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8
Commits
| Author | SHA1 | Message | Date | |
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 Ettore Di Giacinto
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1cf847f29e |
feat(distributed): stop workers listening, and stop them advertising
A worker now opens no listener on a routable interface and states no endpoint at registration. Backend processes and the file-transfer server bind loopback, and the frontend reaches both through the tunnel the worker dials. The bind address is built from loopbackHost, the same constant the tunnel's grpc tag dials, so "the worker binds where its tunnel dials" is one fact in one place rather than two literals that can drift. All three advertisement sites are closed, not one: the registration body, RegisterNodeRequest, and the per-backend address in the install reply. That third one was hiding a live bug. stopModelExact refuses a stop whose ExpectedAddress does not match what the worker recorded for the process. The worker recorded 127.0.0.1:port; handleBackendInstall reported advertiseHost:port; the router stored the reported one and sent it straight back. On any worker whose advertise host was not 127.0.0.1, every acknowledged model stop failed with an address mismatch. Nothing caught it because the e2e harness set LOCALAI_ADVERTISE_ADDR=127.0.0.1, which made the rewrite a no-op. Removing the rewrite makes the two strings the same by construction. The brief was wrong about two of the four functions it called dead. effectiveBasePort is the base of the backend port allocator and resolveHTTPAddr is the file server's bind address; deleting them would have deleted the port allocator and the file server. Only the two advertise* helpers were dead, and addr_test.go is rewritten rather than deleted, because the port arithmetic it pinned still needs pinning. NodeModel.Address survives with a narrowed meaning and is renamed WorkerLocalAddress, along with the install reply field that feeds it. The frontend still has to say WHICH backend process on a worker it means, and the port in this string is how it says it: it travels as a stream target and the worker dials its own loopback. The gorm column and the json key stay "address", so neither a migration nor an API break rides along. Every fall-back to the node's address is gone. installBackendOnNode now errors when a worker reports success without naming one, because substituting the now-always-empty node address would name an empty target, and the worker refuses that as an invalid stream, which is classified as the worker answering about its backend. That is the "a present worker reads as something it is not" class this phase forbids. DistributedModelStore.Range had the same shape and was already wrong: it built each remote model's client from the node's base gRPC port, never the port a backend process listens on, so Free and Status went to the wrong place. It uses the replica's address now. BackendNode.Address and HTTPAddress are kept but made provably inert: no writer, no reader that acts on them, and Register force-clears both on re-registration so an upgraded worker's stale advertisement does not outlive its own upgrade in the API and the Nodes page. Dropping the columns is a ~90-site edit across the specs, the e2e suite, the MCP dto and the UI; it is recorded as a follow-up rather than folded in here. A persistent tunnel 401 still does not trigger re-registration, and now for a reason rather than a deferral. Register CLEARS the node's replica rows, so re-registering on a 401 would delete a live worker's rows on every retry, and under the name collision that causes the 401 the two workers would take turns doing it forever: a credential failure causing model reclamation. It also cannot fix the named cause, since a collision is indistinguishable from a restart. The 401 log now names both causes and says nothing can reach this worker, which is true only now that it has no listener. The container healthcheck did not break the way the brief expected, since the listener still exists on loopback and the probe runs inside the container. It did have a real #10987 defect that this change makes the common case: it read LOCALAI_SERVE_ADDR only, while effectiveBasePort reads LOCALAI_ADDR first, so a worker on a non-default base port was probed on 50050 and reported unhealthy while working. It follows the same precedence now. Docs, the compose file and the e2e harness are updated in step: no inbound rule or published port is needed for a worker, the two advertise variables are gone, the remaining address variables are read for their port only, the firewall-the-file-transfer-port warning is narrowed to the LOCALAI_HTTP_ADDR opt-out, and the upgrade-order note no longer claims the worker still listens. The Nodes page showed node.address, which is now always blank, so it shows the node id instead. Eight mutations, all red on a named spec, including reverting the loopback bind, re-adding the address to the registration body, restoring both node-address fall-backs, dropping the force-clear, storing the endpoint's address again, and un-fixing the healthcheck. One of them caught a defect in a spec I had just written: it asserted 200 where the endpoint returns 201, which went unnoticed because core/http/endpoints/localai is not on the task's verify list. It is run here. Assisted-by: Claude Opus 5 [claude-code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Richard Palethorpe
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f8d3f31594 |
fix(vram): contain malformed GGUF metadata (#11374)
Recover parser panics at metadata boundaries, skip unneeded remote arrays, and use the parser's overflow-hardened release. Keep detached gallery workers and CrispASR probes from terminating their processes on malformed GGUF input. Disable startup warming in the provided Compose files as an operational fallback. Assisted-by: Codex:gpt-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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mudler's LocalAI [bot]andEttore Di Giacinto
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0eb8a1188d |
fix(worker): give the worker a real health endpoint and a mode-aware HEALTHCHECK (#10999)
fix(worker): give the worker a real health endpoint (#10987) The image bakes in a single HEALTHCHECK that curls http://localhost:8080/readyz, but the same image also runs `local-ai worker`, which serves HTTP on the gRPC base port minus one and never binds 8080. Every worker container was therefore permanently `unhealthy` (43 consecutive failures observed on a production node), which is worse than having no healthcheck: a genuinely broken worker and a perfectly good one both report `unhealthy`, so the signal carries no information and orchestration that keys on it misbehaves. The worker already served /readyz on that port via the file-transfer server, but as a constant 200 — it only proved the listener was bound, which is precisely the failure mode at issue. Readiness now tracks the live NATS connection: all of a worker's actual work (backend lifecycle events, inference dispatch, file staging) arrives over NATS, so a worker whose link is dead is up and useless. Registration is already implied, since the server only starts after registration succeeds. This reports something the controller cannot already see. The node registry's status/last_heartbeat is fed by an HTTP heartbeat to the frontend, a different network path from NATS — a worker can keep heartbeating while its NATS connection is dead and still look healthy in the registry. /healthz stays a constant 200: liveness must not follow readiness, or a NATS blip becomes a cluster-wide restart storm. The HEALTHCHECK is now a script that derives its endpoint from the mode the container is actually running plus the env vars that configure the bind address, so a frontend moved off 8080 with LOCALAI_ADDRESS (broken the same way) and a worker on a non-default base port are both probed correctly. Modes with no HTTP surface (agent-worker, one-shot commands) report healthy rather than false-unhealthy. HEALTHCHECK_ENDPOINT remains as an explicit override, so the workaround shipped in docker-compose.distributed.yaml keeps working; both overrides in that file are now unnecessary and have been removed. Also fixes the latent --start-period gap. Since #10949 a frontend's startup preload materializes HuggingFace artifacts before the HTTP server binds (31 GB observed on a live cluster), so a healthy replica can legitimately fail probes for a long time. --start-period is Docker's knob for exactly this: failures inside it leave the container `starting` instead of burning retries, and it ends early on the first success, so a generous 60m costs a fast-starting container nothing. --timeout drops from 10m to 10s — it is a per-probe deadline, and a localhost curl that has not answered in 10s is itself the fault being detected. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]andEttore Di Giacinto
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f3d829e2ef |
feat(distributed): add LOCALAI_DISTRIBUTED_SHARED_MODELS to skip staging on shared volumes (#10556) (#10566)
In distributed mode, even when the frontend and workers share the same models directory via a shared volume mount, starting a model on a worker re-staged (re-downloaded) it: stageModelFiles always uploads model files into a tracking-key-namespaced subdir on the worker, and the staging probe only checks that staged location, so a file already present on the shared volume at the canonical path was never reused. Add a config switch LOCALAI_DISTRIBUTED_SHARED_MODELS (default false). When enabled, the operator asserts that all nodes mount the SAME models directory at the SAME path, so staging is unnecessary: the frontend's absolute model paths are already valid on the worker. In that mode stageModelFiles returns the cloned opts unchanged without uploading, leaving the path fields pointing at their canonical absolute paths so the worker loads them directly from the shared volume. The value is plumbed from DistributedConfig through SmartRouterOptions into the SmartRouter. Docs and docker-compose.distributed.yaml updated. 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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Ettore Di Giacinto
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3810fe1a1e |
fix(distributed): worker container healthcheck always unhealthy
The Dockerfile's HEALTHCHECK probes http://localhost:8080/readyz, which is the OpenAI API server port. When the same image runs as a worker, it listens on the gRPC base port (50051) and an HTTP file transfer server on port-1 (50050) — nothing on 8080 — so docker always reports the container as unhealthy. Add unauthenticated /readyz and /healthz endpoints to the worker's HTTP file transfer server, and override HEALTHCHECK_ENDPOINT for worker-1 in the distributed compose file. Disable the healthcheck for agent-worker since it is NATS-only and exposes no HTTP server. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:claude-opus-4-7 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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2da1a4d230 |
feat(distributed): per-node backend installation from the gallery
In distributed mode the Backends gallery used to fan every install out to every worker — fine for auto-resolving (meta) backends like llama-cpp where each node picks its own variant, but wrong for hardware-specific builds like cpu-llama-cpp that would silently land on every GPU node. Adds a node-targeted install path through the existing POST /api/nodes/:id/backends/install plumbing, with two entry points: - Backends gallery row gets a split-button in distributed mode. Auto- resolving keeps "Install on all nodes" as the primary; chevron menu opens the picker. Hardware-specific routes the primary directly to the picker — no fan-out path on the row. - Nodes-page drawer gets a "+ Add backend" button that navigates to /app/backends?target=<node-id>; the gallery scopes itself to that node (banner, single per-row install button, Reinstall/Remove for already- installed). One gallery, two scopes — no second UI to maintain. The picker (new NodeInstallPicker) shows a 3-state suitability column (Compatible / Override / Installed), an auto-expanding variant override disclosure that fires when selected nodes have no working GPU, parallel per-node installs with inline status and Retry-failed-nodes, and a mismatch confirm that names the consequence on the button itself. A 409 fan-out guard on /api/backends/apply protects CLI/Terraform/script users from the same footgun: hardware-specific installs in distributed mode now return code "concrete_backend_requires_target" with a human- readable error and a meta_alternative pointer. The gallery list payload now surfaces capabilities, metaBackendFor and per-row nodes (NodeBackendRef) so the picker and the new Nodes column have everything they need without re-walking the gallery client-side. GODEBUG=netdns=go is set on the compose services because the cgo DNS resolver follows the container's nsswitch.conf to host systemd-resolved (127.0.0.53), unreachable from inside the container; the pure-Go resolver reads /etc/resolv.conf directly and uses Docker's embedded DNS. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude Code:claude-opus-4-7[1m] [Edit] [Bash] [Read] [Write] |
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Ettore Di Giacinto
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551ebdb57a |
fix(distributed): correct VRAM/RAM reporting on NVIDIA unified-memory hosts (#9545)
Workers on NVIDIA unified-memory hardware (DGX Spark / GB10, Jetson AGX Thor, Jetson Orin/Xavier/Nano) were reporting `available_vram=0` back to the frontend, so the Nodes UI showed the node as fully used even when most of the unified memory was actually free. Three causes addressed: * `isTegraDevice` only matched `/sys/devices/soc0/family == "Tegra"`. DGX Spark (SBSA) reports JEDEC codes there instead — `jep106:0426` for the NVIDIA manufacturer — so the Tegra/unified-memory fallback never ran. Renamed to `isNVIDIAIntegratedGPU` and extended to also match `jep106:0426[:*]` via `/sys/devices/soc0/soc_id`. * The unified-iGPU code defaulted the device name to `"NVIDIA Jetson"` when `/proc/device-tree/model` was missing. That's what happens for Thor inside a docker container, and always on DGX Spark. New `nvidiaIntegratedGPUName` resolves via dt-model → `/sys/devices/soc0/machine` → `soc_id` lookup (`jep106:0426:8901` → `"NVIDIA GB10"`) so the Nodes UI labels the box correctly. * Worker heartbeat sent `available_vram=0` (or total-as-available) when VRAM usage was momentarily unknown — e.g. when `nvidia-smi` intermittently failed with `waitid: no child processes` under containers without `--init`. Each such heartbeat overwrote the DB and made the UI flip to "fully used". `heartbeatBody` now omits `available_vram` in that case so the DB keeps its last good value. Also updates the commented GPU blocks in both compose files with `NVIDIA_DRIVER_CAPABILITIES=compute,utility`, `capabilities: [gpu, utility]`, and `init: true`, and documents the requirement in the distributed-mode and nvidia-l4t pages. Without `utility`, NVML/`nvidia-smi` are absent inside the container, which is what put the DGX Spark worker into the buggy fallback in the first place. Detection verified on live hardware (dgx.casa / GB10 and 192.168.68.23 / Thor) by running a cross-compiled probe of the new helpers on both host and inside the worker container. Assisted-by: Claude:opus-4.7 [Claude Code] |
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Ettore Di Giacinto
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59108fbe32 |
feat: add distributed mode (#9124)
* feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |