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140
Commits
| Author | SHA1 | Message | Date | |
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 mudler-agentandEttore Di Giacinto
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3a02f29edc |
fix(proxy): propagate model env and accept direct keys (#12940)
* feat(proxy): accept direct upstream API keys Support direct credentials for models created in the UI. Keep env and file references as mutually exclusive alternatives. Use model env for frontend probes and omit credentials from structured config logs. Assisted-by: nib:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): isolate model environments in worker processes Forward complete model environment snapshots through backend installation. Restart worker children when overrides change or are removed, and include keyed snapshot identities in frontend install coalescing. Cover wire compatibility, routing, real worker children, and option copying; document rollout requirements and control-transport security. Assisted-by: nib:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(worker): serialize installs by model replica Different backend names can target the same process slot. Hold a slot lock through startup, readiness, and operation attachment so concurrent installs cannot reuse another configuration or an unready child. Assisted-by: nib:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(nodes): update endpoint stub for model env Keep the endpoint command stub aligned with the environment-aware install interface. Assert interface conformance so future changes fail at the stub declaration rather than at endpoint call sites. Assisted-by: nib:gpt-6.1-sol 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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798bb6311c |
fix(gallery): correct HTDemucs checksum (#12919)
* fix(watchdog): track models on address-based external backends A backend reached by address has no process, so StartProcess never registered it with the watchdog and LRU and group eviction never saw it loaded. Fixes #12900 Assisted-by: Claude:claude-opus-5-5 * fix(gallery): correct HTDemucs checksum Match the published SHA256 so HTDemucs downloads pass verification. Fixes #12912 Assisted-by: Codex:gpt-6 --------- Co-authored-by: berce <75228263+bercedev@users.noreply.github.com> Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
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Anush008
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cb97cb1ed9 |
feat(stores): Adds Qdrant vector store backend
Signed-off-by: Anush008 <mail@anush.sh>
(cherry picked from commit
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Anush008
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dee4d8a399 |
refactor(stores): resolve the store backend and its loader slot explicitly
Store loading picked the backend and the loader's process slot in one function, which let an explicit `backend` argument collide with the store's own config and made traces report a fixed "local-store". This changes /stores/* behaviour for every store: - An explicit `backend` that differs from the one named in the store's model config now gets its own loader slot, `<store>@<backend>`, so it no longer reuses (or evicts) the process of the configured backend. Naming the configured backend, or one of its aliases, keeps the store's own slot. - When the config names a different backend than the explicit one, the config's `options` are not passed on, since they are meant for the configured backend. A config without `backend:` still passes its options to the explicit backend. - Backend names are compared and reported in canonical form (aliases resolved, lower case) through the new model.CanonicalBackend, and traces record the backend that was actually used instead of always "local-store". Backend loading itself uses CanonicalBackend for alias handling; type aliases keep their existing effect. Signed-off-by: Anush008 <mail@anush.sh> Assisted-by: Claude Code:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler-agentandEttore Di Giacinto
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0e0e91f95c |
feat(diagnostics): add opt-in profiling (#12610)
* feat(diagnostics): add private opt-in profiler Keep profiling on a dedicated loopback listener rather than the public API. Validate settings and bind synchronously so startup reports configuration and socket failures. Own sampling and shutdown for the run process. Cover private handlers, blocked cmdline access, sampling cleanup, and serving failures with focused Ginkgo tests. Assisted-by: nib:gpt-6-astra * feat(diagnostics): add sanitized phase timing Carry generated request and reload identities through private contexts. Keep timing disabled without allocations and emit only validated fields at Info level when enabled. Cover identity isolation, nested durations, inheritance, and sanitized logging with focused race-tested Ginkgo specs. Assisted-by: nib:gpt-6-astra * fix(diagnostics): retain request observations Reuse an existing request observation across recorders to avoid splitting correlation. Keep the original context, identity, and sink without new allocations. Preserve nil-recorder behavior and fresh reload identities. Verify the regression fails before the fix and passes with the full Diagnostics race suite afterward. Assisted-by: nib:gpt-6-astra * feat(cli): own opt-in diagnostics lifecycle Expose profiling and phase timing flags without enabling them for debug. Bind the private profiler before application initialization and propagate serving failures through the run lifecycle. Bound signal cleanup and preserve preload-only backend startup. Cover flag parsing, preload isolation, cancellation, and once-only shutdown. Document initialization and shutdown cancellation limitations. Assisted-by: nib:gpt-6-astra * feat(config): measure filter and reload phases Separate request lock waits from filtering and held work. Aggregate reload filesystem and parsing durations without logging inside the config lock. Preserve caller option execution under the lock after metadata collection. Extract only the internal diagnostics option before waiting for the lock. Keep direct callers uninstrumented unless they supply diagnostics options. Verify focused Diagnostics examples with the race detector, including option ordering, gated contention, errors, panic propagation, and parity. Assisted-by: nib:gpt-6-astra * fix(config): separate early reload observation Opaque callbacks cannot select timing before their execution point. Carry the startup recorder explicitly through loader construction. Apply late options once under the lock and honor composed last writes. Document early and late phase boundaries and observation identities. Report malformed gallery syntax as an internal parse failure without changing strict or non-strict loader returns. Assisted-by: nib:gpt-6-astra * fix(config): preserve per-model option callbacks The resolved snapshot suppresses existing callbacks during model defaults, even when diagnostics are disabled. Pass original options through the existing defaults pathway without adding diagnostics-driven replay. Test stateful options with two models in enabled and disabled modes. Preserve three calls and thread defaults of two and three. Assisted-by: nib:gpt-6-astra * feat(model): observe discovery phases Carry request diagnostics through config and loose-file discovery to separate directory enumeration from in-memory filtering and fallback. Keep existing APIs as background-context wrappers and preserve discovery policies, ordering, duplicates, errors, and filesystem operation counts. Add focused parity, privacy, phase, and disabled-allocation tests. The focused diagnostics race gate passes for model and galleryop. Assisted-by: nib:gpt-6-astra * feat(http): observe extraction phases Generate diagnostic identity before request discovery, independently of client correlation headers. End each extraction segment before inference so downstream latency does not inflate discovery measurements. Carry observations through discovery helpers and rebuilt request contexts without changing cancellation or model selection. Cover disabled parity, error outcomes, privacy, concurrent identity isolation and route contexts. Assisted-by: nib:gpt-6-astra * fix(http): retain diagnostics across failover Failover restores its entry request before retrying. Initialize the observation before that capture so direct extraction retains one ID. Keep extraction spans per attempt and end them before downstream work. Exercise two real targets without default middleware, including replay, shared identity, phase boundaries, and timing-off response parity. Assisted-by: nib:gpt-6-astra * feat(model): observe initialization and routing Mark loader entry before cache and admission checks. Measure only the ModelRouter callback, without attributing transport or worker latency. Test inherited identity and sanitized events with fake backends. Exercise the actual Echo router to keep profiles private across debug and timing options. Cover capture shutdown, forced close, and lifecycle failures. Assisted-by: nib:gpt-6-astra * docs(diagnostics): guide bounded investigations Document private profiling, sampling ownership, and phase boundaries so operators can interpret captures without assuming request attribution. Add Ginkgo drift checks for flags, defaults, phases, links, and capture warnings. These checks do not certify the operator prose. The focused documentation race test passes after four expected failures. The consolidated Diagnostics race gate passes across all eight packages. This gate does not validate the full suite, auth, or production UI. Assisted-by: nib:gpt-6-astra * refactor(cli): restore inline run lifecycle Remove diagnostic startup hooks so application startup stays readable in Run. Keep the profiler as an optional sidecar with bounded cleanup and an error watcher, without a general lifecycle runner. Replace hook simulations with real CLI startup checks and component capture tests. Document that application cleanup can exceed the private listener budget. The eight-package Diagnostics race gate passes. A cleanup mutation fails the real CLI listener-release regression as expected. Assisted-by: nib:gpt-6-astra * fix(cli): retain concurrent startup errors Cancellation must not hide a public API bind failure. Join the public serve result, cancellation cause, and HTTP shutdown errors inline. Ignore ErrServerClosed only after intentional shutdown. Exercise real startup with an occupied API port and a failed private listener. Isolate the Linux socket fixture in a subprocess and wait for cancellation acknowledgment without timing sleeps. Assisted-by: nib:gpt-6-astra * refactor(http): make request context primary Move context preparation into the request extractor. Diagnostics remain an optional addition, not the entry point for request processing. Preserve context initialization before failover captures the request. Assisted-by: nib:gpt-6-astra --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler-agent
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cd604b5c5b |
fix(distributed): bound, stop and cancel model loads with leases and worker operations (#12524)
Fence model load jobs by generation, lease them on the database clock, bound the work on the worker with operations and a process-group watchdog, and add one stop path with a load-cancel API. See the pull request for the design, the rolling upgrade notes and the test evidence. Assisted-by: Claude Code:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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9e95ef0dbd |
fix: resolve gosec alerts in files this change touches
Code scanning reports alerts on every line of a touched file. Mark the gRPC auth env var name and the mock backend's staged-path reads as reviewed, and log the error when evicting a model after its connection fails instead of dropping it. Assisted-by: Claude:claude-opus-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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8db6c15fe0 |
refactor: name the proxy backends with constants
Review asked for constants instead of the "cloud-proxy" and "localai-proxy" literals. Add CloudProxyBackend and LocalAIProxyBackend next to the other backend-name constants in pkg/model (WhisperBackend, TransformersBackend, ...), which core/config already imports, and use them in every production check: the proxy options builder, IsRemoteProxy, IsCloudProxyBackendPassthrough, the PII defaults, the localai-proxy backend hook and loader warning, and the PII middleware metadata in the routes and the in-process MCP client. The proxy options builder now calls IsRemoteProxy() instead of repeating the two-backend check, so the set of proxy backends is defined once. Assisted-by: Claude:claude-opus-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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9bd7d17ff6 |
[model-config] feat: add environment variables support for backends (#10721)
* feat: add environment variables support for backends in model configurations - Add field to model configuration to pass environment variables to backend processes - Update backend options and model configuration handling - Add documentation for environment variables configuration with examples including CUDA_VISIBLE_DEVICES Assisted-by: qwen-agentworld-35b-a3b Signed-off-by: nold <nold42@pm.me> * fix(test): Test environment variables configuration parsing from YAML Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Signed-off-by: nold <Nold360@users.noreply.github.com> --------- Signed-off-by: nold <nold42@pm.me> Signed-off-by: nold <Nold360@users.noreply.github.com> Co-authored-by: nold <nold42@pm.me> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
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localai-org-maint-botandEttore Di Giacinto
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bf93008ef3 |
fix(backends): bound temporary scratch files (#11941)
Backend processes shared the host temporary directory, so crashes could leave request images and audio behind until the filesystem filled. Give each process a locked LocalAI-owned runtime, remove scratch on exit, and sweep only marked abandoned runtimes at the next start. Also close known request error-path leaks in the Python media backends, CrispASR, LongCat Video, and stable-diffusion.cpp. Assisted-by: Codex:gpt-5 Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]andEttore Di Giacinto
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82c191afad |
fix(distributed): keep model replicas config-consistent (#11664)
* docs: design configurable copy buffering Document the context-aware copy buffer option and its validation plan. Assisted-by: Codex:gpt-5 * docs: design durable distributed staging operations Assisted-by: Codex:gpt-5 * docs: design distributed model config revisions Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] * feat(config): add stable model revisions Hash typed model configuration and effective protobuf options deterministically for distributed revision comparisons. Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] * feat(worker): acknowledge exact model stops Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] * feat(nodes): track model config revisions Assisted-by: Codex:GPT-5 [apply_patch] * fix(distributed): retry quarantined model cleanup Stop quarantined replicas by exact process identity, retain failed cleanup as durable capped retries, and compare-and-delete only the claimed registry row. Process one sufficiently leased row at a time so multiple frontends cannot duplicate slow cleanup work. Assisted-by: Codex:gpt-5 * fix(distributed): bind loads to config revisions Assisted-by: Codex: GPT-5 [OpenAI Codex] * fix(modeladmin): apply config revisions consistently Route model edits, patches, state changes, deletion, and peer refreshes through the same revision lifecycle. Quarantine stale replicas before exact cleanup and report durable pending cleanup without failing successful config writes. Assisted-by: Codex: GPT-5 [OpenAI Codex] * feat(distributed): expose model config revision state Document replica revision observability and durable cleanup behavior. Keep pending cleanup explicit in model mutation responses and verify endpoint contracts expose revision state without serialized load options. Assisted-by: Codex:GPT-5 [OpenAI Codex] * test(distributed): cover model revision convergence Exercise cross-frontend quarantine, stale replay rejection, exact cleanup retry, worker re-registration, and current-generation replica convergence against the distributed PostgreSQL harness. Assisted-by: Codex:gpt-5 * fix(distributed): pass config revision CI checks Keep configured gallery sources out of authoritative runtime snapshots only after validating their real schema, and harden rollback snapshots against symlink races and non-regular files. Assisted-by: Codex: GPT-5 [OpenAI Codex] --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Richard Palethorpe
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799cc9f211 |
feat: bound global admission and expose running backend traces (#11560)
feat: bound backend admission and expose running traces Add process-wide backend execution admission without blocking UI or administrative HTTP work. Represent backend operations while they are in flight, surface running traces with immediate log links, and tie streaming admission leases to the gRPC receive lifecycle. Assisted-by: OpenAI Codex: GPT-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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localai-org-maint-botandlocalai-org-maint-bot
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f2cdc06781 |
fix(model): surface backend startup exits (#11447)
* fix(model): surface backend startup exits Preserve the local backend process exit code and bounded stderr diagnostic when the process dies before its gRPC service becomes ready. Fixes #9050 Assisted-by: Codex:gpt-5 * fix(model): satisfy startup diagnostic checks Assisted-by: Codex:gpt-5.6 [Codex] --------- Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
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7d8e0bac18 |
fix(model): deterministic, type-filtered backend auto-detection (#9287) (#10286)
* fix(model): deterministic, file-type-filtered backend auto-detect (#9287) When a model config declares no explicit `backend:`, Load() fell into a trial loop built by ranging the external-backends Go map (random order) with no filtering, returning the first backend whose gRPC LoadModel succeeded. An unrelated installed backend - e.g. the "opus" audio codec - could therefore win a GGUF/LLM model load, so a model that should run on llama.cpp wrongly tried to use opus. Extract the candidate selection into a pure, testable function SelectAutoLoadBackends that: - sorts the candidate list deterministically (no more map-order nondeterminism), and - for a `.gguf` model, filters to LLM-capable backends (via core/config.BackendCapabilities) and puts llama-cpp first, so an incompatible audio/codec/image backend can never win the trial loop. If filtering would leave zero candidates, the full sorted set is returned unchanged, so a previously-loadable model is never made unloadable. 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> * fix(model): break core/config <-> pkg/model import cycle in backend auto-detect The #9287 auto-detect change made pkg/model/autoload.go import core/config for the backend capability table. core/config already imports pkg/model (runtime_settings_registry.go uses model.DefaultWatchdogInterval), so this closed a core/config -> pkg/model -> core/config import cycle and broke the build and golangci-lint. Invert the dependency so the lower-level pkg/model no longer imports the higher-level core/config. pkg/model exposes RegisterLLMCapableBackendFunc and uses the registered predicate; core/config (which owns the capability table) registers it from an init(). The deterministic, GGUF-type-filtered selection behaviour is unchanged. When the predicate is unwired the GGUF filter is skipped, preserving the existing zero-candidate fallback. The unit test now injects a fake capability predicate so SelectAutoLoadBackends is exercised independently of the core/config table. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:opus-4.8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com> |
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localai-org-maint-botandDaria Korenieva
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9bfd71387b |
feat(stores): add Valkey Search vector store backend (#11196)
* feat: add Valkey Search vector store backend Add a new built-in Go gRPC store backend 'valkey-store' that implements the four Stores RPCs (Set/Get/Delete/Find) against the Valkey Search module (FT.*) using the pure-Go github.com/valkey-io/valkey-go client. It is selected via the existing per-request 'backend' field on /stores, so there is no proto or HTTP API change, and it mirrors the in-memory local-store while adding persistence across restarts and opt-in HNSW. Each vector is a Valkey HASH keyed by hex(little-endian float32); the index is created lazily on first Set (FLAT+COSINE by default), cosine similarity is derived as 1-distance, and namespaces get a collision-resistant token. Includes unit tests (valkey-go mock) and env-gated integration tests against valkey/valkey-bundle, plus build/matrix/gallery wiring and docs. Assisted-by: Kiro:claude-opus-4.8 golangci-lint Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: recover persisted index dimension, harden Find - Load now recovers the persisted vector DIM from FT.INFO (not just index existence), so a post-restart Set/Find validates against the real DIM instead of silently re-learning a wrong one and dropping mismatched vectors from the index. This also restores Find's dimension check after a restart. - StoresFind treats a dropped/missing index as an empty store (empty result, no error) and clears the stale indexCreated flag, matching local-store's empty-store behaviour. - StoresSet reuses checkDims for its per-key length check so the four RPCs share one dimension-guard implementation. - Add unit tests for FT.INFO dimension recovery, loadIndexState, and the dropped-index Find path. Assisted-by: Kiro:claude-opus-4.8 Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: TLS ServerName/CA, Find nil-check, config fail-fast Addresses external review comments on the valkey-store backend: - StoresFind now rejects a nil/empty query Key before dereferencing it, so a malformed gRPC request can no longer panic the backend. - TLS: derive ServerName (SNI) from the VALKEY_ADDR host so certificate verification works for IP-addressed endpoints, and add VALKEY_TLS_CA_CERT (custom CA bundle) and VALKEY_TLS_SKIP_VERIFY (testing-only) knobs. - Config integer parsing now fails fast on a malformed value (e.g. VALKEY_HNSW_M=1x6) instead of silently defaulting, matching the fail-fast behaviour of the index-algo/distance-metric validation. - Add VALKEY_DB (SELECT n) support for logical-DB isolation. - Cap the human-readable part of a namespace token at 64 chars so a very long model name cannot produce an unbounded key prefix / index name (the appended short hash keeps distinct namespaces collision-free). - Document the KNN-query injection-safety invariant (fields are constants) and why StoresGet uses a single aggregate DoMulti deadline for reads. - Unit tests for the Find nil/empty-key guard, fail-fast HNSW parsing, and VALKEY_DB parsing/validation; docs + .env updated for the new vars. Assisted-by: Kiro:claude-opus-4.8 golangci-lint Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: configure valkey-store via model config richiejp asked that the valkey-store backend take its configuration from a model config rather than process-wide VALKEY_* environment variables, so multiple stores can each have their own Valkey config within one LocalAI process. This removes every env access from the backend and routes config through the model-config seam every other backend uses. - config.go: loadConfig(opts *pb.ModelOptions) now parses the model config `options:` list (key:value strings, split on the first ':') instead of os.Getenv. Option keys mirror the old VALKEY_* names without the prefix (addr, index_algo, distance_metric, ...). Defaults, fail-fast validation and the mandatory client name are unchanged. - store.go: Load threads opts into loadConfig; TLS comments/errors renamed off the VALKEY_* names. - core/backend/stores.go: StoreBackend and NewVectorStore take a *config.ModelConfigLoader, resolve the per-store ModelConfig by store name, and pass its Options (and Backend when unset) to the backend via WithLoadGRPCLoadModelOpts. No config -> default backend + built-in defaults, preserving the zero-config experience. - Endpoints/routes/application: thread the config loader to StoreBackend. - Unit + integration tests: configure via options; the integration test passes addr through the model-config path (VALKEY_ADDR is now only the test harness locating the server). - docs + .env: document the model-config options, drop the env var table. Assisted-by: Kiro:claude-opus-4.8 Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Remove valkey-store informational comment from .env The backend is configured via model config, not env vars — the comment was unnecessary noise in .env. The configuration is already documented in docs/content/features/stores.md. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * feat(valkey-store): gate Load on NamespacePrefix to refuse autoload probing Mirror local-store's pattern: reject model names without store.NamespacePrefix so the model loader's greedy autoload probe cannot bind an arbitrary model name to the vector store backend (the #9287 failure mode). Also adds unit tests for the gate covering: prefixed namespace, prefix alone, unprefixed model name, empty model, and nil opts. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * feat(valkey-store): add username_env/password_env credential indirection Add support for resolving Valkey credentials from environment variables named in the model config, mirroring cloud-proxy's api_key_env pattern. This keeps secrets out of model YAML files and lets distinct store configs each reference their own credentials. Options: username_env / password_env name the env var holding the value. The direct username / password options still work and take precedence when both are set (backward compatible). Includes 5 unit tests and updated stores.md documentation. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * fix: correct rebase artifacts in backend-matrix.yml and Makefile Fix two issues introduced by the conflict-resolution script during the rebase onto master: 1. .github/backend-matrix.yml: valkey-store entries were merged INTO the cloud-proxy entries (duplicate keys in same YAML map items) instead of being separate list items. This broke cloud-proxy Linux builds and the cloud-proxy darwin entry lost its build-type/lang. Fixed by making them standalone entries and restoring cloud-proxy exactly as on master. 2. Makefile: duplicated .NOTPARALLEL and docker-build-backends lines. Collapsed to single lines that are master's current content plus the valkey-store additions. Also adds the three optional pickups from #10801: - /valkey-store in .gitignore (the built binary) - valkey-store row in docs/content/reference/compatibility-table.md - valkey-store line in backend/README.md Signed-off-by: Daria Korenieva <daric2612@gmail.com> --------- Signed-off-by: Daria Korenieva <daric2612@gmail.com> Co-authored-by: Daria Korenieva <daric2612@gmail.com> |
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Richard Palethorpeandlocalai-org-maint-bot
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9058a2bb46 |
feat: Add 3d generation UI/API and trellis2cpp backend (#10979)
* feat(3d): add Generate3D RPC, FLAG_3D capability, and /v1/3d/generations endpoint Adds the plumbing for image-conditioned 3D asset generation (binary glTF / GLB output), modeled on the video generation path: - backend.proto: Generate3D RPC + Generate3DRequest (staged image src, glb dst, seed/step/cfg_scale/texture_steps, quality and background enums, params map for backend-specific extras) - pkg/grpc: thread Generate3D through client, server, embed, base and the backend interfaces; connection-evicting and distributed-node wrappers (in-flight tracking + file staging) included - core/config: FLAG_3D usecase (guessed only for the trellis2cpp backend), '3d' canonical usecase string mapped to the Generate3D method, and a '3d' output modality - REST: POST /v1/3d/generations (+ unversioned alias) returning OpenAIResponse with a /generated-3d URL or b64_json; conditioning image accepted as URL, base64, or data URI; quality/background validated at the edge; .glb served as model/gltf-binary - auth: '3d' route feature (default ON); /api/instructions entry Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(trellis2cpp): add the trellis2.cpp image-to-3D backend Wraps localai-org/trellis2cpp (C++/GGML port of Microsoft TRELLIS.2, pbr-textures branch) as a Go+purego backend, following the stablediffusion-ggml pattern: - backend/go/trellis2cpp: purego bindings to the flat C ABI (v9, asserted at startup), eager pipeline load with model-set validation (refuses non-trellis GGUFs; degrades coarse/geometry-only/textured exactly like the upstream demo), Generate3D via t2_generate + t2_bake_glb writing a binary glTF to dst. Weight-free unit tests cover resolution/validation/param mapping — CI never downloads the multi-GB GGUF set or runs inference. - CPU SIMD variants build into per-variant directories (the shared libggml sonames collide across variants, unlike sd-ggml's flat renamed-.so scheme); run.sh picks one via /proc/cpuinfo. - CI wiring: backend-matrix entries (cpu, cuda12/13, vulkan amd64+arm64, l4t, l4t-cuda13, darwin metal), index.yaml meta + latest/master image entries, bump_deps tracking of the pbr-textures branch, changed-backends.js mapping, top-level Makefile targets. - Importer: auto-detects trellis GGUF repos/URIs (registered before llama-cpp so the .gguf match isn't stolen) and expands any trellis URI to the full 10-file component set spanning the three LocalAI-io HF repos. - Gallery: trellis2-4b (full PBR + 1024 cascade) and trellis2-4b-geometry (512 untextured) with verified sha256s. Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(ui): 3D generation page with native GLB viewer and IndexedDB history Adds a Studio tab + /app/3d page for the new image-to-3D endpoint: - GlbViewer ports the trellis2cpp demo's dependency-free WebGL2 renderer (quaternion trackball, metallic-roughness PBR, ACES, hidden-line wireframe with a bounded index budget) and pairs it with a minimal GLB parser for the two forms t2_bake_glb emits — dense vertex-PBR (linear COLOR_0 + _METALLIC_ROUGHNESS, uploaded as normalized integers) and the opt-in UV-atlas textured form. Parsing happens before any GL so stats and errors render without WebGL2. - use3DHistory stores past generations (params, input thumbnail, and the GLB blob itself) in IndexedDB with keep-newest-20 eviction — GLBs are multi-MB binaries localStorage can't hold — and the page offers a download button for the active GLB. - Wiring: CAP_3D capability constant (FLAG_3D — the exact string /api/models/capabilities serves), threeDApi, router entries, Studio tab, vite dev proxy, en locale keys. - e2e: render-smoke entry plus a focused spec that feeds a real one-triangle vertex-PBR GLB through the parser/viewer and exercises IndexedDB persistence, selection, deletion, and API errors. Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(3d): address API correctness and UX issues Keep 3D generation on the LocalAI-specific /3d/generations route and ensure authentication and permissions cover it. Propagate distributed transfer failures, publish a portable ARM64 backend image, honor importer overrides, and align discovery, upload validation, and touch controls. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(3d): add previewable print remeshing Add a single-detail CGAL Alpha Wrap workflow for existing Trellis GLBs, including PBR reprojection, API documentation, tracing, and an in-browser preview before download. Allow the remesh route to enforce its 512 MiB upload cap independently of the smaller global default so generated high-resolution meshes can be processed. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * build(trellis2cpp): centralize remesh dependency pins Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(kokoros): implement Generate3D stub for new proto RPC The Generate3D RPC added to backend.proto for the trellis2cpp backend made tonic's generated Backend trait require generate3_d, breaking the kokoros-grpc build. Return unimplemented like the other unsupported modalities. Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com> |
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mudler's LocalAI [bot]andEttore Di Giacinto
|
54d5c18bfb |
fix(model): only announce a load at INFO when a load actually happens (#11017)
backendLoader logged "BackendLoader starting" at INFO as its very first statement, unconditionally. That reads as "a model is being loaded", but backendLoader is not only a load path: in distributed mode Load() deliberately bypasses the local cache and calls backendLoader on every inference request so SmartRouter can re-pick a replica per request. The model is already resident, no process is spawned, and nothing is loaded, yet the banner fires at request rate. On a live cluster this produced ~5 "BackendLoader starting" lines per second for a single embedding model, sustained, starting 22 seconds after the load had already completed. The model was state=loaded with in_flight=0 and exactly one backend process on the worker. It looked exactly like a retry storm and cost real debugging time during an unrelated production investigation. The adjacent "effective runtime tuning" banner, documented as "logged once per load", had the same problem for the same reason. Emit both banners at INFO only when the model is not already resident, and keep the per-call trace at DEBUG for anyone following the routing path. isResident is a plain store lookup with no health probe and no eviction, so it is safe on the per-request hot path (unlike checkIsLoaded, which probes and can evict). Same class of defect as #10985: a log line that sends the reader after the wrong thing. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] 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
|
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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Richard Palethorpe
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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
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79783120dd |
fix(config): gate parallel-slot default on per-device VRAM too (#10485) (#10507)
The first #10485 fix (#10494) made the Blackwell physical-batch boost per-device/context-aware, which neutralized the big compute-buffer OOM, but the reporter's 2x16 GiB consumer Blackwell still OOM'd. Tracing the post-fix log: the model now loads its weights, builds the main context and warms up fine, and dies only on the *last* allocation — the MTP draft context's 800 MiB KV cache on the tighter device. #10411 changed only two defaults: the physical batch (now gated) and a VRAM-scaled parallel-slot count. The KV cache is unified (n_ctx_seq == full context proves slots share the budget, so parallel doesn't multiply KV), but n_seq_max=4 still adds per-slot compute-graph / context-checkpoint / output scratch. On a device packed ~99% by a 27B model spanning both cards, that overhead is the few-hundred-MiB straw — which is why reverting #10411 (and only #10411) restores a working load. Gate the parallel-slot default on the same per-device headroom predicate as the batch boost: when a large context already fills a single card (largeContextForDevice), keep n_parallel=1. A user running one big-context model that barely fits across two consumer GPUs is not serving four concurrent tenants. Small contexts and large unified-memory devices (GB10) keep full concurrency. Applied on both the single-host path and the distributed router. Also make the auto-tuning visible and reversible (the debugging here needed DEBUG logs and a git bisect): - Log the effective performance-relevant runtime options at INFO once per model load ("effective runtime tuning …": context, n_batch, n_gpu_layers, parallel, flash_attention, f16) so an admin can see what will run and pin or override any value in the model YAML. - LOCALAI_DISABLE_HARDWARE_DEFAULTS=true skips the hardware auto-tuning entirely (mirrors LOCALAI_DISABLE_GUESSING) for stock llama.cpp behavior. Assisted-by: 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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Leoy
|
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
|
8bbe89a537 |
fix(distributed): route per request across loaded replicas + cache probeHealth (#9968)
* refactor(distributed): extract PickBestReplica from FindAndLockNodeWithModel Lifts the replica-selection policy (in_flight ASC, last_used ASC, available_vram DESC) out of the SQL ORDER BY into a pure Go function in the new replicapicker.go. The SQL clause keeps its FOR UPDATE atomicity and remains the production path used by SmartRouter; PickBestReplica is the canonical implementation that the future per-frontend rotating replica cache (TODO referenced from pkg/model) will call against an in-memory snapshot without paying a DB round-trip per inference. A new registry_test mirror spec seeds a multi-tier scenario and asserts both layers pick the same replica, so any future tweak to either side fails the test until the other side is updated. No behavior change. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-7 [Claude Code] * fix(distributed): route per inference request and cache probeHealth Two related fixes that together restore load balancing across loaded replicas of the same model. 1. ModelLoader.Load and LoadModel bypass the local *Model cache when modelRouter is set. The cached *Model wraps an InFlightTrackingClient bound to a single (nodeID, replicaIndex) — reusing it pinned every subsequent request to whichever node won the very first pick, so FindAndLockNodeWithModel's round-robin never got a chance to run even after the reconciler scaled the model out to a second node. In distributed mode SmartRouter.Route now runs per request, and PickBestReplica picks the least-loaded replica each time. SmartRouter has its own coalescing (advisory DB lock for first-time loads + singleflight on backend.install RPC) so concurrent first requests for a not-yet-loaded model still produce a single worker side install. 2. SmartRouter.probeHealth memoizes successful gRPC HealthCheck results in a new probeCache (probe_cache.go) with a 30s TTL. With per-request routing every inference call hits probeHealth, and llama.cpp-style backends serialize HealthCheck behind active Predict — so a burst of incoming requests stalled on the probe to a node already mid-stream, tripping the 2s timeout and falling through to the install path. singleflight collapses N concurrent first-time probes for the same (node, addr) into one round-trip, failed probes invalidate the entry so the staleness-recovery path still triggers, and the TTL matches pkg/model/model.go's healthCheckTTL so the single-process and distributed paths share a staleness budget. The background HealthMonitor still reaps actually-dead backends within ~45s. The bypass introduces one short FindAndLockNodeWithModel transaction per inference. A TODO in pkg/model/loader.go documents the future per modelID rotating-replica cache that would reuse PickBestReplica against an in-memory snapshot and skip the DB round-trip for hot paths. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-7 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
|
bbcaebc1ef |
feat(concurrency-groups): per-model exclusive groups for backend loading (#9662)
* feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
170d55c67d |
fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups (#9652)
* fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups
Two distinct bugs were causing tight retry loops in the distributed scheduler:
1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model
was loaded on multiple nodes and only some matched the current selector,
the function returned the lowest-in_flight node — even one the selector
excluded. Route()'s post-check then fell through to scheduleNewModel,
which targeted the matching node where the model was already at
MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded
model on that node was the one being requested, and it was busy), so
every request looped through "evicting LRU" → "all models busy".
Fix: thread an optional candidateNodeIDs filter through
FindAndLockNodeWithModel. Route() resolves the selector once via a new
resolveSelectorCandidates helper and passes the matching IDs to both
the cached-replica lookup and scheduleNewModel. The same helper
replaces the inline selector block in scheduleNewModel.
2. ScheduleAndLoadModel (reconciler scale-up path) fell back to
scheduleNewModel with backendType="" when no replica had ever been
loaded for a model. The worker rejected the resulting backend.install
("backend name is empty") on every reconciler tick (~30s).
Fix: remove the broken fallback. When GetModelLoadInfo has nothing
stored, return a clear error instead of firing a doomed NATS install.
The reconciler's existing scale-up failure log surfaces it once per
tick; the model auto-replicates as soon as Route() serves it once and
stores load info.
Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that
cleanup attempt usually hits "model not found" because LoadModel failed
before registering the process, and the outer "Failed to load model"
error already carries the real reason.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
* test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard
Two regression tests for the bugs fixed in the previous commit:
1. FindAndLockNodeWithModel — registry-level integration tests verify the
candidateNodeIDs filter:
- Returns the included node even when an excluded node has lower
in_flight (the original selector-mismatch loop scenario).
- Returns not-found when the model is loaded only on excluded nodes,
forcing Route() to fall through to a fresh schedule instead of
reusing the excluded replica.
2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up
path returns an error and does NOT fire backend.install when no replica
has been loaded yet. fakeUnloader gains an installCalls slice so this
negative assertion is direct.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto
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9ca03cf9cc |
feat(backends): add ik-llama-cpp (#9326)
* feat(backends): add ik-llama-cpp Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore: add grpc e2e suite, hook to CI, update README Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Apply suggestion from @mudler Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> * Apply suggestion from @mudler Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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Ettore Di Giacinto
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510d6759fe |
fix(nodes): better detection if nodes goes down or model is not available (#9274)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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59108fbe32 |
feat: add distributed mode (#9124)
* feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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c0351b8e6a |
Remove HuggingFace backend support (#8971)
* Remove HuggingFace backend support, restore other backends - Removed backend/go/huggingface directory and all related files - Removed pkg/langchain/huggingface.go - Removed LCHuggingFaceBackend from pkg/model/initializers.go - Removed huggingface backend entries from backend/index.yaml - Updated backend/README.md to remove HuggingFace backend reference - Restored kitten-tts, local-store, silero-vad, piper backends that were incorrectly removed This change removes only HuggingFace backend support from LocalAI as per the P0 priority request in issue #8963, while preserving other backends (kitten-tts, local-store, silero-vad, piper). Signed-off-by: team-coding-agent-1 <team-coding-agent-1@localai.dev> * Remove huggingface backend from test.yml build command The tests-linux CI job was failing because it was trying to build the huggingface backend which no longer exists after the backend removal. This removes huggingface from the build command in test.yml. * Apply suggestion from @mudler Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> --------- Signed-off-by: team-coding-agent-1 <team-coding-agent-1@localai.dev> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> Co-authored-by: team-coding-agent-1 <team-coding-agent-1@localai.dev> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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b6459ddd57 |
feat(api): Add transcribe response format request parameter & adjust STT backends (#8318)
* WIP response format implementation for audio transcriptions (cherry picked from commit e271dd764bbc13846accf3beb8b6522153aa276f) Signed-off-by: Andres Smith <andressmithdev@pm.me> * Rework transcript response_format and add more formats (cherry picked from commit 6a93a8f63e2ee5726bca2980b0c9cf4ef8b7aeb8) Signed-off-by: Andres Smith <andressmithdev@pm.me> * Add test and replace go-openai package with official openai go client (cherry picked from commit f25d1a04e46526429c89db4c739e1e65942ca893) Signed-off-by: Andres Smith <andressmithdev@pm.me> * Fix faster-whisper backend and refactor transcription formatting to also work on CLI Signed-off-by: Andres Smith <andressmithdev@pm.me> (cherry picked from commit 69a93977d5e113eb7172bd85a0f918592d3d2168) Signed-off-by: Andres Smith <andressmithdev@pm.me> --------- Signed-off-by: Andres Smith <andressmithdev@pm.me> Co-authored-by: nanoandrew4 <nanoandrew4@gmail.com> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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Ettore Di Giacinto
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c844b7ac58 |
feat: disable force eviction (#7725)
* feat: allow to set forcing backends eviction while requests are in flight Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: try to make the request sit and retry if eviction couldn't be done Otherwise calls that in order to pass would need to shutdown other backends would just fail. In this way instead we make the request sit and retry eviction until it succeeds. The thresholds can be configured by the user. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * add tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * expose settings to CLI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Update docs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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c37785b78c |
chore(refactor): move logging to common package based on slog (#7668)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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424c95edba |
fix: correctly propagate error during model load (#7610)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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fc5b9ebfcc |
feat(loader): enhance single active backend to support LRU eviction (#7535)
* feat(loader): refactor single active backend support to LRU This changeset introduces LRU management of loaded backends. Users can set now a maximum number of models to be loaded concurrently, and, when setting LocalAI in single active backend mode we set LRU to 1 for backward compatibility. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore: add tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Update docs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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5dde7e9ac6 |
fix: make sure to close on errors (#7521)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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79a41a5e07 |
fix: register backends to model-loader during installation (#6159)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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98e5291afc |
feat: refactor build process, drop embedded backends (#5875)
* feat: split remaining backends and drop embedded backends - Drop silero-vad, huggingface, and stores backend from embedded binaries - Refactor Makefile and Dockerfile to avoid building grpc backends - Drop golang code that was used to embed backends - Simplify building by using goreleaser Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(gallery): be specific with llama-cpp backend templates Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(docs): update Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ci): minor fixes Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore: drop all ffmpeg references Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: run protogen-go Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Always enable p2p mode Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Update gorelease file Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(stores): do not always load Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fix linting issues Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Simplify Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Mac OS fixup Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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b29544d747 |
feat: split piper from main binary (#5858)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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294f7022f3 |
feat: do not bundle llama-cpp anymore (#5790)
* Build llama.cpp separately Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * WIP Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * WIP Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * WIP Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Start to try to attach some tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add git and small fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: correctly autoload external backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Try to run AIO tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Slightly update the Makefile helps Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Adapt auto-bumper Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Try to run linux test Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add llama-cpp into build pipelines Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add default capability (for cpu) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop llama-cpp specific logic from the backend loader Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * drop grpc install in ci for tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Pass by backends path for tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Build protogen at start Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(tests): set backends path consistently Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Correctly configure the backends path Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Try to build for darwin Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * WIP Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Compile for metal on arm64/darwin Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Try to run build off from cross-arch Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add to the backend index nvidia-l4t and cpu's llama-cpp backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Build also darwin-x86 for llama-cpp Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Disable arm64 builds temporary Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Test backend build on PR Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixup build backend reusable workflow Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * pass by skip drivers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Use crane Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Skip drivers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * x86 darwin Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add packaging step for llama.cpp Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fix leftover from bark-cpp extraction Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Try to fix hipblas build Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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2d64269763 |
feat: Add backend gallery (#5607)
* feat: Add backend gallery This PR add support to manage backends as similar to models. There is now available a backend gallery which can be used to install and remove extra backends. The backend gallery can be configured similarly as a model gallery, and API calls allows to install and remove new backends in runtime, and as well during the startup phase of LocalAI. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add backends docs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * wip: Backend Dockerfile for python backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: drop extras images, build python backends separately Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixup on all backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Tweaks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop old backends leftovers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixup CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Move dockerfile upper Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fix proto Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Feature dropped for consistency - we prefer model galleries Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add missing packages in the build image Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * exllama is ponly available on cublas Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * pin torch on chatterbox Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups to index Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Debug CI * Install accellerators deps Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add target arch * Add cuda minor version Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Use self-hosted runners Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci: use quay for test images Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups for vllm and chatterbox Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Small fixups on CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chatterbox is only available for nvidia Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Simplify CI builds Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Adapt test, use qwen3 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(model gallery): add jina-reranker-v1-tiny-en-gguf Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gguf-parser): recover from potential panics that can happen while reading ggufs with gguf-parser Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Use reranker from llama.cpp in AIO images Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Limit concurrent jobs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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kilavvy
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2e1dc8deef |
Fix Typos in Comments and Error Messages (#5637)
* Update initializers.go Signed-off-by: kilavvy <140459108+kilavvy@users.noreply.github.com> * Update base.go Signed-off-by: kilavvy <140459108+kilavvy@users.noreply.github.com> --------- Signed-off-by: kilavvy <140459108+kilavvy@users.noreply.github.com> |
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Ettore Di Giacinto
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9628860c0e |
feat(llama.cpp/clip): inject gpu options if we detect GPUs (#5243)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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2c425e9c69 |
feat(loader): enhance single active backend by treating as singleton (#5107)
feat(loader): enhance single active backend by treating at singleton Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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05f7004487 |
fix: race during stop of active backends (#5106)
* chore: drop double call to stop all backends, refactors Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: do lock when cycling to models to delete Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Bas Hulsken
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bbf30d416d |
fix: change initialization order of llama-cpp-avx512 to go before avx2 variant (#4837)
changed to initialization order of the avx512 version of llama.cpp, now tries before avx2 Signed-off-by: Bas Hulsken <bhulsken@hotmail.com> |
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DaveandEttore Di Giacinto
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3cddf24747 |
feat: Centralized Request Processing middleware (#3847)
* squash past, centralize request middleware PR Signed-off-by: Dave Lee <dave@gray101.com> * migrate bruno request files to examples repo Signed-off-by: Dave Lee <dave@gray101.com> * fix Signed-off-by: Dave Lee <dave@gray101.com> * Update tests/e2e-aio/e2e_test.go Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> --------- Signed-off-by: Dave Lee <dave@gray101.com> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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Ettore Di Giacinto
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7f90ff7aec |
chore(llama-ggml): drop deprecated backend (#4775)
The GGML format is now dead, since in the next version of LocalAI we already bring many breaking compatibility changes, taking the occasion also to drop ggml support (pre-gguf). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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5177837ab0 |
chore: detect and enable avx512 builds (#4675)
chore(avx512): add support Fixes https://github.com/mudler/LocalAI/issues/4662 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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f9e368b7c4 |
chore(refactor): group cpu cap detection (#4674)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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89429a439b |
feat(transformers): add support to Mamba (#4669)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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e15d29aba2 |
chore(stablediffusion-ncn): drop in favor of ggml implementation (#4652)
* chore(stablediffusion-ncn): drop in favor of ggml implementation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ci): drop stablediffusion build Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(tests): add Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(tests): try to fixup current tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Try to fix tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Tests improvements Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(tests): use quality to specify step Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(tests): switch to sd-1.5 also increase prep time for downloading models Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |