mirror of
https://github.com/mudler/LocalAI.git
synced 2026-11-01 01:59:01 -05:00
86994fac467c714a2dfdcc7e39cea110a68ea449
128
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Plamen K. Kosseff
|
7b9ef6a0f8 |
feat(backends): --disable-backend-install disables backend downloads. (#12754)
feat(backends): --disable-backend-install refuses every backend acquisition A hardening switch for deployments that must run exactly the backend set they were tested with (production, air-gapped, immutable images, package-managed hosts). With LOCALAI_DISABLE_BACKEND_INSTALL=1 every install and upgrade path refuses — gallery, OCI/URL/path, node-scoped, auto-upgrade, boot-time external backends — HTTP routes answer 403 up front, and a model whose backend is missing is refused before any download: 409 on the API, an error on preload and import. Whether a backend is present is asked of the execution target: the local backend directory on a single node, the workers' listings on a distributed frontend, which installs nothing itself. Backends already present, including system-path ones, keep working. Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Plamen K. Kosseff <p.kosseff@gmail.com> |
||
|
mudler-agentandEttore Di Giacinto
|
f85087f992 |
feat(tts): stream Qwen text and add assistant preset (#12770)
* feat(tts): stream Qwen text through audio pipelines Feed cleaned LLM deltas into one persistent Qwen synthesis session. Return audio before input ends and preserve the live RPC through model cache, staging and in-flight wrappers. Stop generation on sink failures or cancellation without replaying speech through a fallback. Pin the incremental native fork and verify early audio, late text, finalization and cancellation with lifecycle and real-model checks. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * build(tts): use the organization Qwen fork Fetch the reviewed incremental synthesis commit from localai-org so backend builds use the organization-maintained fork. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add a Qwen streaming assistant preset Expose an English pipeline using existing VAD, ASR, LLM and named-voice TTS models. Enable incremental text and audio delivery, and document separate component installs because the gallery has no dependency installer. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gallery): use Parakeet TDT v3 for the assistant Select the existing Parakeet TDT 0.6B v3 transcription entry and update its prerequisite install command. Keep the preset's English voice and incremental Qwen synthesis configuration. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(kokoros): reject unsupported backend RPCs Implement the MotionStream and SlotCache methods required by the shared protobuf service. Return Unimplemented so Kokoros compiles without advertising support for either operation. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(tts): mark cleanup and logging results ignored Explicitly ignore connection shutdown, test server shutdown and Ginkgo diagnostic writer errors. These operations do not replace the stream's inference or sink errors, and errcheck requires their return values to be acknowledged. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(tts): stream buffered clauses in realtime pipelines Start clause synthesis while LLM text is still arriving when both streaming flags are enabled. Keep explicit clause opt-out and native Qwen sessions, bound automatic queued work, and choose streaming support on resolved failover targets. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(tts): bound synthetic voice clone generation The sine-wave reference checks speaker conditioning and WAV output, but does not provide a meaningful speech EOS target. Limit that smoke request to 128 frames and verify the request limit reaches native synthesis. Leave production sampling defaults unchanged. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(tts): require explicit clause buffering opt-in Keep whole-reply synthesis for nonnative engines when clause_chunking is unset or false. Use the bounded cancellable worker when explicitly enabled, with unary clauses when TTS streaming is disabled. Preserve native Qwen precedence for every clause setting. Assisted-by: Codex:gpt-6.1-sol Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add VITS and Piper streaming assistants Provide comparable full pipeline configurations with shared VAD, Parakeet transcription, and Qwen chat components. Enable clause buffering explicitly and document the separate prerequisite model installs and Talk selection. Assisted-by: Codex: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> |
||
|
|
e715af1def |
feat(llama-cpp): add slot prompt-cache save and restore API (#12730)
* feat(llama-cpp): add slot prompt-cache save and restore API Add POST /v1/slots/save and POST /v1/slots/restore. They write one llama.cpp slot's prompt cache (KV state) to a file and load it back, so a client can warm a long system prompt in a few hundred milliseconds instead of re-running prefill. Refs #12685. The new SlotCache gRPC call posts the same slot save and restore tasks the llama-server /slots endpoint uses. It is off unless the model sets the new slot_save_path option, so existing models are not affected. The /slots monitoring endpoint is not needed here: the backend has no HTTP server. The file name comes from the caller, so it is checked twice, in Go and again in the backend. It must be one path component: no empty name, "/", "\", "..", NUL, control characters or absolute path. The resolved path, with symbolic links followed, must be a direct child of slot_save_path. The routes are admin only because they write files on the backend host. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(llama-cpp): answer 501 when a backend lacks slot cache A backend that does not implement the SlotCache rpc returns gRPC UNIMPLEMENTED. The API passed that text through, so the client saw "unknown method SlotCache". Map the status to a typed error in core/backend and return 501 with a fixed message instead. Every other error path is unchanged. Make the SlotCache comments in backend.proto backend-neutral: slot is the backend's state slot, filename must stay inside the save directory, and an empty model_identity means the backend does not check it. Only comments change, no field or name. Add tests that the identity sent is the configured model, and for the error mapping. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(llama-cpp): issue slot cache IDs on the server The slot save and restore API let the client pick the file name. Restore could load any file in slot_save_path, and the symlink check ran before llama.cpp opened the file. The backend now issues the name. A save returns a random 128-bit ID (32 lowercase hex characters, read from /dev/urandom) and never overwrites an existing file. Files live in a 0700 directory per model, named from the SHA-256 of the model identity, with a manifest.json that records each save. The manifest is written atomically and a corrupt one stops both save and restore. A restore takes the ID, finds it in the manifest, refuses an entry of another model, builds the path from the entry and checks with lstat that it is a plain file of the recorded size. The directory mode is the main defence against another local user, since llama.cpp still opens the path itself. Each model keeps at most 32 saves and the oldest is deleted first. A file over 8 GiB is deleted after the save, because llama.cpp does not report the size before it writes. Responses carry no host path. The HTTP bodies change: save takes {model, slot}, restore takes {model, slot, id}, and an unknown ID returns 404. In the proto, SlotCacheRequest.filename and SlotCacheResponse.filename become id. SlotCache no longer calls checkModelIdentity, which reads a field this request does not have. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(llama-cpp): copy slot_cache files in prepare.sh grpc-server.cpp includes slot_cache.h, but prepare.sh copies the helper headers into llama.cpp/tools/grpc-server/ one by one and skipped it. The llama-cpp, turboquant and bonsai builds share this step, so they all failed with "slot_cache.h: No such file or directory". Copy slot_cache.h and slot_cache_test.cpp, which CMakeLists.txt builds when LLAMA_GRPC_BUILD_TESTS is on. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(deps): bump LocalAGI to pick up the scheduler start/stop fix LocalAGI's scheduler could hit a nil pointer in run when Start and Stop raced. That made the core/services/agentpool tests panic at random and turned tests-linux red. Move to mudler/LocalAGI@7aa0c8fea0, the merge of mudler/LocalAGI#519 ("make Start and Stop safe to call concurrently"). The new module version also adds a few indirect requirements to go.mod and go.sum. Assisted-by: Claude:claude-sonnet-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> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
||
|
Richard Palethorpe
|
3de91d48d9 |
feat(motion): add GEM-X backend and duplex streaming API
Add the GEM-X native backend with live pose and root displacement output, bounded duplex WebSocket streaming, session authorization, metrics and usage accounting. Share the embedded bidirectional RPC channel adapter across streaming backends.
Include backend build and gallery integration, API documentation, schemas and tests.
Assisted-by: Codex:gpt-6
Signed-off-by: Richard Palethorpe <io@richiejp.com>
(cherry picked from commit
|
||
|
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> |
||
|
mudler-agent
|
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> |
||
|
mudler-agentandEttore Di Giacinto
|
d3724eef50 |
fix(nodes): stage dedicated diarization audio (#12474)
Dedicated diarization forwards frontend audio paths to remote workers, which cannot read those temporary files. Stage the input before the RPC and release it afterward, following the transcription lifecycle. Clone the request so staging does not change caller-owned data. Cover input bytes, request fields, cleanup, and error propagation in tests. Document distributed diarization staging on the existing feature page. Assisted-by: nib:gpt-6-astra Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
mudler-agentandEttore Di Giacinto
|
e4fa051ee3 |
refactor(distributed): put the NATS-only paths behind interfaces (#12395)
* feat(messaging): add shared subject rules Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(messaging): cover BroadcastRoots, ControlRoots and SubjectRoot Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(messaging): add Broadcaster and enforce subject rules in every carrier Broadcaster is the fan-out half of MessagingClient. The NATS client and the in-memory FakeBus now refuse a subject outside the served roots and any wildcard other than a whole single token, and FakeBus shares MatchSubject instead of its own copy. FakeBus Unsubscribe now removes its own subscription instead of the first one with the same subject. A shared conformance suite in messagingtest runs against both carriers. The distributed e2e specs that used invented test.* subjects, and the one that subscribed with a > filter, now use subjects from subjects.go. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor: depend on Broadcaster where only publish and subscribe are used Narrowed to messaging.Broadcaster: nodes/staging_progress.go, nodes/install_progress_publisher.go, galleryop/operation.go, galleryop/service.go, agentpool/user_services.go, agentpool/agent_jobs.go, openresponses/store.go, openresponses/sync.go, syncstate/syncstate.go, finetune/service.go, quantization/service.go and failover/distsync/distsync.go. SubscribeJSON now takes a Broadcaster because it only calls Subscribe, which lets the narrowed consumers use it. Stayed wide: worker/supervisor.go, because its client field also serves the SubscribeReply handlers in worker/lifecycle.go. The request/reply, queue and wiring files (nodes/unloader.go, nodes/file_stager_s3.go, jobs/dispatcher.go, agents/dispatcher.go, agents/events.go, worker/file_staging.go, cli/agent_worker.go, http/app.go) are unchanged by design. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): name the no-route condition and confine the carrier error Consumers matched nats.ErrNoResponders, which names an absence, to demote a node. They now match ErrNoRoute, the control path maps the carrier's failure onto it, and timeouts and worker refusals are pinned as not being no-route. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(nodes): state which FileStager implementations return ErrNoRoute Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): build backend clients through one node-aware seam Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: describe the distributed transport seams Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: correct comments that overclaim after the seams refactor Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(agent-worker): refuse an unserved LOCALAI_AGENT_SUBJECT at startup The messaging client now refuses a subject whose root no carrier serves. An agent worker started with a custom LOCALAI_AGENT_SUBJECT such as tenant-a.agent.execute used to start and then wait on a subject the frontend never publishes to. After the subject rules landed it exited at subscribe time with an error that did not name the setting. Behaviour change: the worker now checks LOCALAI_AGENT_SUBJECT before it registers or connects, and exits with an error that names the variable and says to use a served subject under the agent root, for example agent.execute. The served roots are not widened: a custom root was never delivered by the frontend, and a wider set would reopen the drift the subject rules exist to close. The flag help and the agent worker docs state the constraint. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(nodes): pin the reactions to ErrNoRoute Three callers react to ErrNoRoute and had no spec: the reconciler's upgrade drain falls back to the legacy forced install, the reconciler marks the node unhealthy when a pending op has no route, and the backend-op fan-out marks the node unhealthy. Each spec drives the real caller with a scripted no-responders reply and reads the result from the registry or the recorded requests. A fourth spec pins the other side: a pending op that times out leaves the node healthy and only counts the attempt, so mapping timeouts onto ErrNoRoute would fail here. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(messaging): pin client subject checks and fail the carrier suite in CI Add specs that call Publish, Request, Subscribe, QueueSubscribe, SubscribeReply and QueueSubscribeReply on a client with no connection. Each call must return ErrUnservedSubject for bogus.thing and ErrUnsupportedWildcard for jobs.>. This proves that the subject check runs before the connection is used, and needs no server. The NATS conformance suite is the only check that runs the subject rules against a real carrier. Before this change it skipped without output when Docker was missing. Now it fails when CI is set, so a Linux runner without Docker cannot hide it. It still skips on local runs and on macOS CI, which has no Docker. Add SubjectNodeBackendInstallProgress to the list of constructors that must build served subjects, and ask contributors to extend the list. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: state what ErrNoRoute may change, and group the distributed guides The seams note said MarkUnhealthy was the only state change allowed on ErrNoRoute. A pending backend op still records the failed attempt, counts toward the reconciler's retry limit and is dead-lettered after the maximum attempts. The note now says that MarkUnhealthy is the only change to the node's own state, and that the per-op accounting is not a verdict about the node. The note also documents that the NATS conformance run fails under CI when Docker is missing. The distributed-seams row moves next to the distributed-state row in the topics table. The liveness ping spec header now says no route is a reason to skip the worker, not proof that the worker is gone. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): give the backend client factory the node id Mechanical: the method gains a nodeID parameter and the eight test fakes are updated. No behaviour change. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): drop the optional node-aware factory The node id is now in the main method, so the optional interface and its helper had no behaviour of their own. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): dial backend probes through the client factory Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): dial workers' file servers through a per-node dialer Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(http): proxy backend logs through the per-node worker dialer The admin backend-logs proxy (list, lines and the WebSocket stream) now reaches a worker through the same per-node dialer as the HTTP file stager, so every frontend-to-worker dial goes through one seam. The shared direct dialer keeps alive for 15s where the proxy used 30s. Harmless for requests bounded at 15s. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(http): keep the backend-logs proxy independent of the admin connection The proxy request had no context before the dialer change and is bounded only by its 15s timeout. Keep it that way. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor: move the worker control payloads to workerctl Mechanical move of the request and reply structs, the install progress event and the file payloads out of messaging. The verbs no longer belong to one carrier. No alias is left behind. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(worker): serve the lifecycle verbs through a controlServer The worker registers one handler per verb and a NATS server maps each verb to its subject. Registration errors now name the verb. node.stop is served with SubscribeReply, which is identical on the wire because the handler never replies. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(worker): report install progress through the control sink Install and upgrade now emit download progress through the sink the control server hands them. The debounce and the terminal flush stay in the handler path, built over that sink by the new nodes.NewDebouncedInstallProgressSink, which replaces NewDebouncedInstallProgressPublisher. The subject and payload on the wire are unchanged. The supervisor no longer holds the bus, and installFn and upgradeFn let specs drive both verbs without a gallery. The malformed-request log lines are restored for install, upgrade, backend.delete, model.unload, model.stop and model.delete, with the reply bytes unchanged. The signal adapter is renamed noReply, which also lets worker.go import os/signal without an alias again. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(worker): serve the file-staging verbs through a controlServer An empty list-dir answer is now {} rather than {"files":null}, because the typed reply omits an empty Files slice. The frontend decodes both to a nil slice in nodes/file_stager_s3.go. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(messaging): add WorkQueue and the NATS producer This is the producer side of the competing-consumer seam. The work kinds map one to one to today's subjects and queue groups: task to jobs.new and mcp-ci to jobs.mcp-ci.new (both in group workers), agent-run to agent.execute (group agent-workers). Enqueue publishes the payload as Publish does today, with one JSON marshal. FakeBus now records queue groups and keeps reply handlers so later specs can pin and drive them. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(messaging): add the NATS WorkConsumer An in-flight limit of one runs the handler inline on the delivery goroutine, as the MCP CI consumer does today. Any other limit spawns per delivery, as the agent consumer does. Queue groups are unchanged. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor: publish queued work through WorkQueue The job dispatcher, the agent pool and the agent scheduler enqueue through messaging.WorkQueue; the NATS implementation publishes to the same subjects as before. DistributedServices builds the queue next to the NATS client and hands it to the dispatcher and the agent pool, whose distributed mode switch now reads a non-nil WorkQueue. The unused AgentPoolService.SetNATSClient is removed. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor: consume queued work through WorkConsumer The agent dispatcher and the MCP CI consumer register through messaging.WorkConsumer. The NATS implementation keeps the inline one-at-a-time model for MCP CI and the per-delivery model for agent runs. handleMCPCIJob reports on the events publisher the carrier hands it instead of a captured client. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor: delete the consumers nothing in production reached jobs.new has a producer and no production consumer, and the agent dispatcher's Dispatch was only called from tests. Publishing jobs.new is unchanged. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(mcp): send MCP requests to agent workers through AgentControl Timeouts still honour only the deadline, not cancellation, exactly as today. The NATS no-responders error maps to ErrNoRoute and a timeout does not. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(agent-worker): serve MCP requests and backend.stop through agentRPCServer The agent worker's MCP tool and discovery reply subscriptions and its backend stop listener move behind an unexported agentRPCServer interface, served on NATS by nodes.NATSAgentRPCServer. The handlers become typed mcp.ToolHandler and mcp.DiscoveryHandler values that answer every failure with a reply carrying Error. Queue group (agent-workers), inline execution on the delivery goroutine, the background handler context, the unmarshal error reply texts and the reply-less backend stop subscription are unchanged. The backend stop handler takes the decoded backend name, so it can still close that backend's MCP sessions. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(messaging): remove helpers that only tests used BroadcastRoots, ControlRoots and SubjectRoot had no production caller. The roots spec now asserts every served root through ValidateSubject instead. MatchSubject moves back into the test support package, the only place that used it, with its table. NATSAgentRPCServer drops the subscription list it stored and never read, and NewNATSAgentRPCServer gets a doc comment. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(mcp): round trip the agent RPC server over a real NATS server One spec sends a tool request and a discovery request through NATSAgentControl to NATSAgentRPCServer and checks that the handlers see the decoded requests and the replies come back. It also puts an undecodable body on the tool subject and checks the server answers with an unmarshal error instead of leaving the requester to time out. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: describe the distributed transport seams The developer note now lists the final seams: fan-out, queues, both halves of the control verbs and of agent RPC, and the dial. It records the open items a second carrier has to handle. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test: pin the in-flight limit each queue consumer asks for The work queue specs pin what Consume does for a given limit, but nothing pinned which limit each production consumer passes. Changing the agent worker's MCP CI limit from 1 to 0 would have let MCP CI jobs run concurrently on each worker with every test green. Move the MCP CI Consume call into startMCPCIConsumer with the same wiring and pin that it asks for (WorkMCPCI, 1). Pin that NATSDispatcher.Start asks for (WorkAgentRun, maxConcurrent) for several limits. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor: remove helpers the branch left without a caller SubjectJobCancelWildcard lost its last subscriber when the frontend stopped listening on jobs.*.cancel; the NATS permissions and conformance suite spell the subject out, so nothing reads the constant. decodeBackendStopRequest returned a stopAll flag that production dropped and only a test read. decodeBackendStop is now the single decoder with the same semantics: an empty body is stop-all, an empty Backend is stop-all, malformed JSON is an error. stopBackends still derives stop-all from Backend, so no reply changes. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(messaging): keep an explicitly empty agent queue a plain subscription Before the work queue seam the agent worker passed LOCALAI_AGENT_QUEUE straight to QueueSubscribe, so an explicitly empty value made a plain subscription and every agent worker ran every agent run. WithAgentRunRoute replaced an empty queue with agent-workers, which silently changed that. Keep the queue as given once the option is applied. An empty subject still falls back to agent.execute, since it never had a meaning of its own. The flag default stays agent-workers, so only an explicitly empty value reaches this. Assisted-by: Claude:claude-sonnet-5-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs: correct comments and record the PR B notes Fix the recordingFactory comment (it also records the parallel flag), document that a negative maxInFlight is unbounded and that Unsubscribe from a handler deadlocks, and say a permanently undecodable payload returns nil. Record controlHandler's undecodable return as a kept exception, and add the second carrier notes to the developer note: the reconciler has no ClientFactory option, the logs proxy honours HTTP_PROXY, verbs one carrier serves need an opt-out, terminal replies come from the result event, and agent runs publish through the NATS-bound EventBridge, which is not an additive change. Assisted-by: Claude:claude-sonnet-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> |
||
|
mudler-agentandEttore Di Giacinto
|
590512d9eb |
feat(distributed): report worker version and show models in node inspector (#12328)
* ci: bump Hugo from 0.146.3 to 0.166.0 The hugo-theme-relearn submodule was bumped to 9.1.x in #12096, which requires Hugo >= 0.165.0. The pinned 0.146.3 broke the docs site build with a template error in alias.html that could not evaluate the Locale field on langs.Language. Bump HUGO_VERSION to 0.166.0 (latest stable) to satisfy the theme minimum and resolve the alias.html template error. Assisted-by: nib:claude-sonnet-4.5 [bash] [read] [edit] * feat(distributed): report worker version and show models in node inspector Workers now send their LocalAI build version and git commit at registration. The controller stores them on BackendNode and exposes them through the existing node list/detail API responses. The node inspector side pane now fetches and renders the list of loaded models (name, state, in-flight) instead of showing only a count, matching what the node detail page already displays. --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
mudler-agentandEttore Di Giacinto
|
97ad8f1d70 |
fix(distributed): stage the files a model install declares (#12309)
* fix(distributed): stage every shard of a split GGUF A split GGUF is configured by its first shard only. llama.cpp opens the other "-0000N-of-0000M.gguf" files from the same directory by name. The router staged only the configured path, so the worker received shard 1 and the load failed with "failed to load GGUF split". The router now stages the remaining shards next to the first one. A missing shard fails the load and names the file. The file count for progress and the payload size also include all shards. The payload size feeds the load deadline and the disk-headroom check. For a 111 GB model whose first shard is 10 MB, both were sized for less than 1 GB. Assisted-by: Claude:claude-opus-5-5 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): stage the files a model install declares Replace the split GGUF file name matching with the model's own file list. A gallery install or an import records every file of the model in ._gallery_<name>.yaml (files:), and a config can list more under download_files:. The router now stages all of these files, not only the files that the config's path fields name. This includes the other shards of a split GGUF, which llama.cpp opens by name. The application gives the router a resolver that reads the two lists. The resolver looks up the files by model name when it stages them, so a replica that the reconciler loads from saved load options gets the same files. backend.proto does not change. A declared file that is missing on the frontend is skipped with a warning. The load deadline and the disk headroom check include the declared files. Assisted-by: Claude:claude-opus-5-5 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
|
52a6d62bbc |
fix: return correct HTTP status codes for saturation and no-nodes-available (#12113)
* feat: return 429 when backends are saturated When backends are at capacity (per-model max_concurrent or the process-wide --max-concurrent-backend-requests ceiling), the response was 503. The OpenAI SDK, litellm, and most agent harnesses key on 429 for rate-limit backoff and treat 503 as a hard error. Both saturation paths now return 429 with the existing Retry-After header and type: "rate_limit_error" in the JSON body. The per-model admission middleware keeps admission_rejected as the code field so existing alerts that match on it still fire. Non-saturation 503s are unchanged: model cold-loading (with progress body), model-load failure cooldown, PII detector fail-closed, and classifier unavailable. These mean "not ready" rather than "busy". Assisted-by: AGENT:regolo/glm5.2 [TOOL] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: return 503 when scheduler has no available nodes When the scheduler cannot find any healthy node to serve a model — all nodes are full and eviction cannot free a slot, or a node_selector excludes every candidate — the error fell through to 500. A 500 tells clients something is broken when the condition is transient and retryable. The router now wraps these errors with a new ErrNoAvailableNodes sentinel. The HTTP error handler maps it to 503 via applyNoAvailableNodes, following the same pattern as applyBackendAdmission (429). Unrelated scheduler errors (DB timeouts, registry lookups) still return 500. Three return sites are wrapped: - resolveSelectorCandidates: selector matches zero healthy nodes - scheduleNewModel eviction-busy: all models have in-flight requests - scheduleNewModel eviction-failed: eviction itself errored The existing scheduleAndLoad wrapper ("no available nodes: %w") preserves the sentinel through the chain via errors.Is, as does ModelRouterAdapter. Assisted-by: AGENT:regolo/glm5.2 [TOOL] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(http): use Ginkgo for admission tests Replace forbidden testing.T calls with Ginkgo and Gomega so the lint check accepts the admission handler tests. Assisted-by: Codex:GPT-6 forbidigo * fix(middleware): show the recorded status for admission rejections The admission audit row now records 429, but the Middleware page still printed a hard-coded 503. Read the status from the event, and update the two package comments that still said 503. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5-5 [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 <306269227+localai-org-maint-bot@users.noreply.github.com> |
||
|
Richard Palethorpe
|
2facfc0d88 |
feat: Add kimodo.cpp and 3D animation API/UI (#12095)
* fix(vulkan): preserve host ICD discovery for packaged backends Add bundled Mesa manifests through VK_ADD_DRIVER_FILES instead of replacing the system driver list. Merge inherited and model-specific additive paths while preserving explicit operator overrides, with regression coverage. Assisted-by: Codex:gpt-5 golangci-lint Assisted-by: Codex:gpt-5.6-sol Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(3d): add Kimodo CPU and Vulkan animation backend Introduce a distinct animation capability and model-described 3D operations, with a typed /3d/animate API, RPC transport, distributed media staging, permissions, and tracing. Add a persistent kimodo.cpp adapter, skeleton GLB export, CPU/Vulkan packages, model and backend galleries, importer support, CI builds, and documentation. Adapt Studio inputs to each model and provide real-time skeleton playback, seeking, and history. Cover backend validation, packaging, API behavior, importer inventories, distributed staging, and Studio workflows. Validate real-model CPU/Vulkan generation and deploy the integration to the local QA instance. Assisted-by: Codex:gpt-5 golangci-lint Assisted-by: Codex:gpt-5.6-sol Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(kimodocpp): adopt monolithic encoders and resident inference Update upstream for resident weights, packed execution paths, and cached motion graphs. Default to all 32 text layers while retaining configurable streaming and legacy bundle support. Use monolithic Q8_0 encoders by default and offer all six published quantizations through the gallery and importer. Refresh pinned hashes, tests, and documentation; remove the obsolete thread patch and ensure cached source checkouts follow the upstream pin. Validated CPU and Vulkan generation, lower-bit streaming, gallery/importer suites, packaging, lint, and cold/warm Studio generation on localai-dev. Assisted-by: Codex:gpt-5 golangci-lint Assisted-by: Codex:gpt-5.6-sol Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
997d403de4 |
feat(nodes): add fleet operations dashboard (#12046)
* feat(nodes): report CPU telemetry Assisted-by: Codex:gpt-6 * feat(nodes): add fleet view utilities Assisted-by: Codex:gpt-6 * feat(nodes): add fleet operations dashboard Replace the panel roster with aggregate capacity gauges, fleet filtering and selection, bounded bulk actions, and an on-demand node inspector. Extend node details and distributed-mode documentation with CPU and models-disk telemetry. Assisted-by: Codex:gpt-6 * fix(nodes): harden fleet lifecycle actions Assisted-by: Codex:gpt-6 * fix(nodes): restore compact fleet composition Keep fleet health, capacity, and attention in one compact overview at ordinary desktop widths. The inspector now overlays the roster until the workbench can preserve a useful table beside it. Assisted-by: Codex:gpt-6 * feat(nodes): add accessible running models workbench Assisted-by: Codex:gpt-6 * fix(nodes): correct model view ARIA links Keep each tab panel available for its controlling tab while native hidden state removes inactive content from accessibility navigation. Model controls now expose only supported state and valid inspector relationships. Assisted-by: Codex:gpt-6 * fix(nodes): align lifecycle and capacity states Pending nodes now expose approval wherever node actions appear, while other lifecycle controls follow the server transition rules. Capacity totals exclude incomplete readings so missing availability remains unknown. Assisted-by: Codex:gpt-6 * fix(nodes): restore approved dashboard composition Assisted-by: Codex:gpt-6 * fix(nodes): integrate operate navigation Assisted-by: Codex:gpt-6 * fix(nodes): restore low density fleet view Assisted-by: Codex:gpt-6 * fix(nodes): preserve complete operate menu Assisted-by: Codex:gpt-6 * fix(nodes): preserve inspector workspace height Assisted-by: Codex:gpt-6 * fix(nodes): restore standard operate navigation Assisted-by: Codex:gpt-6 * feat(ui): add collapsible console rail Assisted-by: Codex:gpt-6 * feat(nodes): stop models from fleet view Assisted-by: Codex:gpt-6 * fix(nodes): make inspector a full height drawer Assisted-by: Codex:gpt-6 * fix(model): stop mixed local and remote placements Assisted-by: Codex:gpt-6 * fix(ui): announce action menu navigation Assisted-by: Codex:gpt-6 * fix(nodes): keep inspector within viewport Assisted-by: Codex:gpt-6 * fix(ui): preserve focus across model actions Assisted-by: Codex:gpt-6 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Adira Denis Muhando
|
869000ceb7 |
fix(distributed): exclude pinned models from cluster eviction and idle scale-down
pinned: true was only honoured by the per-node watchdog. Every distributed eviction path was pinned-blind: the router's LRU eviction (EvictLRU, evictLRUAndFreeNode) and the replica reconciler's idle scale-down would happily unload a pinned model — and since eviction is gated on in_flight = 0, a pinned model became eviction-eligible the instant each response completed. Under capacity pressure that surfaces as the backend being freed immediately after every request (#11101). Wire the model config loader into the router and reconciler through a new PinnedModelResolver seam (mirroring ConcurrencyConflictResolver): - EvictLRU passes the pinned set into FindLRUModel's query so the next-oldest unpinned model is selected instead of the attempt failing - evictLRUAndFreeNode filters pinned models inside its locked selection - scaleDownIdle skips pinned models entirely: trimming to the floor still means requests beyond the survivor's capacity pay a cold reload Deliberate teardown (admin unload, model delete, node drain) intentionally still applies to pinned models, as does dead-row reaping (state correction, not eviction). Regression specs verified to fail with the exclusion disabled. Addresses the cluster-side eviction gap in #11101 Assisted-by: Claude Code:claude-fable-5 [Claude Code] Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> |
||
|
Ettore Di Giacinto
|
bbd5488871 |
fix(distributed): make backend.stop report what it stopped
backend.stop was the one lifecycle subject a worker never answered. The controller published and returned nil as soon as the local publish succeeded, so a stop that killed nothing, and a stop that failed outright, were indistinguishable from one that worked. The unload endpoint calls model.unload and then StopBackend. Only the first is acknowledged, so the endpoint answered 200 while the backend kept running and held its VRAM, and its own "backend stop failed" branch could never run. The worker logged the failure and nobody saw it. Give the subject a reply. The worker now enumerates the process keys it terminated and reports any per-process error, so StopBackend fails when the stop failed. Resolving to nothing stays a success: stopping a backend that is not running leaves the caller in the state it asked for, and eviction paths stop already-gone models routinely. The empty list is what says nothing matched, and ReportsStoppedProcesses is what makes that emptiness trustworthy, the same way BackendDeleteReply handles it. A worker built before this reply still receives the request and still stops the backend, it only stays silent, so a timeout degrades to the old assumption rather than failing every stop on a fleet mid-upgrade. Only silence degrades: a transport error is still reported, because UnloadRemoteModel skips its registry cleanup for a node it could not reach and needs to keep hearing about that. Assisted-by: Claude:claude-opus-5 golangci-lint |
||
|
Ettore Di Giacinto
|
db09452d54 |
feat(tts): support multi-reference personalities
Saved profiles previously resolved to one audio path and transcript, so cloning backends could not use several examples of one personality. Store ordered audio and transcript pairs while preserving the legacy first-reference fields. Fish Speech and audio.cpp receive all pairs, including on distributed workers. Other backends retain their single-reference behavior. Assisted-by: Codex:gpt-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
783556bc93 |
feat(prefixcache): index reported KV residency
Add a NATS event contract and exact-residency provider for backend KV cache reports. Keep guessed request observations as the default routing source while maintaining the reported index for future producers. Assisted-by: Codex:gpt-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
a64fc865ba |
fix(distributed): aggregate prefix cache pressure
Broadcast forced-disturb events and successful scale-up resets so every frontend shares the same rolling autoscale signal. Deduplicate NATS echoes, expose an origin-only Prometheus counter, and document cluster behavior. Closes #10083 Assisted-by: Codex:gpt-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
a9f8062dd5 |
feat(nodes): add pluggable routing pipeline
Route prefix-cache replica selection through composable filters, weighted scorers, and a replaceable picker. Preserve the existing load guard and deterministic selection policy while exposing per-model scorer weights through scheduling configuration. Assisted-by: Codex:gpt-5 [go-vet] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
e78271563b |
fix(distributed): pass raw JPEG base64 through staging (#11956)
JPEG base64 starts with /9j and was classified as an absolute path in distributed mode. Detect valid JPEG base64 by its decoded magic bytes so vision requests reach the backend unchanged while malformed path-like inputs retain existing staging behavior. Assisted-by: Codex:gpt-5 Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
8b5f62cc02 |
fix(distributed): bound ephemeral staging (#11924)
* docs: design ephemeral staging retention High-frequency camera and audio inputs can fill a worker before the current six-hour cleanup window expires. Define a one-hour retention policy that preserves recently modified request payloads. Assisted-by: Codex:gpt-6 * docs: make ephemeral staging request-owned Time-based retention can still fill a worker under bursty or high-rate input. Define request-lifecycle cleanup with capacity reservation and crash recovery. Assisted-by: Codex:gpt-6 * feat(distributed): release exact staged keys Request inputs need transport-neutral cleanup after backend calls. Add authenticated exact-key deletion for HTTP and coordinated cache eviction before shared-object deletion for S3/NATS. Preserve URL metacharacters as filename data, reject unsafe keys, and remove upload sidecars while pruning empty request directories. Assisted-by: Codex:gpt-6 * fix(distributed): release staged request inputs Ephemeral inputs remained on workers after inference completed. Release each exact key after synchronous and streaming calls, including partial staging failures. Use a bounded cleanup context so caller cancellation cannot suppress release. Preserve caller requests and backend results when cleanup fails. Assisted-by: Codex:gpt-6 * feat(worker): bound ephemeral staging capacity Concurrent staging can otherwise exceed its byte limit or consume reserved filesystem headroom. Explicit states keep bytes charged through each reservation, write, and commit transition. Use a synchronized waiter count to prove Commit blocks until bounded writers close, and retain committed baselines across re-reservation. Assisted-by: Codex:gpt-6 * feat(worker): enforce ephemeral staging bounds Share capacity accounting across HTTP and S3 request inputs so workers reject uploads before exhausting their filesystem. Reconcile exact release and crash recovery with the same guard. Assisted-by: Codex:gpt-6 * fix(distributed): make staged release race-safe Pin each release path component before removing request-owned inputs and sidecars. Stop pruning when a directory identity changes. Assisted-by: Codex:gpt-6 * fix(worker): retain staged input ownership Keep committed request inputs protected from age recovery until exact release ends their ownership. Startup-scanned files remain reclaimable and can acquire ownership through reservation. Assisted-by: Codex:gpt-6 * fix(worker): claim cached ephemeral inputs Keep startup-scanned cache hits owned while inference uses them and reconcile their actual size against capacity. Assisted-by: Codex:gpt-6 * fix(distributed): enforce staging admission Propagate multimodal staging failures before inference and claim matching ephemeral HTTP cache entries. Fall back to PUT when an older worker does not support claims. Assisted-by: Codex:gpt-6 * fix(distributed): close staging accounting gaps Keep unknown-length reservations charged until bytes reach disk and bound NATS release waits by the lifecycle cleanup deadline. Assisted-by: Codex:gpt-6 * fix(distributed): restage swept cache hits Treat files removed between cache probing and ownership claims as misses so HTTP and S3 workers can stage them again. Assisted-by: Codex:gpt-6 * fix(distributed): release staged inputs by request Release every input from one inference with one fixed-size worker coordination request. Fence request ingress against cleanup, bound staging capacity and cleanup state, and retain exact-key release for rolling upgrades. Assisted-by: Codex:gpt-6 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
aff9db9758 |
fix(distributed): resolve paths for virtual models (#11911)
Virtual model names have no primary file to anchor the worker path. Companion assets still stage successfully, but relative options retain an incorrect model directory and fail to load. Derive the worker root from successfully staged option assets when the primary path is absent. Cover Buffalo packs, files, directories, overrides, and failed transfers. Document the frontend upgrade. Assisted-by: Codex:gpt-6 golangci-lint Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
e494033607 |
fix(distributed): finalize stalled model uploads (#11910)
A worker can retain all model bytes with an unfinished-upload marker. Retries then start at zero and repeatedly fail with HTTP 416. Verify the existing bytes and finalize same-file retries at full size. Reuse the normal integrity checks so corrupt content cannot be accepted. Add regression coverage and document worker recovery. Assisted-by: Codex:gpt-6 golangci-lint Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
fb8b7a359a |
fix(distributed): stage sound detection audio (#11907)
* fix(distributed): stage sound detection audio Sound detection passes frontend temporary paths directly to remote workers, unlike transcription. Stage the WAV before classification so CED can read it without a shared temporary directory. Preserve the original request for retries and propagate staging errors without calling the backend. Cover staging, request preservation, and error handling with regression tests. Assisted-by: Codex:GPT-6 golangci-lint * test(distributed): verify routed sound staging Call sound detection through the client returned by SmartRouter.Route. This checks interface dispatch through both routing wrappers, rather than constructing FileStagingClient directly. The test fails without the sound-staging override and passes with it. Assisted-by: Codex:GPT-6 golangci-lint --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
localai-org-maint-botandEttore Di Giacinto
|
9afe10ba21 |
fix(distributed): survive a slow control-plane database (#11837)
* fix(distributed): evict only when a node is known to be full scheduleNewModel asked the registry for a free replica slot and treated every error as "this node is full", so a control-plane database slow enough to time out the lookup evicted a healthy loaded model. The evicted process died, a peer frontend still holding its address dialled the dead port and retried, and the model thrashed between nodes. The comment on the branch already said it meant a full node; the code never tested for it. Evict only on ErrNoFreeSlot. Any other error now returns and names the lookup that failed, so a slow database degrades into a diagnosable load failure instead of into lost work. An audit of the rest of the router found one branch of the same shape: node selection discarded the error from its last-resort finder, so a database timeout there also produced a nil node and evicted for it. That path now returns unless the finder said gorm.ErrRecordNotFound, which is the only answer that means the cluster had no node to give. No other destructive branch in router.go fires on a generic error. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): checkpoint heartbeat writes instead of writing every beat Every heartbeat UPDATEd backend_nodes. Six nodes at a ten second beat is roughly 52,000 writes a day against a six-row table, and that churn is what turned a blocked autovacuum into a 460 MB table whose six-row scan cost 867 ms and timed out the queries that place models. A beat carrying only a fresher timestamp now waits for the checkpoint interval. Each reported field is compared against the value last persisted rather than tested for presence, because a worker sends its disk figures on every beat and presence alone would suppress nothing. A node's first beat, a changed total VRAM, total disk or GPU vendor, and a free VRAM, RAM or disk reading that has moved more than 256 MiB from the persisted value all still write at once. A node that is not active is never suppressed, because it recovers only when the health monitor sees a fresh timestamp. The persisted column is up to one interval stale by design, so the stale-node threshold moves from 60s to 5m to cover it. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): fail worker readiness when a held backend is unreachable The readiness gate tracked only the NATS link, so a worker whose backend processes had died still answered /readyz with 200 and kept receiving loads. One node did exactly that during an incident: it reported healthy while its backend port refused connections, and every load routed to it failed. Readiness is now the NATS link and, for each backend process the worker believes it is running, a short dial of its recorded address. A worker holding no backends stays ready, because idle is a healthy state. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): keep a starting backend out of the readiness dial set A backend process is inserted into the supervisor map with its gRPC address already recorded, but the address refuses connections until the gRPC server binds, which the startup poll allows up to 30 seconds for and which takes 10 to 15 seconds on a slow node. The new data-path readiness probe dialled that address straight away, so a worker answered /readyz with 503 for the whole of every cold backend start. The container HEALTHCHECK absorbs that, but a Kubernetes readinessProbe at 10s does not, and the worker would leave rotation each time it loaded a model. The skip for a stopping process had no counterpart at the other end of the lifecycle. Backend processes now carry a serving flag, set where the startup health-check gate succeeds, and the probe dials only processes that are serving and not yet stopping. backendStartStillValid becomes markBackendServing: the check and the mark must share one lock hold, so the flag can only ever land on the entry the key currently owns. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): export control-plane database health gauges Four transactions wedged on a corrupt index held the vacuum horizon open for 42 days. Nothing measured it, so the first symptom anyone saw was models failing to load six weeks later, by which time a six-row table had grown to 460 MB. Export the oldest xmin age, the longest open transaction, and the dead tuple ratio on the registry tables. The first is the number that would have caught it: it sits near zero in health and was 21,002,291. Sampling is scrape-driven behind a cache, and a failed sample reports the last good values rather than failing the scrape, because these gauges matter most when the database is already struggling. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): rate-limit failed control-plane database samples The cache advanced its clock only on a successful sample, so once the database started failing every scrape retried the query immediately. That turned the cache off in the one regime it exists for: a retry storm at scrape cadence aimed at a database already in trouble. A catalog read that consistently exceeds the 5 second timeout also paid that cost on every scrape, with all scrapes serialised behind the sampler mutex. Time every attempt rather than every success, so failures and timeouts cost the same interval as good samples. Whether a good sample exists moves to its own field, keeping the gauges absent until the first success and holding the last good values through later failures. Also note in the runbook that pg_stat_activity cannot see prepared transactions or replication slot xmins, so a healthy-looking xmin age does not by itself rule out a blocked horizon. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(distributed): pin that a failing database evicts nothing Exercises the real distributed stack against a control-plane database that refuses the router's slot lookup, and asserts the scheduler reports the lookup it could not answer instead of falling through to eviction. The failure is injected with privileges rather than a statement timeout. A timeout set with ALTER DATABASE also breaks AutoMigrate, and it leaks into every later spec in the suite unless it is reset, so the spec would end up testing the migration rather than the scheduler. Instead the spec creates a dedicated login role, points a second gorm handle at it, and revokes that role's SELECT on node_models.replica_index. This has to be a separate role: the test container's owner is a PostgreSQL superuser, and superusers bypass every privilege check, so revoking from CURRENT_USER is recorded and then ignored. The revoke is scoped to one column on purpose. Revoking the whole table would also blind node selection, which runs first and has a guard of its own, so the scheduler would never reach the slot lookup this spec is about. Leaving every other column readable lets selection succeed and lands the refusal exactly on NextFreeReplicaIndex, which plucks replica_index. The grant is restored from BeforeEach via DeferCleanup, so a failing assertion or a panic cannot hand the next spec a role that cannot read. Reverting the eviction guard fails this spec, which is the point of it: the router then reports "no replica slot on keeper and eviction failed" for an error that was never evidence the node was full. The surviving-row assertions are secondary under this injection, because the eviction path reads whole node_models rows and the same revoke blinds it too; a comment in the spec says so, so nobody mistakes them for the load-bearing ones. Also documents why the vector store and the control plane must not share a database: the removable-tuple cutoff is per database, not per table, so one transaction left open anywhere stops autovacuum reclaiming the node registry, and a six-row table bloats into hundreds of megabytes. The note names LOCALAI_AUTH_DATABASE_URL and LOCALAI_AGENT_POOL_DATABASE_URL as the two knobs that must differ, and the localai_control_plane_oldest_xmin_age gauge as the way to see it coming. grep for StaleNodeThreshold and HealthCheckInterval in core/config/runtime_settings_registry.go returns no matches: the distributed duration knobs are not exposed as runtime settings, so the new heartbeat checkpoint interval follows them and needs no registry entry. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): close the review gaps in the heartbeat and health path The stale-node threshold moved from 60 seconds to 5 minutes in this branch because checkpointing makes last_heartbeat up to one checkpoint interval behind by design. Two things were left inconsistent with that. NewHealthMonitor still fell back to a hardcoded 60 seconds when handed a zero threshold, so any future caller that stopped passing the configured value would mark every healthy, beating node offline on every cycle. And the threshold itself had a flag-name constant but no AppOption, no CLI field and no env binding, so an operator who widened --node-heartbeat-checkpoint had no way to widen the threshold to match. The fallback now tracks config.DefaultStaleNodeThreshold, and --stale-node-threshold / LOCALAI_STALE_NODE_THRESHOLD is wired the same way its sibling is. Heartbeat suppression compared the RAW reported free VRAM against the snapshot, but the column persists capAvailable(raw, ceiling). On any node with a VRAM budget set, whose actual free VRAM oscillates above that ceiling, every beat looked material while the persisted value never moved: suppression was defeated on exactly the nodes an operator had configured, and the write amplification this branch exists to remove came straight back there. The comparison and the snapshot now both hold the capped figure, so they measure the same quantity as the column. Fixing that needs the ceiling, and reading it cost a SELECT on every beat, including suppressed ones. The skip decision therefore moved ahead of the updates map and now reuses the ceiling cached on the last durable write, while the write path still re-reads it before capping anything. A ceiling that changed inside the checkpoint window can cost one extra or one late write; it cannot persist a wrong figure. A suppressed beat now costs no query at all. Also: the operations section now says to grant pg_read_all_stats to the LocalAI role, because PostgreSQL blanks backend_xmin and xact_start for sessions owned by other roles, and the transaction that wedged the horizon in the incident was a co-located vector store connecting as a different role, so without the grant the new gauge sees only our own sessions. The compose healthcheck comment now describes readiness covering the backend data path, and the control-plane gauge registration records the otel.SetMeterProvider ordering it depends on. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): resolve the gauge's table names through gorm The dead-tuple gauge queried pg_stat_user_tables against a hardcoded list of three table names. Those three do not agree on where their name comes from: BackendNode and NodeModel take gorm's default pluralisation, while GalleryOperationRecord overrides TableName, and gallery_operations already had a constant of its own that the list duplicated. A literal list keeps compiling after any of that moves, and the query then matches nothing. The failure is silent and it points the wrong way: a dead-tuple ratio that matched no rows reports the same numbers as a cluster with no bloat, so the gauge would look healthiest exactly when it had stopped working. Ask gorm what each model is stored as instead, which follows a TableName override and the default pluralisation alike. A spec pins that the override really is consulted: naive pluralisation of the type would give gallery_operation_records, so the resolution cannot quietly stop asking the model. 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> |
||
|
Ettore Di GiacintoandClaude Opus 5
|
5555a3c569 |
fix(nodes): skip checksum sidecars when staging option dirs
stageDirectory and countStageableFiles already skip them, but stageOptionDir did not - and it is the path sherpa-onnx voices take for espeak-ng-data. The receiver writes "<file>.sha256" for every file it accepts, so staging the sidecars made it write sidecars for those in turn, one level deeper on every load. Observed on a live node: "<file>.sha256" repeated eleven times, 5077 junk files out of 7832 in the models dir, and still growing. Staging never finished, so vits-piper-it_IT-paola-sherpa stayed permanently "staging on node" and every realtime warmup needing that voice failed with the session then going silent. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0142UfUh8HWxdim5JZqf8Tr6 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
80e3240f2d |
feat(distributed): key scheduling rules by a model alias (#11771)
Node placement and replica rules could only name a model, so an operator who pinned "llama3" to the GPU tier had to rewrite the rule whenever a different model took over that job. An alias already gives a stable name for whichever model serves it, and a rule on that name makes it a deployment slot: repoint the alias and the placement follows. A rule keeps the name the operator chose. Reads resolve that name through the config loader to the model the rule governs, so the reconciler counts, schedules and trims replicas of the target, and the router finds an alias-keyed rule from the target it is already routing. An alias that resolves to nothing governs nothing loadable, so the reconciler skips it and the write paths refuse it. A replica is shared by every name that resolves to it, so only one rule can decide where it runs. The REST and MCP write paths reject a rule whose target another rule already governs. A pair that arrives some other way, such as a seed file or an alias repointed onto a model that already has a rule, resolves in favour of the rule named after the model itself and then the oldest, and the rest are listed as shadowed. The eviction guard is the exception: it matches rules to replicas in raw SQL inside a locking transaction and cannot resolve an alias. It reads a stored target that the reconciler refreshes each tick, and falls back to the rule's own name when that target is empty. Assisted-by: Claude:claude-opus-5 golangci-lint eslint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
29899cd1e0 |
fix(ui): size model fit against the cluster and move node labels into the selector (#11765)
* fix(ui): move node labels into the scheduling selector field The scheduling page kept a node-label browser open above the rules whether or not anyone was writing one, while the field that actually needs labels, the rule's node selector, was two bare text inputs with no hint of what the cluster reports. The browser is gone. The selector's key input now completes against the label keys the cluster uses, and the value input offers only the values that key takes. The roster already loads for the page, so the suggestions cost no request, and a roster that fails to load costs the admin the hints and nothing else. Suggestions stay suggestions: a key no node reports yet still commits as typed, which is how an admin writes a rule before labelling the nodes for it. Assisted-by: Claude:claude-opus-5 golangci-lint eslint playwright Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): size model fit against the cluster, not the frontend The models page asked the frontend how much memory a model may occupy. In distributed mode the frontend is usually a GPU-less pod while every model runs on a worker, so a fleet of GPU nodes was told it could only run the smallest CPU build. The variant picker's fits flag and its auto-selection came from the same place, as did the hardware recommendations. The registry now reports the largest single healthy backend node. The largest node, not the fleet total: a model loads into one node, so four 16GB workers are not a home for a 40GB model. An operator-set VRAM budget caps a node's contribution, because the scheduler refuses a load above that ceiling anyway, and a GPU node beats a CPU node holding more system RAM. GET /api/resources and GET /api/models carry this as an additional cluster object. Their aggregate and ram fields keep reporting the frontend's own hardware, which is what the resource monitor shows. Variant selection judges backends against the union of the capabilities present in the cluster, the way backend discovery already did. Every path degrades to the local host: no cluster object in single-node mode, and none when the registry cannot be read, so a hiccup narrows the answer back to single-node behaviour rather than marking the whole catalog too large. The verdicts now name the node they belong to, since a model fits somewhere or nowhere. Assisted-by: Claude:claude-opus-5 golangci-lint eslint playwright 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> |
||
|
Ettore Di Giacinto
|
f7ded96b1e |
fix(distributed): probe liveness on a subject every worker answers
The scheduler's liveness probe asks a worker a question over NATS and reads "no responders" as proof the worker is gone. That is only sound when every worker in the fleet subscribes to the subject asked. It asked models.running, which arrived in 4.6. A 4.5 worker is alive and serving, answers backend.list, and never subscribes to models.running, so the probe condemned it on every scheduling attempt and marked it unhealthy. A model pinned to such a node by its selector could then never be placed at all: on this cluster an embedding model pinned to the one Apple node was unschedulable for exactly this reason, while that node's log showed it handling backend.list throughout. Ask backend.list, which has been in the worker protocol far longer, and treat a worker that answers anything as alive. Only a node that reports no responders on every subject is absent, so adding a newer subject here can never condemn an older worker. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
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] |
||
|
Ettore Di Giacinto
|
2c68fa1eb6 |
fix(distributed): keep eviction inside the model's node selector
When no node the selector allows has a free slot, scheduling falls back to evicting the least-recently-used idle model. That eviction searched every healthy node, so it freed a slot on a node the selector forbids and the model was then placed there: pinned to one class of hardware and running on another. An unrelated model pays for it. On this cluster an embedding model pinned to Apple hardware could not reach its only matching node, so each attempt evicted a large language model from an Nvidia node, failed to start there anyway, and left the evicted model to reload. Repeated, that reads as one replica bouncing between nodes. Eviction is now restricted to the candidate set the selector produced. With no selector the candidate set is nil and eviction stays global. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
Ettore Di Giacinto
|
38ba3fec63 |
fix(distributed): stop reclaiming healthy reconciler-driven loads
The abandoned-load sweeper treated a replica row with no load job as abandoned. Only the request path creates load jobs; the reconciler's own scale-up loads a replica without one. So any scale-up that ran past the five-minute grace period was deleted mid-transfer, which for a multi-gigabyte checkpoint is every time. The replica never finished anywhere, and the reconciler kept re-placing it, so it looked like one replica hopping between nodes instead of a model reaching its replica count. A row with no job is now reclaimed only once its node stops being healthy, which is the case the sweeper was written for: a worker that dropped out mid-transfer. A job that failed or stopped heartbeating still proves abandonment on its own. Every uncertain case leaves the slot held. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
Ettore Di Giacinto
|
bebd812e7d |
fix(distributed): stop flapping agent nodes on backend listing
Only backend workers subscribe to backend.list. ListBackends asked every node that was not pending, offline or draining, so an agent worker could only answer "no responders", which the error handling reads as a node that has gone away. Every poll of the backends view therefore marked each agent node unhealthy, and its next heartbeat marked it healthy again. While unhealthy the node is not schedulable, so this also cost agent capacity for as long as each flap lasted. Skip non-backend workers, as the backend-op fan-out already does for the same reason. A backend worker that does not answer is still marked unhealthy: that one really is gone. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
Ettore Di Giacinto
|
e6269e3cdd |
fix(distributed): reclaim replica slots held by abandoned loads
A replica row in staging or loading holds its slot, because slot allocation counts every state except unloading. Nothing ever reclaimed such a row: every reconciler pass and the router's eviction query filter state = "loaded", and the per-model probe skips rows without an address, which is exactly what a row that never finished loading has. So a worker that dropped out mid-transfer left a row that pinned the only replica slot for that model on that node. Scheduling then found no free slot and eviction found nothing it was allowed to evict, and the request failed with "no replica slot on <node> and eviction failed: all models busy". The state persisted until an operator intervened. The reconciler now reclaims a row stuck before serving when no load job is driving it. Ownership is decided by the job's LastProgress heartbeat, not by elapsed time: staging a large checkpoint legitimately runs for a long while without touching the replica row, so a deadline would either be a model-size cliff or reclaim a healthy transfer. That heartbeat is the same signal job takeover already trusts. Any error reading the job leaves the slot held, because holding one for another pass costs a scheduling opportunity while a wrong reclaim restarts a multi-gigabyte transfer. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
Ettore Di Giacinto
|
c541dbeef4 |
fix(distributed): check a node answers before scheduling onto it
A node's status comes from its HTTP heartbeat. Backend installs travel over NATS. The two are independent, so a worker that dies stops answering on the bus at once but stays healthy in the database until its heartbeat ages out. Inside that window the scheduler picked a node it could not reach, and the request failed with "no responders available" rather than moving to a node that was up. The scheduler now probes the node it selected and, when nothing answers, marks it unhealthy and selects again. The demotion is what makes the retry terminate: the next selection reads only healthy nodes. It also tells the other frontends what this one learned, so the cluster does not rediscover a dead worker one failed request at a time. Only nats.ErrNoResponders counts as absent. A worker that answers slowly stays eligible, because dropping it would cost capacity that is really there. The probe reuses the models.running subject: a new subject would go unanswered by workers that have not been upgraded, and every one of them would then look dead. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
Ettore Di Giacinto
|
4bad644498 |
fix(distributed): name both revisions in the stale error
"stale model config revision" reported only that two hashes differed. It named neither, so an operator could not tell an edited configuration from a revision that is not reproducible for one unchanged file, and the failing value appears in no table. The error now carries the revision the request brought and the one the controller holds. It still wraps ErrStaleModelConfigRevision, so callers that classify the error keep working. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
||
|
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> |
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
a0252ad6a1 |
fix(distributed): keep staging operations stable (#11663)
* 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 * fix(distributed): merge durable staging operations Use active model load jobs as the durable operations baseline and overlay replica-local staging progress without duplication. Preserve tracker-only operations when the registry cannot be read. Assisted-by: Codex:gpt-5 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
2383726d6d |
Revert "chore(tests): Avoid network, sleep and more during tests" (#11601)
Revert "chore(tests): Avoid network, sleep and more during tests (#11050)"
This reverts commit
|
||
|
Richard Palethorpeandlocalai-org-maint-bot
|
cb3bf7af3f |
chore(tests): Avoid network, sleep and more during tests (#11050)
* test: make coverage failures observable Keep per-root logs, reject concurrent coverage runs, and avoid relying on /bin/sleep in the worker timeout test. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: parallelize coverage without remote fixtures Assisted-by: Codex:gpt-5 [apply_patch] [exec_command] Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: add offline resource infrastructure Introduce versioned resource manifests, a checksum-verified CAS preparer, offline test wrappers, and a guarded network transport. Replace live Hugging Face, GitHub, and OCI cases with deterministic fixtures and inject fixture metadata into importer discovery. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: enforce offline resource replay Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: harden offline resource refresh Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: expose slow coverage waits Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: eliminate avoidable wall-clock waits Inject a clock into Hugging Face retry handling, reuse a process-scoped PostgreSQL container with per-spec schemas in the nodes suite, and poll local import jobs promptly. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: remove repeated fixture startup waits Share PostgreSQL fixtures across parallel endpoint and agent suite workers, and make the worker Free deadline injectable so the wedged-backend test does not spend five seconds on wall-clock time. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: fix offline resource CI portability Normalize Docker archive metadata before content addressing, derive archive checksums during explicit refreshes, make network lint portable to macOS, and prepare distributed images before running their offline suite. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * ci: cache Go modules before offline tests Warm the complete module graph before the Linux and macOS test jobs enter offline replay mode, so tool dependencies such as Ginkgo are not fetched through the guarded proxy. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: drop the static network lint in favour of real isolation The offline test suite already prevents tests from reaching the network twice over: run-test-linux-offline.sh puts the test process in a cgroup and REJECTs egress outside the private ranges, and HardenedTransport installs testnetwork.LocalGuard to refuse dials that resolve to a public address. Both fail the test with a precise error at the moment of the dial. test-network-lint.sh added neither. Its diff stage defaulted to a HEAD base, so on a clean checkout it compared the tree against itself and inspected nothing; the branch's own commits were never examined. It only produced output when an earlier job step dirtied the tree, and then it matched a bare https?:// against whatever changed. make react-ui runs npm install rather than npm ci, so CI rewrote core/http/react-ui/package-lock.json and the lint reported an npm registry URL as forbidden test network access: + "resolved": "https://registry.npmjs.org/hono/-/hono-4.12.25.tgz", Its fingerprint stage was self-defeating in a quieter way: hashing the whole tree's network-mechanism inventory meant every rebase onto a master that touched any _test.go needed a manual baseline bump, so the check mostly caught its own staleness. Remove the script, its make target and the two prerequisite edges, along with the test-network: fixture markers that existed only to suppress it. The isolation itself is untouched. Assisted-by: Claude:claude-opus-5 [go vet] Signed-off-by: Richard Palethorpe <io@richiejp.com> * ci: keep hidden files in the offline test bundle artifact Cherry-picked from 15a37b0ac on the remote branch. The offline bundle lives under .cache/, which actions/upload-artifact skips by default, so the Linux job packed an artifact missing the very file the next step restores. The other half of 15a37b0ac moved test-network-lint out of the `test` and `test-coverage` prerequisite lists into a recipe line, so parallel make could not fingerprint the tree while generated fixtures were still changing. That is dropped: the preceding commit removes the lint entirely, and the race it worked around is one more reason a whole-tree fingerprint was the wrong mechanism. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * refactor: share bounded exponential backoff Use overflow-safe saturating arithmetic for retry delays across model import polling, downloads, registration, node operations, and model loading. Keep model import status checks responsive initially while capping their interval at 500ms. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * ci: mirror Jetson Python wheels Keep the CUDA aarch64 wheel subset in GHCR and serve it as a local PEP 503 index during L4T backend builds, preserving last-known-good packages through upstream outages. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * docs(agents): index the Jetson wheels mirror Mention the GHCR-hosted L4T wheel mirror in the CI caching guide summary so maintainers can find its outage and cache documentation. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * ci: add defensive build network proxy Record build destinations and byte counts, retry observable idempotent HTTP downloads, and isolate explorer database tests that race under coverage. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(kokoros): implement updated backend trait Return unimplemented for image upscaling, matching the backend's other unsupported modalities after the protobuf API update. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): clear recovered proxy errors Do not mark a request failed when a later safe retry succeeds. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * ci: require HTTPS build interception Inject a short-lived proxy CA into BuildKit and Dockerfile RUN steps, reject plain HTTP and opaque tunnels, and retain method/status/byte telemetry for verified HTTPS traffic. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): preserve system trust in unproxied builds Mount the generated interception CA at a dedicated secret path and add it to the trust bundle only in proxy-aware dependency stages. This prevents optional secret mounts from masking the system CA bundle in ordinary backend test builds. Install the requested Go toolchain before starting the proxy and satisfy cleanup error checks found by CI lint. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): persist build proxy trust Install the generated proxy CA through the system-managed local certificate directory so ca-certificates upgrades retain it. Avoid turning canceled matrix jobs into proxy cleanup failures. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): trust proxy in nested build scripts Install the build proxy CA before nested source fetches, route the DS4 package setup through the HTTPS mirror helper, and avoid repeated OCI setup in gallery behavior tests. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): use HTTPS apt sources for Bonsai Rewrite ARM64 package sources before installing GCC and check gallery fixture cleanup errors so the optimized tests satisfy errcheck. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(privacy-filter): trust build proxy CA Install the mounted build proxy certificate before privacy-filter's make target fetches its HTTPS sources, for both source and prebuilt builder paths.\n\nAssisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * test: fail on hidden offline egress Count cgroup-scoped firewall rejects and fail the offline test harness with bounded aggregate diagnostics. Inject the gen-audio GGUF probe so fixture-backed importer tests do not attempt real network access. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): preserve system CA trust Build a combined runner certificate bundle instead of replacing public roots with the generated proxy CA. Centralize additive container installation in the shared proxy CA helper. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
||
|
|
88edd7fc7f |
fix(distributed): run cold model loads as durable jobs instead of holding the advisory lock (#11514)
* fix(advisorylock): set statement_timeout alongside lock_timeout
WithLockCtx already overrides a deployment-wide lock_timeout on its
dedicated connection so a blocking pg_advisory_lock() waits its turn
instead of failing with 55P03. statement_timeout aborts that exact same
statement independently, with SQLSTATE 57014, and was not overridden.
Production roles commonly carry statement_timeout=60s. Any guarded
section longer than that (a cold model load stages for tens of minutes)
therefore killed every concurrent waiter:
advisorylock: acquiring lock 9003261067483446873: ERROR: canceling
statement due to statement timeout (SQLSTATE 57014)
Derive it from the same context budget as lock_timeout, with a matching
RESET so the pooled connection is returned clean.
Assisted-by: Claude Opus 5 [claude-code]
* feat(distributed): add ModelLoadJob, the durable cold-load record
A cold load in distributed mode is a long-running background job, but it
was modelled as a synchronous side effect of an inference request: the
whole of it (backend install, multi-GB staging, checkpoint load) ran
inside the per-model advisory lock. Loading a 35.7 GB GGUF held that lock
for ~20 minutes, so every concurrent request for the same model blocked
on pg_advisory_lock and died at the role's 60s statement_timeout.
Introduce the row that lets the lock shrink to a decision. Exactly one
ModelLoadJob may be active per tracking key; that uniqueness — not the
lifetime of a lock — is what de-duplicates concurrent loaders across
replicas. ClaimLoadJob does its read-then-write under the advisory lock
and nothing else: no network, file or gRPC I/O inside the guarded
section, so a claim costs milliseconds no matter how long the resulting
load takes.
LastProgress is a heartbeat rather than a byte counter. A checkpoint load
legitimately moves zero bytes for many minutes, so a reaper keyed on byte
movement would reclaim a healthy job mid-load; byte progress stays the
concern of load_deadline.go. A job whose heartbeat stops for longer than
the orphan window is reclaimable, so a replica killed mid-load cannot
wedge a model permanently.
Failed jobs keep their row for a short grace so an immediately-following
request reports the real cause instead of silently starting a fresh load
of a model that just failed.
No caller yet — the router moves onto this in the next commit.
Assisted-by: Claude Opus 5 [claude-code]
* refactor(distributed): run cold loads as jobs, outside the advisory lock
Route wrapped the entire cold load — node selection, backend install,
multi-GB staging and the remote LoadModel — in the per-model advisory
lock. The lock's job is to de-duplicate concurrent loaders, a decision
that takes milliseconds; holding it for the tens of minutes the resulting
work takes is what turned a dedup mechanism into a cluster-wide outage
for that model.
Split it into a claim and a run. The claim is the only thing left inside
the lock. The run is a background job owned by the claiming replica and
bounded by the same progress-extended deadline as before; every other
request for that model — local or on another replica — attaches as a
waiter and is served the moment the model is ready, with no duplicate
load and no lock contention.
Waiters share one broadcast rather than an ordered queue: they all want
the identical outcome, so ordering them would add fairness machinery that
changes no result. The local channel wakes same-replica waiters instantly
and a 2s DB poll is the authority, because a waiter on another replica
has no channel to close. On wake a waiter re-runs the warm path rather
than trusting the signal — the model may have been evicted in between.
A waiter whose client disconnects returns immediately and the job keeps
running; it belongs to the job record, not to the request. A failure is
recorded on the row so every waiter reports the real cause, and the row
survives briefly so the next request does not read "no job" as "not
loading" and start a duplicate load of a model that just failed.
The runner heartbeats the row on a fixed interval whether or not bytes
are moving, which is what keeps a legitimately silent checkpoint load
from being reclaimed as an orphan. Phase (installing/staging/loading) and
placement ride to the heartbeat on the context, the same seam
load_deadline.go already uses, so single-host paths are untouched.
Non-distributed mode (no DB) keeps the inline load exactly as it was.
Assisted-by: Claude Opus 5 [claude-code]
* feat(distributed): bound the wait for a loading model and answer with progress
A request whose model is cold-loading now attaches to the running job and
is served the moment the model is ready. That wait has to be bounded: a
held HTTP request cannot survive real infrastructure, and an ingress or LB
idle timeout kills a twenty-minute request regardless of what LocalAI
does.
New LOCALAI_MODEL_LOAD_WAIT (default 60s) bounds the CALLER, never the
load — the job keeps running either way. On expiry the request gets 503
with Retry-After and a structured body naming the model, the node, the
phase, byte progress and an ETA. The `error` envelope keeps OpenAI
clients working; `loading` is additive so they ignore it.
The ETA comes from the job's own observed rate and is omitted rather than
guessed until enough bytes have moved for that rate to mean anything: a
confidently wrong ETA on a twenty-minute wait is worse than none.
Retry-After is that ETA when known, clamped to [5s, 300s], and the wait
budget otherwise.
LOCALAI_MODEL_LOAD_WAIT=0 waits unbounded, for deployments with no proxy
in front. Zero in the config struct still means "unset, use the default",
so the CLI records the operator's zero as ModelLoadWaitUnbounded rather
than losing the distinction.
The distributed branch of ModelLoader.loadModel wrapped the router's
error with %s, which flattened it to a string. Use %w: the typed error is
what the HTTP layer keys the 503 off.
Assisted-by: Claude Opus 5 [claude-code]
* feat(api): add GET /api/models/{id}/load-status
A client that receives 503 while a model stages onto a worker needs
somewhere to poll. This returns the same `loading` object the 503 carries
— phase, node, byte progress and ETA — or 404 when no load is running.
Read-only and observability-shaped, so it is deliberately neither
admin-gated nor feature-gated: it explains a 503 the caller just
received, and hiding that behind a per-modality feature would make the
explanation for a failed image request depend on chat permissions. It
also gets no MCP tool, since there is nothing here an admin would manage
conversationally.
Registered on the surfaces from .agents/api-endpoints-and-auth.md: the
swagger block (existing `models` tag, so /api/instructions needs no new
area), the endpoint discovery maps in RegisterLocalAIRoutes, regenerated
swagger, and the distributed-mode docs page. No FLAG_* usecase is
involved, so capabilities.js is unchanged.
Assisted-by: Claude Opus 5 [claude-code]
* feat(ui): show cold-load progress in Chat and retry when the model is ready
A chat request for a model that is still staging onto a worker now gets a
503 carrying live progress instead of an error. Render it: the composer
shows the phase (installing / staging / loading), the node, the percent
and the ETA, then polls load-status and re-sends the request the moment
the model is ready.
Reuses the staging progress idiom the page already had rather than
inventing a second one — the two sources are folded into one
loadProgress, with the load job winning because it is authoritative
across frontend replicas and knows the phase, where the staging operation
only knows about a byte transfer this replica happens to be performing.
Waiting is bounded (three send attempts, ~30 min of polling each), so a
load that never finishes still surfaces as an error rather than as a
spinner nobody questions. An aborted generation stops the polling too.
Assisted-by: Claude Opus 5 [claude-code]
* fix(distributed): check warm-path cleanup errors
The router moved legacy cleanup calls onto newly linted lines. Report
cleanup failures while preserving the fallback to a cold load.
Assisted-by: Codex:gpt-5 [golangci-lint]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
|
||
|
Peteandlocalai-org-maint-bot
|
8a68f3571c |
feat(api): add POST /v1/images/upscale endpoint (#10227)
* feat(api): add POST /v1/images/upscale endpoint Add a new image upscaling endpoint that accepts a source image and returns an upscaled version. Supports selectable upscaler models (e.g. realesrgan) and a configurable scale factor (2x or 4x). - backend.proto: add UpscaleImage RPC and UpscaleImageRequest message - pkg/grpc: implement UpscaleImage in Backend interface, client, server and embed shim - core/backend/upscale.go: new backend helper (mirrors ImageGeneration) - core/http/endpoints/openai/upscale.go: new multipart/form-data handler - core/http/routes/openai.go: register POST /v1/images/upscale - core/http/auth/features.go: gate upscale routes under FeatureImages - backend/python/diffusers/backend.py: implement UpscaleImage — uses diffusers upscale pipeline when loaded, falls back to Lanczos resize * fix(grpc): add UpscaleImage stub to Base backend All Go backends embedding Base now satisfy the AIModel interface without needing to implement UpscaleImage explicitly. * fix(images): complete upscale endpoint integration Store generated upscales under the served images directory, validate scale factors, document and advertise the endpoint, and add a functional Stable Diffusion x4 gallery model. Assisted-by: Codex:gpt-5 --------- Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
||
|
Adiraandlocalai-org-maint-bot
|
ef724a3c9d |
feat(api): add /v1/detokenize endpoint (#9620)
* feat(api): add /v1/detokenize endpoint Closes #1649. Mirror of the existing /v1/tokenize path, requested by @benniekiss in the issue thread for "complete API workflow" use cases that need to turn token IDs back into text without local processing. - Add Detokenize gRPC RPC with DetokenizeRequest{tokens} / DetokenizeResponse{content} messages. - Implement in the llama.cpp backend using common_token_to_piece, the same primitive TokenizeString already uses internally. - Other backends inherit the default Unimplemented from base.Base, in line with how Detect, Rerank, etc. are gated per-backend. - Wire up the Go gRPC interface, server, client, and in-process embed wrapper alongside their TokenizeString counterparts. - Add the schema types, ModelDetokenize wrapper, HTTP handler, route registration, RouteFeatureRegistry entry (gated by FeatureTokenize so no new feature flag is needed), and the discovery map entry under ai_functions. - Regenerated swagger reflects the new endpoint and types. - Update authentication.md to list /v1/detokenize alongside /v1/tokenize. Assisted-by: Claude:claude-opus-4-7 Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> * test(e2e): add mock backend tests for /v1/detokenize Add Detokenize to the mock gRPC backend and wire up two e2e tests in the MockBackend suite: one that posts known token IDs and asserts a non-empty content response, and a round-trip that tokenizes first then detokenizes the returned IDs. Addresses reviewer feedback on #9620. Assisted-by: Claude:claude-sonnet-4-6 Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> * fix(kokoros): implement detokenize in the Rust backend service The Detokenize RPC added in this PR grows the tonic-generated Backend trait. Unlike the other languages there is nothing to inherit a default from — Rust trait impls must list every method — so backend/rust/kokoros failed to compile: error[E0046]: not all trait items implemented, missing: `detokenize` --> src/service.rs:72:1 72 | impl Backend for KokorosService { Go backends pick up the Unimplemented default from base.Base, and the generated C++/Python servicer bases default to UNIMPLEMENTED, which is why the Rust backend was the only one that broke. kokoros is the sole Rust crate in the tree, so this is the full extent of the fallout. Return Status::unimplemented("Not supported"), matching how this same file already gates tokenize_string and ~20 other unsupported RPCs. Fixes the tests-kokoros and backend-jobs-singlearch-4 (-cpu-kokoros) failures on the previous head. Assisted-by: Claude:claude-opus-5 cargo Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> --------- Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com> |
||
|
Richard Palethorpeandlocalai-org-maint-bot
|
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> |
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
878a0d00a1 |
fix(distributed): reaper reaps live backends, ghost model stubs, in_flight leak, sidecar staging runaway (#11142)
* fix(distributed): stop the probe reaper from orphaning busy backends
The reconciler's liveness probe is a 1s gRPC HealthCheck, and a single
failed probe deleted the model's node_models row. A backend that is
merely busy cannot answer it: single-threaded Python backends (video and
avatar generation) block for minutes inside one request, so the reaper
was deleting registry rows for backends that were alive and mid-request.
The model then vanished from the nodes page while it was still
generating, and because the row was gone the in-flight decrement had
nothing to decrement ("DecrementInFlight: no matching row or already
zero"). Every subsequent request re-routed and re-staged the full model
from scratch.
Two guards:
- Replicas with in-flight requests are excluded in SQL. A row that is
actively serving is proof of life, and the running request is
exactly what stops the backend from answering the probe.
- Idle replicas must miss three CONSECUTIVE probes before removal, so
a transient blip cannot orphan a live replica. A successful probe
resets the streak.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): drop the local model stub when its last replica goes
In distributed mode every routed model leaves an in-process stub in the
frontend's ModelLoader, and DistributedModelStore.Range reports local
stubs UNION the registry rows. Every registry removal path deletes only
the DB row, so the stub outlived the replica and the model was reported
as loaded forever.
That is the "loaded on the home page, absent from every node" ghost:
/system reads the union and still sees the stub, while /api/nodes/models
reads the registry and correctly sees nothing. It never self-healed,
and both frontend replicas showed it independently.
The replica-removed chokepoint could not fix this as it stood, because
it held a SINGLE hook that the prefix cache already owned, and it was
registered only when the prefix cache was enabled. Registering a second
listener would have silently displaced the first.
- Turn replicaRemovedHook into a list (AddReplicaRemovedHook), so
independent subsystems can each register without displacing others.
- Add NewLocalStubInvalidator, which drops the local stub once no
healthy replica of the model remains anywhere in the cluster, and
wire it unconditionally in startup.
The stub is kept while another node still serves the model: the
frontend is right to consider it loaded, and each request re-routes
through SmartRouter to pick a live replica anyway.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): stop staging checksum sidecars back to workers
The file transfer server writes a "<file>.sha256" sidecar next to every
file it accepts. The sender walked the model directory with no filter,
so it staged those sidecars too, and the receiver duly wrote a sidecar
for each sidecar. Every staging pass multiplied the tree:
config.json -> config.json.sha256 -> config.json.sha256.sha256 -> ...
One LongCat snapshot had grown to 498 files, 466 of them chained, up to
29 levels deep, and the staged file count climbed on every pass. This
inflates each transfer and grows disk without bound on both ends.
Skip hash sidecars in stageDirectory, and mirror the skip in
countStageableFiles so the progress bar still reaches 100%. The check is
"a sidecar sitting next to a real file" rather than a blanket suffix
ban, so a model that genuinely ships a .sha256 payload with no
corresponding base file is still transferred.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): classify the liveness probe instead of gating on in_flight
The previous commit excluded replicas with in-flight requests from the probe
reaper. That was the wrong guard, and could invert the bug it fixed.
in_flight has no decrement guarantee: track() balances its increment with a
defer, but a frontend killed mid-request never runs it, and the load-time
reservation is released only when the first inference completes. Nothing
resets a leaked counter. Gating the reaper on it therefore meant a leaked
counter would shield a genuinely dead replica from ever being reaped.
Nor was patience alone a fix: three misses at the default interval is ~90s of
silence, while the generation that triggered this blocks for 15+ minutes.
The real conflation was in the probe itself. A gRPC HealthCheck against the
backend's serving port measures "is it idle enough to answer", not "does the
process exist", and probeLoadedModels discarded the error that tells them
apart. Because the gRPC client is lazy, the status code is decisive:
- DeadlineExceeded: transport fine, nothing serviced the RPC. Busy.
- Unavailable: nothing is listening. Gone.
ModelProber now returns a ProbeOutcome, and only ProbeUnreachable counts
toward the reap threshold. ProbeBusy clears the streak: it is evidence of
life. A blackholed network reads as busy too, deliberately, since whole-node
failure is the health monitor's job.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* feat(distributed): reconcile replicas against worker-reported processes
Probing a backend's own serving port cannot distinguish "busy" from "gone"
without inferring it from an error code. The worker can answer directly: it
spawned the process, holds the handle, and its reply is not blocked by
whatever that backend is doing.
Adds a models.running request-reply subject. The worker answers out of its
in-memory process table, reporting each live process as (modelID,
replicaIndex, address) — the supervisor's process keys are `modelID#replica`,
which is isomorphic to a NodeModel row, so the reconciler can diff the two
directly.
reconcileNodeProcesses runs before the port probe and reaps rows for models
the worker is not running. Models the worker vouches for get updated_at
bumped, which takes them out of the port prober's stale set entirely: that is
what keeps a backend deep in a long generation away from the probe in the
first place, rather than relying on classifying its silence after the fact.
A worker that does not answer is skipped, not assumed empty. A messaging
failure says nothing about the processes, and assuming the worst would delete
a node's rows on a transient NATS blip; the port probe stays as the fallback
for those nodes. Rows younger than probeStaleAfter are ignored so a freshly
created row is never judged against a process table that has not caught up.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): stop in_flight leaking and pin replicas against eviction
A leaked in_flight counter is not cosmetic. FindLRUModel,
FindGlobalLRUModelWithZeroInFlight and the router's eviction query all require
in_flight = 0, so a replica whose counter never came back is pinned and its
VRAM is unreclaimable for the lifetime of the process.
Two halves.
The source: routing reserves in_flight = 1 at load time so a freshly loaded
replica is not evicted out from under the request that caused the load. That
reservation was released ONLY by the first inference completing, so a route
torn down before any inference ran (client disconnect, handler error, failure
between load and the backend call) stranded it. newRouteResult now wires the
reservation to a sync.Once fired by whichever comes first, the first inference
or route teardown, and replaces three copies of the old wiring.
The backstop: a sweeper for counters leaked by paths that cannot run a defer
at all, such as a frontend killed mid-request.
Identifying a leak by elapsed time alone is unsafe. IncrementInFlight stamps
last_used at request START and nothing moves it while the request runs, so a
long generation is indistinguishable from a leak by age, and resetting there
would expose a serving model to eviction. The probe supplies the missing bit:
a backend that answers a health check promptly is not inside a request,
because that is precisely what a busy one cannot do. Requiring the row to also
be idle for 30 minutes covers backends that serve in parallel and can answer
while working, since those keep last_used fresh through each new increment.
Two existing tests asserted the old behaviour ("No decrement on Release").
That assertion was the leak, so both now pin the release instead.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
|
||
|
|
5d57c08c6e |
feat(distributed): cache staged-artifact hashes and publish the model load lifecycle (#11121)
feat(distributed): cache staged-artifact hashes and publish load lifecycle Every load request re-hashed every staged artifact on the controller (probeExisting and the upload path both re-read the full file), which for a large multi-file model on NAS-backed storage is minutes of pure re-reading per request even when nothing changed - observed as ~9 minutes of "Upload skipped (file already exists with matching hash)" before every avatar generation. Cache the local hash in the same .sha256 sidecar the worker-side transfer server already maintains, invalidated whenever the sidecar is older than the file. The whole staging+loading phase was also invisible: the NodeModel row was only written after LoadModel succeeded, so /api/nodes and the UI showed nothing while a cold load spent 10+ minutes staging - indistinguishable from nothing happening. Publish the lifecycle instead: "staging" as soon as the node is chosen, "loading" when the checkpoint load starts, and the existing "loaded" on success, with the row removed on any failure so a dead load does not leave a phantom replica. The early row also reserves the replica slot against concurrent schedulers. The nodes view already renders non-loaded states on model chips; style "staging" like "loading". Audited every state-filtered registry/router query: eviction, routing, reconciler and idle-model queries all filter state='loaded' explicitly, so the new transitional rows are visible to observability surfaces but inert to scheduling decisions (except slot occupancy, intentionally). Co-authored-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Claude Fable 5 <noreply@anthropic.com> |
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
6584db992f |
fix(nodes): never schedule a model onto a node that cannot store it (#11054)
* fix(nodes): never schedule a model onto a node that cannot store it
A worker whose models filesystem was 100% full kept advertising
`status: healthy`, stayed a scheduling candidate, was picked to host a
70 GB video model, accepted the staging request, transferred ~17 GB and
only then failed:
staging .../whisper-large-v3/model.fp32-00001-of-00002.safetensors:
upload to node b7bacbf4-... failed with status 500:
writing file: /models/longcat-video-avatar-1.5/...: no space left on device
The node was at 937G/937G/0-avail. Total elapsed before the truth
surfaced: 16 minutes, for a decision that could never have succeeded.
The worker health signal only ever proved liveness. `/readyz`
(WorkerReadiness/NATSReadiness) checks the NATS link; `status: healthy`
in the registry is driven by heartbeat recency. Node capacity carried
VRAM and RAM but no disk figure at all, and the router compared model
size against VRAM only — nothing anywhere looked at free space on the
filesystem that staging actually writes to.
Report it, then use it:
- Workers now measure the filesystem backing their MODELS directory
(not `/` -- staged weights land in the models path, and that mount is
very often separate) and report `total_disk`/`available_disk` on
registration and on every heartbeat. Free disk moves faster than VRAM
under staging traffic, so the per-heartbeat refresh matters.
- The SmartRouter drops nodes that cannot store the model before it
picks one. The requirement comes from `modelPayloadBytes` -- the same
local paths `stageModelFiles` uploads, already computed for the
size-derived load budget -- plus a 5% / 1 GiB margin, rather than a
fixed percentage of the node's disk. A percentage threshold would take
a small-but-usable node out of rotation for models it could hold, and
on a homogeneous cluster would strand every node at once.
- When no node fits, scheduling fails immediately with an error naming
the requirement and each node's free space, instead of picking one and
discovering it mid-transfer.
Two deliberate non-changes. Low disk does not mark a node `unhealthy`:
the check is per model, so a node too small for one model stays a valid
target for smaller ones. And `total_disk == 0` means "does not report
disk" (pre-upgrade worker, or a failed stat), not "full" -- such nodes
pass through untouched so a rolling upgrade never empties the candidate
pool. A genuinely full node is distinguishable: non-zero total, zero
available. Registry read failures are logged and scheduling continues
unfiltered; a database hiccup must not wedge a cluster.
Free space is surfaced on the node detail page next to VRAM, since the
incident's signature was a node that looked entirely healthy.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
* feat(nodes): make the disk-headroom check operator-controllable
The admission check added in the previous commit had no off switch. A
scheduler-side veto with no escape hatch is a liability: our size
estimate can be wrong (deduplicating or compressing filesystems, a
backend that fetches its own weights rather than loading the staged
copy), and an operator who hits that has no way out but a downgrade.
Add one knob with two surfaces that share a single source of truth:
- `--distributed-disk-headroom-check` / `LOCALAI_DISTRIBUTED_DISK_HEADROOM_CHECK`
(default true), following the `--distributed-prefix-cache` pattern for
a default-on distributed feature.
- `distributed_disk_headroom_check` in the runtime-settings registry, so
it can be flipped without a restart from `POST /api/settings` and from
Settings -> Distributed in the WebUI.
Both write `DistributedConfig.DiskHeadroomDisabled`, and the SmartRouter
reads that member LIVE on every scheduling decision through a closure
over the application config rather than a value snapshotted at
construction. Env/CLI sets the boot value, the runtime setting overrides
it live, last write wins, and there is exactly one member to read.
Snapshotting would have made the runtime toggle a no-op until restart.
Disabled means WARN, not SKIP. Selection goes back to ignoring free disk
-- byte for byte the pre-check behaviour -- but the check still runs, and
when it would have rejected every node it says so, naming the knob that
suppressed it. Going quiet when switched off would reproduce the exact
condition that made the original incident expensive: a cluster doing
something that could not work and saying nothing. Disabling is also
logged once at startup. Warning only on the total-rejection case keeps
it actionable rather than chatty on a heterogeneous cluster.
Also fixes a false positive in the check itself: shared-models mode
(LOCALAI_DISTRIBUTED_SHARED_MODELS) stages nothing at all -- every node
already mounts this models directory at this path -- so demanding the
full checkpoint size of free space per node would have rejected a
cluster that needs no new bytes. The check is skipped there entirely.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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>
|
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
01fca9c9b2 |
fix(distributed): scale the remote model-load deadline with checkpoint size (#11030)
The gRPC deadline for the remote LoadModel call was a fixed 5m. It starts
only after the backend install and file staging have completed, so it
covers the worker's checkpoint read and pipeline init alone - work whose
duration is proportional to the bytes on disk. A fixed value is therefore
a model-size cliff, not a timeout.
Measured in production: a 70 GB video checkpoint (longcat-video-avatar-1.5)
on an NVIDIA Jetson Thor worker failed reproducibly with
"rpc error: code = DeadlineExceeded" after 953.5s of wall clock. Backend
install plus staging consumed ~11m, then LoadModel got its 5m and expired.
The load never had a chance, and the operator saw only a generic
DeadlineExceeded with no hint that a config value was the cause.
Raising the constant does not fix this. It moves the cliff to the next
larger model - the cluster has to support 600 GB checkpoints - and it makes
a genuinely wedged SMALL model hang for the whole inflated duration before
anyone notices, which is a real regression in failure latency.
So derive the budget from the checkpoint size instead:
budget = 5m + 20s/GiB, capped at 6h
2 GiB -> 5m40s, 70 GiB -> 28m20s, 600 GiB -> 3h25m. The per-GiB rate is
deliberately pessimistic (~54 MB/s of weight read) because the errors are
not symmetric: too long costs only failure latency on a load that was going
to fail anyway, too short is a guaranteed false failure on a healthy load.
The size is measured from the frontend's local model files, over the same
path set stageModelFiles uploads. When those files are not present locally -
a backend handed a bare HuggingFace repo id fetches its own weights on the
worker - there is nothing to measure and the budget stays at today's 5m.
An explicit LOCALAI_NATS_MODEL_LOAD_TIMEOUT still wins outright, in both
directions: a shorter override is honoured, so an operator who wants fast
failure is not silently extended by the heuristic.
The cold-load hold needed widening to match. It extends on staging progress,
but LoadModel reports none, so once the last byte lands the hold expires a
stall window later and would cancel a load still well inside its own budget.
scheduleAndLoad now extends the hold by the load budget plus the staging
margin as it enters the load phase; ModelLoadCeilingFor stays the hold's
starting budget rather than its maximum.
Finally, a deadline that does expire now names the budget, the checkpoint
size it was derived from, and the knob that overrides it, instead of
surfacing a bare "context deadline exceeded".
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>
|
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
a4a181d2f7 |
fix(distributed): count staging verification as progress, not as a stall (#11026)
Testing the progress-based cold-load deadline on the live cluster surfaced a false positive. The stall window observed UPLOAD bytes only, but the staging path has a phase that does real work while moving zero upload bytes: the resumable-upload verify phase. When a shard is already present on the worker from an earlier attempt, the frontend HEADs it, hashes the local copy to confirm it matches, and skips the transfer. Staging a 70 GB model with 56 GB already staged: 17:27:34 INFO Upload skipped (file already exists with matching hash) ... 17:28:20 INFO Upload skipped (file already exists with matching hash) ... 17:29:07 INFO Upload skipped (file already exists with matching hash) ... ... six-plus consecutive minutes, no bytes uploaded at all ~45s per skipped ~4 GB shard. That is correct and desirable - it is what makes resume work - but it was indistinguishable from a stall. At 45s per shard it sits inside the 5m window, so the run in flight was fine; the problem is the 600 GB scale this machinery exists to enable, where one shard can plausibly hash for longer than the window. The guard would then fire during verification of a transfer that is working perfectly. Verified mechanism: probeExisting() HEADs the worker and then calls downloader.CalculateSHA(). The staging progress callback is only consulted inside doUpload(), which the skip path never reaches, so observeLoadProgress was called zero times for the whole verify phase. Verification exposed a second, worse bug in the same path: CalculateSHA consults no context at all. An expired cold load kept hashing to completion, compared the hashes, and returned success - reporting a file as staged on a dead load. The failure only surfaced on the NEXT file, whose HEAD died immediately. That is exactly the shape of the red test here, which fails on shard 3. Fix: hash in 1 MiB chunks via hashFileWithActivity(), ticking the cold-load deadline per chunk and checking ctx per chunk. A successful HEAD also counts, since a 200 with a content hash proves the worker is serving right now. Counting hash progress does not make a dead transfer look alive: hashing is bounded, terminating work proportional to file size, in probeExisting it runs only after a HEAD proved the worker was up, and the 24h absolute cap still bounds the whole hold. The alternative of simply widening the window was rejected - it would reintroduce the size cliff this work removes. 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> |
||
|
mudler's LocalAI [bot]andEttore Di Giacinto
|
b700a78ae4 |
fix(distributed): make the cold-load hold scale with progress, not wall-clock (#11019)
A 70 GB video checkpoint (longcat-video-avatar-1.5) could not be loaded on a
distributed cluster. The request failed with HTTP 500 after 1499.98s - exactly
the 25m00s cold-load ceiling - while staging was demonstrably healthy: 26 of 57
files and 39 GB transferred at a sustained ~26 MB/s, zero errors, no stalls. It
was not wedged, it was killed by a timer.
ModelLoadCeilingFor covers node selection, backend install, file staging and the
remote LoadModel. Install and load carry their own budgets; staging was covered
only by a FIXED 5-minute margin. But staging time is bytes over bandwidth, not a
constant: 70 GB at 26 MB/s needs ~45m against a 25m ceiling, so the failure is
deterministic for any sufficiently large model rather than a flake. Simply
raising the constant moves the cliff to the next model size - the deployment
target here is checkpoints of 600 GB and beyond.
The ceiling's real purpose is that "a wedged worker can never pin the lock
indefinitely". Progress, not elapsed time, is what distinguishes a wedged worker
from a large one. The hold is now a deadline that extends whenever the transfer
reports bytes and expires a 5-minute stall window after they stop:
- A large model transferring fine continues, for hours if needed.
- A worker that died mid-transfer still fails within the stall window.
Progress is observed at byte level on the transfer itself, via the existing
staging progress callback. Per-file completion would be too coarse - a single
600 GB shard would be indistinguishable from a stall for hours. The observation
point is back-pressured by the socket, so it reflects the network rather than
local disk reads. Observation is coarsened to one timer touch per stall/20 so
the per-read callback stays cheap.
The base budget (unchanged, and still derived from the install and load
timeouts) continues to cover the steps that report no progress, so
LOCALAI_NATS_MODEL_LOAD_TIMEOUT keeps working exactly as before. An absolute
cap of 24h bounds the hold even while progress keeps arriving, so a peer
trickling bytes forever cannot pin the advisory lock; 600 GB at the measured
26 MB/s is ~6.5h, so the cap sits far above any legitimate transfer.
Also fixes the incoherent layering the same error exposed: the resumable upload
carried a 1h retry budget nested inside the 25m ceiling, so the inner budget was
unreachable and the message still blamed it ("failed after 1 attempts within
1h0m0s budget") while the 25m parent was the actual killer. The upload now
adopts the caller's deadline when there is one, and applies its fixed budget
only when nothing above bounded it - which also stops a fixed 1h from
reintroducing the size cliff under the now-extendable parent.
This is the successor to #10968, where a hardcoded 5-minute LoadModel gRPC
timeout was replaced by this derived ceiling. Fixing the inner timeout exposed
the outer ceiling as the new binding constraint.
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>
|