, so discardTurn can no longer desync them and suppress the next onset. M3 respcoord response coordination: serializes the dual-writer start/cancel so at most one response is live; one response.done per response.create. M4 compactcoord conversation compaction: single-flight (replaces the `compacting atomic.Bool` CAS). M5 ttscoord TTS pipeline: open->closing->closed, idempotent wait(), rejects enqueue-after-close (was a silent drop). The Coordinator/Sink/Next plumbing — only the sealed types and Next differed per machine — is extracted once into core/http/endpoints/openai/coordinator as a generic Coordinator[S,E,F]; each machine keeps its public API via type aliases, so no sink, call-site, or test moved. Hierarchy. session_lifecycle.fizz models M1 as the parent region with its children (M2/M3/M4) as one statechart and asserts ChildrenDieWithParent (conn torn => all children terminal, none start after teardown). respcoord and compactcoord gain an absorbing Terminated state + Shutdown event; conncoord's teardown drives the children terminal. This closes a compaction teardown gap: a fire-and-forget compaction could outlive a torn session — compactionSink now takes a session-scoped cancellable context + WaitGroup and joins the in-flight summarize+evict on shutdown. Formal verification. formal-verification/ holds one authoritative FizzBee spec per machine plus the composition spec, each with an always-assertion and a documented one-line edit that makes the checker fail (verified non-vacuous). scripts/realtime-conformance.sh is fail-closed: all Go conformance suites under -race AND a model-check of every .fizz spec; a missing FizzBee is a hard error (only the loud REALTIME_CONFORMANCE_SKIP_FIZZBEE=1 bypasses it, never in CI). FizzBee is pinned by sha256 and installed via scripts/install-fizzbee.sh into .tools/ (gitignored). Wired as make test-realtime-conformance, a CI workflow, and a pre-commit path filter. Go conformance tests are Ginkgo/Gomega (per the repo's forbidigo lint): transition tables + fixed-seed property walks + concurrent/-race specs, no rapid dependency. Design map: docs/design/realtime-state-machines.md. Parakeet streaming backend. The same treatment applied to the parakeet-cpp streaming paths: - AudioTranscriptionStream returns codes.Unimplemented for non-streaming models instead of decoding offline and emitting it as one delta + final. A client that asked for streaming learns the model cannot stream rather than receiving a batch result shaped like a stream. New grpcerrors.StreamTranscriptionUnsupported carries that signal; the HTTP /v1/audio/transcriptions stream path surfaces it as an SSE error event. Mirrors AudioTranscriptionLive, which already did this. - utteranceBoundary (boundary.go): a single definition of the end-of-utterance latch, replacing three open-coded finalEou toggles. Modelled as a two-valued type so illegal states are unrepresentable. - Shared decode driver (driver.go): streamFeedResult (one per-feed event) + feedChunk (hides the ABI v4 JSON vs text-only split) + feedSlices + flushTail. The feed loop is written once. - AudioTranscriptionLive becomes a bidi adapter: it streams the per-feed {delta,eou,eob,words} the realtime turn detector consumes and a terminal FinalResult carrying only Text. Segments/duration/eou are offline-only and no longer produced (nor read) on the live path; liveTraceState drops the terminal eou and keeps the per-feed eou_events count. - AudioTranscriptionStream + streamJSON merge into one driver-based function; streamSegmenter is generalized to the unified event with a text-only fallback that preserves the legacy (no-words) library's per-utterance segmentation. Verified: build/vet/gofumpt clean, golangci-lint 0 issues, all coordinator and parakeet packages under -race, the fail-closed conformance gate green, and make test-realtime (12 e2e WS+WebRTC). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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LocalAI [bot]andEttore Di Giacinto
|
ade9cc9e37 |
fix(openresponses): bound resume-stream buffer and enforce response ownership (#10569)
The background=true resumable-stream path had two latent issues. 1. Unbounded resume buffer. AppendEvent grew StreamEvents without limit, so a long-running or abandoned background generation could consume process memory without bound. The store now caps the buffer (event count and total bytes, mirroring llama.cpp's byte-capped slot ring), evicting oldest events from the front and advancing a droppedThrough watermark. GetEventsAfter returns ErrOffsetLost when the requested starting_after is below the watermark, and handleStreamResume surfaces that as HTTP 409 before committing to the SSE response, so a resuming client gets a clear error instead of a silently truncated stream. 2. Missing ownership check (IDOR). GET /responses/:id, its stream resume, and /cancel looked up responses purely by ID, letting any caller who knows or guesses an ID read or cancel another caller's response. Responses now carry the creating caller's identity (auth.GetUser), stamped at creation and compared on read/cancel/resume; a mismatch returns 404 (not 403) so existence is not leaked. Backward compatible: responses with no owner (single-key / no-auth deployments) remain accessible. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
91885c2c7e |
fix(distributed): return empty backend list for agent nodes instead of failing backend.list (#10545) (#10565)
Opening an AGENT-type worker node's detail page errored with "failed to list backends on node" / NATS "nodes.<id>.backend.list: no responders available". Agent workers only subscribe to agent.*, jobs.*, mcp.* and <prefix>.backend.stop; they never subscribe to backend.list, so the per-node ListBackendsOnNodeEndpoint request had no responder and timed out. The aggregate cluster-wide list already guards this in managers_distributed.go (skip nodes whose NodeType is set and not "backend"). The single-node endpoint lacked the same guard. Thread the NodeRegistry into ListBackendsOnNodeEndpoint and short-circuit to an empty (non-nil) list for non-backend node types before issuing the doomed NATS request, mirroring the aggregate-list gate so both views stay consistent. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
d7d7721eae |
feat(distributed): SyncedMap component + migrate finetune/quant/agent-tasks to cross-replica state (#10542)
* feat(distributed): add SyncedMap cross-replica in-memory state component Introduce core/services/syncstate.SyncedMap[K,V]: a thread-safe in-memory map that keeps itself consistent across frontend replicas via NATS, with an optional pluggable durable Store and hydrate-from-source convergence. Several features keep process-local state surfaced to the API (finetune/quant jobs, agent tasks, model configs) and each hand-wired the same in-memory + NATS broadcast + read-through-store legs - or forgot to, reintroducing cross-replica staleness. SyncedMap makes that consistency a configuration choice: - local writes mutate the map, write through the Store, then broadcast a delta; - the apply path is memory-only and never re-publishes or re-writes the Store (structural echo-loop guard, mirroring galleryop.mergeStatus); - on Start and on NATS reconnect the map re-hydrates from the source (Store, else Loader); an optional periodic Reconcile repairs silent drift; - standalone mode (nil NATS client) is a strict in-memory no-op. Reconnect re-hydrate is wired via a new *messaging.Client.OnReconnect callback, consumed through an optional type-assertion so MessagingClient stays minimal. Adds messaging.SubjectSyncStateDelta and a reusable testutil.FakeBus (synchronous in-process MessagingClient with wildcard matching) for adopter tests. Component only; service migrations follow in subsequent commits. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * refactor(finetune): back jobs with SyncedMap for cross-replica consistency FineTuneService kept jobs in a process-local map and, although it wrote them to Postgres, ListJobs/GetJob never read the store back and the wired natsClient was never used - so in distributed mode a job created on one replica was invisible to the others. Replace the map and the dead client with a syncstate.SyncedMap keyed by job ID, value *schema.FineTuneJob (the exact REST shape, so responses are unchanged). - Add a Store adapter (core/services/finetune/syncstore.go) over FineTuneStore, plus FineTuneStore.ListAll (global hydrate; per-user List kept) and an idempotent Upsert (create-or-update; Create alone fails on dup key). - Writes go through SyncedMap.Set/Delete (write-through + broadcast); reads use List/Get. The on-disk state.json path becomes the standalone Loader, keeping single-node restart recovery (stale->stopped / exporting->failed fixups). - Fold SetNATSClient/SetFineTuneStore into NewFineTuneService; app.go passes the distributed NATS client + store when distributed, nil otherwise. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * refactor(agentpool): back agent tasks with SyncedMap for cross-replica consistency AgentJobService.ListTasks read the process-local tasks map only, while ListJobs already read through the DB persister + dispatcher NATS - so in distributed mode a task created on one replica was invisible to the others. Back tasks with a syncstate.SyncedMap keyed by task ID (value schema.Task, the exact REST shape); jobs are left untouched. - Store adapter (task_syncstore.go) over the existing JobPersister (LoadTasks/SaveTask/DeleteTask); reads svc.persister/userID live so a persister swap needs no rebuild. No new persister methods required. - Task reads -> SyncedMap.List/Get; create/update -> Set (write-through + broadcast); delete -> Delete. The file persister now owns its own task set so the write-through path does not re-enter the SyncedMap lock (deadlock guard). - The distributed NATS client is not available at construction (start() precedes initDistributed), so it is injected via SetTaskSyncNATS, which rebuilds the still-empty map before Start/hydrate. Wired at the main, restart, and per-user (UserServicesManager) distributed sites. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * refactor(quantization): back jobs with SyncedMap + durable QuantStore QuantizationService kept jobs in a process-local map persisted only to a local state.json, so in distributed mode jobs were neither visible across replicas nor durable cluster-wide. Back jobs with a syncstate.SyncedMap keyed by job ID (value *schema.QuantizationJob, the exact REST shape). - New distributed.QuantStore (GORM, table quantization_jobs) mirroring FineTuneStore: Create/Get/ListAll/Upsert(idempotent)/Delete, registered for AutoMigrate via distributed.InitStores (Stores.Quant). - New adapter (quantization/syncstore.go) over QuantStore implementing syncstate.Store, with record<->schema conversion. - Reads go through List/Get, writes through Set/Delete (write-through + broadcast); state.json is kept as the standalone Loader for single-node restart recovery (stale-job fixups preserved). - app.go passes the distributed NATS client + QuantStore when distributed, nil otherwise; Start/Close lifecycle mirrors finetune. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(syncstate): annotate gosec G118 false positive on lifeCtx gosec flagged the WithCancel in Start as "cancellation function not called" because the returned cancel is stored on the struct rather than called/deferred in scope. It is invoked in Close (covered by tests), and lifeCtx must outlive Start to drive the reconnect/reconcile goroutines. Suppress the verified false positive with a justified #nosec G118. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * test(distributed): e2e two-replica SyncedMap sync over real NATS + Postgres Adds the real-infrastructure counterpart to the fake-bus unit tests, in the existing distributed e2e suite (testcontainers NATS + PostgreSQL). Two SyncedMap instances stand in for two frontend replicas - each with its OWN NATS connection to a shared server and a SHARED Postgres store (the distributed-mode invariant) - and assert, over the wire: - a create on replica A is observed by replica B; - an update and a delete propagate A -> B (delete prunes, which a reload cannot); - a late-joining replica recovers a job it never received a delta for, via store hydrate on Start (the at-most-once gap a fake bus cannot exercise); - a local Set is written through to the shared Postgres store. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
64150ca7ab |
fix(distributed): broadcast admin model-config changes across replicas (#10540)
In distributed mode the admin model endpoints (/models/edit, /models/import, /models/toggle-state and the PATCH config-json endpoint) wrote the YAML to the shared models dir but reloaded only the local replica's in-memory ModelConfigLoader. With multiple frontend replicas behind one service, a save landed on whichever replica handled the request; peers kept serving their stale in-memory view, so a load-balanced request was a coin-flip between old and new config (a created alias visible on one replica and missing on the other, an edited alias target diverging, etc.). The NATS cache-invalidation channel (SubjectCacheInvalidateModels + OnModelsChanged) already existed for the gallery install/delete path; these admin endpoints simply never published on it. Wire them up via a new GalleryService.BroadcastModelsChanged helper (no-op in standalone mode). Also fix delete propagation: LoadModelConfigsFromPath is additive and never drops an entry whose file is gone, so the subscriber hook (which only reloaded from disk) could not propagate a removal. ApplyRemoteChange now honors the event op - pruning the element on "delete" and reloading otherwise - and shuts down any running instance of the affected model so the new config takes effect. This closes the same latent gap on the gallery delete path. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
56600eec3e |
fix(nodes): show a node's existing labels on the detail view (#10529)
fix(nodes): return labels in single-node GET so the detail view shows them The node detail view (/app/nodes/:id) reads `node.labels` to render a node's existing labels, but the single-node GET endpoint returned a bare BackendNode whose Labels live in a separate table - so the list was always empty and operators could only add labels, never see what was already set (#10527). The same response also lacked in_flight_count and model_count. Add NodeRegistry.GetWithExtras, mirroring the existing List vs ListWithExtras split: bare Get stays cheap for the routing hot paths and existence checks, while the detail endpoint uses the enriched variant to attach the labels map and live counts. No frontend change is needed - the UI already renders existing labels once the data is present. Closes #10527 Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
f72046b5b5 |
fix(auth): make advisory locks dialect-aware and harden SQLite DSN (#10509)
* fix(auth): make advisory locks dialect-aware and harden SQLite DSN Fixes #10506. Two failures hit deployments that use the default SQLite auth database: 1. advisorylock executed PostgreSQL-only SQL (pg_advisory_lock / pg_try_advisory_lock) unconditionally. On a SQLite auth DB the job store, agent store and node registry migrations failed with "no such function: pg_advisory_lock". WithLockCtx/TryWithLockCtx now branch on the gorm dialect: PostgreSQL keeps the cross-process advisory lock, every other dialect uses a context-aware, per-key in-process lock (a SQLite auth DB is effectively single-process, so serializing within the process is sufficient). 2. The SQLite auth DSN set no busy timeout, so transient SQLITE_BUSY over network-backed storage (SMB/CIFS/NFS, e.g. Azure Files) failed the auth migration immediately with "database is locked". The DSN now sets _busy_timeout=5000 and _txlock=immediate (caller-supplied values are preserved). WAL is intentionally not enabled since its shared-memory mmap does not work over network filesystems. Docs note that PostgreSQL should be used when the data directory lives on shared storage. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * test(jobs): regression test for #10506 SQLite job store migration Exercises the exact caller chain that failed in the issue: auth.InitDB(sqlite) -> jobs.NewJobStore -> advisorylock.WithLockCtx -> AutoMigrate. Before the dialect-aware advisory lock fix this failed with "no such function: pg_advisory_lock"; the test now asserts it migrates cleanly on a SQLite auth DB. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
fe4f425fb5 |
fix: correct scheme/host on self-referential URLs behind an HTTPS reverse proxy (#10482) (#10504)
* fix(http): harden BaseURL proxy scheme/host detection Split comma-separated X-Forwarded-Proto and honor the RFC 7239 Forwarded header so generated links use https behind common reverse-proxy setups. Refs #10482 Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(http): honor explicit external base URL in BaseURL When _external_base_url is set in the request context it dictates the origin (scheme+host+port); the proxy path prefix is still appended. Refs #10482 Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(config): generalize LOCALAI_BASE_URL to ExternalBaseURL LOCALAI_BASE_URL now sets a single instance-wide external base URL used for OAuth callbacks and all self-referential links. A Pre middleware stamps it into the request context for middleware.BaseURL. Refs #10482 Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: document LOCALAI_BASE_URL and reverse-proxy headers Refs #10482 Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(http): cover parseForwarded edge cases; clarify base-url flag group Adds direct unit coverage for quoted/malformed/multi-element Forwarded headers and regroups the external base URL flag away from auth-only. Refs #10482 Assisted-by: Claude:claude-opus-4-8 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> |
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LocalAI [bot]andEttore Di Giacinto
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f88981cdce |
feat(ui): data-driven hardware model recommendations + gallery surfacing (#10500)
* feat(ui): make hardware starter models data-driven The empty-state starter widget recommended from a hardcoded list, which drifts as the gallery evolves. Add useRecommendedModels: it queries the live gallery for chat-capable models (their natural curated order, since the gallery exposes no popularity signal), estimates size/VRAM for the top candidates via the existing estimate endpoint, and ranks by hardware fit - smallest on CPU-only boxes, largest-that-fits on GPUs. StarterModels now renders those live picks and keeps the curated static list only as an offline/trimmed-gallery fallback. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): recommend models for your hardware in the gallery Hardware-aware recommendations were only shown on the first-run empty state. Surface them on the main Models gallery too: a dismissible "Recommended for your hardware" strip at the top, sharing the useRecommendedModels fit-ranking with the starter widget. CPU-only boxes get small models; GPUs get the largest picks that fit VRAM, with size and VRAM shown per card. One-click install; dismissal persists per browser. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): gpu-mid tier + NVIDIA NVFP4 model recommendations Refine the hardware recommendation tiers and curated picks: - Add a gpu-mid tier (8-24GB VRAM) between gpu-small and gpu-large, so ~27B-class models are suggested separately from the 30B+ large tier. - Detect NVIDIA GPUs (resources.gpus[].vendor) and, on NVIDIA only, prefer NVFP4 + MTP variants (Blackwell-optimised); NVFP4 models are filtered out of recommendations on non-NVIDIA hardware where they can't run. This applies to both the live ranking and the static fallback, with an NVFP4 badge shown on those picks. - Refresh the curated fallback to current models: Gemma-4 QAT Q4 builds at every tier, low qwen3.5 (4B distilled / 9B) on CPU/small, qwen3.6-27b and MTP variants at mid, qwen3.6/qwen3.5 35B-A3B apex/distilled at large. All names verified against gallery/index.yaml. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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5c3d48ab50 |
feat(ui): usage & UX enhancements (last-used model, polling, starter models, usage cost, a11y) (#10496)
* feat(ui): remember last-used model per capability ModelSelector auto-selected the first option whenever the bound value was empty or stale, so every visit to the Home chat box, Image, TTS or Talk pages reset the choice to whatever sorted first. Persist the user's pick in localStorage keyed by capability and prefer it on auto-select when the model is still available, falling back to the first option otherwise. Because every modality picker funnels through ModelSelector, this fixes the friction everywhere at once. External-options callers pass no capability and keep the previous first-item behaviour. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): add visibility-aware polling hook The app had 26 hand-rolled setInterval polls, none of which paused when the browser tab was hidden, so backgrounded dashboards kept hitting the server every few seconds for data nobody was looking at. Add usePolling: runs immediately, polls on a fixed interval, pauses while document.hidden, fires a catch-up poll on return, and guards against overlapping slow requests. Route useResources (the highest-frequency shared poll) through it. Further callers can be migrated incrementally. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): hardware-aware starter models on empty home A fresh install dropped admins straight into a 1000+ model gallery with no guidance. Add a StarterModels widget to the empty-state wizard that recommends a small, curated set tuned to the detected hardware: - CPU-only machines (no GPU VRAM) are steered to genuinely small models (1-4B, Q4) that stay responsive without a GPU. - GPU machines get suggestions scaled to available VRAM. Curated names are real gallery entries, intersected against the live gallery at render time so a trimmed/custom gallery degrades gracefully. Install is one click via the existing model-install API. Also routes Home's cluster and system-info polls through usePolling so a backgrounded home page stops fetching. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): optional token-cost estimates on usage dashboard The usage dashboard tracked tokens but had no monetary view. Multi-user deployments that bill back or budget compute had to export and compute cost elsewhere. Add an opt-in pricing control: admins set $ per 1M prompt/completion tokens (stored per-browser). When set, an estimated-cost summary card and per-model / per-user cost columns appear, computed from recorded token counts. The entire cost surface stays hidden until a price is entered, so the default view is unchanged. Cost is clearly labelled an estimate - LocalAI itself has no notion of price. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(ui): label icon-only send buttons for screen readers The chat and agent-chat send buttons were a bare paper-plane icon with no accessible name, so screen readers announced only "button". Add an aria-label/title ("Send message") and mark the icon aria-hidden. An audit of all icon-only buttons found these were the only two unlabeled controls; the rest already carry visible text. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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482314c623 |
fix(realtime): resolve model aliases for pipeline sub-models (#10484)
Realtime pipeline sub-models (llm/transcription/tts/vad/sound-detection)
were loaded via cl.LoadModelConfigFileByName without alias resolution,
unlike top-level API requests which resolve aliases in
core/http/middleware/request.go. So a pipeline that references an alias
(e.g. `pipeline.llm: default`, where `default` is an alias for a real
LLM) reached model loading as the alias stub with an empty Backend.
This was silently broken on a single host (it failed downstream) and a
hard error in distributed/p2p mode:
routing model : loading model default: ... installing backend on
node X: backend name is empty
Fix by routing every pipeline sub-model load through a small helper that
follows a single alias hop (mirroring the top-level resolution), so
non-alias sub-models behave identically and aliased ones get the
target's full config (Backend, Model, ...).
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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Dedy F. Setyawan
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e8ae88a2a0 |
i18n(id): update and complete Indonesian translations (#10480)
- translate remaining English strings in chat, common, home, and media locales. - fix typo and improve wording consistency (e.g., klaster -> kluster, otomasi -> automasi). Signed-off-by: Dedy F. Setyawan <dedyfajars@gmail.com> |
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Richard PalethorpeandEttore Di Giacinto
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e1994579f8 |
fix(pii): load default detectors at startup + add LOCALAI_PII_DEFAULT_DETECTORS (#10474)
pii_default_detectors was applied to the live config only by a live POST /api/settings (ApplyRuntimeSettings) — neither the startup loader nor the config file watcher read it back. So after a restart the persisted default detectors were dropped, and the cloud-proxy MITM listener (which resolves each intercept host's detectors once at start via ResolvePIIPolicy) came up with an empty set and forwarded intercepted traffic unredacted, even though the MITM model had pii.enabled:true and the defaults were on disk. Request-side default redaction broke the same way. - startup.go: loadRuntimeSettingsFromFile now applies pii_default_detectors, before startMITMIfConfigured, with env > file precedence. - config_file_watcher.go: apply pii_default_detectors on live file edits, matching the existing env-guard pattern used for the other fields. - settings endpoint: rebuild the MITM listener when pii_default_detectors changes (its per-host detector map is frozen at listener start), not only on a mitm_listen change — so toggling a default detector takes effect on cloud-proxy traffic immediately. - new LOCALAI_PII_DEFAULT_DETECTORS env var / CLI flag (WithPIIDefaultDetectors) so the default detector set can be pinned at boot for immutable deployments. Assisted-by: Claude:claude-opus-4-8 Claude-Code Signed-off-by: Richard Palethorpe <io@richiejp.com> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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LocalAI [bot]andEttore Di Giacinto
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e6042080c0 |
fix(agents): URL-decode collection/agent name path params (#10443) (#10471)
fix(agents): URL-decode collection/agent name path params
Collection and agent names carry a "legacy-api-key:" prefix, so the ':'
arrives percent-encoded as %3A in the request path. Echo routes such
paths via URL.RawPath and stores the matched path-param value still
escaped, so c.Param("name") returned "legacy-api-key%3ALiteraryResearch"
and the store lookup 404'd ("collection not found").
This was second-order fallout of #10375/#10387: once colons became valid
in names, the URL-decode gap surfaced on every name-bearing endpoint.
Add a decodedParam helper that url.PathUnescape's the param (falling back
to the raw value on invalid encoding) and wire it into all collection
endpoints and the agent :name endpoints, which share the identical
prefix. The entry endpoints already unescaped c.Param("*"); this closes
the same gap for :name.
Fixes #10443
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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Richard Palethorpe
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7888067914 |
fix(settings): merge partial /api/settings updates instead of overwriting (#10463)
POST /api/settings rebuilt runtime_settings.json from only the request body, so a focused admin page that submits a single field wiped every other persisted setting. The Middleware proxy tab (mitm_listen) and detector table (pii_default_detectors), plus the MCP SetBranding tool (instance_name/instance_tagline), all POST partial bodies; the no-omitempty api_keys and pii_default_detectors fields even round-tripped as JSON null. Read the persisted settings and overlay only the fields the request set (RuntimeSettings.MergeNonNil) before writing. Every field is a pointer, so the reflection-based merge is total over the struct and any field added later is preserved automatically. Absent or null fields are now kept; clearing a setting is done by sending its explicit empty/zero value (api_keys [], mitm_listen "", etc.), unchanged from before. The full Settings page sends every field, so its Save behaves identically. Assisted-by: Claude:claude-opus-4-8 Claude-Code Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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Ettore Di Giacinto
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4755d676a3 |
Revert "feat(ui): role and deployment-mode adaptive UI (landing, sidebar, top navbar)" (#10453)
Revert "feat(ui): role and deployment-mode adaptive UI (landing, sidebar, top…"
This reverts commit
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LocalAI [bot]andEttore Di Giacinto
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fdf475ec5f |
feat(realtime): conversation compaction (summarize-then-drop) + OpenAI item.delete/truncate/clear (#10446)
* feat(realtime): add pipeline.compaction config + resolution Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(realtime): extract itemID helper, reuse in item.retrieve Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(realtime): drop duplicate Ginkgo bootstrap, fold specs into openai suite Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): implement conversation.item.delete Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): implement input_audio_buffer.clear Add a handler for the input_audio_buffer.clear client event that discards a partially-captured utterance (raw PCM + buffered Opus frames) via a unit-tested clearInputAudio helper, then acks with input_audio_buffer.cleared. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): implement conversation.item.truncate (text) Clears both .Text and .Transcript of the assistant content part at contentIndex so barge-in truncation also works for audio turns whose spoken words live in .Transcript. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): add Conversation.Memory + pair-safe compactionCut Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(realtime): compactionCut returns 0 for keep<=0 (no-cap sentinel, avoids panic) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(realtime): gofmt compaction test helper closures Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): inject rolling memory into the prompt + summary builders Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): server-side summarize-then-drop compactor Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(realtime): unit-test prefixMatches eviction-safety predicate Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): resolve summarizer model + schedule compaction per turn Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(realtime): document conversation compaction + new item events Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(realtime): resolve summary model inside compaction goroutine (lazy, off-path) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(realtime): reuse reasoning.ExtractReasoningComplete for summary stripping Replace the bespoke <think> regex in the compactor with the shared pkg/reasoning extractor (via spokenReasoningConfig), matching the rest of the realtime path and covering all reasoning tag families, not just <think>. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(config): register pipeline.compaction fields in meta registry TestAllFieldsHaveRegistryEntries requires every ModelConfig field to have a UI/meta registry entry; add the four pipeline.compaction.* leaves so they render with proper labels/descriptions instead of the reflection fallback. Assisted-by: Claude:claude-opus-4-8 [Claude Code] 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> |
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LocalAI [bot]andEttore Di Giacinto
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9d54a599b0 |
feat(ui): role and deployment-mode adaptive UI (landing, sidebar, top navbar) (#10449)
* feat(ui): add shared DeploymentContext (features + p2p signal) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(ui): extract launchAssistantChat shared helper Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): role/mode-aware landing redirect at /app Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): pin Cluster group and collapse Create for cluster admins Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): desktop top navbar with mode pill and admin-via-chat jump Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): admin token-usage meter in the top navbar Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ui): top-navbar breakpoint handoff + assistant jump from chat page M1: the desktop .top-navbar was hidden at max-width 768px while the .mobile-header only appears at max-width 639px, leaving 640-768px with neither bar so admins lost the mode pill, token meter and admin-via-chat jump. Hide the top bar at 639px instead so it covers every width the rail sidebar is shown and hands off to the mobile-header exactly at 639px. M2: the navbar 'Admin via chat' button wrote localStorage and called navigate('/app/chat'), but when already on the chat page Chat does not remount so its mount-time payload reader never fired and the click was a no-op until reload. The payload consume logic is factored into a shared callback; the launcher now dispatches a localai-open-assistant event that the mounted Chat listens for to re-consume the payload. Mount behavior is unchanged. Assisted-by: Claude:claude-opus-4-8 [Claude Code] 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> |
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Richard Palethorpe
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63bcbf6c12 |
fix(pii): post-merge review fixes + live NER e2e for the privacy-filter tier (#10401)
* fix(pii): post-merge review fixes + live NER e2e for the privacy-filter tier Follow-up to the NER tier engine (#10360), already on master. This carries only the incremental review fixes and tests that postdate that merge — the feature itself is not re-introduced. Review fixes: - openai_completion.go: remove the dead `elem >= 0` conjunct in applyAnyText (the `elem < 0` guard above already returns). - application.go: collapse ResolvePIIPolicy's inline re-implementation of PIIIsEnabled to a single cfg.PIIIsEnabled() call (sole source of the "explicit pii.enabled wins, else cloud-proxy default" rule) and return true past the !enabled guard where it is provable. - pattern.go: hoist the triple `appConfig != nil && EnableTracing` check in patternDetector.Detect into one local. - grammar.go: MaxQuantifier was 4096, but Go's regexp/syntax rejects repeat bounds above 1000 at Parse time, so walk()'s {n,m} guard could never fire — dead code shadowed by the parser. Lower it to 512 so a bound in (512,1000] is rejected here with an actionable error; >1000 still fails closed via Parse. Specs pin the relationship so the guard can't silently revert. - PatternListEditor.jsx: clamp a directly-typed negative min_len to >=0 and force the DOM value back when clamping (min={0} only constrained the spinner, so a negative reached saved config and silently disabled the length filter). Tests: - piipattern_test.go: MaxQuantifier guard specs (must stay live, not dead). - model-config.spec.js: assert the min_len clamp, and that entity_actions collapses a duplicate group to a single row (map semantics; regression guard against emitting an array that drops a row on save). - tests/e2e-backends: token_classify capability driving the TokenClassify gRPC RPC against the backend image, asserting byte-correct, UTF-8 rune-aligned spans (entity.Text == text[start:end]) at threshold 0. Verified on CPU via `make test-extra-backend-privacy-filter` (3/3 specs). - Makefile: test-extra-backend-privacy-filter wrapper. - tests/e2e: e2e_pii_ner_test.go drives /api/pii/analyze + /api/pii/redact (mask + block) through the full HTTP -> detector -> redactor path; gated on PII_NER_MODEL_GGUF so the default suite is unaffected. - .github/workflows/tests-pii-ner-e2e.yml: path-filtered / nightly CI job running the container harness on CPU. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(gallery): add privacy-filter-nemotron (f16 + q8) GGUF conversions of OpenMed/privacy-filter-nemotron — a fine-grained English PII token-classifier (55 categories / 221 BIOES classes), fine-tuned from openai/privacy-filter on NVIDIA's Nemotron-PII dataset. Sibling to the existing privacy-filter-multilingual entry, trading language breadth for category depth. - privacy-filter-nemotron: F16 reference artifact (~2.8 GB). - privacy-filter-nemotron-q8: Q8_0 quant (~1.64 GB) for RAM-constrained / edge use; description notes the size/speed tradeoff and to validate on your own data (a single dropped span is a PII leak). Both run on the privacy-filter backend with known_usecases [token_classify] and a default mask policy (min_score 0.5); operators add per-category entity_actions as needed. sha256s taken from the HF repo's LFS object ids. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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LocalAI [bot]andEttore Di Giacinto
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95b058e1c5 |
feat(ui): restructure Cluster Nodes view (pulse + panel roster + detail page) (#10447)
* chore: gitignore SDD scratch directory Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(nodes): add GET /api/nodes/models cluster-wide loaded-models endpoint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): add nodesApi.allModels() for cluster-wide model roster Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): move Scheduling to its own page and nav item Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): replace nodes stat-card strip with cluster pulse + attention callout Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): node-panel roster with inline model chips and segmented filter Replace the Nodes table with a full-width node-panel roster that shows each backend node's running-model chips without an expand click, plus an All/Backend/Agent segmented filter. Per-node detail (models, backends, labels, capacity) moves to the node detail page. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * feat(ui): add deep-linkable node detail page at /app/nodes/:id Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(ui): remove em-dash from CapacityEditor comment; align detail spec backend mock Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * chore(ui): nodes page cleanup, hover/chip polish, docs for restructured cluster view Nodes.jsx dead-code sweep confirmed clean (no StatCard/table/expand state/scheduling-form leftovers). Two App.css polish fixes: move the node-panel hover border-color onto the bordered element so hover gives real feedback, and add the missing .model-chip__state rule the ModelChip component already emits. Update distributed-mode docs prose to describe the restructured cluster view (cluster pulse, attention callout, node-panel roster with inline model chips, All/Backend/Agent filter, node detail page at /app/nodes/:id, Scheduling as its own page). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * chore(ui): drop unused gpuVendorLabel export from nodeStatus Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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600dafd20b |
feat(ced): sound-event classification backend (CED audio tagger) (#10425)
* feat(ced): sketch sound-classification backend (CED audio tagger) Wires ced.cpp (CED, 527-class AudioSet sound-event tagger; baby cry, footsteps, glass, alarms, dog bark) into LocalAI as a Go/purego backend. SKETCH (backend skeleton real; core REST wiring + CI/gallery is a checklist in DESIGN.md): - backend/backend.proto: new SoundDetection rpc + SoundClass messages (run `make protogen-go` to regenerate pkg/grpc/proto). - backend/go/ced: main.go (purego dlopen libced.so + ced_capi.h), goced.go (Ced gRPC backend: Load + SoundDetection), Makefile (clone-at-pin CED_VERSION, ggml static-PIC shared build), run.sh, package.sh, .gitignore. - DESIGN.md: REST /v1/audio/classification wiring (handler/route/capability registration checklist), gallery/index + CI registration, and a scoping note for the realtime/websocket live-recognition path (sliding-window classify over the existing ws transport + voicegate; the ced C-API per-PCM entry point is already window-friendly). Backend code does not compile until protogen-go regenerates the pb types and a libced.so is built (Makefile clones+builds it). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): REST /v1/audio/classification endpoint + capability registration Wires the ced sound-event classification backend (AudioSet audio tagger) end to end through the REST surface, mirroring the transcription path. - Handler: core/http/endpoints/openai/sound_classification.go parses the multipart audio upload, temp-files it, resolves the model config and calls the SoundDetection RPC; returns {model, detections[]} JSON. - Backend wrapper: core/backend/sound_classification.go (ModelSoundDetection) loads the model and normalizes the proto response into schema types. - Schema: core/schema/sound_classification.go (SoundClassificationResult). - gRPC layer: SoundDetection wired through the LocalAI wrapper (interface, Backend client, Client, embed, server, base default) so the loader-typed client exposes the RPC; proto regenerated via make protogen-go. - Route: POST /v1/audio/classification (+ /audio/classification alias) with the audio/multipart default-model middleware in routes/openai.go. - Capability surfaces: swagger @Tags/@Router on the handler; FLAG_SOUND_ CLASSIFICATION usecase flag + UsecaseSoundClassification + UsecaseInfoMap + GuessUsecases + ModalityGroups + GetAllModelConfigUsecases; meta usecase option; /api/instructions audio area updated; auth RouteFeatureRegistry + FeatureAudioClassification (APIFeatures, default ON) + FeatureMetas; UI usecaseFilters, capabilities.js CAP_SOUND_CLASSIFICATION, Models.jsx filter + i18n; docs page features/audio-classification.md + whats-new + crosslink. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): realtime sound-event detection over the websocket API When a realtime pipeline configures a sound-classification model, each VAD-committed utterance (the same window the transcription path produces) is also run through the CED sound-event classifier and the scored AudioSet tags are emitted as a new server event. No new backend rpc is needed: the SoundDetection gRPC method already exists on this branch. - config: add Pipeline.SoundDetection (yaml/json sound_detection,omitempty) beside Transcription/VAD. - realtime: add Model.SoundDetection(ctx, audio, topK, threshold) to the ModelInterface; implement it on wrappedModel and transcriptOnlyModel by calling backend.ModelSoundDetection with the session's sound-classification model config (mirrors how Transcribe dispatches). Load the optional config in newModel / newTranscriptionOnlyModel; nil config keeps it additive. - types: add ConversationItemSoundDetectionEvent (item_id, content_index, detections[]{label,score,index}) with type conversation.item.sound_detection, its ServerEventType constant and MarshalJSON, mirroring the transcription completed event. - realtime: add emitSoundDetection (unary path: classify the committed window, build the event, t.SendEvent) and wire it at the utterance-commit hook right after emitTranscription; gated on session.SoundDetectionEnabled (resolved from Pipeline.SoundDetection at session setup, defaults top_k=5, threshold=0). Its error is logged via xlog but never aborts the turn. - test: Ginkgo specs for emitSoundDetection (tags emitted, empty detections, classifier error) plus a SoundDetection method on the fakeModel double. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ced): implement SoundDetection in nodes backend test doubles The SoundDetection method added to the grpc backend interface left two test doubles (fakeBackendClient, fakeGRPCBackend) incomplete, so core/services/nodes failed to compile under `go vet`/`go test` (go build missed it: the doubles live in _test.go). Add the method to both, mirroring their existing Detect mock. Repairs CI for the nodes package. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): decouple realtime sound detection from VAD (sound-only sessions) Sound-event detection must activate on sounds, not speech, so it no longer runs through the voice VAD/transcription path. A sound-detection-only pipeline (sound_detection set, no transcription/LLM) now: - is accepted by prepareRealtimeConfig (sound_detection counts as a pipeline stage), - builds a lightweight model via newSoundDetectionOnlyModel (no VAD/STT/LLM/TTS loaded), and - defaults the session to turn_detection none (no VAD) with no transcription stage, so the client drives windowing via input_audio_buffer.commit (option A: client-side sliding window). The per-PCM C-API already supports arbitrary windows. commitUtterance gains a sound-only branch: it emits the conversation.item.sound_detection event (scored AudioSet tags) and stops - no transcription, no LLM response. generateResponse is now guarded on a transcription stage being present, so a sound-only turn never invokes the LLM. Existing transcription/VAD sessions are unchanged (additive). Added a commitUtterance sound-only Ginkgo spec asserting it emits the sound event and neither transcribes nor generates a response. go vet + golangci-lint (new-from-merge-base) clean; openai suite green. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): register sound-classification backend in gallery + CI Mechanical backend-image registration for the ced sound-event classifier, mirroring the parakeet-cpp Go/purego backend everywhere it is wired up. - .github/backend-matrix.yml: add the ced build matrix, field-for-field copies of the parakeet-cpp entries (cpu amd64/arm64, cublas cuda 12/13 amd64, l4t cuda-13 arm64, l4t-jetpack cuda-12 arm64, sycl f32/f16, vulkan amd64/arm64, rocm hipblas, and the metal darwin entry), changing only backend and tag-suffix. dockerfile stays ./backend/Dockerfile.golang. - backend/index.yaml: add the &ced meta anchor (capabilities map per platform) plus ced-development and the per-arch image entries, each uri/mirror tag-suffix matching the matrix exactly. The model gallery (GGUF) entry is intentionally deferred pending the HuggingFace publish (TODO note inline). - scripts/changed-backends.js: add an explicit item.backend === "ced" branch in inferBackendPath mapping to backend/go/ced/, same mechanism and ordering as the parakeet-cpp branch (before the generic golang fallthrough). - .github/workflows/bump_deps.yaml: register mudler/ced.cpp -> CED_VERSION in backend/go/ced/Makefile so the daily bot bumps the pin. - swagger/{docs.go,swagger.json,swagger.yaml}: regenerated via make swagger so the existing /v1/audio/classification annotations land in the generated spec. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): server-side windowing for realtime sound detection (option B) Adds an optional server-driven sliding-window classifier so a sound-only realtime client only has to stream audio (no input_audio_buffer.commit): - Pipeline.sound_detection_window_ms / sound_detection_hop_ms config knobs. When both > 0 on a sound-only session, the server classifies the last window of streamed audio every hop and emits a conversation.item.sound_ detection event; the input buffer is trimmed to one window so a long stream stays bounded. When unset, the session stays client-driven (option A). Runs independent of VAD (sound events are not speech). - handleSoundWindow (ticker) + classifySoundWindow (one tick, extracted so it is unit-testable) + writeWindowWAV, which declares the true InputSampleRate (NewWAVHeaderWithRate) so the classifier resamples correctly. Goroutine is started after toggleVAD and torn down with the session (close + wg.Wait). - Register pipeline.sound_detection (+window_ms/hop_ms) in the config meta registry; the earlier realtime commit added pipeline.sound_detection without a registry entry, failing TestAllFieldsHaveRegistryEntries. This fixes that and covers the two new knobs. Tests: classifySoundWindow emits an event + trims the buffer to one window, no-ops on too-little audio; writeWindowWAV declares the given sample rate. go build/vet + golangci-lint (new-from-merge-base) clean; config + openai suites green. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): add ced-base GGUF model gallery entries (f16 + q8_0) The ced-base weights are now published at mudler/ced-base-gguf (Apache-2.0, converted from mispeech/ced-base). Adds gallery/ced.yaml (backend: ced + known_usecases: sound_classification) and two gallery/index.yaml entries (ced-base-f16 default, ced-base-q8 smallest) with sha256-pinned files, and removes the now-resolved TODO from backend/index.yaml. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): add tiny/mini/small GGUF model gallery entries Publishes the rest of the CED family (same architecture, metadata-driven port verified end-to-end on ced-tiny) to mudler/ced-{tiny,mini,small}-gguf and adds their f16 + q8_0 gallery entries: ced-tiny (5.5M, edge/Pi-class) f16 11MB / q8_0 6MB ced-mini (9.6M) f16 19MB / q8_0 11MB ced-small (22M) f16 42MB / q8_0 23MB All sha256-pinned. ced-base remains the accuracy default. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ced): point gallery entries at the consolidated mudler/ced-gguf repo All CED quantizations (tiny/mini/small/base, f16/q8_0) now live in a single HuggingFace repo, mudler/ced-gguf, instead of per-model repos. Repoint the 8 gallery model entries' urls + file uris accordingly. sha256 and filenames are unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ced): bump CED_VERSION to the short-clip fix Pin the ced backend to ced.cpp 99c6ed3, which fixes a crash on any clip shorter than target_length (~10.11s): time_pos_embed was added at its full 63-frame grid instead of being sliced to the clip's actual time grid, tripping ggml_can_repeat in ggml_add. Surfaced by the live realtime e2e (sub-10s windows) and gated with a short-clip parity test upstream. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(ced): list ced.cpp as a LocalAI-team engine + backend-guide directive - README.md: add ced.cpp to the "native C/C++/GGML engines developed and maintained by the LocalAI project" table. - docs/content/features/backends.md: add a Sound Classification backend category (sound-event classification / audio tagging) listing ced.cpp. - .agents/adding-backends.md: add a "Documenting the backend" section and two verification-checklist items requiring new backends to be documented in the backends.md category list, and in-house native engines to be added to the README maintained-engines table. This directive was missing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ced): repin CED_VERSION to the v0.1.0 release commit ced.cpp history was squashed into a single release commit (tagged v0.1.0), so the previous pin (99c6ed3) no longer exists upstream. Pin to c04ac14, the v0.1.0 release commit, so the backend builds against a commit that exists. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ced): silence gosec G304/G103 + govet unsafeptr on audited paths - sound_classification.go: os.Create(dst) where dst = temp dir + path.Base of the upload (no traversal). #nosec G304, matching the depth-anything-cpp handler. - goced.go: reading a NUL-terminated C string from a libced-owned buffer. #nosec G103 (gosec) + //nolint:govet (golangci-lint's unsafeptr check), since the uintptr is a C-owned malloc'd buffer, not Go-GC memory. 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> |
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32c47706ae |
feat(realtime): speaker-aware conversations - surface identity to client and LLM (#10424)
* feat(realtime): add voice_recognition enforce + identity config Add Enforce *bool and Identity *VoiceIdentityConfig to PipelineVoiceRecognition, plus EnforceGate/IdentityEnabled/ AnnounceEnabled/PersonalizeEnabled helpers. Enforce nil defaults to gating (backward compatible); identity surfacing is independent of the gate. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): add Speaker type and conversation.item.speaker event Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(realtime): split voiceGate into Resolve + authorize Split the speaker authorization into a Resolve step (embed once, produce a types.Speaker identity) and a pure authorize policy step, with a 0..100 confidence score mirroring /v1/voice/identify. The legacy Authorize wrapper is kept so existing specs stay green. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): resolve speaker per turn and emit conversation.item.speaker Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): personalize LLM turns with recognized speaker Set the per-message name field on each recognized user turn and append a current-speaker note to the system message, both gated by the voice recognition identity config. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(realtime): document speaker identity surfacing and personalization Document the new voice_recognition keys (enforce, identity.*) and the LocalAI-extension conversation.item.speaker server event in the realtime feature docs. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(realtime): cover when:first+identity re-resolution and multi-speaker history Add two integration specs to harden the speaker-aware realtime path: - when:first with an Identity block re-resolves the speaker every turn even though re-authorization is skipped after the first match: a later resolve error now fails closed, while a clean later resolve still surfaces and names the speaker. - multi-speaker history attribution: each user turn carries its own per-message name and the injected system note reflects the latest speaker. Test-only change; no production behavior was modified. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(realtime): surface speaker labels in conversation.item.speaker Carry the registered speaker's labels (identify mode) on types.Speaker so they flow into the conversation.item.speaker event and the stored item. Verify mode has no labels, so the field is omitted there. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(e2e): cover conversation.item.speaker over a real websocket Add a realtime-pipeline-identity config (verify mode, enforce:false, identity announce+announce_unknown+personalize) and two e2e specs driving the real server over a real WebSocket with the mock VoiceEmbed backend: an authorized speaker yields a conversation.item.speaker event naming e2e-speaker (matched true) and reaches response.done; an unauthorized speaker yields an unknown (matched false, no name) event and still responds, proving enforce:false never drops a turn. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(config): register voice_recognition enforce + identity fields The meta registry coverage test (TestAllFieldsHaveRegistryEntries) requires every config field to have an entry in core/config/meta/registry.go. The new voice_recognition.enforce and voice_recognition.identity.* fields were missing, failing tests-linux and tests-apple. Add registry entries (toggles) so the fields are surfaced in the model-config editor and the coverage test passes. Assisted-by: Claude:claude-opus-4-8 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> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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Tai An
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e58870a573 |
feat(react-ui/chat): paste images from clipboard into chat input (#10428)
The chat input only accepted attachments via the file picker, so users who copied an image from a webpage or a screen region had to first save it to a file before attaching it (#10361). Add an onPaste handler on the input textarea that pulls image items out of the clipboard and routes them through the same staging path as the file picker. The per-file processing in handleFileChange is extracted into a shared processFiles helper so both entry points stay in sync. Clipboard images, which arrive unnamed or as a generic "image.png", are given unique typed names so multiple pastes don't collide, and the default paste is suppressed only when an image is actually attached so normal text paste is unaffected. Closes #10361 Signed-off-by: Anai-Guo <antai12232931@outlook.com> |
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Leoy
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b50b1fe418 |
feat(watchdog): add size-aware LRU eviction mode (#9527)
* feat(watchdog): add size-aware LRU eviction mode When the model count hits the LRU limit or the memory reclaimer fires, evict the largest model by on-disk file size first rather than the least-recently-used one. For GGUF models the file size is a reliable proxy for GPU/RAM footprint, so evicting the largest candidate maximises freed memory per eviction round while keeping small utility models (embeddings, classifiers, rerankers) resident. Changes: - `pkg/model/watchdog.go`: add `sizeAwareEviction` flag and `modelSizes map[string]int64` to `WatchDog`; sort candidates by `sizeBytes` desc (LRU time as tiebreaker) when the flag is set; add `RegisterModelSize`, `SetSizeAwareEviction`, `GetSizeAwareEviction` - `pkg/model/watchdog_options.go`: add `WithSizeAwareEviction` option - `pkg/model/initializers.go`: stat model file after load and call `RegisterModelSize` so size data is available before the first eviction - `core/config/application_config.go`, `runtime_settings.go`: add `SizeAwareEviction` field and `WithSizeAwareEviction` app option; expose via `ToRuntimeSettings` / `ApplyRuntimeSettings` for the `POST /api/settings` live-reload path - `core/cli/run.go`: add `--size-aware-eviction` flag / `LOCALAI_SIZE_AWARE_EVICTION` env var - `core/application/startup.go`, `watchdog.go`: wire the new option through to `NewWatchDog` - `pkg/model/watchdog_test.go`: 5 new specs — option enable, dynamic toggle, largest-first ordering, equal-size LRU tiebreaker, no-size fallback to LRU, and size-map cleanup on eviction Closes #9375 Signed-off-by: supermario_leo <leo.stack@outlook.com> * refactor(watchdog): use vram estimation scaffolding for model size Replace the brittle os.Stat(modelFile) approach with a proper call to pkg/vram, which handles multi-file models (DownloadFiles, MMProj) and all weight file types, not just single GGUF files. - Add estimateModelSizeBytes() in core/backend/options.go that collects all weight file URIs from the model config, resolves them to file:// URIs, and calls vram.Estimate() with the shared DefaultCachedSizeResolver (15-min TTL cache avoids redundant stat calls on repeated loads) - Thread the result through via a new WithModelSizeBytes() loader option - In initializers.go, consume the pre-computed size instead of calling os.Stat; if no size was supplied (e.g. for external/router-dispatched models) the registration is simply skipped Signed-off-by: supermario_leo <leo.stack@outlook.com> * refactor(watchdog): use EstimateModel with HF fallback for size estimation Switch estimateModelSizeBytes from calling vram.Estimate directly to the unified vram.EstimateModel entry point, which adds automatic fallbacks: file-based GGUF metadata → HF API → size string. Also extract the HuggingFace repo ID from model URIs (huggingface://, hf://, https://huggingface.co/ and org/model short-form) and pass it as ModelEstimateInput.HFRepo, so models not yet downloaded locally can still get a size estimate via the HF API. Addresses @mudler's review feedback: "better to rely on EstimateModel and pass by the HF URL of the model extracted from the URI". Signed-off-by: supermario_leo <leo.stack@outlook.com> * feat(webui): add Size-Aware Eviction toggle to settings page The size-aware eviction setting was wired through the CLI flag and the RuntimeSettings live-reload path (POST /api/settings) but had no handle on the React settings page, so it could not be toggled from the UI. Add a Size-Aware Eviction toggle to the Watchdog section, next to the existing Force Eviction When Busy / LRU eviction handles. The settings page loads and saves the whole RuntimeSettings object, so the new size_aware_eviction key is picked up with no extra plumbing. Addresses @mudler's review feedback: the application config setting should land on the same UI settings page as the other handles. Signed-off-by: supermario_leo <leo.stack@outlook.com> --------- Signed-off-by: supermario_leo <leo.stack@outlook.com> |
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LocalAI [bot]andEttore Di Giacinto
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3e96d811b7 |
fix(ui): keep row action menu anchored and stop scroll snap on /app/manage (#10419)
Opening a model row's kebab (ActionMenu) on the Manage dashboard snapped the
page scroll to the top and rendered the menu detached from its trigger, making
it impossible to operate.
Two compounding causes:
- The menu auto-focus called el.focus() without preventScroll, so the browser
scrolled the focused element into view, yanking the page to the top.
- The position:fixed Popover was rendered inline inside the table row. The
editorial UI overhaul added hover transforms to rows/cards, and a transformed
ancestor re-anchors position:fixed to itself instead of the viewport, so the
menu (positioned from the trigger's viewport rect) landed in the wrong place.
Fix: portal the Popover to document.body so position:fixed always resolves
against the viewport, position it before paint with useLayoutEffect (no {0,0}
flash), and pass preventScroll:true to both focus calls.
Adds an e2e regression test that reproduces the symptom (scroll jumped from 564
to 0 on the old code) and asserts the menu tracks its trigger.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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LocalAI [bot]andEttore Di Giacinto
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9565db5f94 |
feat(models): model aliases - redirect a model name to another configured model (#10414)
* feat(config): add model alias field and self-validation Add ModelConfig.Alias (yaml: alias), IsAlias(), and an alias short-circuit at the top of Validate() that rejects self-reference and forbids setting backend/parameters.model on a pure-redirect alias. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(config): resolve and validate model alias targets in the loader Assisted-by: Claude:opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(middleware): resolve model aliases and stamp requested/served identity Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(modeladmin): reject alias configs with invalid targets on create/edit Validate alias targets at create/swap entry points (ImportModelEndpoint, EditYAML, PatchConfig) so a dangling, chained, or disabled alias target is rejected at save time rather than surfacing as a runtime error. Assisted-by: Claude:opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(api): add GET /api/aliases to list model aliases Adds an admin-gated read-only endpoint that lists every model alias config as {name, target} pairs, backed by the loader's existing GetAllModelsConfigs(). Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(mcp): add set_alias and list_aliases tools Expose model-alias management over the LocalAI Assistant MCP surface: list_aliases (read-only, GET /api/aliases) and set_alias (mutating). SetAlias is swap-first: PATCH /api/models/config-json/:name swaps an existing alias's target (validated, non-destructive) and a 404 falls back to POST /models/import to create a fresh {name, alias} config. The inproc client mirrors this via ConfigService.PatchConfig + a create path modeled on ImportModelEndpoint. Deletion reuses delete_model. Assisted-by: Claude:claude-opus-4 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(mcp): replace em dashes in alias tool comments Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(config-meta): expose alias as a model-select field Add an 'alias' section to DefaultSections() and an 'alias' field override in DefaultRegistry() so the schema-driven React editor renders the new top-level ModelConfig.Alias field as a model picker in its own section. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): add alias template card and Manage alias badge Add an 'Alias / Routing' template to the create-flow gallery that seeds a minimal name + alias config, and a read-only 'alias -> target' badge on the Manage Models tab. The capabilities row payload does not carry the alias field, so the badge resolves targets from GET /api/aliases looked up by name. Assisted-by: Claude:claude-opus-4 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: document model aliases Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(swagger): regenerate for GET /api/aliases Adds the /api/aliases path and AliasInfo schema generated from the ListAliasesEndpoint annotation. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(localai): check os.RemoveAll error in aliases_test Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: correct alias conversion docs and advertise /api/aliases in instructions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(mcp): write alias config 0600 to satisfy gosec G306 The inproc createAlias path wrote the alias YAML with 0644, which gosec flags as a new G306 finding on the PR. The LocalAI process is the sole reader/writer of model configs, so 0600 is correct and keeps the scan clean. Assisted-by: Claude:claude-opus-4-8 [Claude Code] 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> |
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LocalAI [bot]andEttore Di Giacinto
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b081247d95 |
feat(config): hardware-tuned defaults — Blackwell batch + VRAM-scaled concurrency (#10411)
* feat(config): node-aware hardware defaults — larger physical batch on Blackwell A larger physical batch (n_batch/n_ubatch) materially lifts MoE prefill on NVIDIA Blackwell consumer GPUs (sm_120/121, incl. GB10 / DGX Spark) — measured on a GB10 with Qwen3-Coder-30B-A3B, the prefill ceiling rises (ub512 ~2994 -> ub2048 ~3316 t/s) and saturates around 2048. The heuristic lives in core/config alongside the other config overriders (ApplyInferenceDefaults, guessDefaultsFromFile/NGPULayers) — they all fill the ModelConfig from heuristics, so hardware tuning is the same domain and stays in one place. It is parameterized on a GPU descriptor (not direct detection) so it works in both deployment shapes: - Single host: SetDefaults applies it with the LocalGPU. - Distributed: only the worker sees the GPU, so the worker reports its compute capability on registration (gpu_compute_capability -> BackendNode), and the router re-applies the SAME core/config heuristic for the SELECTED node before loading — fixing the case where the frontend has no GPU at all. Explicit `batch:` always wins (only managed default values are touched). xsysinfo gains NVIDIAComputeCapability() (detection only); all interpretation lives in core/config. Tests: core/config, pkg/xsysinfo, core/services/nodes. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(config): injectable local-GPU seam + single-instance coverage Make local GPU detection an injectable package var (localGPU) so the single-instance path (SetDefaults -> ApplyHardwareDefaults) is deterministically testable without a real GPU, mirroring the distributed override's coverage. Adds specs asserting SetDefaults sets the Blackwell physical batch, leaves it unset on non-Blackwell, and never overrides an explicit batch. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(config): default concurrent serving (n_parallel) by GPU VRAM The llama.cpp backend defaults n_parallel=1, which serializes multi-user requests and leaves continuous batching off (it auto-enables only at n_parallel>1). Fold a VRAM-scaled parallel-slot default into the hardware-config path so multi-user serving works out of the box: >=32GiB->8, >=8GiB->4, >=4GiB->2, else unchanged. With the backend's unified KV the slots SHARE the context budget, so this adds concurrency without multiplying KV memory. Explicit parallel/n_parallel always wins. EnsureParallelOption is shared by the single-host path (ApplyHardwareDefaults with the local GPU) and the distributed router (per selected node's reported VRAM, since the frontend may have no GPU). LocalGPU now also reports VRAM. Assisted-by: Claude:opus-4.8 [Claude Code] 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> |
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LocalAI [bot]andEttore Di Giacinto
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079ac0e15a |
fix(realtime): raise WebRTC data-channel max-message-size + keep sendLoop alive (#10407)
* fix(realtime): raise WebRTC data-channel max-message-size for large events Browsers advertise a conservative SCTP max-message-size in their SDP offer (Chrome uses 256 KiB). pion enforces the remote's advertised value on send, so a single realtime event larger than it cannot be sent over the "oai-events" data channel: SendText fails, the event is dropped, and the turn silently yields no response. Some turns legitimately produce a >256 KiB JSON event — notably tool calls with sizeable schemas or results. Browsers advertise the value conservatively but their SCTP stacks reassemble much larger messages, so raise the max-message-size honored for our own server-generated events by rewriting the attribute in the offer before SetRemoteDescription. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(realtime): keep the WebRTC sendLoop alive when one event send fails A failed SendText on the oai-events data channel exited the sender goroutine, so a single dropped event (e.g. one over the negotiated SCTP max-message-size) tore down the session and silently dropped every subsequent event. Log and skip the offending event instead and keep draining; a genuinely dead transport is still handled by the closed / connection-state path. Assisted-by: Claude:claude-opus-4-8 [Claude Code] 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> |