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5effa4752789f2bbe4e17029ee00ff731d8afffa
122
Commits
| Author | SHA1 | Message | Date | |
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 Ettore Di Giacinto
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5effa47527 |
feat(distributed): make MCP execution and discovery a selection
mcp.tools.execute and mcp.discovery were the only NATS subjects that combined a queue group with a reply, and no carrier in this design provides both. They never needed one: a queue group is a way of choosing a subscriber, and choosing is a query. The frontend now lists the approved, non-draining agent nodes, asks the node_connections table in one joined statement which of those tunnels a live replica holds, prefers one this replica holds so the call skips the relay hop, and issues an ordinary control RPC on the path task 4 already mounted. A peer-held tunnel is reached through the relay. That is a choice a broker's hidden balancing could not make. The selection reads presence and nothing else. It is filtered only on node type and on the two statuses an operator controls, never on a health verdict written on another clock, because refusing a worker that is connected and answering is the same defect as picking one that is gone. An empty fleet answers ErrNoAgentWorker, which is deliberately neither ErrWorkerUnroutable nor anything cluster.IsWorkerAnswer accepts: nothing was asked of any worker, so no reap guard may act on it. A reply carrying an Error is the worker's own answer and is returned unchanged; it is never offered to a second worker, which would turn "this MCP server rejected your arguments" into "the fleet is broken" and could run a tool twice. A call that never reached a worker is retried against a different pick, at most three times, and whatever error is finally returned is returned unwrapped so its identity survives the loop. MCP prompts and resources now answer 501 in distributed mode instead of an empty 200. They are served only from sessions the frontend holds, and in distributed mode it holds none. That gap predates the removal of the bus and is not closed by it; this only stops it being silent. Agent workers keep every other subject, including nodes.<id>.backend.stop. Their minted JWT loses the two MCP subjects and keeps a non-empty allow list, because NATS reads an empty one as no restriction at all. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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8f71c08d94 |
fix(distributed): order LISTEN and UNLISTEN on one lock
Unsubscribe decided a channel had lost its last subscriber under one lock and issued the UNLISTEN after releasing it. A Subscribe on the same root could decide to LISTEN in that window, and the two reached the connection in the wrong order: the root ended up not listened with a live subscription on it. It does not heal, because the next Subscribe sees the registration already there and never re-LISTENs, so the whole root stays deaf on that replica until the connection drops. The decision and the statement it implies now happen under one lock, held across both, at both call sites. A second lock and not the registration lock: issuing waits on the listener goroutine, delivery takes the registration lock, and holding that across the wait deadlocks the carrier. The race is spec'd through a barrier seam rather than by racing goroutines. The natural window is microseconds wide, and a spec that waits for it to open passes by luck; the seam scripts the interleaving, so the spec decides in both directions. Resolving a spilled message moved off the listener. PostgreSQL keeps undelivered notifications in a shared, fixed-size queue, so a listener that stops draining it can block COMMIT for every publisher on the server, not only this one. The listener now only drains; one resolver goroutine reads the row back and dispatches, which also keeps a spilled message and an inline one on the same subject in the order they were published. Three wiring lines that could be deleted with the suite staying green: the sweeper's start is now pinned by a Config interval, and the two lines that carry the bus into the deployment now refuse to boot when either is missing. A subscription can also report what it dropped, so the party that missed a message is the party that can see it. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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cf619fc91b |
feat(distributed): carry fan-out on PostgreSQL LISTEN/NOTIFY
Distributed mode needs an operator to run a NATS cluster. This adds the carrier that replaces its fan-out half, so a deployment eventually needs PostgreSQL and its own HTTP listener and nothing else. pgbus holds one PostgreSQL session per replica, pinned for the life of the process because LISTEN registrations belong to one backend session and a pooled handle would lose them on the next checkout. Publishes go out on the pool with pg_notify. Subjects map onto a channel by their first token, from a closed set of roots. A subject outside the set is refused at publish AND at subscribe rather than mapped to a channel of its own: a channel name is capped at 63 bytes, and one LISTEN per job id would be unbounded. Refused rather than dropped, because a subject that goes nowhere and reports nothing is the class of defect this work exists to remove. PostgreSQL refuses a notify payload of 8000 bytes or more, and several subjects on this bus exceed that in normal operation: a job result carries a whole LLM output, a gallery progress event carries one entry per node. Those are written to a row and the notification carries the id. What is measured against the cap is the ENCODED notification, not the caller's payload, because the subject and the envelope travel too. The filter grammar is not respelled here. Subscribe asks messaging.ValidFilter and delivery asks messaging.SubjectMatches, which makes this the first production caller of a matcher that had only test doubles. New refuses a DSN that names a different database from the pool: that pairing publishes successfully, delivers nothing, on every replica, and reports no error anywhere. Nothing publishes on it and nothing subscribes yet. The construction is wired anyway, because the DSN has exactly one legitimate source and a setting that decides whether any broadcast is delivered should not be invented by whichever call site is migrated first. Delivery is at-most-once, like NATS core. Nothing downstream may read a message it did not receive as evidence about a node: a carrier that cannot deliver is not a worker that is gone. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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749cc7ad81 |
fix(distributed): let absence be decided by something, at all three call sites
Removing "Presence: clusterRegistry" from the options literal in initDistributed left all seven suites and tests/e2e/distributed green. The predicate was right and its input was silently nil, which returns the deployment to absence being decided by nothing, with no log line and no failing request. That is the fourth finding of this exact shape in this phase. The two assignments move out of a twenty-field literal into distributedSchedulerOptions, a named function a unit spec can reach. Deleting either is now red. The health monitor takes its presence reader and grace as a required positional pair instead, so deleting those does not compile at all. requireAbsenceWiring then refuses to start a distributed frontend whose scheduler or health monitor has no source of absence, because refusing to boot is the only symptom either failure has. With a fresh heartbeat and a permanently gone tunnel there was no reaper at all. A heartbeat says the worker's supervisor is alive; it says nothing about whether anything here can reach that worker's backends, because those are reached over the tunnel. A proxy that stops upgrading WebSockets, a rotated registration credential or a reconnect loop longer than the grace left a node listed healthy forever while every request for a model already loaded on it failed "no route to that worker", and every reaper keyed on the heartbeat. The health monitor now reads presence from the same place and against the same window as the scheduler and demotes such a node. That also ends the 15s re-promotion: the demotion arm returns before the recovery arm, so the scheduler's demotion is no longer undone on the next tick, and recovery needs the tunnel back rather than just the heartbeat. The demotion is status-only. MarkOffline would DELETE the node's rows, and deleting rows on a presence read would give any future defect in that read the widest blast radius in the system for nothing the demotion does not already deliver. LRU eviction is the third path that commits work to a node, and it read only the stored status. A node full enough to be an eviction target is exactly the node the VRAM and idle selectors never offer, so pickReachableNode structurally cannot cover it. It now runs its chosen node through the same nodeMayTakeWork predicate, demotes it and evicts again rather than handing back an install that cannot land. Presence is read after the transaction and not inside it: reading it inside would hold a FOR UPDATE lock across a query needing a second pooled connection, which is how concurrent evictions deadlock a pool. Also: a router built with a presence reader and no grace now has its documented default pinned by a spec rather than only claimed by a comment; ageDeparture asserts RowsAffected, since an UPDATE matching nothing succeeds and the inside-the-grace spec returned the same verdict either way; the scheduler comment that still described the bus is corrected; the docs stop conflating heartbeat recovery with tunnel recovery and name the third reader; and an overlong rewrapped line in membership.go is folded. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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93af91419b |
feat(distributed): read worker absence from the database, not from a bus timeout
The scheduler decided whether a worker had gone away from nats.ErrNoResponders: one frontend's observation that nobody answered IT within a request budget. Two replicas asking in the same moment could disagree and demote each other's workers, and a worker re-homing its tunnel between replicas looked identical to one that had died. SmartRouter now reads cluster.Presence instead. Only PresenceGone -- no live replica holds the tunnel AND the departure has outlived the reconnect grace -- excludes a node from placement, and it is a fact every replica reads identically from the database. PresenceReconnecting, PresenceUnknown and a failed presence query are all non-verdicts and place work as normal: excluding on a database hiccup would cost the fleet its capacity for a reason that has nothing to do with any worker. nodeAnswersOnBus is deleted. It excluded on a sentinel no control RPC can produce, so it decided nothing while PingNode cost a relayed round trip per scheduling decision to feed it. PingNode goes with it, from the adapter and from NodeCommandSender. isRequestTimeout drops nats.ErrTimeout: every verb this adapter sends now travels over the worker's tunnel. The predicate is named nodeMayTakeWork rather than nodeHasRoute. "Route" is ErrWorkerUnroutable in this package, the condition nobody may act on; PresenceGone is the one a scheduler may. Spelling them the same way is the collapse this work exists to prevent. Also folds in ReapStale's return rename: it counts connection rows CLEARED, never rows deleted, and reading it as a delete count would make a worker that is re-dialling right now look forgotten. The spec pinning that a message merely quoting "nats: timeout" is not a timeout was scripting a SUCCESSFUL reply carrying the phrase, which comes back with a nil error and never reaches the classifier. Restoring the string match left it green. It now scripts a 5xx whose body carries the phrase, and asserts that the phrase reaches the classifier as a precondition. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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7fc617c8ed |
feat(distributed): serve file staging over the worker tunnel
The four nodes.<id>.files.* subjects were the last commands a serve-backend worker took off the bus. They are now HTTP routes under workerctl.Prefix, on the same loopback server and behind the same bearer check as the ten lifecycle verbs, so the frontend reaches them through the worker's tunnel. files.listdir is the verb this matters most for. Its reply had to fit a payload the bus would carry, which put a wide model directory close to the limit; a response body has no such ceiling, so nothing truncates the listing at either end. A short listing reads to the frontend as files the worker does not have. S3NATSFileStager becomes S3FileStager and calls ControlClient, which means every failure now lands in the bucket phase 3 exists to keep straight: a route this frontend could not use is unroutable and nothing may act on it, while the worker's own answer, including "that file is not there", is evidence a caller may act on. Each RPC's deadline is DERIVED FROM the caller's context rather than started fresh, at every one of the five call sites, so a caller that gave up stops the RPC too. A worker started without an object store mounts no file verb at all and answers 404, which is the same answer a build too old to know them gives. The subjects and the backend worker's files.> publish grant go with them; a backend worker now publishes nowhere but its own inbox. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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44f12b2adb |
feat(distributed): call the worker's control routes instead of the bus
The ten backend and model lifecycle verbs stop being NATS requests and become HTTP calls on the worker's own control routes, reached through that worker's tunnel on the `http` stream tag that already carries file staging. Nine subject builders and the per-op install-progress subject are deleted with their entries in the worker's NATS permissions; the request and reply DTOs are untouched, so a body on the wire is byte for byte what the subject carried. This closes the merge gate Task 3 left open, which was worse than lost commands. Once the worker stopped subscribing, PingNode was still asking nodes.<id>.backend.list and nodes.<id>.models.running, so EVERY healthy worker answered no-responders, nodeAnswersOnBus read it as absence and pickReachableNode demoted it on the scheduling path. PingNode is a control RPC now, and no control RPC can produce ErrNoResponders, which is the only error that exclusion acts on. Two specs drive pickReachableNode against a real adapter and a worker answering over its control plane, which is the only arrangement that can see the difference: the router's own double never touches a transport and stayed green for the whole window the defect was live. How a control RPC FAILS is the whole of this change, so it is decided in ONE function reading ONE table. A worker's answer passes through unwrapped, so cluster.IsWorkerAnswer still sees it and a reap guard may act on it; everything else is wrapped in ErrWorkerUnroutable so nothing can. There is no third branch, because a third branch is how the eight collapses on this branch happened: each was a site that decided for itself which errors were evidence. A 404 under the prefix is its own sentinel, because it is the worker stating a deployment fact about ITSELF rather than a verdict about a backend, and only the legacy upgrade fallback may act on it. The caller's budget is checked FIRST. A timeout is not a verdict: a refusal arriving in the instant a deadline expires would otherwise be reported as the worker's non-transient answer, which reaps a row, and nothing orders the two timers. A 5xx and an undecodable body are transport failures, not answers. An empty ModelsRunningReply means "this worker is running nothing", which the reconciler acts on, so it must never be manufactured from a body that would not parse. A stream that ends before its reply line is the same rule one layer up: a tunnel dying mid-install is not the worker saying the install failed. backend.stop is split by node type rather than moved. Agent workers hold no tunnel, so they have no control plane to serve, and they still subscribe to nodes.<id>.backend.stop to drop cached MCP sessions; that subject and its agent permission both survive. It is the honest intermediate state until agent workers hold tunnels too. A failed control RPC no longer demotes a node anywhere. ErrNoResponders meant "not on the bus"; a control failure means "this frontend could not route to it", which is equally what a healthy worker re-homing its tunnel between replicas produces. Absence is a fact read from the database, and the scheduler starts reading it in a later task. The rolling-update fallback re-fires a DESTRUCTIVE force-reinstall, so it runs only on the worker's own 404. Its negative direction was pinned at the admin call site and unpinned at the reconciler's, where widening the condition to any error left all 676 specs green: a background drain nobody is watching would then force-reinstall every queued backend the moment a replica lost its tunnels. Three specs cover it, arranged so the force install IS reachable in the negative case and a fallback that fired would show as a call and a drained row. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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6b4ce58207 |
feat(cluster): answer presence with four values on the database clock
A worker whose tunnel is gone is not, by that fact, a worker that has left. Absence is what makes the scheduler stop placing work, reap the worker's rows and evict its models, and one of those paths runs during inference, so the deployment needs to tell a worker re-homing between frontend replicas from one that is really gone before anything acts. Registry.Presence answers that in one joined statement, with four values and not a boolean: unknown when there is no row at all (this package cannot tell a worker that has never dialled from one whose departure aged out, and must not guess), connected while a live replica holds the tunnel, reconnecting while the departure is inside the grace, and gone once it is older. Only the last is a verdict a caller may act on. Held-ness is asked FIRST and the departure only refines it, in the SQL and again in the switch that reads it. Every writer here clears disconnected_at in the statement that writes the owner, but that is a property of these writers rather than of the table: a replica running a binary from before the column existed re-claims without clearing the stamp, so during a rolling upgrade a held row carries an old departure, and a read that consults the stamp first reports a connected worker as gone for the whole upgrade. Both windows are computed by the database, for the reason every other window in this package is: they are compared across replicas, and replicas disagreeing about whether a worker is gone is the flapping this branch exists to remove. No behavioural spec can see the difference, since the test container shares the host clock, so the statement shape is pinned instead. The grace is an operator's knob, defaulting to twice the worker tunnel's maximum reconnect backoff. That made the fixed departure retention wrong: an operator raising the grace past it gets a purge that deletes departures before the grace elapses, so a worker that is gone reads as unknown forever and nothing ever reaps it. The retention is now derived from the grace, with the old constant as its floor. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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d26263f9c0 |
fix(distributed): let a worker's own refusal be evidence about its backend
A worker that refuses a stream has answered, and cluster.Dial keeps the three tunnelproto sentinels out of the ErrNoRoute umbrella precisely so a consumer can act on that. No consumer did. Since workers stopped listening, a backend process that crashed on a healthy worker is no longer a dead listener's codes.Unavailable: the worker refuses the stream with ErrStreamTargetUnavailable, gRPC flattens it into Unavailable anyway, and nodes.unroutable reported the whole thing as "this frontend has no route". Every reap path then answered ProbeUnknown and left the row, so the replica slot never freed and at the default MaxReplicasPerModel=1 the only cleanup left was LRU eviction of models that were working. isWorkerAnswer is exported as cluster.IsWorkerAnswer, so the errors the dialer keeps out of the umbrella are by construction the errors the consumers treat as the worker answering. nodes.unroutable and pkg/model's transportFailure both use it; ConnectionEvictingClient, the site reached during inference, goes through transportFailure rather than asking the transport directly. A reply code this frontend does not recognise is still not an answer, so a newer worker's vocabulary costs a retry and not a replica. The reap guards keep the allow-list rather than requiring ErrNoRoute: an unrecognised dial error must mean "no route", never "the backend is gone". Also in this final pass over the branch: - Docs: recommend upgrading FRONTENDS first, with the symptom of each order. Workers-first fails now that a 4xx registration is a verdict rather than an outage, so an old frontend's "address is required for backend workers" makes each restarted worker exit and drains the fleet a node per restart. - Docs: LOCALAI_WORKER_TUNNEL=false is a fatal startup error, not a degraded mode, in both places that described it; and a frontend rollback needs every worker restarted, because re-registration force-clears the address columns. - A replica with no advertised address now says so every five minutes and names the workers only it can reach, instead of one startup warning for a cost paid for the life of the process. - callerRanOut's rule now holds at all three siblings, so an expired caller deadline stops reading as a broken tunnel; probeHealth's withdrawn reason for using the raw client is corrected; the dead DoOrCached is deleted and its coverage kept on DoOrCachedResult; sweepLeakedInFlight enumerates the outcomes that reach it. - The peer route's self-declared id is recorded as a phase-3 deferral, in the handler, in the isolation claim it narrows, and in the operator docs. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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0683fb1579 |
test(distributed): prove the worker tunnel end to end, under real inference
Everything this phase built was proven by unit and integration specs. This is the first run of it against the real binaries: a frontend replica per process, a worker that binds nothing routable, real inference over the result. Four scenarios, each with the question "what would make this pass if the tunnel were doing nothing" answered rather than left open. A worker with no advertised address is reached through its tunnel. The roster is asserted to report it advertising nothing, so there is no address a frontend could have dialled instead, and node_connections is asserted to name the replica that serves the request. A request landing on the replica that does NOT own the worker is relayed to the one that does. With N replicas behind round robin that is (N-1)/N of production traffic, so it gets the FIRST request for its model: the backend install, the file staging on the http tag, and the gRPC load and predict all cross the relay. Which replica owns the tunnel is read from the ownership table through the production Owner query and mapped to a frontend index through the address the harness pins per replica; the non-owner is derived from that reading and asserted to be a non-owner immediately before the request, rather than assumed from the harness default. Sending the same request to the owner reddens it. Killing the owning replica re-homes the worker onto the survivor. The worker dials a balancer rather than a replica, because LOCALAI_REGISTER_TO is resolved once at boot and is the tunnel endpoint as well as the registration one: aimed at a single replica, a worker has nowhere to reconnect to when that replica dies, and the re-home cannot happen at all. Removing the kill reddens it. And the negative control for the whole suite, which is why the other three mean anything. Frontend and worker share a host here, so every backend port the frontend names in a stream target is one it could have dialled directly; if it did, the first three would pass with the tunnel inert. LOCALAI_WORKER_TUNNEL is no longer usable for this, because it is a fatal startup error and a worker that never started says nothing about a worker reachable some other way. The balancer answers the tunnel connect path itself instead, leaving a worker that registers, heartbeats, reports healthy and holds no tunnel. It is asserted to have dialled and been refused, asserted to be held by nobody, and then asserted unreachable with the refusal naming the missing route. Then the block is lifted, nothing else changes, and the same request succeeds: that is what attributes the refusal to the tunnel rather than to any of the ordinary reasons an e2e inference fails. The fifth spec measures the head-of-line blocking this phase deferred three times. 128 MiB crosses the session while a warm model is probed back to back, direct and relayed. Median latency is unchanged, the worst probe is about 3x the baseline median and about a seventeenth of the transfer window, and the transfer runs at 415-490 MB/s direct and 222-268 MB/s relayed. A session that head-of-line blocked would park a probe for the length of the window. Leave the yamux windows untuned; and note this is loopback, so it says the multiplexing does not serialise and says nothing about a link with a bandwidth-delay product. The load spec is measured against a control that the first version did not have. It passed with the bulk artifact cut to 4 KiB, because the window it read probes against was mostly cold-load overhead: it would have reported a clean bill on a session carrying no large message. The same cold load now runs twice, once empty and once bulk, and the difference between the windows is asserted to be real before any latency is read from it. Two defects on the base commit came out of this. cluster_peerlink_test.go has been red since the relay landed, deterministically, in isolation and in the suite. It asserted that an accepted peer stream is refused at once, on the premise that phase 1 installs no relay. The relay correctly waits fifteen seconds for a frame naming the worker, and the spec's budget was five. It now writes a relay request for a node no replica holds and asserts the refusal is ErrNotOwner and specifically not ErrNoConnection, which is a stronger spec than the one it replaces and the only thing in the e2e suite that exercises the relay's refusal path. The harness handed a worker's own HTTP port to a backend process. It took two ports from freeport and used one as the gRPC base and the other for the file transfer server; freeport returns adjacent ports often, and the backend allocator hands out base, base+1, base+2, so the second backend started on a worker was regularly given the HTTP server's port and died with EADDRINUSE. No spec had started two backends on one worker before, so it had never fired; the load spec starts five and it failed about one run in three. Each worker now reserves a contiguous bind-probed block laid out the way production lays it out, below the kernel's ephemeral range, with LOCALAI_GRPC_MAX_PORT bounding the allocator to it. The underlying production defect is not fixed here and is recorded in the report: allocatePort never checks that a port is free, and its default range overlaps the ephemeral range on every Linux box. Constraint 6, whether distributed mode should now refuse to start without an advertised address, is DEFERRED, and the comment and the docs that described the cost were understating it. A replica with no advertised address writes no instances row, and Owner joins a connection against a live instance, so a worker whose tunnel lands there is unroutable from every OTHER replica while being registered and healthy. Refusing to start would still be wrong, because the deployments it would break are single-host ones with no peers to be unreachable by, and telling those apart at startup is a design with its own specs. Both places now say what actually happens. Suite wall clock 592s for 15 specs, up from 502s for 10 of which 2 were red. The CI budget of 20 minutes does not move. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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a8ac2af167 |
fix(cluster): make "no route" a condition of its own, and let it out of the package
Review round 1 on task 6. Five blocking findings, all with the same root: the conditions the dialer kept apart were erased one layer out, because every one of them arrived at core/services/nodes as a gRPC codes.Unavailable, which is also what a backend process that died produces. Four call sites acted on that by deleting a replica row, one of them after a single failed probe. The fifth condition is ErrNoRoute: this replica could not get a request to a worker's backend, and no claim at all about the worker. A worker's presence is its HEARTBEAT, which nodes owns; a route is a separate fact that cluster owns, and the two now differ. They differ in normal operation, not exotically: a worker that has not dialled its tunnel yet after a frontend-first upgrade is unroutable on every request while it heartbeats and serves. Two properties, both mutation-tested. Every failure to resolve or open a route carries ErrNoRoute, so a consumer has one check to make. No failure carries an absence sentinel: routeFailure is the single place that rule lives, and it keeps ErrNoConnection and ErrInstanceNotFound in the message and out of the unwrap chain, the guarantee unreachableError already made for peers. Everything else stays matchable, so ErrNotOwner and ErrPeerUnreachable are unchanged for anyone who can act on them. A worker's own refusal carries no umbrella, because a worker that answers has demonstrated it is there and that is the only real evidence on the path. Crossing the boundary needed a value, not a code. NewClientWithDialer wraps the dialer and records each outcome; LastDialError hands it back behind a narrow interface, and nodes.unroutable turns it into ErrWorkerUnroutable with the cluster sentinels still in the chain. A spec asserts a dial failing with ErrNoRoute plus ErrPeerUnreachable arrives matching all three and matching neither absence sentinel. The sweep found a fourth site the review had not named: pkg/model checkIsLoaded evicts a remote model on a connection error, and a tunnel dial failure is one. Four other reap sites were cleared with reasons - inflight and the worker authoritative pass reap only on semantic answers, scale-down is driven by last_used, abandoned loads decide on the node's heartbeat. Every fixed site also grew the opposite spec, so the new check cannot pass by never reaping. probeCache carries the reason through singleflight rather than a closed-over variable. A variable is only written by the goroutine that runs the probe, so the leader would correctly decline to reap while every joiner reaped on the leader's own observation; a mutation reproduces exactly that. The docs sentence promising LOCALAI_WORKER_TUNNEL=false restores direct dialling is gone. There is no such path, so it said the operator could take a worker dark and call it a rollback. Replaced with the upgrade order that is actually safe. The deadline spec the reviewer found vacuous now waits on the dial context's own Done channel before touching the stream, so the armed deadline has really expired; the mutation that survived for the reviewer reddens it. Nine mutations, each reddening a named spec, including both halves of isAbsenceClaim independently. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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75953d9f63 |
feat(cluster): reach every worker through its tunnel, never its address
The tunnel, the fence, the registry and the relay were all built and none of them carried a byte: every dial from the frontend still went to the address a worker registered. This is where that stops. One WorkerDialer resolves where a worker's tunnel is held, opens a stream on it locally or relays through the owning replica, and hands back a conn past both handshakes; gRPC, the file stager's HTTP client and the log-streaming WebSocket are all pointed at it. A worker's address stops being somewhere to connect to and becomes the name of which backend process a stream is for. It still appears in URLs, logs and errors, because that is what identifies the process; what it no longer decides is where the bytes go. Nothing falls back to dialling it. BackendClientFactory now has exactly one method, NewClientForNode, and returns an error where there is no way to reach the worker. The direct-dial constructor was removed rather than kept beside it, because leaving one on the interface keeps the bypass one word away from every call site that holds an address, which is all of them. The second construction path is closed too. DistributedModelStore built remote models with a nil client, and pkg/model.Model.GRPC then dialled the raw address lazily on first use - reached in production by ShutdownModel's Free and by the backend monitor's Status. Those models now carry the tunnel-backed client, and a model that cannot be given one is logged and not listed. Four conditions stay unmixable, and one path produces absence: the dialer answers ErrNoConnection only where Owner's liveness join did. A peer that will not answer, a stale ownership row, a worker's own refusal and a missing relay path are each reported as themselves. This matters because nodes ACTS on absence, and the collapse would have it reclaim the models of a worker that is connected and busy. That is not hypothetical. Writing the mutation for it exposed the bug in this change's own first draft: probeHealth returned bare false when it could not build a client, and tryWarmPath deletes the replica row on a false probe. A frontend whose dialer broke would have emptied node_models for the whole deployment while every model kept running. probeHealth now returns alive and probed separately, the reconciler gets a ProbeUnknown outcome that neither advances nor clears a failure streak, and the health monitor skips rather than counting a miss. Task 5 left the relay's open timeout at a fixed 15s and said so: no operator has the information to set it, because the number that matters is the original client's remaining budget, which is invisible on the relay side. The dialer has that budget, so it now states it in the relay request frame and the owner takes the smaller of the two. It can only shorten - a patient client must not be able to park a relay goroutine and a stream slot on a worker that stopped accepting. Zero is written as no budget at all, since on the far side the number zero is a caller with nothing left and would refuse healthy traffic. Seven mutations, each reddening a named spec: peer-unreachable as absence; the local-failure guard dropped; max instead of min on the budget; the nil-client model restored; ProbeUnknown falling through to the reaper; OwnerRow instead of Owner; probed collapsed into alive. The first budget spec passed for the wrong reason - a handshake deadline, not the relay - and was replaced by three that each assert one link, including one where the spec plays the owning replica and reads the budget out of the frame instead of inferring it from a clock. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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|
Ettore Di Giacinto
|
cce914b3fd |
feat(cluster): relay a peer's stream onto a worker tunnel held here
A worker holds ONE tunnel and it lands on ONE frontend replica, so with N
replicas behind a load balancer roughly (N-1)/N of requests arrive somewhere
that cannot reach the worker directly. This is the piece that carries them:
the SessionStore stream handler reads which worker a peer's stream is for,
opens a stream on the tunnel this replica holds, and splices the two.
Splice has had no production caller since phase 1. It has one now, and being
the first caller it settles the two endings phase 1 deliberately left open,
both of which read as normal termination until now:
- a peer-initiated *StreamError{Remote: true}, which yamux builds only from
an RST frame the far side sent (stream.go:432-449); a reset this side asks
for carries Remote: false, and Splice never resets anything, its own Close
sending a FIN;
- a graceful ErrRemoteGoAway, which handleGoAway returns for code
goAwayNormal (session.go:829-833) and close hands unwrapped to every live
stream (session.go:328-337).
Both truncate whatever was in flight. Reporting them as normal termination is
how a half-finished inference comes to look like a short one that completed,
so both are now reported; the local forms stay silent, because those are the
teardown Splice provokes itself. The decision cannot live in a caller reading
Splice's result, since a result already mapped to nil carries nothing left to
reclassify, so it lives at the classifier with the reasoning beside it. The
relay logs it at debug: a client cancelling a relayed request produces one per
cancellation, and the truncation is separately visible to the frontend's own
gRPC or HTTP client.
The relay hop gets its own request and reply frames. They have to be distinct
from the worker tunnel's, because a relayed stream carries both hops' frames
back to back, and a vocabulary shared between them would let a reader applied
to the wrong hop hand back a plausible sentinel belonging to the other. Its
three refusals stay apart for the reason the worker's three do: ErrNotOwner is
a routing fact and the caller should resolve the owner again; unavailable is
infrastructure at this replica and a retry is worth something; bad-request is
the caller's bug. None of them is, or may be built over, an absence error.
One hop, always. A stream naming a worker this replica does not hold is
refused, never resolved and relayed onward, so a stale ownership row cannot
become a loop between two replicas each certain the other holds the worker.
PeerPool is constructed and closed alongside SessionStore, so both halves of
the peer mesh now have an owner and a shutdown.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Opus 5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto
|
6e55092a4b |
feat(cluster): open the door a worker dials its tunnel through
A worker needs no inbound port: it dials GET /api/cluster/connect, the connection becomes one multiplexed yamux session, and the frontend opens a stream on it per request. This adds the endpoint that accepts that dial and attaches it to the tunnel registry. The dial is authenticated against the NODE's own stored token hash rather than the deployment's registration token. That is the mechanism, not yet the isolation, since a worker still registers by presenting the shared token; what it rules out is the shortcut of comparing against the configured value, which would have to be unpicked the day workers get their own secrets. Every refusal happens BEFORE the WebSocket upgrade, so a dialer reads an HTTP status rather than a handshake error. The route is registered in every deployment, single-binary ones included, which is what puts it in front of the route-coverage test that holds that rule in place; with no node registry it refuses every dial, and tells a credentialed one the frontend has no cluster rather than that its token is wrong. A lookup that FAILED is answered as a failure. Reporting a database that could not be read as "unauthorized" would send a worker re-registering, throwing away the identity its tunnel and loaded models are keyed by. Wires the tunnel registry in core/application/distributed.go and hands it to the membership loop. Without that call the re-claim after a replica is reaped had no production caller and could never run. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Opus 5 [claude-code] |
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Ettore Di Giacinto
|
e26d556594 |
fix(cluster): hold the guarantees phase 1's comments were claiming
Review found the recurring class: assertions that a wrong implementation also satisfies. The "refuse promptly, never park the peer" guarantee was stated in three places and tested in none. Removing the Close from the no-relay branch left the whole cluster suite green, because the specs asserted only that some error arrived and yamux reports a read deadline as ErrTimeout: a parked stream satisfied that as well as a refused one. Both specs now require an ENDING, EOF or a reset, inside a deadline short enough that parking is unmistakable, and both go red when the Close is removed. Deregistration existed only in a comment. Membership.Stop ended the loop and left the row behind, so every clean rolling restart had peers dialling a corpse for the full liveness window; the shutdown comment described the opposite. Registry.Deregister deletes the row and the connections that replica owned, in one transaction, for the reason the sweeper does both, and an e2e spec pins departure inside a budget shorter than the liveness window so it cannot pass on the sweeper doing the work. Before: the spec times out with both replicas still live. After: 3.6s. The configured advertised address bypassed every check discovery makes, so the one value most likely to be copied between hosts, 127.0.0.1, was taken verbatim and would make every peer dial itself. Both paths now share one rejection rule: unparseable is refused, "this host" is warned about once and honoured, because a single-host deployment uses it correctly. Two comments claimed more than the code does. The sweeper said a stalled replica recovers via re-register; only its instance row does, while the connections another replica reaped stay gone and the sockets stay held here - phase 2 must re-claim, on re-register, every connection a replica still holds locally. And Owner became OwnerRow, documenting that the owner it names may be dead for up to InstanceLiveness plus a heartbeat and that any caller acting on it must join instances itself, so the deferred constraint lives at the call site rather than in a report; the plain name is left free for the joining version. Minors: warn once when the peer link mounts with no registration token, so an operator sees the cause rather than 401s; Stop no longer blocks forever when Start was never called; corrected the NewRegistry migration doc and an e2e comment that described a 6s window as "throughout". Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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|
Ettore Di Giacinto
|
aca383d263 |
feat(cluster): give phase 1 a call site, and prove it against real replicas
Tasks 1 to 5 built an instances table, a splice, both halves of a peer link and an epoch fence, and nothing in the tree called any of it: no replica registered, no route was mounted, no sweeper ran. Proving phase 1 end to end therefore had to start by wiring it. A frontend in distributed mode now publishes the address its peers dial, heartbeats it, and sweeps replicas that stopped answering along with the connection rows they owned, in one pass so the two can never disagree about who is alive. It serves the peer link and owns the sessions peers dial in, refusing streams on them until phase 2 installs a relay: a session nobody accepts on does not fail a peer's Open, it hangs it. The address is the one peers use, not the one the process binds, and it is derived from the route to PostgreSQL. That derivation only holds while the database is remote, so LOCALAI_DISTRIBUTED_ADVERTISE_ADDR sets it explicitly and a replica that can determine neither warns and keeps serving rather than failing to start. Three e2e scenarios run against real local-ai processes, real PostgreSQL and real dials: replicas publish addresses that can actually be connected to; a sibling opens a stream over the peer link and is refused without the cluster token; and a killed replica is reported unreachable, never absent, loses the claim it held, and takes no worker with it. Each was verified by mutation: eight injected defects, each failing the scenario that claims to catch it. Also moves RegisterClusterRoutes to core/http/routes beside every other registrar, folds AutoMigrate and the epoch sequence into one cluster.Migrate, and turns the peer route's auth-coverage spec into a real assertion: it drives the request through the actual auth middleware instead of comparing two string constants, which the old spec would have passed even with the exemption deleted. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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Ettore Di Giacinto
|
505a6d040b |
fix(distributed): publish the revision a request actually carries
Two code paths computed a model's revision. Inference resolves the config through the loader, which applies SetDefaults a second time. Everything that publishes a revision hashed the stored config instead, with SetDefaults applied once. SetDefaults is not idempotent for every model: it re-runs the GGUF guess and the hardware defaults, both of which read state the stored config does not carry. Where the two disagree, a publisher wrote a revision no request would ever carry, and the model became unroutable the moment it was published. On this cluster the startup resync republished one such value and every request for that model was then rejected against it. The publishers now resolve the revision through the loader, exactly as a request does, so there is one definition rather than two that agree only when SetDefaults happens to be idempotent. This covers the startup resync, a saved config edit, and enabling or disabling a model. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
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|
Ettore Di Giacinto
|
5c9d8190d9 |
fix(distributed): resync revisions after the configs are loaded
The resync added in
|
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|
Ettore Di Giacinto
|
3953448f60 |
fix(distributed): resync stored config revisions at startup
The controller pins a model's replicas to a stored revision and rejects any request carrying a different one. Nothing ever re-derived that value from the configuration on disk: it moved only on an edit, a gallery install, or a peer's change broadcast. An inference request may only establish a revision, never replace one. So any other way for the two to diverge left the model permanently unroutable. A configuration edited while a frontend was down lands there, and so does a change in what the revision is computed over: an upgrade that alters the hashed form leaves every stored revision describing a configuration that no longer exists. The only recovery was deleting the row by hand, which is not something a cluster should need. Each frontend now reconciles the stored revisions against the loaded configurations at startup and republishes the ones that disagree. Only those: republishing quarantines every replica loaded under the old revision, so doing it for a model that did not drift would unload a healthy replica for nothing. A model with no stored revision has never been served and is left for its first request to establish. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-5 [golangci-lint] |
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|
localai-org-maint-botandlocalai-org-maint-bot
|
8f56e4e042 |
fix(vram): persist remote probe metadata (#11487)
* fix(vram): persist remote probe metadata The startup warmer repeated remote size and GGUF metadata probes after every restart because both caches lived only in memory. Store successful HTTP probes for 24 hours so frequent restarts reuse the prior results. Bound the cache, reject invalid records, and purge it when gallery data changes. Local model files continue to bypass persistence. Assisted-by: Codex:gpt-5 * fix(vram): check temporary file cleanup The lint gate rejects the unchecked cleanup call in the persistent cache writer. Assisted-by: Codex:gpt-5.6 [golangci-lint] * fix(vram): make persistent cache optional Remote metadata probes can transfer enough data that operators need control over disk reuse and startup warming. Gallery autoload now gates both behaviors, and the runtime setting applies changes immediately. Assisted-by: Codex:gpt-5 * fix(ui): expose gallery startup pre-warm The existing gallery autoload setting also gates the startup metadata warmer. Name both effects in Settings so operators can find the requested boot control. Assisted-by: Codex:gpt-5 --------- Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
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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> |
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|
Richard Palethorpe
|
d10374f849 |
feat(router): make KNN a first-class classifier with a persisted, curated corpus (#10652)
* feat(router): make KNN a first-class classifier with a persisted, curated corpus
Add `classifier: knn` — similarity-weighted voting over labelled
example prompts. Unlike score/colbert it needs no classifier model:
label knowledge lives in a corpus seeded and curated through the
admin API, so routing decisions are deterministic, auditable, and
grounded in graded experience rather than a model's opinion.
Epistemic gate: corpus entries below knn.similarity_threshold cannot
vote; when none clears it the classifier activates no labels and the
router uses the fallback — a prompt unlike all labelled experience is
treated as undecidable, not guessed. Decisions record
nearest_similarity (also on fallback rows) so admins can see how far
the nearest labelled experience was; the Routing tab explains
out-of-corpus fallbacks and shows per-label corpus counts.
Persistence: one JSONL file per router under
<data path>/router-corpus (text, labels, vector, embedder
fingerprint). The file is the source of truth; the local-store index
is rebuilt from it at classifier build time and stays a pure
in-memory index. Entries recorded under a different embedding model
re-embed on load. Also corrects the docs' false claim that
local-store collections persist — the embedding cache never survived
restarts (and still doesn't); the corpus does.
Corpus input is API-only by design (entries may contain example user
content): POST /api/router/{name}/corpus seeds (labels validated
against declared policies, embedded server-side, indexed
immediately), GET .../corpus/stats inspects — label counts only,
entry texts are never returned by any surface — DELETE .../corpus
wipes. Admin-gated like the sibling router endpoints, and exposed as
MCP tools (seed_router_corpus / get_router_corpus_stats /
clear_router_corpus) in both the httpapi and inproc clients with
coverage-test route mappings.
Plumbing: VectorStore gains SearchK (top-K was hardcoded to 1);
local-store gets InsertBatch/Delete as optional fast paths;
RouterConfig gains a knn block (embedding_model, k,
similarity_threshold, vote_threshold, store_name) with meta-registry
fields; the classifier dropdown now offers knn and the
previously-missing colbert; embedding_cache is ignored (with a
warning) for knn — it IS an embedding-KNN lookup; the stale
/api/instructions intelligent-routing entry is rewritten (it
described a classifier that no longer exists); swagger regenerated.
Tests: KNN vote/gate specs with hand-computed vote shares, corpus
manager suite (restart reload without re-embedding, fingerprint
re-embed, dedupe, hostile store names), middleware specs (corpus
routing, gate fallback, config validation, cache-wrap refusal),
corpus endpoint specs pinning the texts-never-returned contract, MCP
catalog + route-mapping gates, and a Playwright spec for corpus
stats and the out-of-corpus decision detail.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): name consulted corpus neighbours in knn decisions
Every knn decision (decision log rows and the /api/router/decide
response) now carries neighbors: the K retrieved corpus entries by
descending similarity - including ones below the epistemic gate, which
is what makes fallback decisions diagnosable - each as {id, similarity,
labels}. The id is the entry's content hash (first 8 bytes of the
SHA-256 of its text, hex): stable across reseeds and re-embeds, and
text-free, so an external platform that seeded the corpus can recompute
text->id on its own copy and bucket decisions by corpus region (per-
region reliability accounting) without corpus text ever leaving the
server. A corrupt index payload surfaces as an id-less neighbour at a
real similarity instead of disappearing.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* refactor(router): deduplicate knn plumbing and cut corpus hot-path waste
Post-review cleanup of the knn-first-class-router branch; no behaviour
changes on the API surface.
Reuse/altitude:
- RouterKNNConfig.ResolvedStoreName is now the single source of the
router-corpus-<name> default (was hand-derived in four files).
- corpus.ResolveKNNRouter + corpus.Seed carry the shared model
resolution and seed validation; the REST endpoints and the assistant
MCP client are thin transport adapters over them, with sentinel
errors mapped to HTTP statuses at the echo boundary.
- middleware.NewClassifierDeps assembles the classifier dependency set
once for all five entry points (OpenAI, Anthropic, realtime, decide,
corpus) instead of five hand-copied literals.
- router.AllClassifiers feeds both the status endpoint and the
unknown-classifier error, ending the classifier-list drift.
- Per-classifier requirements moved out of validateRouterPolicies into
their buildClassifier arms; the knn arm owns its embedding_cache
opt-out instead of a name-check in the shared wrap tail.
- adminOnly replaces four inline copies of the admin gate in the
middleware routes.
- localVectorStore.Search delegates to SearchK (identical traces).
Efficiency:
- Manager.Add embeds outside the manager mutex and appends to the
JSONL file (O(new) instead of O(corpus) rewrite); a torn tail from a
crash mid-append is tolerated on read and repaired on next write.
- Stats memoises per store keyed on the file's stat fingerprint and no
longer takes the manager mutex, so the 5s status poll stops parsing
vector-laden JSONL and stops blocking behind seeds.
- KNN Classify decodes each neighbour payload once (was twice) and
builds refs and votes in a single pass with one fallback return.
- Corpus file writes fsync before rename/close.
- The corpus manager is built eagerly in newApplication (sync.Once
dropped); test helper dead branch removed.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): bind knn corpus vectors to an embedder fingerprint and fail closed on mismatch
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(mcp): align corpus tool prompts and the mutating-tool safety list
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(proto,backend): report embedding shape from the llama-cpp backend
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): Go-side pooling — mean/last/decayed_mean with half-life
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): accept chat messages[] and per-request pooling on /v1/embeddings
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(middleware): name the failing fields when post-merge validation 400s
An intermittent post-merge validation failure surfaced as an opaque 400
during integration (pooling scheme mismatch that no client had sent).
Log the model, the request's pooling override, and the merged config's
pooling fields at the failure point so the next occurrence identifies
whether the request or the stored config carried the bad value.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(embeddings): scheme override must not inherit the config's half-life
A model config defaulting to decayed_mean pooling carries
pooling_half_life_tokens; a request overriding the scheme to mean/last
without its own half-life inherited that value, and post-merge
validation rejected the pair the server itself had assembled. Zero the
inherited half-life when the overridden scheme is not decayed_mean; a
request that explicitly pairs a half-life with a non-decayed scheme
still 400s.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix embedding pooling validation and router bounds
Declare backend embedding layouts and reject incompatible pooling modes. Reset local-store dimensions after a full clear, validate KNN thresholds, and add real backend and store integration coverage.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: run local-store integration tests
Build and install the local-store backend in the Linux test job, then run the existing store integration suite so new specs are discovered automatically.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
|
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|
Richard Palethorpe
|
799cc9f211 |
feat: bound global admission and expose running backend traces (#11560)
feat: bound backend admission and expose running traces Add process-wide backend execution admission without blocking UI or administrative HTTP work. Represent backend operations while they are in flight, surface running traces with immediate log links, and tie streaming admission leases to the gRPC receive lifecycle. Assisted-by: OpenAI Codex: GPT-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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|
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>
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Owen Adirah
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8f74f74b10 |
feat(mcp): expose scheduling admin tools (#11228)
* feat(mcp): add scheduling client contracts Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * feat(mcp): add scheduling HTTP client support Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * feat(mcp): add in-process scheduling stubs Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * feat(mcp): register scheduling tools Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * test(mcp): map scheduling tools to REST routes Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * docs(mcp): document scheduling assistant tools Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * fix(mcp): wire in-process scheduling Use an explicit MCP scheduling DTO and route in-process scheduling calls through the distributed node registry so the embedded assistant matches the REST scheduling surface. Assisted-by: Hephaestus:openai/gpt-5.5 Signed-off-by: Owen Adirah <owenadira@gmail.com> * fix(mcp): narrow scheduling dto Assisted-by: Hephaestus:openai/gpt-5.5 [opencode] Signed-off-by: Owen Adirah <owenadira@gmail.com> --------- Signed-off-by: Owen Adirah <owenadira@gmail.com> |
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mudler's LocalAI [bot]andEttore Di Giacinto
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74b7ea2829 |
feat(ui): replace the gallery and inventory tables with a rail and a detail pane (#11288)
* feat(ui): rename the Install Models nav entry to Discover "Install Models" named the action rather than the destination, and it was the only multi-word entry in a rail of one-word ones (Home, Chat, Studio, Talk, Build, Operate). A bare "Models" was the obvious fix but it collides with the installed-models view under Host, which is a different page for a different job. "Discover" keeps the rhythm and says what the page is for. The icon moves from a download arrow to a compass for the same reason: the page is browsed before it is installed from. Translated in all seven locales rather than left to fall back, so a locale switch does not leave the entry in English. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * feat(ui): replace the gallery table with a rail and a detail pane The eight-column table was not the real problem; the click-to-expand row underneath it was. Variants, files and a VRAM estimate never fitted inside a <tr>, so they were pushed into a drawer that could hold one model at a time, could not be linked to, and had no room to say anything useful. The gallery is now a rail to scan and a pane that answers. The pane has two states and no third: with nothing selected it is the discovery page, and with a model selected it is that model's detail. Selection lives in the URL, so a model is linkable and Back steps out of the detail instead of off the page. The rail groups by capability while browsing and flattens to results the moment a term is typed. That is a rule rather than a toggle: once someone has said what they are looking for, the buckets are between them and the answer, and making the user choose would be handing them our problem. The detail pane plots VRAM against context length with the host's own limit drawn across it. This is new information, not a restyle. A single number invites "so will it run?", and the honest answer is usually "yes, up to a 32k context", which is a shape rather than a number. The estimates were already fetched for every context size, so it costs no new request. Backends that take no context length say so instead of being given a meaningless chart, and a host with no GPU gets no chart at all rather than bars with nothing to compare against. The split-button variant menu goes with the actions column. The pane lists every build with its backend, quantization, size, fit and a details disclosure, each installable, which is what the dropdown was a cramped substitute for. Its tests move onto that list; the three contracts it alone carried (fetch-once caching, the loading state, an unfit build staying installable) are backfilled against the pane. RecommendedModels moves inside the pane, where it has the width to argue for a model instead of listing one, and keeps its own dismissal and collapse. Rail entries carry no description. Two lines is the budget and the second is better spent on whether the thing will run; the stripped-Markdown contract moves to the pane's lede, tooltip included. e2e: 123 passing across models-gallery, navigation, recommended-panel, model-artifact-operation, operations-strip and page-render-smoke. Inline styles in Models.jsx drop from 82 to 41. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * refactor(ui): extract the split view into shared components Discover shipped its rail, pane and detail header as private functions inside Models.jsx. Backends and Host have the same defect and want the same shape, so leaving them there guarantees three rails that drift. SplitView, EntityRail, DetailHeader and StatGrid now live under components/split/. EntityRail is deliberately data-driven: a surface maps its own entity onto { id, name, icon, meta, stripe, groupId } and keeps its vocabulary to itself, which is what stops the rail learning about models, backends and loaded state all at once. The CSS moves with it. What was .discover__rail is .entity-rail, .discover__ pane is .split-view__pane and so on, because a class named after one page is a lie on the next two. Only what is genuinely Discover's stays behind the old prefix: the shelves, the hero and the VRAM-by-context chart. Two additions the shared rail needs and Discover did not: a state stripe, for surfaces read by condition before they are read by name, and an empty label. Discover passes neither. No behaviour change. e2e 100 passing across models-gallery, navigation and models-recommended-panel. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * feat(ui): put the backend gallery on the split view Same defect as the model gallery, so the same shape: a seven-column table over a click-to-expand row that was the only place the repository, licence, tags and links could go. The rail groups backends by the use case they serve, sharing Discover's taxonomy on purpose: a backend is the runtime a use case needs, so "vision" ought to mean the same thing one level down. It flattens on a query for the same reason it does on Discover. The zero state is the one real departure. A backend's fitness is not free memory, it is the accelerator and platform it was built for, so the pane leads with what this host is, then what is not installed yet, then whether anything installed has gone stale. The table listed 37 runtimes and left "which of these can even run here" entirely to the reader. Distribution moves into the pane, which is the one thing a row could never carry: which nodes hold a copy and which do not, with the install-on-more control next to it rather than squeezed against a chip. The distributed and target-node action logic is unchanged, including the guard that keeps a hardware-specific build off the fan-out path. The split-button popover loses its per-row anchoring because there are no rows; one pane, one anchor. Selection lives in ?backend=, preserving the ?target= scope rather than clobbering it. e2e: 139 passing across models-gallery, navigation, backends-management, models-recommended-panel, nodes-per-node-backend-actions, page-render-smoke, operations-strip and model-artifact-operation. The backends spec gains six split-view tests; its three description-cell tests move onto the pane lede. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * feat(ui): put the Host inventory on the split view The last of the three surfaces, and the one that is not a catalog. Both tabs had the same click-to-expand row, so the shell transfers; what does not transfer is the zero state, because there is nothing to discover in your own inventory. With nothing selected the pane reports what is happening: how many models are loaded, what failed, what has an update, and which models are holding VRAM right now. Every number was already on the page. None of them had been assembled into one statement, so "what is going on" was a question the tabs could not answer however long you looked at them. The rail buckets by state rather than capability - Running, Idle, Disabled for models; Update available, Installed for backends - which is the opposite of the galleries and deliberately so: nobody opens Host wondering which of their models does vision. Entries carry a state stripe for the same reason. Load and Stop are promoted out of the kebab, because that is what an operator came for; the rest stays behind the menu rather than diluting it. Adopted, pinned and alias badges follow the model into the pane: they are facts about the thing, not about its state, and the rail line is spent on state. Deliberately NOT done: folding the two tabs into one rail, as the mock had it. It costs five URL parameters, the manage-tab localStorage key and the stat-card shortcuts, all of which are live deep-links today. The tabs stay as the group selector; merging them is a follow-up with its own migration. e2e: full suite 355 passing. New host-split-view spec; alias-template, manage-logs-link, manage-action-menu-position and model-editor-back-nav move off `.table` and the row kebab onto the rail and the pane. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * polish(ui): accessibility and consistency pass over the three split views Findings from a pass over what the previous four commits actually shipped, rather than what they were supposed to. The rail was not a listbox. ARIA lets a listbox contain options and groups, and nothing else, but each group's collapse control is a button that has to sit inside the scroller with the entries it folds. It is now a labelled group of buttons, which is the honest description; selection is announced with aria-current and the arrow keys are unaffected. Every entry was its own tab stop, so tabbing past a forty-entry rail to reach the pane took forty keystrokes. Roving tabindex makes the rail one stop, and arrowing now moves focus with the selection instead of leaving it behind on an entry Tab can no longer reach. The rail rounds its corners with overflow:hidden, which was clipping the focus ring off the first and last entries entirely. Inset outlines fix it. A 30px row is fine under a mouse and too small under a thumb, so coarse pointers get a 44px target without costing density on a desktop. One slot said three different things: "9 models loaded" on Discover, "12 loaded" on Backends, "3 of 9" on Host. All three lists are a page of a larger set, so all three now say so the same way. Also removed: an emptyLabel prop on EntityRail that nothing passed, its dead CSS rule, and MODELS_COLSPAN and ResourceRowDesc, which died with the tables. e2e: full suite 355 passing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * fix(ui): correct three defects only a real gallery exposed Running the branch against a live instance with 1,595 models and 1,017 backends, rather than against mocked fixtures, surfaced three things the e2e suite could not. Grouping did nothing. The rails matched on the use-case keys the filter chips send (`chat`, `tts`, `transcript`), but those are a server-side vocabulary the handler maps onto entries. What entries actually carry is free-form and inconsistent: models come back tagged `llm`, `gguf`, `vision`, `coding`, and backends `LLM`, `text-to-text`, `audio-transcription`. Nothing matched, so every model landed in "Everything else" and the feature was decorative. Grouping now lives in utils/entityGroups.js, shared by both galleries, matching case-insensitively against the vocabulary the API really uses, with the entry's backend as a fallback signal - a backend named `whisper` is a speech backend whatever its tags say. Order is specific before general and that is load-bearing: a vision model is tagged `llm` too, so testing text first would swallow it. The zero state claimed GPU memory on a machine with no GPU. The resources endpoint reports system RAM in the same field when gpu_count is 0, so the hero read "84.4 GB of GPU memory" next to the recommendations panel correctly saying "No GPU detected". The number was never wrong, only its label; it now says system memory unless a GPU is actually present. The page title still said "Install Models" under a nav entry saying Discover. Also: the keyboard test named the model it expected to arrive at, which made it a hostage of the grouping table and broke the moment the buckets were fixed. It now asserts that the selection moves and returns. e2e: full suite 355 passing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * fix(ui): the filters and the rail were fighting over the same job Four things you find odd on Discover, and they turn out to be one mistake seen from four sides. The rail grouped the current page. The listing is paginated at nine rows, so those bucket headers described nine entries out of 1,595, and turning a page reshuffled the sections under the reader. The structure was never stable because it was computed over the wrong set. The chips were redundant for the same reason, seen from the other side. They send tag= and filter all 1,595 server-side. The rail grouped nine of them client-side by the same axis. Two controls for one job, and the weaker one was the one this branch added, so it goes. Grouping stays only on Host, where the list is complete, local, and bucketed by state rather than capability. The search bar felt odd because it sat in a full-width band while the thing it narrowed was a 290px rail below and to the left. The whole band now lives in the rail column: search, backend, use cases, refinements, then the list it narrows. One column to say what you want, one to show what you got. Nineteen chips do not fit at that width, so they fold into a disclosure that states the selection. A disclosure and not a popover, deliberately: picking use cases is multi-select and interleaves with the backend select and the toggles below, and a popover dismisses itself the moment you touch either. The header held two counts and two buttons at arm's length from all of it. The counts were the third statement of the same number on one screen, after the rail's "9 of 1,247" and the pane's own headline, so they go. The buttons move into the pane's zero state, which is the surface that answers "what do I do here". Also: the two first-run empty states wore .loading-center, which is display:flex in the default row direction because it exists to centre one spinner. With four children that put the icon, the heading, the sentence and the buttons on a single line with no gap. They are now a proper full-height empty state. e2e: full suite 353 passing. Grouping tests are replaced by ones asserting the rail stays flat; chip tests open the disclosure first; two filter-layout tests that asserted the old three-band arrangement now assert the column. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * polish(ui): make Discover a full-height view, group the chips, name the refinements Four things, all of them the same complaint: the page read as a document with controls scattered on it rather than as one view. The header is fused. A title block with its own padding, a subtitle and two counts made the split view look like an attachment to a document that happened to sit below it. It is now a slim bar carrying the title, the count and the two page-level actions, and the split fills the rest of the window. Rail and pane scroll independently, so the filters and the pane's headline stay put while a long list moves under them. The chips group. Nineteen in a flat row is a lot to scan even behind a disclosure, and they already belong to the four families the rest of the UI speaks, so they are bucketed by those. "All" sits on its own above them without a heading, because it is a reset rather than a use case. The refinements stop looking dumped. When the band became a column they were three controls left where they landed; they now read as a named section with one control per row. The zero state suggests again. It had decayed into a "Browsing / 9 of 1,247 / select a model" line that restated the count for the third time on one screen. It now offers the four use cases as tiles that set the filter, which is the shelf idea from the mock without inventing curation or paying for a second fetch. Two bugs found by looking at it rather than at the tests: the disclosure was clamped to 190px, which cut it off partway through its third section so two of the five never appeared at all; and the creation actions rendered twice, once in the new bar and once in the pane hero a few pixels away. e2e: full suite 353 passing. The chip-row test now holds its contract across the per-family rows rather than a single one, and additionally asserts every family is present and non-empty. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * fix(ui): pin the split view's height so a long detail scrolls the pane Selecting a model with a long description grew the whole page and dragged the rail down with it, which is the opposite of what "full height" was supposed to buy. The flex chain was right and the ceiling was missing. .app-layout and .main-content are min-height:100dvh, which is a floor: flex distributes free space but nothing caps growth, so a pane taller than the viewport expanded the column, the document scrolled, and the rail stretched to match. height:100% on the pane then resolved against an auto-height parent and did nothing. The chat route already solves this by pinning .main-content to 100dvh. The same treatment now applies to any route containing a .page--app, selected with :has() so the shell does not have to learn which pages happen to be split views. Below the stacking breakpoint the pin is lifted, because two stacked halves in two short scrollers is worse than a page that scrolls. Measured on a live instance: document height stays at the viewport across selection (950px either side) and the pane overflows internally instead. Adds discover-height.spec.js, which asserts the page height and the rail height are unchanged by selection and that the pane is the thing that scrolls. The existing specs could not have caught this: they mock short descriptions, and the bug only appears when the pane has more content than the viewport holds. e2e: full suite 355 passing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * feat(ui): give Backends and Host the full-height view, and fix the Update button Backends now matches Discover: the header fuses into a slim bar carrying the title, the count and the page-level actions, the filters move into the rail column where they narrow the rail and nothing else, and the split fills the window. Its seven chips fit at rail width, so unlike Discover's nineteen they need no disclosure. Host gets the bar and the height; its resource monitor, summary cards and tabs stay above the split, because those are read once while the rail and the pane are worked in. Two things the height change surfaced. The console layout is a flex row with align-items:flex-start, so its body sizes to content. Right for the pages it was built for, wrong for a split view, which needs a ceiling to scroll inside: without it the Backends rail ran past the viewport and over the footer. Pinned with :has() so only split-view routes are affected. The filters vanished when nothing matched. Both galleries swapped the whole shell for an empty state, which took the search box and the chips with it, so the page said "try adjusting your search or filters" while offering neither. The shell now stays and the empty state moves into the pane. Also fixes the Update control on Host, which had no className at all and rendered as bare text, next to a status span that had picked up btn classes and two copies of `fas` and so rendered as a button you cannot press. They have swapped appearances back. e2e: full suite 355 passing. The render-smoke selector learns .view-bar__title, since the pages it checks no longer all use PageHeader. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * fix(ui): keep the view mounted while searching, and bring rail grouping back Searching replaced the whole view with a loader. The search box lives in the rail column, so every debounced refetch unmounted the field being typed into and dropped its focus with it. The list, the filters and the pane went too. The shell now stays and the rail says it is busy: a sweep bar under its header and the stale list dimmed, so the eye knows the answer is being replaced without losing its place. A cold start still gets the skeleton, because there is nothing to keep. The condition for that is "nothing has loaded yet", not "the list is empty". Those differ exactly when someone is editing a query that matched nothing, and getting it wrong there would unmount the view on the keystroke after a no-results search - the worst possible moment. Grouping comes back on both galleries. It was removed because nine rows could not fill five buckets, so a page turn rebuilt the rail's whole structure. That was a symptom of the page size rather than of grouping: the rail now asks for 30 rows instead of 9 (Backends 60 instead of 21), which is enough for the sections to read as structure and turns five times fewer pages. The order of the sections is fixed, so what changes between pages is membership, not arrangement. Grouped while browsing, flat while searching, as before: once a term is typed the buckets stand between the reader and the answer. Also gives GalleryLoader a class and a testid instead of six inline style declarations on a bare div, which is why nothing could select it. e2e: full suite 359 passing, including a new spec asserting the search box keeps its focus and its value across a refetch, and that a cold start still shows the skeleton. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * perf(gallery): stop invalidating the VRAM estimate caches on every request Searching or turning a page felt slow. It was not the search and not the listing: /api/models answers in 3-9ms. It was the VRAM estimate, which the gallery asks for once per row, and which took ~2.3s every single time however often the same model was asked about. pkg/vram already caches what makes that expensive - the remote content-length probes, the GGUF metadata reads and the HF repo sizes. Those caches key on a gallery generation counter, and AvailableGalleryModelsCached triggered a background refresh on every call, with each refresh bumping the counter. One page view is one listing request plus thirty estimate requests, each of which re-read the gallery and started another refresh, so the generation moved constantly and every cache entry was stale before it could ever be read. The caches were dead in production. Three changes, each doing one thing: A refresh interval. The cached list is still served immediately; this only decides how often re-fetching from upstream is worth starting. Five minutes, as a package variable so tests can drive it without waiting. A generation bump only when the gallery actually changed. An unchanged gallery re-fetched on schedule must not throw away work that is still valid, which is the difference between an estimate costing nothing and costing a network round trip. A separate "loaded" flag. The cache engaged on `cached != nil`, so a gallery that legitimately holds nothing read as never-loaded and took the blocking path on every call, bumping the generation each time. Found by the test for the interval, which could not pass while this was true. Measured against a live instance with 1,595 models: one estimate, repeated 2.3s -> 2ms a page of 30, in parallel 10s -> 0.04s A first, genuinely unseen model still costs its remote probe. That is inherent; what changed is that it is now paid once per model per gallery version rather than once per request. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * perf(gallery): warm VRAM estimates at startup, and stop the UI waiting on them Two halves of the same complaint: the gallery stalls on VRAM estimation. Server side, the estimates are now warmed in the background at startup. Estimating an entry nobody has asked about costs a remote probe of its weight files, and the gallery needs one per row, so the first visitor was paying for the whole page. The warm-up walks the gallery in the order the UI lists it, so the first page is ready before anyone reaches it. It is bounded and it never blocks: 300 entries at 4 at a time by default, on its own goroutine, stopping with the server's context. Warming the whole gallery would be thousands of probes on every boot, which is rude to the upstream and slow to finish; warming nothing leaves the first page paying two seconds a row. Anything past the limit still warms itself on first view. LOCALAI_VRAM_WARM_LIMIT=0 turns it off for an air-gapped host, LOCALAI_VRAM_WARM_CONCURRENCY=1 slows it for a metered link. Client side, the page no longer waits on estimates it does not need yet. It fired one request per row at once; a browser allows about six connections per host, so thirty estimates took every slot and the request behind a click - the variant list, an install - queued behind work nobody asked for. That is the freeze: the list was already usable, and the UI was busy fetching sizes. Four at a time leaves room for the interactive request to overtake, and a row whose estimate is still in flight says "sizing…" rather than leaving a blank where a number will appear. buildEstimateInput moves to core/gallery as EstimateInput, since the handler and the warmer both need it. Measured against 1,595 models, from a cold boot: page 1, 30 estimates in parallel 10s -> 0.04s full warm-up (299 of 300 entries) 3m, in the background Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-5 [Claude Code] * chore: untrack data/.local_user_id and ignore the runtime data dir `local-ai run` writes its instance state under ./data when started from the repo root, which is exactly what a contributor testing a build does. The identity file ended up committed on this branch by a `git add -A` while verifying the gallery changes against a live instance. Anchored, so it matches the runtime directory at the repo root and not a `data` directory nested inside some package. 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> |
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|
localai-org-maint-botandlocalai-org-maint-bot
|
1189c6825b |
feat(tracing): persist bounded trace histories (#11203)
* feat(tracing): persist bounded trace histories Retain API and backend traces below the data path, restore them at initialization, and serialize clears with asynchronous consumers. Assisted-by: Codex:gpt-5 * fix(tracing): satisfy persistence security checks Document why persisted filenames cannot escape the trace directory and explicitly ignore the best-effort temporary-file cleanup result. Assisted-by: Codex:gpt-5 [golangci-lint] --------- Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> |
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|
localai-org-maint-botandDaria Korenieva
|
9bfd71387b |
feat(stores): add Valkey Search vector store backend (#11196)
* feat: add Valkey Search vector store backend Add a new built-in Go gRPC store backend 'valkey-store' that implements the four Stores RPCs (Set/Get/Delete/Find) against the Valkey Search module (FT.*) using the pure-Go github.com/valkey-io/valkey-go client. It is selected via the existing per-request 'backend' field on /stores, so there is no proto or HTTP API change, and it mirrors the in-memory local-store while adding persistence across restarts and opt-in HNSW. Each vector is a Valkey HASH keyed by hex(little-endian float32); the index is created lazily on first Set (FLAT+COSINE by default), cosine similarity is derived as 1-distance, and namespaces get a collision-resistant token. Includes unit tests (valkey-go mock) and env-gated integration tests against valkey/valkey-bundle, plus build/matrix/gallery wiring and docs. Assisted-by: Kiro:claude-opus-4.8 golangci-lint Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: recover persisted index dimension, harden Find - Load now recovers the persisted vector DIM from FT.INFO (not just index existence), so a post-restart Set/Find validates against the real DIM instead of silently re-learning a wrong one and dropping mismatched vectors from the index. This also restores Find's dimension check after a restart. - StoresFind treats a dropped/missing index as an empty store (empty result, no error) and clears the stale indexCreated flag, matching local-store's empty-store behaviour. - StoresSet reuses checkDims for its per-key length check so the four RPCs share one dimension-guard implementation. - Add unit tests for FT.INFO dimension recovery, loadIndexState, and the dropped-index Find path. Assisted-by: Kiro:claude-opus-4.8 Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: TLS ServerName/CA, Find nil-check, config fail-fast Addresses external review comments on the valkey-store backend: - StoresFind now rejects a nil/empty query Key before dereferencing it, so a malformed gRPC request can no longer panic the backend. - TLS: derive ServerName (SNI) from the VALKEY_ADDR host so certificate verification works for IP-addressed endpoints, and add VALKEY_TLS_CA_CERT (custom CA bundle) and VALKEY_TLS_SKIP_VERIFY (testing-only) knobs. - Config integer parsing now fails fast on a malformed value (e.g. VALKEY_HNSW_M=1x6) instead of silently defaulting, matching the fail-fast behaviour of the index-algo/distance-metric validation. - Add VALKEY_DB (SELECT n) support for logical-DB isolation. - Cap the human-readable part of a namespace token at 64 chars so a very long model name cannot produce an unbounded key prefix / index name (the appended short hash keeps distinct namespaces collision-free). - Document the KNN-query injection-safety invariant (fields are constants) and why StoresGet uses a single aggregate DoMulti deadline for reads. - Unit tests for the Find nil/empty-key guard, fail-fast HNSW parsing, and VALKEY_DB parsing/validation; docs + .env updated for the new vars. Assisted-by: Kiro:claude-opus-4.8 golangci-lint Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: configure valkey-store via model config richiejp asked that the valkey-store backend take its configuration from a model config rather than process-wide VALKEY_* environment variables, so multiple stores can each have their own Valkey config within one LocalAI process. This removes every env access from the backend and routes config through the model-config seam every other backend uses. - config.go: loadConfig(opts *pb.ModelOptions) now parses the model config `options:` list (key:value strings, split on the first ':') instead of os.Getenv. Option keys mirror the old VALKEY_* names without the prefix (addr, index_algo, distance_metric, ...). Defaults, fail-fast validation and the mandatory client name are unchanged. - store.go: Load threads opts into loadConfig; TLS comments/errors renamed off the VALKEY_* names. - core/backend/stores.go: StoreBackend and NewVectorStore take a *config.ModelConfigLoader, resolve the per-store ModelConfig by store name, and pass its Options (and Backend when unset) to the backend via WithLoadGRPCLoadModelOpts. No config -> default backend + built-in defaults, preserving the zero-config experience. - Endpoints/routes/application: thread the config loader to StoreBackend. - Unit + integration tests: configure via options; the integration test passes addr through the model-config path (VALKEY_ADDR is now only the test harness locating the server). - docs + .env: document the model-config options, drop the env var table. Assisted-by: Kiro:claude-opus-4.8 Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Remove valkey-store informational comment from .env The backend is configured via model config, not env vars — the comment was unnecessary noise in .env. The configuration is already documented in docs/content/features/stores.md. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * feat(valkey-store): gate Load on NamespacePrefix to refuse autoload probing Mirror local-store's pattern: reject model names without store.NamespacePrefix so the model loader's greedy autoload probe cannot bind an arbitrary model name to the vector store backend (the #9287 failure mode). Also adds unit tests for the gate covering: prefixed namespace, prefix alone, unprefixed model name, empty model, and nil opts. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * feat(valkey-store): add username_env/password_env credential indirection Add support for resolving Valkey credentials from environment variables named in the model config, mirroring cloud-proxy's api_key_env pattern. This keeps secrets out of model YAML files and lets distinct store configs each reference their own credentials. Options: username_env / password_env name the env var holding the value. The direct username / password options still work and take precedence when both are set (backward compatible). Includes 5 unit tests and updated stores.md documentation. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * fix: correct rebase artifacts in backend-matrix.yml and Makefile Fix two issues introduced by the conflict-resolution script during the rebase onto master: 1. .github/backend-matrix.yml: valkey-store entries were merged INTO the cloud-proxy entries (duplicate keys in same YAML map items) instead of being separate list items. This broke cloud-proxy Linux builds and the cloud-proxy darwin entry lost its build-type/lang. Fixed by making them standalone entries and restoring cloud-proxy exactly as on master. 2. Makefile: duplicated .NOTPARALLEL and docker-build-backends lines. Collapsed to single lines that are master's current content plus the valkey-store additions. Also adds the three optional pickups from #10801: - /valkey-store in .gitignore (the built binary) - valkey-store row in docs/content/reference/compatibility-table.md - valkey-store line in backend/README.md Signed-off-by: Daria Korenieva <daric2612@gmail.com> --------- Signed-off-by: Daria Korenieva <daric2612@gmail.com> Co-authored-by: Daria Korenieva <daric2612@gmail.com> |
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|
Richard Palethorpe
|
49ef40a187 |
feat(classifier/VAD): support voice control on low power devices (#10804)
* feat(llama-cpp): route Score through the slot loop Score previously bypassed the slot loop with a direct llama_decode: a conflict guard aborted the whole process if scoring raced generation, the config validator had to reject score alongside chat/completion/embeddings, and every candidate re-decoded the full shared prompt. Add SERVER_TASK_TYPE_SCORE to the (patched) upstream server so score tasks are scheduled like any other slot work: generation and scoring serialize naturally, the shared prompt is decoded once per call, and the slot's prompt cache carries the conversation prefix across calls. Context checkpoints at the score boundary and at the cache-divergence point keep SWA/hybrid/recurrent models (e.g. LFM2.5) from re-prefilling the whole prompt per candidate: warm-turn scoring on a 6-option set drops from ~8s to ~0.5s on a desktop CPU. The conflict guard and the validation split are removed; declaring score with generation usecases on one config is now supported and shares the slot cache. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): classifier wire types and pipeline config Wire types and YAML config for realtime classifier mode: sessions carry a localai_classifier extension (options with canned replies/tool calls, softmax threshold, normalization, history trimming, fallback modes, and a deterministic wake-word address gate), mirrored by pipeline.classifier in the model YAML and surfaced in the config-meta registry. The localai.classifier.result server event reports the full score distribution per turn. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): classifier response flow Classifier-mode responses: instead of autoregressive generation, each user turn is prefill-scored against the option list (router.ScoreClassifier prompt/candidate shapes over the Score primitive) and the winning option's canned reply and tool call are emitted through the existing response machinery. Below-threshold turns take the configured fallback (none / canned reply / generate); empty transcripts and unaddressed turns (wake word not mentioned) skip scoring entirely. The scoring probe defaults to the latest user message only — small scorers echo canned replies from prior turns back as the top option otherwise. Built for hardware that can afford prompt processing but not decode: with slot-based Score the option list stays KV-cached across turns, so a turn costs roughly one forward pass over the new words. session_update_error events now carry the validation cause instead of a generic message. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(realtime): bound the VAD tick's scan window and buffer retention The VAD tick loop re-scanned the entire input buffer every 300ms and only trimmed it on zero-segment ticks or commits. Audio that keeps producing segments without a committing pause (steady noise a mic pipeline lets through, music, continuous speech) grew the buffer toward the 100MB cap with each tick rescanning all of it — O(n^2), measured at ~3.3ms of silero per buffered second: past ~90s retained, ticks run back to back and pin ~4 cores until the stream stops. Silero's recurrent state only carries a few hundred ms of context, so rescanning old audio buys nothing. Clip the slice handed to the VAD to the largest silence the commit test can need to measure (server_vad silence window or the semantic eagerness fallback) plus a warm-up margin, and rebase the returned segment times so every downstream consumer keeps whole-buffer coordinates. An open turn whose clipped window is all silence now commits (the silence outran the window) instead of being discarded as no-speech. Independently, retain at most 90s of raw buffer, rebasing the live-feed and EOU cursors on trim — this also bounds the previously unbounded VAD-error path. Turn boundaries are otherwise unchanged: no forced commits, no new coordinator states. pipeline.turn_detection.vad_window_sec can widen the scan window; values below the automatic floor are ignored. The tick body is extracted into vadTick so specs can drive turn detection synchronously (same shape as classifySoundWindow); the babble reproduction that pinned 4 cores now plateaus under 10% of one core. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(backend): let per-model threads override the global default ModelOptions overrode a set per-model threads value with the app-level --threads whenever the latter was non-zero — and WithThreads defaults it to the physical core count, so it always was. The YAML threads: knob has been dead config: a tiny VAD model could never opt down from the global pool size. SetDefaults already fills an unset per-model value from the app config, which is the intended precedence; resolve threads through a helper that honors it (explicit threads: 0 still means unset). Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * chore(gallery): single-thread the silero VAD Silero is a ~2MB recurrent model with no exploitable graph parallelism: measured per-call latency is identical at 1 and 10 ORT threads, while every extra pool thread just spin-waits between the realtime loop's frequent tiny inferences. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * docs(realtime): classifier mode, VAD scan window, threads precedence Document the realtime classifier mode (options, threshold guidance, wake-word address gate, empty-transcript handling), the VAD scan window and 90s buffer retention (pipeline.turn_detection.vad_window_sec), the per-model threads precedence, and the M3 classifier note in the realtime state-machine design doc. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * perf(llama-cpp): score all candidates in one batched decode One scoring call is now a single SERVER_TASK_TYPE_SCORE task: the slot decodes the shared prefix (prompt + longest common candidate token prefix) once, then forks one sequence per candidate off it (metadata-only for the unified KV cache, copy-on-write for recurrent state) and decodes every candidate's unique tail in one llama_decode. Previously each candidate was its own task that restored the boundary checkpoint and re-decoded its full tail sequentially, paying per-candidate task and decode overhead. The context reserves SERVER_SCORE_FORK_SEQS extra sequence ids (and recurrent-state cells) beyond the parallel slots via the new common_params::n_seq_score_forks. Forking requires the unified KV cache (already this backend's default) since per-sequence streams would shrink n_ctx_seq; an explicit kv_unified:false disables forking and Score calls that need it fail cleanly. Candidates beyond the fork/output budget decode in successive chunks. Wire contract and scores are unchanged: per-token logprobs are stitched from the shared region and the forked tails. Verified bitwise deterministic call-to-call and independent of candidate order (no cross-fork leakage via equal-length candidate swap); ranking matches the per-candidate implementation on the drone battery (winner softmax 0.99996 vs 0.99997), and >16-candidate chunking, prefix-of-another and empty candidates all pass. Measured on a desktop CPU: warm /api/score calls 0.52s -> 0.23s; warm realtime classifier turns 196-303ms. The 9-candidate drone turn decodes ~17 unique tail tokens in one batch instead of nine sequential ~220ms checkpoint-restore tasks. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(realtime): gate scoring capacity by model usecase Reserve llama.cpp scoring slots only for models that explicitly declare the score usecase, while allowing score to coexist with chat and completion. Reject incompatible unified-KV settings and classifier activation on models without scoring capacity. Propagate application defaults when resolving realtime and preload pipeline stages so unset thread counts are resolved consistently without overriding explicit model settings. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ci): honor APT mirrors in the prebuilt llama-cpp compile step The builder-prebuilt path installs gcc-14 with apt directly and ignored the APT_MIRROR/APT_PORTS_MIRROR build args the from-source path already honors, so an ubuntu mirror outage broke every arm64 backend build. Pass the args into the stage and run apt-mirror.sh (already in the build context via COPY . /LocalAI) before the apt step. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): classifier argument slots via constrained completion Hybrid classify-then-complete: a classifier option's canned tool call can declare typed argument slots (number | enum | string, with defaults and prompt hints) referenced as "{{name}}" in the arguments template. When the option wins, the slots are filled by a short grammar-constrained completion that continues the exact scoring prompt — rendered by the same cached ScoreClassifier, so the llama.cpp prompt cache is already warm — with the chosen route JSON re-opened at the first slot field. A GBNF grammar pins the field skeleton and frees only the values; temperature 0, a couple dozen tokens at most (~300ms on a desktop CPU for two slots). Slot declarations and hints ride the option descriptions in the shared system prompt, informing scoring and the fill alike at no per-turn token cost. The localai.classifier.result event carries the final arguments and a fill_latency_ms. On inference failure the slots' defaults apply; a slot without a default fails the response (or falls through with fallback.mode: generate). Slot filling requires completion alongside score in the scoring model's known_usecases. Verified end-to-end on the Pi drone demo: "fly forward three meters" in distance mode classifies forward and infers {"distance": 3, "units": "meters"} in ~310ms, and the drone flies exactly 3 units. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): splice filled slot values into classifier replies A classifier option's spoken reply can now reference its tool's argument slots ("Going forward {{distance}} {{units}}."): the values inferred by the slot-fill completion — or the recovery defaults — are spliced into the reply as plain text before it is emitted, so what the assistant says confirms what it actually inferred. Placeholders without a value stay literal, and options without slots are untouched. FillToolArguments now returns the raw slot values alongside the spliced arguments JSON to make the reply templating possible. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(realtime): harden classifier slot completion Reserve context for constrained slot filling, size completions from their encoded output, and encode enum grammar literals as valid JSON. Reject empty enum values and cover the failure modes with regression tests. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): prewarm the classifier scoring prompt on registration Swapping a session's classifier option list (a voice-switched command mode, for instance) made the next turns pay a full re-prefill of the new option-list prompt — measured 2.4s vs 0.3s warm on a desktop CPU, and worse: on hybrid-memory models like LFM2.5, whose state cannot be partially rewound (llama.cpp can only restore checkpoints), *every* probe change re-prefilled from scratch whenever the last checkpoint missed the probe boundary, so even same-list turns intermittently cost full prefills. Registering an option list (pipeline seed or session.update) now fires a best-effort background prewarm: two throwaway scores with distinct probes. The first prefills the new option-list prompt; the second, diverging exactly where per-turn probe text starts, plants the backend's rewind point (KV checkpoint) at the stable-prefix boundary that every real turn reuses. The prewarm hides behind the canned mode-switch reply — by the time it finishes speaking, the cache is warm. Idempotent per option set, detached from the registering request's lifetime. Measured on the drone demo (LFM2.5-1.2B, desktop CPU): first turn after a mode switch 2374ms -> 340ms; intermittent same-list full prefills (1.3-2.1s) all -> under 0.5s. For clients that swap lists frequently, options: [parallel:2] on the scoring model additionally keeps one slot per list via prefix-similarity routing (+26MB RSS, unified KV). Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * perf(llama-cpp): checkpoint scoring at the caller-declared stable prefix Hybrid-memory models (LFM2.5 shortconv, Qwen3.5 deltanet — where new small models are headed) cannot rewind their state, so any prompt-cache reuse that needs a rewind falls back to a full re-prefill. For classifier scoring that meant every probe change re-processed the whole option-list prompt: the server's checkpoints were placed reactively (at wherever the previous task happened to diverge), so a checkpoint past the next divergence was erased rather than restored — measured as intermittent 2-10s turns on prompts with a 95%+ common prefix. The classifier now computes the probe-invariant prompt prefix once (the byte-wise common prefix of two synthetic probe renders) and declares its length with every Score request; the server maps it to a token boundary and forces a KV checkpoint exactly there on each score prefill. That checkpoint sits at or before every future divergence under the same option list, so it always survives and always restores — repeat scoring costs probe+candidates regardless of how the probe changes. Also: - prewarm reruns on every option-list registration instead of memoizing per list: with boundary checkpoints a redundant rewarm costs two probe-sized decodes, while skipping one after a slot eviction (three lists sharing fewer slots evict in LRU cascades) silently moves a full re-prefill onto the user's next turn - new llama.cpp backend option rs_seq:N exposes bounded recurrent-state rollback outside speculative decoding; measured impractical for deltanet-scale states (65GB for 64 snapshots on Qwen3.5-4B) but cheap insurance for small-state models - docs: the multi-list recipe (parallel:N + sps:0.5 — the default slot similarity threshold funnels distinct lists onto one slot) Measured on the drone demo (LFM2.5-1.2B scorer, desktop CPU), steady state: every turn 285-421ms including mode switches, vs 2.4s post-switch and intermittent 1.3-2.9s re-prefills before. Assisted-by: Claude:claude-fable-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(realtime): align classifier cache guidance Document the single-score prewarm behavior and clean the vendored score patch formatting. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(llama-cpp): guard score task for fork backends TurboQuant and Bonsai reuse the primary gRPC server against llama.cpp forks that do not carry LocalAI's slot-based Score patches. Compile the Score integration only for the patched primary backend and return UNIMPLEMENTED from fork builds instead of referencing absent task types and common_params fields. Assisted-by: Codex:gpt-5 [gh] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(dev): generate gRPC code before commit lint The coverage phase regenerates ignored protobuf bindings, but lint runs first and can fail against missing or stale output. Generate the pinned bindings before lint so the gate always type-checks the current schema. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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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>
|
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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>
|
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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>
|
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mudler's LocalAI [bot]andEttore Di Giacinto
|
f01038f479 |
fix(modelartifacts): stage each writer's artifact in its own partial tree (#10995)
Every writer used to stage into the same `.artifacts/.partial/<cacheKey>`. That was safe only because the artifact lock held: two writers that both believed they had it opened the same blob with O_APPEND and interleaved their bytes into one file, while the resume probe read the other writer's in-flight size. SHA verification caught the damage only after both had burned the entire download. #10986 restored the lock's precondition on CIFS but left the dependency in place. Suffix the staging tree with a writer identity drawn once per process run, so concurrent writers cannot corrupt each other whatever the lock does. The lock stops being a correctness dependency and becomes a pure efficiency optimisation: a lock failure now costs a duplicated download, not a corrupted one. Commit stays an atomic rename. The loser of a commit race reconciles onto the winner's tree instead of surfacing a bare ENOTEMPTY for work that actually succeeded, since the artifact is content-addressed and both trees hold the same verified bytes. Writer-unique staging means a crashed writer's tree is no longer overwritten by its successor, so two things are added to keep it from becoming a disk leak and a resume regression: - A sweep reclaims trees whose contents have been untouched for 24h, matching the window the startup reaper already uses for stray *.partial files. It reads the newest mtime anywhere inside the tree, because writing a blob never touches an ancestor, and refuses any name this package did not write. A live download writes continuously, and the downloader's stall watchdog aborts a silent one long before it could look abandoned. - Adoption lets a restarted process claim a dead predecessor's tree for the same artifact and resume from its bytes, which a tens-of-gigabytes repo depends on. The claim is an atomic rename, so racing adopters cannot both win. It runs only under the artifact lock - which is released exactly when the owning process dies - and only on a tree idle for 5 minutes as a second line of defence for when the lock does not exclude. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]andEttore Di Giacinto
|
65bdbc4ee3 |
fix(http): make /readyz reflect startup readiness, plus gitignore and coverage-ratchet fixes (#10989)
* fix(http): make /readyz reflect startup readiness instead of always 200 /readyz was registered as a static handler returning 200 unconditionally, so it carried no information: it was green whenever it could be reached at all. Readiness could not distinguish "serving" from "still starting", and any future change that started the HTTP listener earlier would silently turn the probe into a lie. Track startup completion on the Application (atomic flag, flipped at the very end of New() on the success path only) and have the readiness handler consult it per request, returning 503 with a small JSON body while startup is in progress. A nil readiness source fails open so embedders keep the historical behaviour. /healthz is deliberately left readiness-independent. Liveness and readiness answer different questions, and failing liveness during a long preload makes an orchestrator restart the pod mid-download so the preload never finishes. This matters because since #10949 the startup preload materializes HuggingFace artifacts for managed backends: tens of GB for a large model (31 GB observed on a live cluster). Both probes stay in quietPaths and stay exempt from auth. Note the listener is still started only after New() returns, so today the not-ready state is not observable over HTTP. Moving the listener earlier is a separate, deliberate decision and is not made here. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * chore(gitignore): anchor the mock-backend pattern so its source dir is traversable The bare `mock-backend` pattern matched the *directory* tests/e2e/mock-backend/, not just the binary built into it. Git will not descend into an ignored directory even for tracked files, so `git add tests/e2e/mock-backend/main.go` required -f. This was hit while working on #10970. Anchor it to the artifact's full path. The built binary stays ignored (it is also covered by tests/e2e/mock-backend/.gitignore) while the source directory becomes traversable again. Verified with `git check-ignore -v`: a new source file under tests/e2e/mock-backend/ is no longer ignored, and the binary produced by `make build-mock-backend` still is. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * chore(coverage): raise the coverage ratchet from 48.5% to 54.2% The committed baseline had drifted well below reality: it still read 48.5% while a full instrumented run measures 54.2%. A stale-low baseline makes the gate meaningless — coverage could regress by more than 5 percentage points and still pass. Raising a ratchet is a deliberate act, not something to fold into an unrelated fix, so it gets its own commit. The headroom was earned by tests landed in #10946, #10947, #10948, #10949, #10956, #10967, #10968, #10970 and #10975. Measured with `make test-coverage` on this branch (the same instrumented run `make test-coverage-baseline` uses: ginkgo over ./pkg and ./core plus the in-process tests/e2e suite, --covermode=atomic, --coverpkg over core/... and pkg/..., generated protobuf excluded). The run completed with exit 0 and zero spec failures; the total was then written with the exact command the test-coverage-baseline target uses: go tool cover -func=coverage/coverage.out \ | awk '/^total:/{gsub(/%/,"",$NF); print $NF}' > coverage-baseline.txt Verified afterwards with scripts/coverage-check.sh, which reports OK. Note the measured figure includes the readiness specs added earlier on this branch, so it is a demonstrated floor rather than an estimate. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]andEttore Di Giacinto
|
fb4c61d1c9 |
fix(distributed): configurable remote model-load timeout, and reap the load when it times out (#10948)
* fix(distributed): make the remote LoadModel deadline configurable
The router hardcoded a 5 minute gRPC deadline for the remote LoadModel
call. Staging finishes before the timer starts, so those five minutes
cover only the worker backend's own checkpoint load and pipeline init.
A cold load of meituan-longcat/LongCat-Video-Avatar-1.5 (~83 GB) on an
ARM64 Thor worker fails at exactly 302s with DeadlineExceeded while the
backend process is still making progress (CPU time accumulating, RSS
moving as weights are mapped), so the load was cut short rather than
wedged.
Add LOCALAI_NATS_MODEL_LOAD_TIMEOUT / --model-load-timeout mirroring the
existing backend-install timeout knob, defaulting to 5m so unset
clusters keep today's behaviour.
The cold-load hold ceiling (which bounds how long one load may hold the
per-model advisory lock) was derived from the install timeout alone, so
raising the load deadline past it would have been silently clipped.
Derive it from both budgets via ModelLoadCeilingFor:
max(install + load + 5m staging margin, 25m)
With the defaults that is 15m + 5m + 5m = 25m, identical to the previous
constant, and the 25m floor means shrinking either budget can never
tighten the ceiling below what clusters relied on before.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): reap the abandoned replica when a remote load times out
The gRPC deadline on the remote LoadModel call only cancels the client
side. A backend blocked in a synchronous weight load never observes its
cancelled handler context, so when scheduleAndLoad gave up it left the
worker loading with nobody waiting for the result.
Observed on an ARM64 Thor worker loading LongCat-Video-Avatar-1.5: the
client returned DeadlineExceeded at 302s, and the backend process was
still alive 30 minutes later having pulled ~57GB from HuggingFace. Every
retry stacked another multi-GB loader on the worker; they had to be
reaped by hand via POST /api/nodes/:id/models/unload.
Send backend.stop for the exact `modelID#replicaIndex` process key we
just abandoned. The exact key matters: a bare model ID stops every
replica on that node, including healthy ones serving traffic.
Only a deadline or cancellation triggers the reap. Any other LoadModel
failure is the backend answering, which means its handler returned and
the process is idle - stopping it there would discard a warm process and
its downloaded weights. The reap is best-effort and never replaces the
load error the caller is waiting on.
The `modelID#replicaIndex` format was already hand-rolled in two places
(the worker's buildProcessKey and pkg/model's log store). Rather than add
a third, export model.BackendProcessKey from pkg/model, the lowest common
dependency of both sides.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 golangci-lint
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
|
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Tai AnandAnai-Guo
|
45b8047736 |
fix(p2p): serialize access to p2pCtx/p2pCancel (#10839) (#10861)
StopP2P() read and wrote a.p2pCtx/a.p2pCancel without holding a.p2pMutex, and StartP2P() reassigned both fields with no lock at all -- including when RestartP2P() calls it from a background goroutine after releasing the mutex. Both paths are reachable from POST /api/settings (empty p2p_token -> StopP2P, non-empty -> RestartP2P), so concurrent requests race on the same fields. Take a.p2pMutex in StopP2P and around the field publication in StartP2P, factor the shared teardown into stopP2PLocked() so RestartP2P reuses it, and route the goroutine error path through StopP2P instead of touching a.p2pCancel unlocked. Signed-off-by: Anai-Guo <antai12232931@anaiguo.com> Co-authored-by: Anai-Guo <antai12232931@anaiguo.com> |
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LocalAI [bot]andEttore Di Giacinto
|
c1a891662c |
refactor(settings): single declarative registry for runtime settings (fixes the #10845 bug class) (#10864)
* feat(settings): add declarative runtime-settings field registry One fieldSpec row per RuntimeSettings field, with a reflection completeness spec so a field added without a registry row is a red test instead of a silently-dropped setting (the #10845 bug class). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * refactor(settings): drive ToRuntimeSettings/ApplyRuntimeSettings from the field registry Behavior-preserving: ~350 hand-written per-field lines become two loops over runtimeSettingsFields, gated by a To->Apply->To round-trip spec. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * feat(settings): baseline-driven startup merge for persisted runtime settings ApplyRuntimeSettingsAtStartup compares the live config against DefaultRuntimeBaseline (option-less-run defaults incl. kong-injected flag defaults) instead of per-field == 0 guards. Fixes persisted lru_eviction_max_retries, tracing_max_items, agent_job_retention_days, memory_reclaimer_threshold, galleries and autoload flags being silently ignored at boot. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * fix(settings): registry-driven startup merge, applied before consumers loadRuntimeSettingsFromFile becomes a thin wrapper over ApplyRuntimeSettingsAtStartup and runs at the top of New(), before model configs capture app-level defaults. WithThreads stops eagerly resolving 0 so a persisted thread count survives restart while LOCALAI_THREADS still wins (#10845); the physical-core fallback moves after the merge. Also: run.go now injects the memory-reclaimer threshold unconditionally so the option-less boot matches DefaultRuntimeBaseline and a UI-saved threshold survives restart. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * refactor(settings): file watcher delegates to the registry merge; shared API-key merge Manual edits to runtime_settings.json now behave like a boot-time load (env still wins) instead of the inverted diverged-from-startup guard that ignored most manual edits. MergeAPIKeys dedups env keys in one place for the endpoint and the watcher. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * docs(settings): document unified runtime-settings precedence Document the single env/CLI > runtime_settings.json > defaults rule, applied identically at boot, on POST /api/settings, and on manual file edits, plus the two known limitations (default-valued env vars are indistinguishable from unset; API-changed fields hot-apply on the next restart only). Also add a completion debug log when the watcher applies runtime_settings.json. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 * test(settings): reset the global VRAM cap leaked by the round-trip spec The round-trip spec applies vram_budget=12GiB, whose post-loop hook installs a process-global default cap; without a reset every spec ordered after it runs under that phantom budget. Also drop a stale enumeration in the ApplyRuntimeSettings doc comment. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-fable-5 --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
|
bbe018c1a0 |
feat(bonsai): PrismML llama.cpp fork backend + Bonsai/Ternary-Bonsai gallery models (#10834)
feat(bonsai): add PrismML llama.cpp fork backend + Bonsai gallery models Adds a new `bonsai` backend that runs the PrismML fork of llama.cpp (github.com/PrismML-Eng/llama.cpp, `prism` branch), which ships the Q1_0 (1-bit) and Q2_0 (ternary / 1.58-bit) weight-quantization kernels used by the Bonsai and Ternary-Bonsai models. Stock llama.cpp cannot decode these quants. Modeled on the turboquant backend: reuses backend/cpp/llama-cpp/grpc-server.cpp against the fork's libllama via a thin wrapper Makefile, so the sub-2-bit models are served with the same OpenAI-compatible API. No grpc-server allow-list patch is needed (bonsai adds weight quants, transparent to the server, not KV-cache types), and the reused server compiles cleanly against the fork with no skew patches (validated locally via a CPU docker build; patches/ is present but empty for any future re-pin skew). Backend wiring: backend/cpp/bonsai/, .docker/bonsai-compile.sh, backend/Dockerfile.bonsai, top-level Makefile targets, backend-matrix.yml build rows (CPU, CUDA 12/13, L4T, SYCL f32/f16, Vulkan, ROCm/hipblas), backend/index.yaml meta-backend + per-platform images, and a nightly bump_deps entry tracking the `prism` branch. Gallery: 8 entries across 4 families - bonsai-8b-1bit, ternary-bonsai-8b (+g64, +pq2), bonsai-27b-1bit (vision), ternary-bonsai-27b (+pq2, +g64, vision). The 27B models wire the mmproj vision tower; the DSpark speculative drafter GGUFs are not wired (custom semi-autoregressive drafter, not a standard llama.cpp draft model). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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|
Tai AnandAnai Guo
|
808312b4b9 |
fix(watchdog): guard StopWatchdog with watchdogMutex to prevent double close (#10841) (#10859)
fix(watchdog): guard StopWatchdog with watchdogMutex to prevent double close StopWatchdog checked, closed and cleared a.watchdogStop without holding a.watchdogMutex, while startWatchdog and RestartWatchdog reassign and close the same channel under that lock. POST /api/settings dispatches to StopWatchdog or RestartWatchdog depending on ApplicationConfig.WatchdogShouldRun(), so both are reachable concurrently. Two callers can observe a non-nil watchdogStop and both close it, which panics with 'close of closed channel' and takes the server down. Take the mutex, matching the other two writers. StopWatchdog is only called from the settings handler, which holds no lock, so this cannot deadlock. Fixes #10841 Co-authored-by: Anai Guo <antai12232931@anaiguo.com> |
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Tai AnandAnai-Guo
|
688f904a10 |
fix(runtime-settings): apply persisted threads/context_size/f16 at startup (#10853)
ApplyRuntimeSettings persists the performance settings (threads, context_size, f16) on the live /api/settings path, but the startup loader loadRuntimeSettingsFromFile never read them back, so a value saved via the Middleware UI was silently ignored on the next restart: the model booted with the CLI/physical-core default and GET /api/settings echoed that default instead of the saved value (#10845). Threads needs special handling: unlike context_size/f16, WithThreads eagerly resolves an unset (0) value to xsysinfo.CPUPhysicalCores() at option-apply time, so options.Threads is never 0 in the loader and the usual "== default" heuristic cannot tell an env/CLI value from the physical-core fallback. Detect LOCALAI_THREADS/THREADS explicitly so the env still wins over the persisted file value. Signed-off-by: Anai-Guo <Anai-Guo@users.noreply.github.com> Co-authored-by: Anai-Guo <Anai-Guo@users.noreply.github.com> |
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LocalAI [bot]andEttore Di Giacinto
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3601174ce0 |
fix(distributed): make per-node backend upgrade actually upgrade (#10838)
* test(core/http): make the suite's HTTP port overridable app_test.go and openresponses_test.go hardcoded 127.0.0.1:9090. When another service already listens on 9090 the suite does not fail fast: the server goroutine logs the bind error and the specs then poll whatever is squatting the port until Eventually times out. On machines where 9090 is permanently taken this makes the pre-commit coverage gate impossible to pass. Introduce testHTTPAddr, defaulting to 127.0.0.1:9090 (what CI has always used) and overridable via LOCALAI_TEST_HTTP_PORT for local runs. Assisted-by: Claude:claude-fable-5 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): make per-node backend upgrade actually upgrade The node detail page's Upgrade button reused the node-scoped install path (POST /api/nodes/:id/backends/install). That fires NATS backend.install with force=false, and the worker's install handler is deliberately "ensure installed": when the backend binary already exists on disk it short-circuits without touching the gallery. Since only an installed backend can be upgraded, the whole chain was a guaranteed successful no-op - the UI then toasted "backend upgraded" without even waiting for the async job. Route upgrades through the real force-reinstall path instead: - BackendManager.UpgradeBackend now receives the ManagementOp (like InstallBackend already did) so implementations can honor op.TargetNodeID. - DistributedBackendManager.UpgradeBackend scopes the backend.upgrade fan-out to op.TargetNodeID when set, and errors when the target node does not report the backend as installed. - New POST /api/nodes/:id/backends/upgrade endpoint enqueues an Upgrade=true node-scoped op (async 202 + jobID, mirroring install). - NodeDetail UI calls the new endpoint and reports the dispatch ("Upgrading ... on this node...") instead of claiming success; the Operations panel tracks the actual job. Verified against a live local cluster (NATS + Postgres + two workers): the target worker stops the running process, force-reinstalls from the gallery and re-downloads the OCI image; the second worker receives no backend.upgrade event; upgrading a backend missing from the target node fails the job with a clear error. Assisted-by: Claude:claude-fable-5 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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bcc41219f7 |
feat: materialize Hugging Face model artifacts (#10825)
* feat(config): add model artifact source contract Assisted-by: Codex:GPT-5 [Codex] * feat(downloader): add authenticated raw-byte progress Assisted-by: Codex:GPT-5 [Codex] * feat(huggingface): resolve immutable snapshot manifests Assisted-by: Codex:GPT-5 [Codex] * feat(models): add artifact storage primitives Assisted-by: Codex:GPT-5 [Codex] * feat(models): materialize pinned Hugging Face snapshots Assisted-by: Codex:GPT-5 [Codex] * feat(models): bind managed snapshots at runtime Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): materialize model artifacts during install Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): declare managed Hugging Face artifacts Assisted-by: Codex:GPT-5 [Codex] * feat(models): preload managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * fix(gallery): retain shared artifact caches on delete Assisted-by: Codex:GPT-5 [Codex] * feat(models): report artifact acquisition progress Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load managed models from ModelFile Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load staged speech model snapshots Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): use staged snapshots in engine backends Assisted-by: Codex:GPT-5 [Codex] * test(distributed): cover staged artifact snapshots Assisted-by: Codex:GPT-5 [Codex] * docs: explain managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * docs: add product design context Assisted-by: Codex:GPT-5 [Codex] * feat(ui): show model artifact download progress Assisted-by: Codex:GPT-5 [Codex] * Eagerly materialize Hugging Face artifacts Materialize HF-backed model references as managed GGUF artifacts during load, with lazy download retained only as fallback. Assisted-by: Codex:GPT-5 [shell] * Refactor HF downloads through a shared executor Assisted-by: Codex:GPT-5 [shell] * drop Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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4056283aa4 |
[voice] feat: add managed voice cloning profiles (#10799)
* feat(ui): add voice library workflow Give administrators a production-ready flow to record or upload consented reference audio, manage reusable profiles, inspect API usage, discover compatible models, and hand a saved voice directly to text-to-speech. Assisted-by: Codex:gpt-5 * feat(voice): add managed voice cloning profiles Make reusable reference voices manageable through the admin API instead of requiring model-directory and YAML edits. Discover compatible installed and gallery models from server-side backend capabilities, retain explicit model configuration controls, and stage saved references for supported backends. Expose profile management through REST and MCP, document backend-specific behavior, and cover the workflow from profile creation through real Qwen3-TTS synthesis. Harden the agent-job HTTP test against completion racing cancellation. Assisted-by: Codex:gpt-5 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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40c29db8c4 |
fix(logs): capture backend logs by default in single mode (#10742)
Backend log capture into the per-model BackendLogStore (which feeds the UI "Backend Logs" page and /api/backend-logs) was opt-in and off by default in single mode, while worker/distributed mode force-enables it via SetBackendLoggingEnabled(true). There was no CLI flag either, so the only way to populate the store was the Settings UI toggle - and the page was silently empty out of the box. Distributed "just worked"; single mode looked broken. Default EnableBackendLogging to true in NewApplicationConfig so single mode matches worker mode. The store is a small in-memory ring buffer, so the cost is negligible. Now that the default is on, loadRuntimeSettingsFromFile's usual "only flip false->true" merge would ignore a persisted false and revert the UI toggle-off on every restart. There is no env var/CLI flag for this setting, so an explicit persisted value is now authoritative in both directions, letting the toggle-off survive a restart. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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97175f4b5a |
feat(model): debounce model loads after a failure to stop retry-storms (#10728)
A client that keeps polling a model whose load fails (e.g. a backend that crashes deterministically on init) triggered a fresh backend start on every request: request -> load -> crash in ~10s -> 500, repeat on the next poll. Each attempt could leak GPU/CUDA state, and under LOCALAI_SINGLE_ACTIVE_BACKEND it kept stealing the active slot from healthy models. The existing loading-coalesce map only dedups *concurrent* loads, so sequential polls were never covered. Track load failures per modelID in ModelLoader. After a load fails, refuse fresh load triggers for that model until a cooldown elapses, returning a typed ModelLoadCooldownError that the HTTP layer maps to 503 with a Retry-After header. The cooldown grows exponentially per consecutive failure (base, doubling, capped at 5m) and resets on a successful load. The coalesced follower-retry of an in-flight burst bypasses the gate, so a genuinely concurrent burst still gets its one retry -- only new, independent triggers are refused, matching the report's "refuse new load-triggers" wording. Configurable via --model-load-failure-cooldown / LOCALAI_MODEL_LOAD_FAILURE_COOLDOWN (default 10s, 0 disables), plumbed through ApplicationConfig and applied unconditionally at startup. Closes #10719 Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Richard Palethorpe
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eb32cd9073 |
feat(realtime): eager blocking pipeline warm-up + /backend/load API (#10662)
Realtime sessions previously lazy-loaded each pipeline sub-model (VAD,
transcription, LLM, TTS) on first use, so every cold session paid a
per-request model-load stall and load errors only surfaced mid-stream.
Warm the whole pipeline eagerly and blockingly at session start
(including the voice-gate speaker-recognition model, which an enforced
gate blocks each utterance on; compaction's summary_model stays lazy
since it only runs off the response path):
- Add backend.PreloadModel / PreloadModelByName as the single load path
for every modality (no transcription special-case; backend-omitted
configs are deprecated).
- The realtime session blocks on Model.Warmup and returns a
model_load_error to the client if any stage fails to load;
updateSession warms in the background. Opt out per pipeline with
pipeline.disable_warmup, exposed as a UI toggle via the
config-metadata registry.
Add a LocalAI-native POST /backend/load (and /v1/backend/load) that
pre-loads a model -- expanding realtime pipelines into their sub-models
-- as the inverse of /backend/shutdown. There is one preload engine
(backend.PreloadStages): the realtime Warmup methods, /backend/load and
the --load-to-memory startup flag all use it, so --load-to-memory now
also expands pipeline models and records load-failure traces. Pipeline
sub-model alias resolution is likewise shared
(ModelConfigLoader.LoadResolvedModelConfig). Surface the endpoint
everywhere an admin manages models:
- MCP admin tool load_model (httpapi + inproc clients, safety/catalog
prompts, catalog/dispatch tests).
- "Load into memory" action in the React models UI.
- Swagger regenerated; docs moved to the general backend-monitor page
since it is not realtime-specific.
Fix a Traces UI crash ("json: unsupported value: -Inf"): audio-snippet
RMS/peak now floor at a finite dBFS, and backend-trace data is sanitized
to drop non-finite floats before marshaling. The sanitizer is
copy-on-write -- it runs on every RecordBackendTrace, so containers are
only re-allocated on the paths that actually changed.
Migrate core/http/openresponses_test.go onto the prebuilt mock-backend
the rest of the http suite already uses -- it was the last spec still
pointing at a real HuggingFace model, so it 404'd wherever no vision
backend was built -- and fix its item_reference specs to send the
spec's "id" field instead of "item_id", which the handler never
accepted.
Assisted-by: Claude:claude-opus-4-8 Claude Code
Signed-off-by: Richard Palethorpe <io@richiejp.com>
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LocalAI [bot]andEttore Di Giacinto
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6eea3ef2ac |
fix(backends): make backend install ops idempotent unless forced (#10643)
* fix(backends): make backend install ops idempotent unless forced POST /backends/apply hardcoded force=true through LocalBackendManager.InstallBackend, so applying an already-installed backend re-downloaded and re-extracted the whole artifact every time. API clients that ensure a backend exists at startup paid a full OCI image pull on every boot. Backend install ops now default to non-forced — an installed, runnable backend short-circuits (the orphaned-meta reinstall path in InstallBackendFromGallery is preserved) — and reinstall stays available: - ManagementOp gains a Force field; the local manager passes it through instead of hardcoding true. - /backends/apply accepts an optional "force" boolean in the body. - The React UI install route keeps forcing, since its button doubles as the explicit "Reinstall backend" action. Distributed installs already behaved this way (workers skip when the binary exists unless force is set); this aligns single-node behavior. Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(backends): don't force-reinstall LOCALAI_EXTERNAL_BACKENDS on boot The startup loop for LOCALAI_EXTERNAL_BACKENDS runs InstallExternalBackend for each listed backend on every boot, and its gallery-name path hardcoded force=true — so every start re-downloaded and re-extracted each listed backend's OCI image even when it was installed and runnable. Supervising apps that list several backends paid several full OCI pulls per launch. Give InstallExternalBackend an explicit force parameter (it only affects the gallery-name fallback; URI installs always write) and pass: - false from the boot loop and `local-ai backends install` (idempotent ensure — `backends upgrade` is the refresh path), - op.Force from the local manager's external-URI op, - the request's force on the worker install path and true on its upgrade path (behavior unchanged). Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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29001a88c1 |
fix(distributed): don't let a dead worker pin the model-load advisory lock (#10600)
* fix(distributed): don't let a dead worker pin the model-load advisory lock In distributed mode a chat request could fail with: failed to route model with internal loader: routing model ...: loading model ...: advisorylock: acquiring lock <id>: ERROR: canceling statement due to lock timeout (SQLSTATE 55P03) Root cause is two independent defects in the cross-replica model-load path: 1. SmartRouter.Route holds a per-model PostgreSQL advisory lock for the whole cold-load sequence, which includes installBackendOnNode -> InstallBackend, a NATS request-reply with a 15m deadline (DefaultBackendInstallTimeout) that ignored ctx. When the chosen worker died mid-install, the holder sat on the lock for up to 15m. The detached loadCtx (WithoutCancel) had no deadline, so nothing capped the hold. 2. The acquiring statement, pg_advisory_lock(), is subject to any deployment global lock_timeout. A common operator setting (e.g. 10s) aborts the wait with SQLSTATE 55P03, so every other replica's request for that model hard -errored instead of waiting for the in-progress load and reusing it. For the ~15m window the model was effectively unroutable. Fixes: - advisorylock.WithLockCtx (postgres): SET lock_timeout = 0 on its dedicated connection (RESET before it returns to the pool) so the Go context, not a deployment-wide GUC, governs how long we wait. Waiters now block and then re-check, reusing the model another replica just loaded. - SmartRouter: bound the detached loadCtx with a single ModelLoadCeiling so the lock is always released in bounded time even if a sub-step wedges. Default is the configured backend.install deadline + 10m (staging + LoadModel margin), so a legitimately slow load is never cut. - installBackendOnNode: use singleflight.DoChan + select on ctx.Done() so the install wait honors cancellation; the ceiling can then actually free a caller pinned behind a dead worker. The shared install still coalesces via singleflight. Reproduced both defects as failing tests first (a real 55P03 against a testcontainer with a short lock_timeout; a wedged install that blocks Route) and confirmed green. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(distributed): bound advisory-lock wait instead of disabling lock_timeout Setting lock_timeout = 0 to override a deployment's short global lock_timeout meant "wait forever" server-side. Safe for SmartRouter.Route (its loadCtx now carries the model-load ceiling) but unsafe for the schema-migration callers that pass context.Background(): a holder whose session never releases would hang them indefinitely. Derive the server-side lock_timeout from the caller's context instead: its remaining budget plus a margin (so the Go context's cancellation still wins with a clean error and the server bound is only a backstop), or a finite 30m backstop when the context has no deadline. Never zero - "wait forever" is no longer possible, while a deployment's hostile short lock_timeout is still overridden so legitimate cross-replica waits don't fail with 55P03. Added a spec proving a deadline-less waiter gives up at the (shrunk) backstop rather than hanging. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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LocalAI [bot]andEttore Di Giacinto
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fd8cebd0b3 |
fix(watchdog): persist UI-saved Check Interval across restarts (#10601) (#10605)
fix(watchdog): persist a UI-saved Check Interval across restarts (#10601) The watchdog Check Interval saved via /api/settings reverted to 500ms on every restart, while the idle/busy timeouts persisted correctly. Root cause: NewApplicationConfig baseline-defaulted WatchDogInterval to 500ms, whereas the idle/busy timeouts default to 0. The startup loader (loadRuntimeSettingsFromFile) applies a persisted runtime_settings.json value only when the field is still at its zero default - its heuristic for "this wasn't set by an env var". Because the interval was always 500ms at that point, the loader never read the persisted value back, so the saved interval was silently discarded on each boot. Fix: drop the non-zero baseline default so the interval behaves like the sibling timeouts (0 = unset). The effective 500ms default is now supplied at the watchdog layer: WithWatchdogInterval ignores a non-positive value so DefaultWatchDogOptions' 500ms is preserved (and a 0 interval can never turn the watchdog loop into a busy spin). Also mirror the interval in the live config file watcher alongside idle/busy, and report the real 500ms default (not the stale "2s") from ToRuntimeSettings. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |