5 Commits

Include renames

Author	SHA1	Message	Date
mudler-agentandEttore Di Giacinto	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>	2026-10-10 20:27:28 +02:00
mudler-agentandEttore Di Giacinto	895d50385f	fix(distributed): converge model configs across frontends (#12558) ... * fix(galleryop): announce model changes before the preload After a gallery install or delete, the replica that ran it replaced its config loader, then preloaded every installed model, and only then published the models invalidation. The preload does remote lookups and checksums for each model, so on a large models directory peers learned about the change minutes after the originator listed it. When the preload failed or the operation was cancelled, the event was never sent. Publish the invalidation, and apply the delete lifecycle, as soon as the loader holds the new set. The preload still runs afterwards with its own error handling. Its failure is reported on the operation, but it no longer rolls back a deletion that peers have already applied. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): resync model configs from the models directory Frontends refresh their model configs only when a models invalidation arrives on NATS. NATS keeps no history, so a frontend that is disconnected when the message is published never applies the change. It keeps serving the old config, for example an alias that points at the previous model, until some later change happens to touch it. Each frontend now reruns the peer reconcile against the shared models directory after every NATS reconnect, and every --model-config-resync-interval (default 30s) when a config file changed. The pass names no model, so only models whose file changed get a revision transition, and an unchanged directory costs one read of the config files. The reconcile replaced the whole loader with a parse of the models directory, which dropped models loaded with --config-file and published a deletion revision for them. Configs defined outside the directory are now kept, both there and after a gallery install. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(nodes): stop stale frontends from retargeting alias rules A scheduling rule keyed by an alias derives its target from the alias mapping of the frontend that reads it. Every frontend keeps its own copy of the model configs, so after an alias is repointed a frontend that has not reloaded it still resolves the old target. Two frontends then rewrote the rule's stored target_model against each other on alternate reconciler ticks, and the outdated one scaled up the model the alias used to point at. The registry already records the accepted config revision of each model. A frontend now derives a rule's target from its own alias mapping only when its config revision for the rule's name matches that record. Otherwise it keeps the stored target_model: it neither writes the column nor reconciles replicas of the old target. The check reads the database only for a rule whose stored and derived targets differ. With no accepted revision on record, the old behaviour stays. Assisted-by: Claude Code:claude-opus-5-5 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>	2026-10-08 09:56:12 +02:00
Ettore Di Giacinto	1dc3aeef87	fix(distributed): resolve config revisions through one entry point ... A model's revision is published by administration and checked against on every inference request. Those were computed by separate code: the request path resolves through the loader, while each publisher hashed whatever ModelConfig it happened to hold. By then SetDefaults had folded in the GGUF guess and app-level options, so the published value was one no request would ever carry and the model became unroutable until the row was deleted by hand. Fixing the publishers one at a time did not hold. Three rounds each found another: the startup resync, then a saved edit and a toggle, then a rename and the peer-change path. ModelConfigLoader.RevisionFor is now the only way to obtain a revision, and the raw hash is unexported, so a caller outside this package cannot hash a config it holds. A publisher and a request agree by construction rather than by two implementations happening to match. The request path no longer falls back to hashing its merged config either: an unstamped config is routed without a revision rather than with a wrong one. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint]	2026-08-24 19:11:16 +00:00
mudler's LocalAI [bot]andEttore Di Giacinto	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>	2026-08-22 22:44:03 +02:00
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>	2026-06-27 01:36:57 +02:00