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7 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
LocalAI [bot]
|
447c186089 |
fix(distributed): make backend upgrade actually re-install on workers (#9708)
* fix(distributed): make backend upgrade actually re-install on workers UpgradeBackend dispatched a vanilla backend.install NATS event to every node hosting the backend. The worker's installBackend short-circuits on "already running for this (model, replica) slot" and returns the existing address — so the gallery install path was skipped, no artifact was re-downloaded, no metadata was written. The frontend's drift detection then re-flagged the same backends every cycle (installedDigest stays empty → mismatch → "Backend upgrade available (new build)") while "Backend upgraded successfully" landed in the logs at the same time. The user-visible symptom: clicking "Upgrade All" silently does nothing and the same N backends sit on the upgrade list forever. Two coupled fixes, one PR: 1. Force flag on backend.install. Add `Force bool` to BackendInstallRequest and thread it through NodeCommandSender -> RemoteUnloaderAdapter. UpgradeBackend (and the reconciler's pending-op drain when retrying an upgrade) sets force=true; routine load events and admin install endpoints keep force=false. On the worker, force=true stops every live process that uses this backend (resolveProcessKeys for peer replicas, plus the exact request processKey), skips the findBackend short-circuit, and passes force=true into gallery.InstallBackendFromGallery so the on-disk artifact is overwritten. After the gallery install completes, startBackend brings up a fresh process at the same processKey on a new port. 2. Liveness check on the fast path. installBackend's "already running" branch read getAddr without verifying the process was alive, so a gRPC backend that died without the supervisor noticing left a stale (key, addr) entry. The reconciler then dialed that address, got ECONNREFUSED, marked the replica failed, retried install — and the supervisor said "already running addr=…" again. Loop forever, exactly what we observed on a node whose llama-cpp process had died but whose supervisor record persisted. Verify s.isRunning(processKey) before trusting getAddr; if the entry is stale, stopBackendExact cleans up and we fall through to a real install. Backwards-compatible: the new Force field is omitempty, older workers ignore it (their default behavior matches force=false). The signature change on NodeCommandSender.InstallBackend is internal-only. Verified: unit tests in core/services/nodes pass (108s suite). The pre-existing core/backend build break (proto regen pending for word-level timestamps) blocks core/cli and core/http/endpoints/localai package tests but is unrelated to this change. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-7 [Claude Code] * test(e2e/distributed): pass force=false to adapter.InstallBackend NodeCommandSender.InstallBackend gained a final force bool in the upgrade-force commit; the e2e distributed lifecycle tests still called the old 8-arg signature and broke compilation. These tests exercise the routine install path (single replica, default behavior), so force=false preserves their existing semantics. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-7 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Richard Palethorpe
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8e43842175 |
feat(vllm, distributed): tensor parallel distributed workers (#9612)
* feat(vllm): build vllm from source for Intel XPU
Upstream publishes no XPU wheels for vllm. The Intel profile was
silently picking up a non-XPU wheel that imported but errored at
engine init, and several runtime deps (pillow, charset-normalizer,
chardet) were missing on Intel -- backend.py crashed at import time
before the gRPC server came up.
Switch the Intel profile to upstream's documented from-source
procedure (docs/getting_started/installation/gpu.xpu.inc.md in
vllm-project/vllm):
- Bump portable Python to 3.12 -- vllm-xpu-kernels ships only a
cp312 wheel.
- Source /opt/intel/oneapi/setvars.sh so vllm's CMake build sees
the dpcpp/sycl compiler from the oneapi-basekit base image.
- Hide requirements-intel-after.txt during installRequirements
(it used to 'pip install vllm'); install vllm's deps from a
fresh git clone of vllm via 'uv pip install -r
requirements/xpu.txt', swap stock triton for
triton-xpu==3.7.0, then 'VLLM_TARGET_DEVICE=xpu uv pip install
--no-deps .'.
- requirements-intel.txt trimmed to LocalAI's direct deps
(accelerate / transformers / bitsandbytes); torch-xpu, vllm,
vllm_xpu_kernels and the rest come from upstream's xpu.txt
during the source build.
- requirements.txt: add pillow + charset-normalizer + chardet --
used by backend.py and missing on the Intel install profile.
- run.sh: 'set -x' so backend startup is visible in container
logs (the gRPC startup error path was previously opaque).
Also adds a one-line docs example for engine_args.attention_backend
under the vLLM section, since older XE-HPG GPUs (e.g. Arc A770)
need TRITON_ATTN to bypass the cutlass path in vllm_xpu_kernels.
Tested end-to-end on an Intel Arc A770 with Qwen2.5-0.5B-Instruct
via LocalAI's /v1/chat/completions.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(vllm): add multi-node data-parallel follower worker
vLLM v1's multi-node story is one process per node sharing a DP
coordinator over ZMQ -- the head runs the API server with
data_parallel_size > 1 and followers run `vllm serve --headless ...`
with matching topology. Today LocalAI can already configure DP on the
head via the engine_args YAML map, but there's no way to bring up the
follower nodes -- so the head sits waiting for ranks that never
handshake.
Add `local-ai p2p-worker vllm`, mirroring MLXDistributed's structural
precedent (operator-launched, static config, no NATS placement). The
worker:
- Optionally self-registers with the frontend as an agent-type node
tagged `node.role=vllm-follower` so it's visible in the admin UI
and operators can scope ordinary models away via inverse
selectors.
- Resolves the platform-specific vllm backend via the gallery's
"vllm" meta-entry (cuda*, intel-vllm, rocm-vllm, ...).
- Runs vLLM as a child process so the heartbeat goroutine survives
until vLLM exits; forwards SIGINT/SIGTERM so vLLM can clean up its
ZMQ sockets before we tear down.
- Validates --headless + --start-rank 0 is rejected (rank 0 is the
head and must serve the API).
Backend run.sh dispatches `serve` as the first arg to vllm's own CLI
instead of LocalAI's backend.py gRPC server -- the follower speaks
ZMQ directly to the head, there is no LocalAI gRPC on the follower
side. Single-node usage is unchanged.
Generalises the gallery resolution helper into findBackendPath()
shared by MLX and vLLM workers; extracts ParseNodeLabels for the
comma-separated label parsing both use.
Ships with two compose recipes (`docker-compose.vllm-multinode.yaml`
for NVIDIA, `docker-compose.vllm-multinode.intel.yaml` for Intel
XPU/xccl) plus `tests/e2e/vllm-multinode/smoke.sh`. Both vendors are
supported (NCCL for CUDA/ROCm, xccl for XPU) but mixed-vendor DP is
not -- PyTorch's process group requires every rank to use the same
collective backend, and NCCL/xccl/gloo don't interoperate.
Out of scope (deferred): SmartRouter-driven placement of follower
ranks via NATS backend.install events, follower log streaming through
/api/backend-logs, tensor-parallel across nodes, disaggregated
prefill via KVTransferConfig.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test(vllm): CPU-only end-to-end test for multi-node DP
Adds tests/e2e/vllm-multinode/, a Ginkgo + testcontainers-go suite
that brings up a head + headless follower from the locally-built
local-ai:tests image, bind-mounts the cpu-vllm backend extracted by
make extract-backend-vllm so it's seen as a system backend (no gallery
fetch, no registry server), and asserts a chat completion across both
DP ranks. New `make test-e2e-vllm-multinode` target wires the docker
build, backend extract, and ginkgo run together; BuildKit caches both
images so re-runs only rebuild what changed. Tagged Label("VLLMMultinode")
so the existing distributed suite isn't pulled along.
Two pre-existing bugs surfaced by the test:
1. extract-backend-% (Makefile) failed for every backend, because all
backend images end with `FROM scratch` and `docker create` rejects
an image with no CMD/ENTRYPOINT. Fixed by passing
--entrypoint=/run.sh -- the container is never started, only
docker-cp'd, so the path doesn't have to exist; we just need
anything that satisfies the daemon's create-time validation.
2. backend/python/vllm/run.sh's `serve` shortcut for the multi-node DP
follower exec'd ${EDIR}/venv/bin/vllm directly, but uv bakes an
absolute build-time shebang (`#!/vllm/venv/bin/python3`) that no
longer resolves once the backend is relocated to BackendsPath.
_makeVenvPortable's shebang rewriter only matches paths that
already point at ${EDIR}, so the original shebang slips through
unchanged. Fixed by exec-ing ${EDIR}/venv/bin/python with the script
as an argument -- Python ignores the script's shebang in that case.
The test fixture caps memory aggressively (max_model_len=512,
VLLM_CPU_KVCACHE_SPACE=1, TORCH_COMPILE_DISABLE=1) so two CPU engines
fit on a 32 GB box. TORCH_COMPILE_DISABLE is currently mandatory for
cpu-vllm: torch._inductor's CPU-ISA probe runs even with
enforce_eager=True and needs g++ on PATH, which the LocalAI runtime
image doesn't ship -- to be addressed in a follow-up that bundles a
toolchain in the cpu-vllm backend.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(vllm): bundle a g++ toolchain in the cpu-vllm backend image
torch._inductor's CPU-ISA probe (`cpu_model_runner.py:65 "Warming up
model for the compilation"`) shells out to `g++` at vllm engine
startup, regardless of `enforce_eager=True` -- the eager flag only
disables CUDA graphs, not inductor's first-batch warmup. The LocalAI
CPU runtime image (Dockerfile, unconditional apt list) does not ship
build-essential, and the cpu-vllm backend image is `FROM scratch`,
so any non-trivial inference on cpu-vllm crashes with:
torch._inductor.exc.InductorError:
InvalidCxxCompiler: No working C++ compiler found in
torch._inductor.config.cpp.cxx: (None, 'g++')
Bundling the toolchain in the CPU runtime image would bloat every
non-vllm-CPU deployment and force a single GCC version on backends
that may want clang or a different version. So this lives in the
backend, gated to BUILD_TYPE=='' (the CPU profile).
`package.sh` snapshots g++ + binutils + cc1plus + libstdc++ + libc6
(runtime + dev) + the math libs cc1plus links (libisl/libmpc/libmpfr/
libjansson) into ${BACKEND}/toolchain/, mirroring /usr/... layout. The
unversioned binaries on Debian/Ubuntu are symlink chains pointing into
multiarch packages (`g++` -> `g++-13` -> `x86_64-linux-gnu-g++-13`,
the latter in `g++-13-x86-64-linux-gnu`), so the package list resolves
both the version and the arch-triplet variant. Symlinks /lib ->
usr/lib and /lib64 -> usr/lib64 are recreated under the toolchain
root because Ubuntu's UsrMerge keeps them at /, and ld scripts
(`libc.so`, `libm.so`) hardcode `/lib/...` paths that --sysroot
re-roots into the toolchain.
The unversioned `g++`/`gcc`/`cpp` symlinks are replaced with wrapper
shell scripts that resolve their own location at runtime and pass
`--sysroot=<toolchain>` and `-B <toolchain>/usr/lib/gcc/<triplet>/<ver>/`
to the underlying versioned binary. That's how torch's bare `g++ foo.cpp
-o foo` invocation finds cc1plus (-B), system headers (--sysroot), and
the bundled libstdc++ (--sysroot, --sysroot is recursive into linker).
`run.sh` adds the toolchain bin dir to PATH and the toolchain's
shared-lib dir to LD_LIBRARY_PATH -- everything else (header search,
linker search, executable search) is encapsulated in the wrappers.
No-op for non-CPU builds, the dir doesn't exist there.
The cpu-vllm image grows by ~217 MB. Tradeoff is acceptable -- cpu-vllm
is already a niche profile (few users compared to GPU vllm) and the
alternative is a backend that crashes at first inference unless the
operator manually sets TORCH_COMPILE_DISABLE=1, which silently disables
all torch.compile optimizations.
Drops `TORCH_COMPILE_DISABLE=1` from tests/e2e/vllm-multinode -- the
smoke now exercises the real compile path through the bundled toolchain.
Test runtime is +20s for the warmup compile, still <90s end to end.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(vllm): scope jetson-ai-lab index to L4T-specific wheels via pyproject.toml
The L4T arm64 build resolves dependencies through pypi.jetson-ai-lab.io,
which hosts the L4T-specific torch / vllm / flash-attn wheels but also
transparently proxies the rest of PyPI through `/+f/<sha>/<filename>`
URLs. With `--extra-index-url` + `--index-strategy=unsafe-best-match`
uv would pick those proxy URLs for ordinary PyPI packages —
anthropic/openai/propcache/annotated-types — and fail when the proxy
503s. Master is hitting the same bug on its own l4t-vllm matrix entry.
Switch the l4t13 install path to a pyproject.toml that marks the
jetson-ai-lab index `explicit = true` and pins only torch, torchvision,
torchaudio, flash-attn, and vllm to it via [tool.uv.sources]. uv won't
consult the L4T mirror for anything else, so transitive deps fall back
to PyPI as the default index — no exposure to the proxy 503s.
`uv pip install -r requirements.txt` ignores [tool.uv.sources], so the
l4t13 branch in install.sh now invokes `uv pip install --requirement
pyproject.toml` directly, replacing the old requirements-l4t13*.txt
files. Other BUILD_PROFILEs continue using libbackend.sh's
installRequirements and never read pyproject.toml.
Local resolution test (x86_64, dry-run) confirms uv hits the L4T
index for torch and falls through to PyPI for everything else.
Assisted-by: claude-code:claude-opus-4-7-1m [Read] [Edit] [Bash] [Write]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
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LocalAI [bot]
|
170d55c67d |
fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups (#9652)
* fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups
Two distinct bugs were causing tight retry loops in the distributed scheduler:
1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model
was loaded on multiple nodes and only some matched the current selector,
the function returned the lowest-in_flight node — even one the selector
excluded. Route()'s post-check then fell through to scheduleNewModel,
which targeted the matching node where the model was already at
MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded
model on that node was the one being requested, and it was busy), so
every request looped through "evicting LRU" → "all models busy".
Fix: thread an optional candidateNodeIDs filter through
FindAndLockNodeWithModel. Route() resolves the selector once via a new
resolveSelectorCandidates helper and passes the matching IDs to both
the cached-replica lookup and scheduleNewModel. The same helper
replaces the inline selector block in scheduleNewModel.
2. ScheduleAndLoadModel (reconciler scale-up path) fell back to
scheduleNewModel with backendType="" when no replica had ever been
loaded for a model. The worker rejected the resulting backend.install
("backend name is empty") on every reconciler tick (~30s).
Fix: remove the broken fallback. When GetModelLoadInfo has nothing
stored, return a clear error instead of firing a doomed NATS install.
The reconciler's existing scale-up failure log surfaces it once per
tick; the model auto-replicates as soon as Route() serves it once and
stores load info.
Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that
cleanup attempt usually hits "model not found" because LoadModel failed
before registering the process, and the outer "Failed to load model"
error already carries the real reason.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
* test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard
Two regression tests for the bugs fixed in the previous commit:
1. FindAndLockNodeWithModel — registry-level integration tests verify the
candidateNodeIDs filter:
- Returns the included node even when an excluded node has lower
in_flight (the original selector-mismatch loop scenario).
- Returns not-found when the model is loaded only on excluded nodes,
forcing Route() to fall through to a fresh schedule instead of
reusing the excluded replica.
2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up
path returns an error and does NOT fire backend.install when no replica
has been loaded yet. fakeUnloader gains an installCalls slice so this
negative assertion is direct.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto
|
6b63b47f61 |
feat(distributed): support multiple replicas of one model on the same node (#9583)
* feat(distributed): support multiple replicas of one model on the same node The distributed scheduler implicitly assumed `(node_id, model_name)` was unique, but the schema didn't enforce it and the worker keyed all gRPC processes by model name alone. With `MinReplicas=2` against a single worker, the reconciler "scaled up" every 30s but the registry never advanced past 1 row — the worker re-loaded the model in-place every tick until VRAM fragmented and the gRPC process died. This change introduces multi-replica-per-node as a first-class concept, with capacity-aware scheduling, a circuit breaker, and VRAM soft-reservation. Operators can declare per-node capacity via the worker flag `--max-replicas-per-model` (mirrored as auto-label `node.replica-slots=N`) or override per-node from the UI. * Schema: BackendNode gains MaxReplicasPerModel (default 1) and ReservedVRAM. NodeModel gains ReplicaIndex (composite with node_id + model_name). ModelSchedulingConfig gains UnsatisfiableUntil/Ticks for the reconciler circuit breaker. * Registry: replica_index threaded through SetNodeModel, RemoveNodeModel, IncrementInFlight, DecrementInFlight, TouchNodeModel, GetNodeModel, SetNodeModelLoadInfo and the InFlightTrackingClient. New helpers: CountReplicasOnNode, NextFreeReplicaIndex (with ErrNoFreeSlot), RemoveAllNodeModelReplicas, FindNodesWithFreeSlot, ClusterCapacityForModel, ReserveVRAM/ReleaseVRAM (atomic UPDATE with ErrInsufficientVRAM), and the unsatisfiable-flag CRUD. * Worker: processKey now `<modelID>#<replicaIndex>` so concurrent loads of the same model land on distinct ports. Adds CLI flag --max-replicas-per-model (env LOCALAI_MAX_REPLICAS_PER_MODEL, default 1) and emits the auto-label. * Router: scheduleNewModel filters candidates by free slot, allocates the replica index, and soft-reserves VRAM before installing the backend. evictLRUAndFreeNode now deletes the targeted row by ID instead of all replicas of the model on the node — fixes a latent bug where evicting one replica orphaned its siblings. * Reconciler: caps scale-up at ClusterCapacityForModel so a misconfig (MinReplicas > capacity) doesn't loop forever. After 3 consecutive ticks of capacity==0 it sets UnsatisfiableUntil for a 5m cooldown and emits a warning. ClearAllUnsatisfiable fires from Register, ApproveNode, SetNodeLabel(s), RemoveNodeLabel and UpdateMaxReplicasPerModel so a new node joining or label changes wake the reconciler immediately. scaleDownIdle removes highest-replica-index first to keep slots compact. * Heartbeat resets reserved_vram to 0 — worker is the source of truth for actual free VRAM; the reservation is only for the in-tick race window between two scheduling decisions. * Probe path (reconciler.probeLoadedModels and health.doCheckAll) now pass the row's replica_index to RemoveNodeModel so an unreachable replica doesn't orphan healthy siblings. * Admin override: PUT /api/nodes/:id/max-replicas-per-model sets a sticky override (preserved across worker re-registration). DELETE clears the override so the worker's flag applies again on next register. Required because Kong defaults the worker flag to 1, so every worker restart would have silently reverted the UI value. * React UI: always-visible slot badge on the node row (muted at default 1, accented when >1); inline editor in the expanded drawer with pencil-to-edit, Save/Cancel, Esc/Enter, "(override)" indicator when the value is admin-set, and a "Reset" button to hand control back to the worker. Soft confirm when shrinking the cap below the count of loaded replicas. Scheduling rules table gets an "Unsatisfiable until HH:MM" status badge surfacing the cooldown. * node.replica-slots filtered out of the labels strip on the row to avoid duplicating the slot badge. 23 new Ginkgo specs (registry, reconciler, inflight, health) cover: multi-replica row independence, RemoveNodeModel of one replica preserving siblings, NextFreeReplicaIndex slot allocation including ErrNoFreeSlot, capacity-gated scale-up with circuit breaker tripping and recovery on Register, scheduleDownIdle ordering, ClusterCapacity math, ReserveVRAM admission gating, Heartbeat reset, override survival across worker re-registration, and ResetMaxReplicasPerModel handing control back. Plus 8 stdlib tests for the worker processKey / CLI / auto-label. Closes the flap reproduced on Qwen3.6-35B against the nvidia-thor worker (single 128 GiB node, MinReplicas=2): the reconciler now caps the scale-up at the cluster's actual capacity instead of looping. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Read] [Edit] [Bash] [Skill:critique] [Skill:audit] [Skill:polish] [Skill:golang-testing] * refactor(react-ui/nodes): tighten capacity editor copy + adopt ActionMenu for row actions * Capacity editor hint trimmed from operator-doc-style ("Sourced from the worker's `--max-replicas-per-model` flag. Changing it here makes it a sticky admin override that survives worker restarts." → "Saved values stick across worker restarts.") and the override-state copy similarly compressed. The full mechanic is no longer needed in the UI — the override pill carries the meaning and the docs cover the rest. * Node row actions migrated from an inline cluster of icon buttons (Drain / Resume / Trash) to the kebab ActionMenu used by /manage for per-row model actions, so dense Nodes tables stay clean. Approve stays as a prominent primary button — it's a stateful admission gate, not a routine action, and elevating it matches how /manage surfaces install-time decisions outside the menu. * The expanded drawer's Labels section now filters node.replica-slots out of the editable label list. The label is owned by the Capacity editor above; surfacing it again as an editable label invited confusion (the Capacity save would clobber any direct edit). Both backend and agent workers benefit — they share the row rendering path, so the action menu and label filter apply to both. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] [Skill:critique] [Skill:audit] [Skill:polish] * fix(react-ui/nodes): suppress slot badge on agent workers Agent workers don't load models, so the per-node replica capacity is inapplicable to them. Showing "1× slots" on agent rows was a tiny inconsistency from the unified rendering path — gate the badge on node_type !== 'agent' so it only appears on backend workers. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] * refactor(react-ui/nodes): distill expanded drawer + restyle scheduling form The expanded node drawer used to stack five panels — slot badge, filled capacity box, Loaded Models h4+empty-state, Installed Backends h4+empty-state, Labels h4+chips+form — making routine inspections feel like a control panel. The scheduling rule form wrapped its mode toggle as two 50%-width filled buttons that competed visually with the actual primary action. * Drawer: collapse three rarely-touched config zones (Capacity, Backends, Labels) into one `<details>` "Manage" disclosure (closed by default) with small uppercase eyebrow labels for each zone instead of parallel h4 sub-headings. Loaded Models stays as the at-a-glance headline with a single-line empty hint instead of a boxed empty state. CapacityEditor renders flat (no filled background) — the Manage disclosure provides framing. * Scheduling form: replace the chunky 50%-width button-tabs with the project's existing `.segmented` control (icon + label, sized to content). Mode hint becomes a single tied line below. Fields stack vertically with helper text under inputs and a hairline divider above the right-aligned Save / Cancel. The empty drawer collapses from ~5 stacked sections (~280px tall) to two lines (~80px). The scheduling form now reads as a designed dialog instead of raw building blocks. Both surfaces now match the typographic density and weight of the rest of the admin pages. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] [Skill:distill] [Skill:audit] [Skill:polish] * feat(react-ui/nodes): replace scheduling form's model picker with searchable combobox The native <select> made operators scroll through every gallery entry to find a model name. The project already has SearchableModelSelect (used in Studio/Talk/etc.) which combines free-text search with the gallery list and accepts typed model names that aren't installed yet — useful for pre-staging a scheduling rule before the node it'll run on has finished bootstrapping. Also drops the now-unused useModels import (the combobox manages the gallery hook internally). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Edit] * refactor(react-ui/nodes): consolidate key/value chip editor + add replica preset chips The Nodes page was rendering the same key=value chip pattern in two places with subtly different markup: the Labels editor in the expanded drawer and (post-distill) the Node Selector input in the scheduling form. The form's input was also a comma-separated string that operators were getting wrong. * Extract <KeyValueChips> as a fully controlled chip-builder. Parent owns the map and decides what onAdd/onRemove does — form state for the scheduling form, API calls for the live drawer Labels editor. Same visuals everywhere; one component to change when polish needs apply. * Replace the comma-separated Node Selector text input with KeyValueChips. Operators were copying syntax from docs and missing commas; the chip vocabulary makes the key=value structure self-documenting. * Add <ReplicaInput>: numeric input + quick-pick preset chips for Min/Max replicas. Picked over a slider because replica counts are exact specs derived from VRAM math (operator decision, not a fuzzy estimate). The chips give one-click access to common values (1/2/3/4 for Min, 0=no-limit/2/4/8 for Max) without the slider's special-value problem (MaxReplicas=0 is categorical, not a position on a continuum). * Drop the now-unused labelInputs state in the Nodes page (the inline label editor's per-node draft state lived there and is now owned by KeyValueChips). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Edit] [Skill:distill] * test: fix CI fallout from multi-replica refactor (e2e/distributed + playwright) Two breakages caught by CI that didn't surface in the local run: * tests/e2e/distributed/*.go — multiple files used the pre-PR2 registry signatures for SetNodeModel / IncrementInFlight / DecrementInFlight / RemoveNodeModel / TouchNodeModel / GetNodeModel / SetNodeModelLoadInfo and one stale adapter.InstallBackend call in node_lifecycle_test.go. All updated to pass replicaIndex=0 — these tests don't exercise multi-replica behavior, they just need to compile against the new signatures. The chip-builder tests in core/services/nodes/ already cover the multi-replica logic. * core/http/react-ui/e2e/nodes-per-node-backend-actions.spec.js — the drawer's distill refactor moved Backends inside a "Manage" <details> disclosure that's collapsed by default. The test helper expanded the node row but never opened Manage, so the per-node backend table was never in the DOM. Helper now clicks `.node-manage > summary` after expanding the row. All 100 playwright tests pass locally; tests/e2e/distributed compiles clean. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:opus-4-7 [Edit] [Bash] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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c54897ad44 |
fix(tests): update InstallBackend call sites for new URI/Name/Alias params (#9467)
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Ettore Di Giacinto
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6b6c136210 |
fix(inflight): count inflight from load model, but release afterwards (#9194)
This should fix the count of 1 in flight always showing in the node list Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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59108fbe32 |
feat: add distributed mode (#9124)
* feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |