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feat/audio-cpp-backend-v2
116 Commits
| Author | SHA1 | Message | Date | |
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localai-org-maint-bot
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823fc25bb7 |
fix(kokoro): add CPU backend fallback (#11161)
Publish the existing Kokoro CPU profile for amd64 and arm64 and use it as the default gallery capability so Vulkan-only and CPU hosts can install the backend. 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]
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4baa36ddd8 |
feat(backend): vllm-cpp - text-generation backend for vllm.cpp with llama.cpp-parity tool calling (#11100)
* feat(backend): add vllm-cpp text-generation backend (vllm.cpp) Wrap https://github.com/mudler/vllm.cpp - the LocalAI-team from-scratch C++20 port of vLLM (paged KV cache, continuous batching, prefix caching, safetensors + GGUF loading, no Python at inference) - as a Go gRPC backend over its stable C ABI (ABI v2) via purego. Backend (backend/go/vllm-cpp): - Load -> vllm_engine_load: accepts a .gguf file or a config.json model dir (anything else is refused, satisfying the greedy-probe rule); context_size maps to max_model_len, options block_size/num_blocks/max_num_seqs size the KV cache and scheduler admission. - Predict -> vllm_complete (blocking); PredictStream -> vllm_complete_stream with the per-delta C callback bridged into the gRPC stream. The backend embeds base.Base (not SingleThread): concurrent requests batch continuously in the engine's shared AsyncLLM scheduler. - PredictOptions.Grammar -> the ABI's structured_grammar (GBNF), giving grammar-constrained tool calling at parity with llama-cpp; the ABI also exposes JSON-schema/regex/choice constraints. - Hand-mirrored POD structs with layout locked by unit tests (unsafe.Offsetof vs the C offsets) and a runtime vllm_abi_version gate. - One portable library per platform (vllm.cpp uses per-file SIMD tiers with runtime dispatch), so no avx/avx2/avx512 variant builds. Wiring: - backend-matrix: CPU amd64+arm64 (per-arch + manifest merge), CUDA 12/13 amd64 (120a;121a Blackwell fat binary), L4T arm64 (121a, GB10/DGX Spark - the runtime-proven GPU target), Vulkan amd64, and Darwin arm64 Metal. - backend/index.yaml meta + 12 image entries (latest/development x cpu, cuda12, cuda13, l4t, vulkan, metal); bump_deps registration for the VLLM_CPP_VERSION pin; root Makefile registration; test-extra runs the unit specs (pure Go, no engine build). - Importers: preference-only swaps - llama-cpp (GGUF) and vllm (safetensors) advertise vllm-cpp via AdditionalBackends and emit backend: vllm-cpp without tokenizer templating (the C ABI takes the FINAL prompt; templating and tool parsing stay LocalAI-side). No auto-detect importer. - Docs: backends list, top-level README maintained-engines table, compatibility table. Verified: 20/20 Ginkgo specs against the real pinned engine and Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU - blocking + streaming parity, greedy determinism, stop words, GBNF-constrained generation, and 4 concurrent streams; plus a dlopen/ABI-gate smoke of the built gRPC server binary. Upstream ABI v2 + production structured-output wiring landed as mudler/vllm.cpp@86013f3. Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vllm-cpp): ride the autoparser code path - engine-side chat templating and tool engagement (ABI v3) The backend now implements AIModelRich (PredictRich / PredictStreamRich) over vllm.cpp's ABI v3 chat entry points, so chat and tool calling ride the SAME code path as the llama.cpp autoparser: the ENGINE renders the model's chat template, decides when a tool call engages, and parses it - LocalAI receives pre-parsed ChatDelta / ToolCallDelta protos exactly as it does from llama-cpp. - With use_tokenizer_template + structured Messages, PredictOptions lowers to ONE OpenAI chat request JSON (messages, tools, tool_choice, sampling, stream_options.include_usage) for vllm_chat / vllm_chat_stream. tool_choice auto lowers engine-side to a LAZY structural-tag decode constraint - free text until the model emits the tool trigger, then the call is grammar-constrained; required/named force a call. Tool output is parsed by the engine's streaming Hermes-style parser; each chat.completion.chunk maps onto ChatDeltas (content / reasoning_content / tool_calls) which the host already prefers over Go-side tag extraction. Without structured messages the plain path (LocalAI templating + optional GBNF grammar) applies unchanged. - The engine resolves the chat template from the GGUF tokenizer.chat_template metadata (or tokenizer_config.json); templates beyond its minja subset - e.g. the full Qwen3.5 namespace()/macro template - degrade engine-side to a Hermes-aware fallback prompt (tools schemas + <tool_call> instruction) with a stderr witness, so structural-tag engagement keeps working. - Importers now emit the same config shape as llama-cpp for vllm-cpp (use_tokenizer_template: true, no-grammar autoparser flow); only the llama-cpp-specific use_jinja option and the vllm-python parser options are dropped. - Pin bumped to mudler/vllm.cpp@aaed7ec (ABI v3 + chat-prompt resolution). Verified against the real engine and Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU: full suite green - blocking chat, streaming deltas concatenating byte-equal to the blocking answer, a REQUIRED tool call returning schema-valid arguments JSON, and an AUTO run where the engine itself engages get_weather and streams parsed tool deltas; plus unit specs for the request lowering, chunk->ChatDelta mapping, and the C struct mirrors (ABI gate now v3). Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vllm-cpp): ABI v5 - engine-side parser selection for 30 tool dialects + reasoning Bump the vllm.cpp pin to the autoparser-parity engine: 30 tool-call dialects (every pure-text parser in the pinned vLLM registry, each ported 1:1 with its upstream tests), 7 reasoning parsers, google/minja as the template renderer (the full Qwen3.5 template now renders engine-side), per-family structural tags (tool_choice required/named compiles the model's NATIVE syntax where expressible), and template auto-detection for both parser axes. Backend changes: - cModelParams mirrors ABI v5 (tool_parser + reasoning_parser fields, layout-locked by the offset tests; ABI gate now v5). - New model options tool_parser:<name> / reasoning_parser:<name> pass through to the engine; unset means template auto-detection (18-row tool marker table; [THINK]->mistral, <think>->think_auto for reasoning); "none" disables the reasoning split; unknown names fail the first chat call. - Chat chunks parse the `reasoning` field (the pin renamed reasoning_content), flowing into ChatDelta.ReasoningContent which the host already prefers. Live e2e against Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU, full suite green: the real chat template renders (no more fallback), reasoning auto-detection picks think_auto so markerless answers stay pure content (the live run caught the deepseek_r1 content-swallow upstream and drove the think_auto fix), required tool_choice returns schema-valid arguments, auto tool_choice engages engine-side and streams parsed deltas, and blocking/streaming stay byte-identical. Turn latency also dropped (proper template EOS behavior). Upstream program landed as mudler/vllm.cpp 86013f3..5fffe7e (ABI v2-v5, minja, parser waves B1/B2/B4, reasoning seam, structural-tag registry, think_auto). Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(vllm-cpp): bump the engine pin to the ENG-wave close-out mudler/vllm.cpp@df8909b: the six engine-backed vLLM tool-parser families (qwen3-coder/xml/mimo, kimi_k2, glm45/47, minimax_m2, gemma4, seed_oss) text-reimplemented from their wire formats and held to the upstream test suites - 39 registered dialects; the pinned vLLM registry is now covered except the three Rust/Harmony-backed families, descoped by decision. kimi_k2 also gains a full native structural-tag builder; four new template auto-detection rows land with test-pinned ordering. Full backend e2e re-run green against Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU. Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): add the vllm-cpp-development gallery meta The gallery grew the twelve latest/development image entries but was missing the separate vllm-cpp-development meta (own capabilities map targeting the -development image names), which every backend ships so the development gallery resolves per-platform. Validated: all capability targets in both metas resolve to existing entries, and every image URI's tag suffix matches a backend-matrix build. Also full-stack verified in this change's context (single-node local-ai from this branch, locally-built backend under --backends-path, Qwen3.5-2B GGUF): /v1/chat/completions non-stream (clean content + usage), streaming (SSE deltas), tool_choice auto engaging get_weather engine-side with schema-valid arguments and finish_reason=tool_calls, and streamed tool-call deltas in the standard name-first cadence. Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): repair the CI backend builds - gcc-14 -Werror + fat-arch Triton Two distinct failures took down all five vllm-cpp backend builds on the PR: 1. gcc-14 (ubuntu:24.04 CI images; the local toolchain is gcc-13) fails the engine build with -Werror=maybe-uninitialized in InputBatch::condense - a false positive through a staging std::optional's raw storage. Fixed upstream (mudler/vllm.cpp@61f3e85) by moving slot-to-slot directly; verified BOTH ways under dockerized g++-14.2 (unfixed reproduces CI's two diagnostics exactly, fixed compiles clean) with the engine's behavior suites green. Pin bumped to that sha. 2. The amd64 CUDA builds died at CMake configure: the vendored Triton-AOT cubin trees are per-arch and the engine refuses -DVLLM_CPP_TRITON=ON on a multi-arch (120a;121a) fat build unless pinned to one tree, which would be unsound for the other arch. Triton is now enabled only on the single-arch arm64/GB10 build (where the cubins matter); the fat amd64 binary uses the engine's non-AOT GDN path. Backend e2e re-run green at the new pin (Qwen3.5-2B on CPU, full suite). Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): cuda-12 images cannot compile compute_121a - target 120a only The second CI round surfaced a CUDA-version constraint: the cuda-12 (12.8) image's nvcc rejects 'compute_121a' (GB10 arch support landed with CUDA 13), killing the amd64 cuda-12 build at nvcc. Gate the architecture list on CUDA_MAJOR_VERSION (exported by Dockerfile.golang): cuda-12 builds consumer Blackwell 120a only, cuda-13 keeps the 120a;121a fat binary, arm64/l4t (cuda-13) keeps single-arch 121a with the Triton cubins. GB10 is arm64, so the amd64 cuda-12 image never served it - no capability change. Verified by Makefile dry-run variable dumps for all three combinations (cuda12 -> 120a; cuda13 -> 120a;121a; cpu -> CUDA off). Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): drop the cuda-12 variant - the engine needs the CUDA 13 toolchain Third CI round, third layer: with the arch list already narrowed to 120a, the cuda-12 (12.8) build still dies in ptxas compiling the sm_120a NVFP4 MMA kernels ("Vector type too large, exceeds 128 bit limit") - the Blackwell fp4 path genuinely requires the CUDA 13 toolchain, and vllm.cpp supports Blackwell-family GPUs only. Shipping a cuda-12 image without the fp4 kernels would be a crippled build of an engine whose whole GPU story is fp4, so the variant is dropped instead: - backend-matrix: cuda-12 vllm-cpp entry removed (cuda-13 amd64, l4t arm64, cpu, vulkan, metal remain). - gallery: cuda12 image entries removed; the nvidia capability now resolves to the cuda13 image in both metas; the nvidia-cuda-12 key is dropped so older-driver hosts fall back to the CPU image instead of an unrunnable one. - backend Makefile: BUILD_TYPE=cublas under CUDA_MAJOR_VERSION=12 now fails fast with a clear message; cuda-13 keeps the 120a;121a fat binary and arm64/l4t keeps 121a with the Triton cubins. Verified: Makefile branch dumps for all four combinations (cuda12 loud error, cuda13 fat, arm64 121a+Triton, cpu off), YAML parses, matrix filter tests green, gallery capability targets all resolve. Assisted-by: Claude Code:claude-fable-5 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): forward multi-turn tool identity and reasoning to the engine chatRequestJSON dropped Message.ToolCallId and Message.Name on role="tool" replies and Message.ReasoningContent on assistant history, so a second turn after tool execution reached the engine's chat template without the fields that bind a tool result to the call it answers. Forward all three (present-only, matching the OpenAI wire shape) and pin vllm.cpp to 6a0bd3e7, where ChatMessage parses/round-trips tool_calls, tool_call_id, name and reasoning and the minja adapter exposes them to the template context. Adds the round-trip request-lowering spec (user -> assistant tool_call -> tool reply -> lowered request) and re-ran the gated e2e suite against the new engine pin with a real Qwen3.5 GGUF: chat, reasoning split, streaming parity, required-tool and auto-tool cases all green. Assisted-by: Claude Code:claude-fable-5 [Bash] [Edit] [Read] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): bump vllm.cpp for the darwin arm64 i8mm build fix The darwin-metal CI job was the first build to compile the engine's arm CPU-quant files on macOS and hit their Linux-only <asm/hwcap.h> / <sys/auxv.h> includes. vllm.cpp 9e1c9025 detects i8mm per-OS (auxv on Linux, sysctl on Apple Silicon) with kernels untouched. Gated e2e suite re-run green against the new pin with a real Qwen3.5 GGUF. Assisted-by: Claude Code:claude-fable-5 [Bash] [Read] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(vllm-cpp): darwin build - bound cmake parallelism when nproc is absent The macOS runners have no nproc, so JOBS evaluated empty and `cmake --build -j$(JOBS)` became bare `-j`: unlimited clang jobs on a 3-core/7GB Mac, which swap-thrashed until the 6h GHA timeout (the log shows "nproc: Command not found" and 7+ concurrent clang processes being reaped at the cutoff). Use the same portable fallback chain as the other darwin backends: nproc, then sysctl hw.ncpu, then 4. Assisted-by: Claude Code:claude-fable-5 [Bash] [Edit] [Read] 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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mudler's LocalAI [bot]
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2b61e4bc1d |
fix(upgrade-check): don't filter upgrade candidates by controller capability (#11024)
CheckUpgradesAgainst resolved gallery entries through AvailableBackends, which drops every entry the *local* host cannot run. In distributed mode the host running the check is a CPU-only controller while the GPU backends live on worker nodes, so FindGalleryElement returned nil for every cuda/rocm/l4t entry and those backends were silently skipped. Measured on a live cluster: GET /backends reported 48 installed backends, POST /backends/upgrades/check evaluated 5 — all of them plain or cpu-prefixed. The 43 skipped were all hardware-specific builds. As a result cuda13-nvidia-l4t-arm64-longcat-video-development stayed at sha256:0b8dc851 while the registry tag held sha256:38dae6ff, and a cuDNN packaging fix sat unnoticed on a GPU worker for two days. Every name looked up here is already installed somewhere in the cluster, so hardware compatibility was decided at install time; re-deciding it against the controller is wrong. Switch both CheckUpgradesAgainst and UpgradeBackend to AvailableBackendsUnfiltered. 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]
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a4bab71f27 |
gallery: remove duplicated entries and lint against them recurring (#10996)
gallery: remove duplicated entries and lint against them coming back gallery/index.yaml declared eight names twice: deepseek-r1-distill-llama-8b, llama3.2-3b-enigma, qwen3-asr-0.6b, qwen3-asr-1.7b, qwopus-glm-18b-merged, voice-en-us-kathleen-low, whisper-large-q5_0 and whisper-small-q5_1. FindGalleryElement resolves a reference by returning the first match, so in every pair the second copy was unreachable: it could not be installed, could not be selected as a variant target, and could not be corrected, because any edit to it went to a copy nobody reads. A reference to such a name is also ambiguous to anything reasoning over the catalog, which is why the variant proposal job refuses to propose against them. Each pair was compared both as parsed entries and as raw text, and all eight were byte-identical apart from position. None of the sixteen blocks defines a YAML anchor or pulls one in with a merge key, so nothing was reachable only through a deleted block, and no entry named a removed copy as a variant target. Removing the second copy of each therefore changes no behaviour: the parsed set loses exactly eight entries and every surviving entry is field-for-field unchanged. The removal is textual, by line range, so the diff is pure deletions rather than a reflow of forty thousand lines. checkNoDuplicateEntryNames is the rule that keeps them out, added beside the existing gallery invariants and reporting in the same style. checkSingleVariantClaim closes the adjacent gap in the same place. VariantParents resolves a build claimed by two parents by taking the first in gallery order and calls that deterministic "for a gallery the linter would reject", but nothing rejected it: the invariant was held by curation alone. Now it is a rule, and the comment describes something real. No target is doubly claimed today, so the rule is green on arrival. Assisted-by: Claude:claude-opus-4-8 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]
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2f33ad6669 |
fix(modelartifacts): treat CIFS EACCES as lock contention, not failure (#10986)
flock(2) on CIFS/SMB returns EACCES when another client holds the lock: the kernel maps STATUS_LOCK_NOT_GRANTED and STATUS_FILE_LOCK_CONFLICT to -EACCES and never produces EWOULDBLOCK on that path. gofrs/flock only recognises EWOULDBLOCK as contention, so TryLockContext returned a bare "permission denied" and Ensure aborted. Both replicas then fell back to legacy loading, which makes the worker download the whole repo in-band inside LoadModel and blow the remote-load deadline. Replace TryLockContext with an explicit wait loop over a new Locker interface, classifying EWOULDBLOCK/EAGAIN/EACCES/EBUSY as contention. EACCES is ambiguous at the syscall boundary but not here: the lock file is already open O_CREATE|O_RDWR, so a real permission problem would have failed the open with an *fs.PathError, and flock(2) documents no EACCES on Linux at all. The wait is bounded (DefaultLockWait, overridable via WithLockWait), so even a misclassification degrades to a delay. On timeout the committed result is re-checked before reporting the new ErrLockContended, so a peer that finished the work still wins. Locker also exists so the contention path is testable without a network filesystem: nothing in CI can make flock(2) return EACCES on demand. Raise the fallback to error for a managedArtifactBackends backend, via a shared config.LogArtifactFallback used by both call sites. For those backends the legacy path is not graceful degradation, and the operator otherwise sees only a timeout with no causal link. The fallback stays non-fatal. Drop the os.Chmod(layout.Lock, 0o600) after acquisition: flock.New already creates the file 0600, and the chmod was gratuitous risk on a nounix mount that ignores modes. Fixes #10981 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]
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83a0f16a21 |
feat(gallery): let one gallery entry offer several builds of the same model (#10943)
* feat(system): expose raw detected capability for model meta resolution Model meta gallery entries express hardware fallback through candidate ordering rather than a capability map, so they need the undecorated detected capability string without Capability's default/cpu fallback chain. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(system): drop duplicate capability accessor, cover DetectedCapability ReportedCapability was added with a body identical to the existing DetectedCapability. Keep one accessor and move the specs onto it, since DetectedCapability had no direct coverage of its no-fallback behavior. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): parse IEC binary size suffixes (KiB..PiB) ParseSizeString accepted only SI suffixes, so a "20GiB" floor was rejected outright. Model and VRAM sizes are conventionally quoted in IEC units, and silently reading GiB as GB would understate a floor by about 7%. Purely additive: these inputs previously returned an unknown-suffix error. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add Candidate type for meta model entries Candidate is one option in a meta entry's ordered variant list. It names a concrete gallery entry and declares when that entry suits the host. EffectiveMinVRAM resolves the VRAM floor, letting an authored min_vram win over a nightly-inferred one. An unparseable floor errors instead of being treated as absent: swallowing a typo would turn a constrained candidate into an unconstrained one and select a too-large variant rather than fail loudly. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add hardware-aware model variant resolver Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): allow gallery model entries to declare variant candidates A gallery entry with a non-empty candidates list is a meta entry: it names an ordered list of concrete entries and resolves to the first one the host can satisfy, instead of describing model files directly. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): resolve meta model entries to hardware-appropriate variants at install Meta gallery entries carry an ordered candidate list; at install time the first candidate the host satisfies is resolved and its payload installed under the meta's name, so the model keeps a stable name regardless of which variant backs it. The resolution is recorded in the installed gallery config so a reinstall honors a prior pin and operators can see the backing variant. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gallery): key meta pin recall on the installed name and detach resolved entries Six review findings on the meta-entry install path. Pin recall was keyed on the gallery entry name while applyModel writes the record under the install name (req.Name when supplied), so a meta installed under a custom name with a pin lost that pin on reinstall and was silently re-resolved onto a different variant, possibly swapping its backend. Compute the install name with applyModel's own precedence before the recall. ResolveMetaModel returned a shallow struct copy, so the resolved entry's Overrides aliased the gallery entry's map and the install path's in-place mergo merge wrote the caller's request into the shared catalog. Detach Overrides, ConfigFile, AdditionalFiles, URLs and Tags. Not exploitable today only because this path re-unmarshals the gallery per call, which is a property nobody should have to rely on. Also: overlay the meta's name onto the persisted config for meta installs so the gallery file no longer records the variant's name; move the pinned-VRAM warning below the variant validation so a pin naming a nonexistent entry does not warn about VRAM before failing for an unrelated reason; and stop seeding config.URLs in the config_file branch, which duplicated every declared URL. Add seven network-free specs driving InstallModelFromGallery with a meta entry: variant payload wins over the meta's legacy url fallback, the resolution record round-trips to disk, a pin is recorded and honored on reinstall including under a custom install name, and the resolved entry does not alias the gallery's maps. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gallery): deep-copy meta overrides and make two specs functional ResolveMetaModel detached the resolved entry's Overrides and ConfigFile with maps.Clone, which only copies the top level. Gallery overrides are nested in practice (parameters.model is near-universal) and the install path merges the caller's request with mergo.WithOverride, which recurses into nested maps and overwrites them in place, so the gallery entry's own inner maps were still reachable and still got rewritten by the last caller to install. Copy both maps all the way down instead, recursing through the container shapes a YAML decoder produces. ConfigFile is not mutated on the install path today, but it carries the same kind of nested payload and leaving it shallowly cloned would invite the bug back. Also fix two specs that passed whether or not their target fix was present: - "does not write the caller's overrides back into the gallery entry" re-read the catalog from disk, which re-unmarshals fresh structs and so cannot observe in-memory aliasing. It now asserts against the in-memory gallery entry and drives the real mergo merge. - "round-trips the resolution record to disk under the meta's name" asserted a name that is already correct in the config_file branch. It now drives the url branch via a file:// fixture, where the meta-name overlay actually applies. Both were verified red by reverting their fix. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(gallery): lint meta model entry invariants in index.yaml Adds Ginkgo specs that parse the shipped gallery/index.yaml and enforce the invariants that keep meta entries safe: a legacy url fallback equal to the final candidate's url, references only to existing non-meta entries, a min_vram floor on every candidate but the last-resort one, a capability drawn only from the vocabulary the system can report, and descending VRAM floors within a capability group. The capability check is the only compensating control for a typo there. Candidate matching is a case-sensitive exact comparison against SystemState.DetectedCapability(), so an unknown value never matches and falls through silently instead of erroring. The vocabulary therefore mirrors the raw return set of getSystemCapabilities(), which notably excludes "cpu": that is a fallback key inside Capability(capMap) on the meta backend path, never a reported capability. A CPU-only host reports "default". These pass vacuously until the pilot meta entry lands; the guard is intentionally in place before the thing it guards. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(gallery): close coverage gaps in the meta entry lint The ordering invariant grouped candidates by capability and asserted floors descend within a group. A candidate with an EMPTY capability matches every host, so it does not belong in its own group: it dominates every later candidate whose floor is at or above its own, across capability groups. Track a running minimum floor over the unconditional candidates instead, which subsumes the old same-group check for the empty capability. Every spec skipped non-meta entries, so with zero meta entries in the index all five bodies were no-ops. Aligning GalleryModel.IsMeta() with GalleryBackend.IsMeta(), whose semantics are deliberately opposite, would have made all of them pass while checking nothing. Extract each invariant into a helper over a slice of entries returning the violations it finds, and cover those helpers with synthetic fixtures so the logic stays tested at zero meta entries. The index-driven specs are now a thin application of already proven logic. Also assert the index parses non-empty, report every violation in one run rather than aborting on the first, and parse the index once for the suite. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci(gallery): add nightly denormalization of meta model candidates Fills the read-only backend, quantization and inferred_min_vram fields on meta gallery candidates and opens a PR, modeled on the existing checksum_checker job. Computing these needs network access, so it happens nightly rather than at install time. An authored min_vram is never modified: a human who measured a real load knows more than a pre-download estimate does. The index is rewritten via yaml.Node rather than a document round-trip. A full round-trip reflows all ~26k lines of gallery/index.yaml, which would bury the computed values and make the nightly PR unreviewable. The rewrite touches only the three derived keys, so authored styling survives and a run that computes nothing leaves the file untouched. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ci): keep the gallery denormalize diff reviewable and self-healing The nightly denormalization job edits YAML nodes instead of round-tripping structs so its PR stays small enough for a human to review, but the write path undid that: yaml.Marshal re-encoded the node tree at yaml.v3's default 4-space indent and dropped the leading document marker, reflowing roughly 6000 lines around the handful of real changes. Encode through yaml.NewEncoder at the index's authored 2-space indent and restore the header. A write that changes three fields now changes three lines. Stale inferred_min_vram values were also never cleared. Both skip paths (an authored min_vram is present, or the candidate is the last resort) returned before touching the field, so a candidate that gained a floor or became the last resort after a reorder kept an inferred value that EffectiveMinVRAM reported as a real constraint, failing the meta lint with no way for the job to self-heal. Clear the field before both skips. The workflow discarded a whole night's work on any single failure: the program exits 1 when a candidate cannot be estimated, which aborted the job before the PR step, so one unreachable candidate blocked every other refresh indefinitely. Capture the status, open the PR with what was computed, mark the PR body as partial, and fail the run afterwards so the problem still surfaces. Also preserve the index's existing file mode instead of forcing 0644, and drop the redundant //go:build ignore tag, since Go already skips dot directories and the sibling modelslist.go carries no tag. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add nanbeige4.1-3b meta entry with hardware-resolved variants Adds the first real meta entry to the gallery index. It resolves to the Q8_0 build on hosts with at least 6GiB of VRAM and to the Q4_K_M build everywhere else, installing either payload under the stable name nanbeige4.1-3b. The entry carries a url equal to its final candidate's url. LocalAI releases that predate candidates support parse the index non-strictly and drop the key silently, so without that url they would list the entry and install nothing. A regression spec parses the index the way those releases do and asserts every meta entry stays installable for them. Also teaches core/schema/gallery-model.schema.json about candidates. The schema sets additionalProperties: false at the top level, so an author following CONTRIBUTING.md and adding the yaml-language-server comment would otherwise get a validation error on this entry. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): make candidate entries complete, installable entries Reworks hardware-resolved gallery variants after a design pivot. There is no longer a separate "meta" entry kind. A gallery entry is a normal, complete entry that may additionally carry candidates:, a list of hardware-gated upgrades over itself, and the entry is itself the last-resort candidate. The previous design relied on a bare url: as the fallback for LocalAI releases that predate candidates support. That fallback is empty in practice: none of the 80 gallery/*.yaml files carry a top-level files:, and 1216 of 1281 index entries carry their payload in the index entry itself, so a url alone yields a config template with nothing to download. Since every released LocalAI reads gallery/index.yaml live from master, merging a payload-less entry would have shown every existing user a model that installs to a broken state. Making the entry its own base candidate removes the problem at the root: old clients drop the candidates key and install the entry exactly as they do today. Resolution order is now explicit pin, then capability plus VRAM over the declared upgrades, then the entry itself. The entry ALWAYS installs: when its own min_vram or capability is unmet the installer warns and installs it anyway, because there is nothing below it and refusing would make the gallery behave worse the newer the client is. A pin naming the entry's own name is valid and is how an operator declines an upgrade. IsMeta() becomes HasCandidates(), ResolveMetaModel becomes ResolveVariant, and the persisted meta_name record key becomes entry_name. GalleryBackend.IsMeta() is a separate concept and is untouched. The lint drops the three rules the pivot makes wrong (url equality with the final candidate, no inline payload, unconstrained final candidate) and gains one: the entry's own floor must sit strictly below every candidate's, since a base that outranks a candidate makes that candidate unreachable. The pilot entry is now the existing nanbeige4.1-3b-q4, which gains a 2GiB floor of its own and a single 6GiB upgrade to nanbeige4.1-3b-q8, replacing the separate nanbeige4.1-3b entry added in |
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mudler's LocalAI [bot]
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626ae4d51e |
fix(model-artifacts): materialize longcat-video on the controller, and support companion repos (#10949)
* fix(model-artifacts): materialize longcat-video checkpoints on the controller longcat-video loads a checkpoint directory: its backend.py takes request.ModelFile when os.path.isdir(request.ModelFile) and otherwise falls back to snapshot_download. That places it in the same class as transformers/vllm/diffusers/sglang, but the allow-list added in #10910 did not enumerate it, so PrimaryArtifactSpec returned no managed artifact for a bare HuggingFace repo id. The consequence in distributed mode: nothing was acquired on the controller, ModelFileName fell through to the raw repo id, and staging skipped the resulting phantom /models/<owner>/<repo> path. The worker received a blank ModelFile, fell back to request.Model, and downloaded ~83GB from HuggingFace inside the remote LoadModel deadline - so the load could only ever fail with DeadlineExceeded while an abandoned backend process kept downloading. Note this materializes the full repository. The backend restricts its own snapshot_download with allow_patterns, and the avatar repo ships both base_model/ and base_model_int8/ where only one is ever loaded; inferred specs have no way to carry patterns today. Tracked separately. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): warn when staging skips a non-existent model path stageModelFiles logs "Staging model files for remote node" up front, then silently drops any path field that does not exist on the controller. The skip itself is legitimate and must stay: a backend outside managedArtifactBackends that takes a bare HuggingFace repo id gets an optimistically constructed path (ModelFileName falls through to the raw model reference) that was never materialized, and sources its own weights on the worker. Erroring would break those configs. But at debug level the operator is left with a reassuring staging line and no trace of the skip, so a genuine controller-side acquisition gap is indistinguishable from a healthy pass-through - it surfaces much later as a remote LoadModel timeout, on a worker that is quietly downloading tens of gigabytes. Raise the skip to warn and name the field, path, node and tracking key. Behavior is unchanged. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(model-artifacts): allow a config to declare companion artifacts A composed pipeline needs more than one HuggingFace snapshot. LongCat-Video-Avatar-1.5 loads its own transformer but takes the tokenizer, text encoder and VAE from the separate LongCat-Video base repo, so a single-artifact config cannot express it and the backend is left to fetch the second repo itself at load time. Widen the artifact model to target: model plus any number of named target: companion entries. Normalize accepts the new target and constrains a companion name to [a-z0-9][a-z0-9_-]{0,63} because that name is the option key the backend later receives; a companion may not claim primary_file, which only means anything for a load target. ModelConfig.Validate requires exactly one primary and requires it first, since Artifacts[0] is what ModelFileName, size estimation and staging all resolve from. Both acquisition paths now loop instead of touching index 0 alone: preloadOne for an already-installed config, bindPrimaryArtifact for a gallery install. Failure policy differs by provenance. An inferred primary keeps its warn-and-fall-back, because the legacy download path still exists for it. Companions are explicit by construction, so they are all-or-nothing: a config naming one is asserting the backend needs it, and failing at the acquisition boundary is far more legible than a missing-weights error surfacing later inside the backend. The cache key is deliberately unchanged. It hashes source identity only, never name or target, so every already-installed managed model still hits its existing snapshot instead of silently re-downloading. Two specs pin that: one proving a companion and a primary with identical sources agree on the key, and one pinning the digest of a known primary outright. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(model-artifacts): hand resolved companion snapshots to the backend A materialized companion is useless until the backend can find it, and its location is a content-addressed cache key that does not exist until the artifact resolves. A static gallery override cannot carry that, and persisting it into the config YAML would rot the moment a re-resolve produced a new key. Synthesize it instead at load time: each resolved companion becomes "<artifact name>:<snapshot path>" in ModelOptions.Options, reusing the key:value convention backends already parse for options like attention_backend. The value stays relative to the models directory so a remote worker can resolve it under its own ModelPath once staging has rewritten the model root. An option the author set explicitly always wins, so pinning a companion to a local checkout still beats the managed snapshot. longcat-video resolves base_model through ModelPath, the same convention qwen-tts, voxcpm, outetts and ace-step already use for companion assets. Its sibling-directory heuristic is deleted: it looked for a LongCat-Video directory next to the model, which cannot exist under the content addressed .artifacts/huggingface/<key>/snapshot layout, so it was dead code the moment the model became managed. The gallery entry declares both repositories and restricts each with allow_patterns. The avatar repo ships base_model/ and base_model_int8/ and only ever loads one, so fetching the whole repo would roughly double the download. The patterns match the entry's own options (use_distill true, use_int8 default false); enabling use_int8 here also requires adding base_model_int8/**, which is called out in the entry. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): stage managed artifact trees from the models root Staging anchored the worker's models directory on the primary snapshot whenever a model was managed, so a companion snapshot could not reach the worker at all. frontendModelsDir was derived by stripping the Model relative path off the end of ModelFile. For a managed artifact nothing matches: ModelFile is .artifacts/huggingface/<key>/snapshot while Model stays a bare HuggingFace repo id, so the strip was a no-op and the "models directory" came out as the snapshot itself. Two consequences, both silent. Staging keys lost the .artifacts/huggingface/<key>/snapshot prefix, so two snapshots of one model were indistinguishable on the worker. And a companion, which lives in a sibling snapshot directory outside the primary, fell outside that directory entirely: StagingKeyMapper.Key collapsed its files to bare basenames and resolveOptionPath could not resolve the relative option at all, so it was skipped without a word. Derive the models root from the artifact tree instead when the path runs through it, and compute the worker's ModelPath from the file's path relative to that root rather than from the Model field. The legacy layout is unaffected: where Model really is the relative path, the new derivation reduces to the old one, which a regression spec pins. This deliberately changes an invariant that router_dirstage_test.go pinned: for a managed primary, ModelFile and ModelPath were both the snapshot directory, and staging keys were relative to it. Now ModelFile is the snapshot, ModelPath is the models root above it, and keys keep the full relative path. That spec is updated rather than accommodated, with the reasoning recorded inline, because the old invariant is exactly what made a sibling companion unreachable. Assisted-by: Claude:opus-4.8 [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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mudler's LocalAI [bot]
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b19afb192a |
fix(distributed): backend discovery hid GPU-only backends behind the controller's capability (#10947)
* fix(backends): list backends runnable on worker nodes in distributed mode GET /backends/available filtered the gallery against the system state of the host serving the request. In a distributed deployment that host is the controller, which typically has no GPU, while the GPUs live on worker nodes. Any meta backend whose capabilities map lacks a "default" (or "cpu") key was therefore dropped from the listing entirely — longcat-video, vllm-omni, ltx-video, parakeet, edgetam and qwentts were invisible in the UI even though installing them by name on a GPU worker worked fine. Workers now report their own meta-backend capability at registration and the controller persists it on the node row. The controller cannot derive it: OS-dependent capabilities (metal, darwin-x86, nvidia-l4t) and the CUDA runtime refinements are only observable on the worker. Nodes registered before this field existed fall back to a coarse capability derived from their GPU vendor and VRAM. Backend discovery then evaluates compatibility as the union over healthy backend nodes, so a backend runnable on any node is offered while one no node can run stays hidden. Each remote capability is evaluated through a capability-pinned system state, otherwise a forced capability on the controller image (LOCALAI_FORCE_META_BACKEND_CAPABILITY or /run/localai/capability) would silently override every worker's verdict. With no registered nodes the listing is byte-for-byte what it was, so single-node deployments are unaffected. Also fixes the same-root-cause misclassification in /api/operations, which used the capability-filtered listing to decide whether an operation was a backend or a model install. A GPU-only backend installing on a worker is still a backend operation on the controller, so that lookup is now unfiltered. Assisted-by: Claude:claude-opus-4-8 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(backends): union worker capabilities in backend discovery Implementation for the specs added in the previous commit, plus the two remaining discovery endpoints. Capability-filtered backend discovery evaluated compatibility against the system state of the host serving the request. In a distributed deployment that host is the controller, which typically has no GPU, while the GPUs live on worker nodes. Any meta backend whose capabilities map lacks a "default" (or "cpu") key was dropped entirely — longcat-video, vllm-omni, ltx-video, parakeet, edgetam and qwentts were invisible in the UI even though installing them by name on a GPU worker worked fine. Workers now report their own meta-backend capability at registration and the controller persists it on the node row. The controller cannot derive it: OS-dependent capabilities (metal, darwin-x86, nvidia-l4t) and the CUDA runtime refinements are only observable on the worker. Nodes registered before this field existed fall back to a coarse capability derived from their GPU vendor and VRAM. Discovery then evaluates compatibility as the union over healthy backend nodes, so a backend runnable on any node is offered while one no node can run stays hidden. Each remote capability is evaluated through a capability-pinned system state, otherwise a forced capability on the controller image (LOCALAI_FORCE_META_BACKEND_CAPABILITY or /run/localai/capability) would silently override every worker's verdict. With no registered nodes the listing is byte-for-byte what it was, so single-node deployments are unaffected. Four surfaces shared this root cause and are all routed through the same helper now: - GET /backends/available - GET /api/fine-tuning/backends - GET /api/quantization/backends - /api/operations backend-vs-model classification, which additionally had no reason to filter by capability at all: a GPU-only backend installing on a worker is still a backend operation on the controller, so that lookup is now unfiltered. Assisted-by: Claude:claude-opus-4-8 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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mudler's LocalAI [bot]
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2dade4a9f9 |
fix(model-artifacts): gate inferred artifact materialization by backend (#10910)
The managed-artifact materializer stages a HuggingFace snapshot into a directory (.artifacts/huggingface/<key>/snapshot/). That is the right load target for directory-consuming backends (transformers, vLLM, diffusers, ...), but PrimaryArtifactSpec inferred a managed artifact from ANY HuggingFace-shaped model reference regardless of backend. A single-file backend such as llama.cpp or whisper was therefore handed the snapshot directory instead of the weight file and failed to load it. The /import-model importer already guards this with a backend allow-list (managedArtifactBackends), but the loader-side inference did not. Move the allow-list into core/config as IsManagedArtifactBackend and apply it in PrimaryArtifactSpec: only directory-consuming backends may have an artifact inferred from a bare reference; every other backend stays on the legacy download-to-file path. An explicit artifacts: block still bypasses the gate, where single-file snapshot resolution handles the load path. The importer now shares the same predicate, so both paths agree on which backends auto-materialize. Assisted-by: 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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LocalAI [bot]
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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]
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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]
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b00422e45f |
feat(backends): add LongCat video and avatar generation (#10792)
* feat(backends): add LongCat video and avatar generation Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] [web] * refactor(config): declare model I/O modalities Make model configs declare input and output modalities so capability discovery no longer branches on backend or checkpoint names. Complete the LongCat gallery and user documentation, make the SDPA patch apply to the pinned upstream revision, and stabilize the Agent Jobs race exposed by the required hook. Assisted-by: Codex:GPT-5 [web] --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]
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94bdc825dc |
feat(backend): add moss-transcribe-cpp backend (MOSS-Transcribe-Diarize) (#10756)
C++/ggml transcription + speaker diarization + timestamps backend. Purego dlopens libmoss-transcribe.so (ggml statically linked) from moss-transcribe.cpp and serves offline AudioTranscription, parsing the [start][Sxx]text[end] output into segments with nanosecond timestamps. Adds the importer (surfaces in GET /backends/known), backend-matrix (Linux + Darwin/metal), backend/index.yaml, and a gallery entry (default q5_k GGUF from mudler/moss-transcribe.cpp-gguf). Local L0 smoke (go build + go test ./... = 16 pass, golangci-lint 0 issues) passed against the real libmoss-transcribe.so. The pre-commit coverage gate (full pkg/core + tests/e2e) could not run in the authoring sandbox (no live models, port 9090 held); CI must enforce it before merge. 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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LocalAI [bot]
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1d5139f0a0 |
fix(gallery): make backend (re)install a clean replace instead of an overlay (#10726)
InstallBackend extracted the artifact directly into the target directory with no pre-clean, so a reinstall overlaid the new files onto the old ones. Files present in a previous version but absent in the new artifact (a stale .so, an orphaned package dir) survived and could shadow the new build at import time -- e.g. an old vllm shared object lingering next to a freshly pulled one. Only a failed download cleaned the directory. Stage the download/extraction into a `<name>.install-tmp` dir, validate run.sh is present, write metadata, then atomically swap it into place (rename current -> .install-backup, staging -> current, drop backup), rolling back on failure. This mirrors the atomic swap UpgradeBackend already performs, so install and upgrade now leave identical on-disk state with no orphaned files. Reported as part of #10720. 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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LocalAI [bot]
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2cbb3c96b3 |
fix(gallery): block SSRF in gallery config URL fetch (#10665) (#10673)
POST /models/apply with an empty "id" fetches the attacker-supplied "url" gallery config directly via http.Client, with no check that the URL resolves to a public IP. In the default Docker deployment no API key is configured, so any network-reachable client can coerce LocalAI into issuing requests to internal services or cloud-metadata endpoints (and exfiltrate a small slice of the response through the job error message). Guard the config fetch chokepoints (GetGalleryConfigFromURL and GetGalleryConfigFromURLWithContext, which back both the /models/apply worker and gallery installs) with utils.ValidateExternalURL, matching the protection already applied to the CORS proxy and image/video/audio download paths. Only plain http(s) URLs are validated; non-network schemes (huggingface://, github:, oci://, ollama://, file://) resolve to fixed public services or local files and are left untouched. 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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Adira
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dfaec3bd51 |
fix(import): strip file:// scheme from model path for local imports (#10599)
Importing a model from a local directory (e.g. a HuggingFace checkout or an LM Studio store) via a file:// URI produced a config whose model field kept the scheme verbatim, e.g. model: file:///Users/u/.../Qwen3-4bit. The mlx and vllm backends treat that field as a HuggingFace repo id or local path and reject the file:// form with "Repo id must be in the form 'repo_name' or 'namespace/repo_name'", so the model imported fine but failed to load (issue #7461). Add a shared LocalModelPath helper that reduces a file:// URI to the bare filesystem path it points at and leaves HuggingFace/HTTP URIs untouched, and route the mlx, vllm, transformers and diffusers importers (all of which pass details.URI straight into the model field for from_pretrained-style loading) through it. Cover the helper directly plus end-to-end file:// import specs for the mlx and vllm importers. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> |
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Adira
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1a4f68ed4a |
fix(import): derive model name from selected GGUF for repo-root URIs (#10589)
When importing a HuggingFace GGUF model from a repository-root URI (no file component, e.g. hf://owner/repo) with the Model Name field left blank, the importer named the model after the repository (filepath.Base(details.URI)) instead of the GGUF file it actually selected from the repo listing (issue #10587). Track whether the user supplied an explicit name; the URI base is now only a fallback. In the HuggingFace branch, once the model group is picked, re-derive the name from the selected GGUF via a new modelNameFromShardGroup helper that uses ShardGroup.Base minus the .gguf extension. For sharded models this yields a clean logical name (e.g. Qwen3-30B-A3B-Q4_K_M) rather than a shard filename like ...-00001-of-00002. An explicit name preference still always wins, and the .gguf/URL/OCI paths are unchanged. Add network-free unit specs covering name-from-GGUF, clean-name-from-shard-base, and explicit-name precedence, and update the live integration specs that had encoded the previous repo-name behaviour. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com> |
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LocalAI [bot]
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f1fcafb888 |
fix(gallery): match mmproj/model quant as a whole token so F16 no longer selects BF16 (#10559) (#10564)
pickPreferredGroup matched a quant preference against the shard base filename with strings.Contains. Because `f16` is a substring of `bf16`, asking for the `F16` mmproj quant would wrongly satisfy a `BF16` file and select it when its group came first. Match the preference as a whole token instead: it must be delimited by a non-alphanumeric character (or the string start/end) on both outer edges. Separators inside the preference itself (e.g. `ud-q4_k_xl`) are left untouched, and all occurrences are scanned before rejecting. 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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LocalAI [bot]
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114eeaae81 |
feat(backends): make PreferDevelopmentBackends install the development image as primary (#10520)
When LOCALAI_PREFER_DEV_BACKENDS is set, install the -development image as the primary backend URI (keeping the released image reachable as the first fallback), instead of only reaching development as a download fallback when the released image is missing. This lets an operator force backends built from the development branch — e.g. to pick up a fix already on master before a release. Threads PreferDevelopmentBackends through SystemState so InstallBackend can see it, and reuses the same development-URI convention as the existing failure-path fallback (released tag -> branch tag + dev suffix). The unexported developmentURI helper is covered by a Ginkgo spec. Assisted-by: Claude:claude-opus-4-8 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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3fa7b2955c |
feat(pii): NER tier engine — privacy-filter.cpp backend + NER-centric PII filter (#10360)
Squashed feat/pii-ner-tier-engine rebased onto master (was 45 commits; see backup/pii-ner-tier-engine-prerebase). Net change: - privacy-filter.cpp: standalone GGML engine for the openai-privacy-filter PII/NER token classifier, wired as a LocalAI gRPC backend (CPU/CUDA/Vulkan). TokenClassify moves off the patched llama.cpp path onto this backend. - PII filter reworked to be NER-centric (encoder/NER detection tier scanning whole conversations as one document), with a recreated bounded restricted- regex secret-matching pattern detector tier alongside it (per-model pii_detection.builtins / .patterns + core/services/routing/piipattern). - Detection labelled by source (ner vs pattern); backend trace / confidence / debug observability; analyze/redact exposed as a synchronous API. - Instance-wide default detector policy + per-usecase default-on; request filtering extended to completions, embeddings, edits & Ollama. - React UI: NER-centric PII editor, detector-models table, pattern/builtins editor, middleware default-policy UI. - Gallery: privacy-filter-multilingual token-classify model + NER install filter; token_classify known_usecase; batch sized to context for NER models. privacy-filter backend registered in the backend gallery (cpu/vulkan/cuda-13 meta + image entries with a capabilities map) matching its CI matrix jobs, and an /import-model auto-detect importer (PrivacyFilterImporter, narrow privacy-filter GGUF detection) replacing the prior pref-only registration. Reconciled against master's independent evolution: - Dropped master's PIIPatternOverrides feature (global-pattern runtime overrides + /api/pii/patterns API + runtime_settings.json persistence). The per-model NER + pattern-detector design supersedes it; it was built on the global redactor pattern set this branch replaced. - Reverted the llama.cpp Score carry-patch (0006-server-task-type-score): removed the patch and restored master's grpc-server.cpp Score RPC (direct llama_decode, slot-loop bypass) and LLAMA_VERSION pin, plus master's model_config validation forbidding score + chat/completion/embeddings on llama-cpp. token_classify is unaffected (it runs on the privacy-filter backend, not llama-cpp). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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LocalAI [bot]
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294170d3ed |
feat(backend): add depth-anything (Depth Anything 3) C++/ggml backend + gallery (#10352)
* feat(backend): add depth-anything (Depth Anything 3) C++/ggml backend + gallery Mirrors the locate-anything-cpp backend to register a new depth-anything backend that wraps the Depth Anything 3 ggml port (depth-anything.cpp) via purego (cgo-less, no Python at inference). - backend/go/depth-anything-cpp/: gRPC backend (Load + Predict + GenerateImage), purego binding to the da_capi_* C ABI, CMake/Makefile/run/package/test scripts building depth-anything.cpp's DA_SHARED static .so per CPU variant. - backend/index.yaml: depth-anything backend meta + all hardware-variant capability entries (cpu/cuda12/cuda13/intel-sycl-f32+f16/vulkan/nvidia-l4t). - gallery/index.yaml: 8 Depth Anything 3 GGUF models (base q4_k/q8_0/f16/f32, small, large, giant, mono-large). - .github/backend-matrix.yml: one build entry per hardware variant. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(depth): typed Depth RPC + REST endpoint exposing full DA3 data Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(depth): pin depth-anything.cpp to e0b6814 (ABI 3 dense C-API) The Depth RPC handler calls da_capi_depth_dense / da_capi_points (C-API ABI 3); pin the native build to the commit that exports them. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(depth): pin depth-anything.cpp to v0.1.0 release (b515c31) Repoint the native version from the now-orphaned e0b6814 to the b515c31 release commit, kept alive by the upstream v0.1.0 tag. C-API is unchanged (da_capi_abi_version == 3). Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(depth): wire depth-anything-cpp into build, CI bump, and importer The backend dir, gallery index, and CI build-matrix were present but the backend was never wired into the integration points that adding-backends.md requires: - root Makefile: add to .NOTPARALLEL, the test-extra chain, a BACKEND_* definition, the docker-build target eval, and docker-build-backends (mirrors parakeet-cpp; the backend's own Makefile already documented that its `test` target is driven by test-extra). - bump_deps.yaml: register the DEPTHANYTHING_VERSION pin so the daily auto-bump bot tracks mudler/depth-anything.cpp master (it cannot see an unregistered Makefile pin). - import form: add a preference-only KnownBackend entry so depth-anything is selectable at /import-model (mirrors sam3-cpp; no reliable GGUF auto-detect signal, so pref-only per the doc's default). changed-backends.js needs no entry: the generic golang suffix branch already resolves backend/go/depth-anything-cpp/. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(depth): auto-detect importer for depth-anything GGUFs Replace the preference-only entry with a real auto-detect importer (mirrors parakeet-cpp / locate-anything): - DepthAnythingImporter matches a .gguf whose name carries a depth-anything token (depth-anything-<size>-<quant>.gguf), so /import-model recognises mudler/depth-anything.cpp-gguf repos and direct GGUF URLs without an explicit backend preference. preferences.backend= "depth-anything" still forces it. - Registered before LlamaCPPImporter so its GGUF bundles aren't claimed by the generic .gguf importer; the narrow name match means it cannot claim arbitrary llama GGUFs or the upstream safetensors PyTorch repos. - Multi-quant repos pick the smallest quant by default (q4_k -> ... -> f32, depth stays >0.998 corr even at q4_k); quantizations preference overrides. - Drops the now-redundant knownPrefOnlyBackends entry (importer-backed backends are not listed there, matching parakeet-cpp). - Table-driven Ginkgo test covers detection, negative cases (llama GGUF, upstream safetensors), default/override/fallback quant pick, and direct URL import. 10/10 specs pass. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(depth): check conn.Close error in grpc Depth client (errcheck) The new Depth() client method used a bare `defer conn.Close()`. golangci-lint runs with new-from-merge-base, so although the 39 sibling methods use the same bare form (grandfathered), the newly added line trips errcheck. Drop the result explicitly to satisfy the linter. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 * fix(depth): bump depth-anything.cpp to v0.1.1 (embeddable CMake) v0.1.0 (b515c31) used ${CMAKE_SOURCE_DIR} for its include dirs, which points at the parent project when built via add_subdirectory() as this backend does, so the container build failed with missing stb_image.h / da_gguf_keys.h. v0.1.1 (2d42897) switches to project-relative paths. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 * fix(depth): resolve gosec findings in the backend wrapper The code-scanning gate flagged three new failure-level alerts in godepthanythingcpp.go (gosec runs with -no-fail; GitHub gates on new alerts): - G301: export dirs were created with 0o755. Tighten to 0o750 (no world access needed for backend-written export output). - G304: writeDepthPNG creates req.GetDst(). That path is chosen by the LocalAI core as the intended output destination (same pattern every image backend uses), not attacker input, so annotate with #nosec G304 and document why. The remaining G103 "audit unsafe" notes on the unsafe.Slice C-buffer copies are warning-level (the same purego interop whisper/parakeet use) and do not gate the check, per the supertonic exclusion precedent in secscan.yaml. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 * fix(depth): bump depth-anything.cpp to v0.1.2 (CUDA cross-build arch) v0.1.1 forced CMAKE_CUDA_ARCHITECTURES=native, which breaks the GPU-less l4t/cublas CI builds (nvcc "Unsupported gpu architecture 'compute_'" on CMake 3.22). v0.1.2 (442eea4) drops the override and lets ggml pick its default cross-build arch list. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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LocalAI [bot]
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0854932a25 |
feat(omnivoice-cpp): add OmniVoice TTS backend (file + streaming, voice cloning + voice design) (#10310)
* feat(omnivoice-cpp): add C wrapper + CMake/Makefile build over OmniVoice ov_* ABI Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(omnivoice-cpp): add option/language parsing + WAV framing helpers with tests Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(omnivoice-cpp): wire purego binding with TTS + streaming TTSStream Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * build(omnivoice-cpp): wire backend into root Makefile Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci(omnivoice-cpp): add build matrix entries + dep-bump registration Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(omnivoice-cpp): register backend meta + image entries Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(omnivoice-cpp): expose as preference-only importable backend Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add omnivoice-cpp TTS models (Q8_0 default + BF16 HQ) Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(omnivoice-cpp): document the OmniVoice TTS backend Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(omnivoice-cpp): add env-gated e2e for TTS + streaming Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(omnivoice-cpp): honor tts.audio_path/tts.voice config as default cloning reference The model config tts.audio_path (ModelOptions.AudioPath) and tts.voice now provide a default voice-cloning reference used when a request omits Voice, so a cloned voice can be pinned in the model YAML instead of passed per request. A per-request voice still overrides. Paths resolve relative to the model dir. Assisted-by: claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(omnivoice-cpp): add missing omnivoice-cpp-development backend meta Mirrors the whisper/vibevoice convention: a -development meta aggregating the master-tagged image variants (the production meta and per-variant prod+dev image entries already existed; only the development meta aggregator was missing). Assisted-by: claude:claude-opus-4-8 [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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LocalAI [bot]
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a7a7bd646b |
fix(mlx): route vision-language models to the mlx-vlm backend (#10274)
Vision-language checkpoints such as mlx-community/gemma-4-E4B-it-qat-4bit declare the "image-text-to-text" pipeline tag on HuggingFace. The mlx importer hardcoded backend "mlx" for every mlx-community model, so these VLMs were served by the text-only mlx-lm backend whose tokenizer does not carry the processor chat template. The template was never applied and the model produced degenerate, looping output that echoed the prompt. Detect the "image-text-to-text" pipeline tag in the importer and route those models to mlx-vlm, which applies the processor-aware chat template. An explicit backend preference still wins. As a defensive backstop, the mlx backend now warns loudly when the loaded model has no chat template, so a misrouted VLM surfaces the problem instead of silently looping. Fixes #10269 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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085fc53bbc |
fix(router): production-ready request router + auto-size batch for embedding/rerank (#10104)
* fix(router): score classifier production-readiness Conversation trimming runs through the classifier model's chat template and trims by exact token count, sized to the model's n_batch which is now scaled to context so long probes can't crash the backend. Missing chat_message templates are a hard error at router build time. Router- facing factories (Embedder/Scorer/Reranker/TokenCounter) re-resolve ModelConfig per call so a model installed post-startup doesn't bind a stub Backend="" config and silently fall into the loader's auto- iterate path. New 'vector_store' backend trace recorded inside localVectorStore on every Search/Insert — including the backend-load-failure path that previously vanished into an xlog.Warn — with outcome tagging (hit/miss/empty_store/backend_load_error/find_error/insert_error/ok). Companion cleanup drops misleading similarity:0 and input_tokens_count:0 from non-hit and text-mode traces. Gallery local-store-development aliases to 'local-store' so the master image satisfies pkg/model.LocalStoreBackend lookups from the embedding cache. Misc: llama-cpp TokenizeString reads the correct 'prompt' JSON key (the original bug); ModelTokenize nil-guard; non-fatal mitm proxy startup; PII 'route_local' renamed to 'allow' with docs/UI in sync; model-editor footer no longer eats the edit area on small screens; several config-editor template/dropdown/section fixes. Tests: e2e router specs (casual/code-hint + long-conversation trim), vector_store trace specs, lazy-factory specs, gallery dev-alias resolution, Playwright trace badge + scroll regression. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(backend): auto-size batch to context for embedding and rerank models Embedding and rerank models pool over the whole input in a single physical batch (n_ubatch). With batch left at the 512 default, the backend rejects longer inputs with "input is too large to process", silently capping a large-context embedder (e.g. 8k/32k) at 512 tokens. Size n_batch to the context for these single-pass usecases, mirroring the existing FLAG_SCORE behaviour; an explicit batch: still wins. Extracts EffectiveContextSize/EffectiveBatchSize from grpcModelOpts so the effective decode window has one home for other callers to reuse. Adds an e2e-aio regression test that embeds a >512-token input. The AIO embedding model is switched to nomic-embed-text-v1.5 (2048 context) because the previous granite model was capped at 512 tokens and could not exercise the larger batch. Assisted-by: claude-code:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(gallery): raise arch-router scoring output cap via parallel:64 Scoring decodes the whole prompt+candidate in a single llama_decode and reads one logit row per candidate token. The vendored llama.cpp server caps causal output rows at n_parallel, so the default of 1 aborts with GGML_ASSERT(n_outputs_max <= cparams.n_outputs_max) on multi-token route labels. Set options: [parallel:64] on both arch-router quant entries to lift the cap; kv_unified (the grpc-server default) keeps the full context per sequence, so this does not split the KV cache. Assisted-by: claude-code:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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LocalAI [bot]
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56cc4f63fc |
feat(backend): locate-anything-cpp (open-vocabulary object detection via ggml) (#10264)
* feat(backend): add locate-anything-cpp backend (open-vocab detection via la_capi) A Go/purego backend wrapping locate-anything.cpp's la_capi C ABI, implementing the gRPC Detect RPC: image + open-vocabulary text prompt -> labeled boxes. Mirrors backend/go/rfdetr-cpp; static-links ggml into a per-CPU-variant .so. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci(backend): register locate-anything-cpp in build matrix Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): locate-anything gallery entry + model importer Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(backend): locate-anything-cpp Load+Detect wire test Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add locate-anything-3b model to the gallery index Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci(backend): register locate-anything.cpp in bump_deps auto-bump Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: mudler <mudler@localai.io> * ci(test): e2e smoke for locate-anything-cpp in test-extra (loads the 3B + image, runs Detect) Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: mudler <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: mudler <mudler@localai.io> Co-authored-by: mudler <mudler@localai.io> |
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LocalAI [bot]
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4912c9b73a |
feat(parakeet-cpp): add NVIDIA NeMo Parakeet ASR backend (parakeet.cpp) (#10084)
* feat(parakeet-cpp): L0 backend scaffold, LoadModel + AudioTranscription (text) Add a Go gRPC backend that bridges LocalAI to parakeet.cpp via the flat C-API (parakeet_capi.h), loaded with purego (cgo-less, mirrors the whisper / vibevoice-cpp backends). L0 scope: - main.go: dlopen libparakeet.so (override via PARAKEET_LIBRARY), register the C-API entry points, start the gRPC server. - goparakeetcpp.go: Load (parakeet_capi_load), AudioTranscription (parakeet_capi_transcribe_path, decoder=0 = per-arch default head), Free, serialized through base.SingleThread since the C engine is a thread-unsafe singleton. char* returns are bound as uintptr so the malloc'd buffer is freed via parakeet_capi_free_string after copy. - AudioTranscriptionStream returns a clear "not implemented in L0" error (closes the channel so the server doesn't hang), wired in L2. - Makefile: clone-at-pin + cmake (PARAKEET_VERSION for bump_deps.sh), with a local-symlink dev shortcut; run.sh / package.sh mirror whisper. - Test auto-skips without PARAKEET_BACKEND_TEST_MODEL/_WAV fixtures. Builds clean (CGO_ENABLED=0), gofmt clean, test passes. The single unsafeptr vet note in goStringFromCPtr is documented and matches the whisper backend's tolerated pattern. Word/segment timestamps (L1) and cache-aware streaming (L2) follow. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(parakeet-cpp): L1 word/segment timestamps via transcribe_path_json AudioTranscription now calls parakeet_capi_transcribe_path_json and shapes the per-word / per-token timestamps into the TranscriptResult: - Bind parakeet_capi_transcribe_path_json (purego, char* as uintptr like the other returns) and register it in main.go + the test loader. - Parse the JSON document ({"text","words":[{w,start,end,conf}], "tokens":[{id,t,conf}]}) into typed structs. - Synthesise a single whole-clip segment (parakeet emits no native segment boundaries) spanning the first word start to the last word end; token ids populate Segment.Tokens. - Attach word-level timings only when timestamp_granularities=["word"], matching the OpenAI API (segment-level default). secondsToNanos mirrors the whisper backend's nanosecond convention. Verified end-to-end against tdt_ctc-110m (f16): both the default and word-granularity specs pass; builds clean, gofmt clean, vet shows only the one documented unsafeptr note shared with the whisper backend. Cache-aware streaming (L2) follows. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(parakeet-cpp): L2 cache-aware streaming with EOU segmentation Wire AudioTranscriptionStream to the streaming RNN-T C-API: - Bind parakeet_capi_stream_{begin,feed,finalize,free}; feed takes 16 kHz mono float PCM ([]float32 via purego) and writes *eou_out on <EOU>/<EOB>. - Decode opts.Dst to 16 kHz mono PCM (utils.AudioToWav + go-audio, same as the whisper backend), feed it in 1 s chunks, and emit each newly-finalized text run as a TranscriptStreamResponse delta. - <EOU>/<EOB> events close the current segment; a closing FinalResult carries the full transcript plus the per-utterance segments (with a whole-clip fallback segment when no EOU fired). - stream_begin returns 0 for non-streaming models, surfaced as a clear error instead of an empty stream. Honours context cancellation between chunks. Frees every malloc'd delta and the session. Verified end-to-end against realtime_eou_120m-v1 (f16): the streamed transcript matches the offline 110m reference word-for-word, deltas reconstruct the final text, and the spec passes alongside the offline specs. Builds clean, gofmt clean, vet shows only the shared documented unsafeptr note. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(parakeet-cpp): L3 register backend in build/CI/gallery (whisper parity) Wire the new Go gRPC parakeet-cpp backend (parakeet.cpp ggml port of NVIDIA NeMo Parakeet ASR) into LocalAI's build/CI/gallery surfaces, matching the existing ggml whisper Go backend 1:1. - .github/backend-matrix.yml: add 11 linux entries + 1 darwin entry mirroring every whisper build (cpu amd64/arm64, intel sycl f32/f16, vulkan amd64/arm64, nvidia cuda-12, nvidia cuda-13, nvidia-l4t-arm64, nvidia-l4t-cuda-13-arm64, rocm hipblas, metal-darwin-arm64), all on ./backend/Dockerfile.golang with backend: "parakeet-cpp" and -*-parakeet-cpp tag-suffixes. - scripts/changed-backends.js: explicit inferBackendPath branch resolving parakeet-cpp to backend/go/parakeet-cpp/ before the generic golang branch. - .github/workflows/bump_deps.yaml: track the PARAKEET_VERSION pin in backend/go/parakeet-cpp/Makefile (repo mudler/parakeet.cpp, branch master). - backend/index.yaml: add ¶keetcpp meta + latest/development image entries for every matrix tag-suffix. - Makefile: add backends/parakeet-cpp to .NOTPARALLEL, BACKEND_PARAKEET_CPP definition, docker-build target eval, and test-extra-backend-parakeet-cpp- transcription target (mirrors test-extra-backend-whisper-transcription). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(parakeet-cpp): L4 gallery importer for parakeet GGUFs Add ParakeetCppImporter so parakeet.cpp GGUFs auto-detect on /import-model and route to the parakeet-cpp backend (it also surfaces in /backends/known, which drives the import dropdown). - Match is narrow: a .gguf whose name carries a parakeet architecture token (<arch>-<size>-<quant>.gguf, e.g. tdt_ctc-110m-f16.gguf, rnnt-0.6b-q4_k.gguf, realtime_eou_120m-v1-q8_0.gguf), a direct URL to one, or preferences.backend="parakeet-cpp". It deliberately does NOT claim arbitrary llama-style GGUFs, nor the upstream nvidia/parakeet-* NeMo repos (.nemo, not runnable here). - Registered in the ASR batch BEFORE LlamaCPPImporter so its GGUFs aren't swallowed by the generic .gguf importer. - Import nests files under parakeet-cpp/models/<name>/, defaults to the smallest quant (q4_k, near-lossless on parakeet) with a size-ladder fallback, and honours preferences.quantizations / name / description. Tested with synthetic HF details (no network): metadata, positive matches (HF repo, direct URL, preference), narrowness negatives (llama GGUF, NeMo repo), and import (default quant, override, direct URL), 9 specs pass, build/vet/gofmt clean. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(parakeet-cpp): document the parakeet-cpp transcription backend Add parakeet-cpp to the audio-to-text backend list and a dedicated usage section: direct GGUF import (auto-detects to the backend), model YAML, word-level timestamps via timestamp_granularities[]=word, and cache-aware streaming with the realtime_eou model. Points at the mudler/parakeet-cpp-gguf collection repo. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci(parakeet-cpp): wire transcription gRPC e2e test into test-extra The L3 commit added the test-extra-backend-parakeet-cpp-transcription Makefile target but never invoked it in CI. Mirror the whisper job: - Add a parakeet-cpp output to detect-changes (emitted by changed-backends.js from the matrix entry). - Add tests-parakeet-cpp-grpc-transcription, gated on the parakeet-cpp path filter / run-all, building the backend image and running the transcription e2e against tdt_ctc-110m + the JFK clip. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(parakeet-cpp): drop em dashes from comments and docs Replace em dashes with plain punctuation in the backend comments, the importer, package.sh, and the audio-to-text docs section (and use "and" instead of the multiplication sign). No behaviour change. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add parakeet-cpp f16 models to the model gallery Add the 10 NVIDIA Parakeet models (f16, the recommended quality/speed default) as gallery entries that install on the parakeet-cpp backend from mudler/parakeet-cpp-gguf: tdt_ctc-110m/1.1b, tdt-0.6b-v2/v3, tdt-1.1b, ctc-0.6b/1.1b, rnnt-0.6b/1.1b, and the cache-aware streaming realtime_eou_120m-v1. Each pins the file sha256 and routes transcript usecases to the backend. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(parakeet-cpp): satisfy govet lint + bump PARAKEET_VERSION - goparakeetcpp.go: //nolint:govet on the C-owned-pointer unsafe.Pointer conversion (golangci-lint reports new-only issues, so unlike the whisper backend's identical line this one is flagged). - Makefile: bump PARAKEET_VERSION to the current parakeet.cpp master commit (the previous pin's commit no longer exists after upstream history was squashed), so the backend image clone/build resolves again. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(parakeet-cpp): pin PARAKEET_VERSION to a tag-stable commit The previous SHA pin was orphaned when parakeet.cpp's single-commit master was amended/force-pushed, so the backend image clone (git fetch <sha>) failed across every build variant. Repoint to 845c29e, which upstream now keeps permanently fetchable via the `localai-backend-pin` tag, so future upstream amends no longer break the backend build. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(parakeet-cpp): init the ggml submodule in the backend image clone The backend Dockerfile clones parakeet.cpp at PARAKEET_VERSION with a shallow fetch + checkout but never initialised submodules, so third_party/ggml was empty and the parakeet.cpp cmake build failed at `add_subdirectory(third_party/ggml)` (CMakeLists.txt:53) on every build variant. Add `git submodule update --init --recursive --depth 1 --single-branch` after checkout, mirroring the whisper backend. Verified locally: clone + submodule + cmake configure now succeeds. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(parakeet-cpp): statically link ggml into libparakeet.so The shared libparakeet.so linked ggml's shared libs (libggml*.so), but the package only ships libparakeet.so, so at runtime dlopen failed with "libggml.so.0: cannot open shared object file" (the e2e transcription test panicked on load). Build ggml static + PIC (BUILD_SHARED_LIBS=OFF, CMAKE_POSITION_INDEPENDENT_CODE=ON) so libparakeet.so embeds ggml and depends only on system libs already present in the runtime image. Verified locally: ldd shows no libggml dependency. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(parakeet-cpp): non-streaming fallback in AudioTranscriptionStream The e2e streaming test ran AudioTranscriptionStream against tdt_ctc-110m (not a cache-aware streaming model), so stream_begin returned 0 and the call errored. Per LocalAI's streaming contract (and the whisper backend), a non-streaming model should fall back to a single offline transcription emitted as one delta plus a closing FinalResult. Do that instead of erroring, so the streaming endpoint works for every parakeet model. Verified locally: the streaming spec passes against the non-streaming 110m model via fallback. Assisted-by: Claude:claude-opus-4-8 [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> |
||
|
LocalAI [bot]
|
7a4ca8f60d |
feat(backend): rfdetr-cpp native object detection + segmentation backend (#10028)
Adds a Go native gRPC backend that dlopens librfdetrcpp.so (built from
mudler/rf-detr.cpp at the pinned RFDETR_VERSION) via purego and exposes
the rfdetr.cpp inference pipeline through LocalAI's existing Detect RPC.
Supports all 5 RF-DETR detection variants (Nano/Small/Base/Medium/Large)
and 6 segmentation variants (SegNano/SegSmall/SegMedium/SegLarge/
SegXLarge/Seg2XLarge) with F32/F16/Q8_0/Q4_K quantizations. Pre-built
GGUFs ship at mudler/rfdetr-cpp-* on HuggingFace.
Detection returns Bbox + class_name + confidence; segmentation also
returns PNG-encoded per-detection masks via the rfdetr_capi accessor
functions (rfdetr_capi_get_detection_{class_id,box,score,class_name,
mask_png}).
End-to-end verified through POST /v1/detection: HTTP -> gRPC -> purego
dlopen -> rfdetr.cpp -> ggml -> response (9 detections on the detection
model, 21 detections + valid PNG masks on the seg-nano model against
the kitchen fixture).
Wiring:
- backend/go/rfdetr-cpp/{main.go,gorfdetrcpp.go,CMakeLists.txt,
Makefile,run.sh,package.sh,test.sh,.gitignore}
- Top-level Makefile: BACKEND_RFDETR_CPP, docker-build target,
.NOTPARALLEL, prepare-test-extra, test-extra
- backend/go/rfdetr-cpp/Makefile: `test` target invoked by test-extra
- .github/backend-matrix.yml: CPU + CUDA-12/13 + L4T CUDA-12/13
(arm64) + HIP + Vulkan (amd64 + arm64) + SYCL f32/f16
- backend/index.yaml: rfdetr-cpp meta anchor + latest/development
image entries for every matrix tag-suffix
- .github/workflows/bump_deps.yaml: RFDETR_VERSION pin tracking
(mudler/rf-detr.cpp branch main)
- gallery/index.yaml: 11 rfdetr-cpp-* entries (nano + 4 detection
variants + 6 seg variants), all backed by mudler/rfdetr-cpp-*
on HuggingFace with sha256 pinning on the F16 default
- core/gallery/importers/rfdetr.go: GGUF auto-routing for HF imports
(mudler/rfdetr-cpp-* repos route to rfdetr-cpp, Transformer-format
repos stay on the Python rfdetr backend; explicit preferences.backend
overrides both heuristics)
- core/gallery/importers/rfdetr_test.go: table-driven coverage of the
auto-routing + a live mudler/rfdetr-cpp-nano cross-check
scripts/changed-backends.js needs no change: the existing
Dockerfile.golang -> backend/go/${item.backend}/ branch already routes
the 9 rfdetr-cpp matrix entries to the correct backend path.
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>
|
||
|
Richard Palethorpe
|
5d0b549049 |
feat(gallery): verify backend OCI images with keyless cosign (#9823)
* feat(gallery): verify backend OCI images with keyless cosign Close a trust gap where a registry compromise or MITM could silently replace a backend image: the gallery YAML tells LocalAI which image to pull, but until now nothing verified the bytes came from our CI. Consumer (pkg/oci/cosignverify): - New package using sigstore-go to verify keyless-cosign signatures. - OCI 1.1 referrers API + new bundle format (no legacy :tag.sig). - Policy fields: Issuer / IssuerRegex / Identity / IdentityRegex / NotBefore. NotBefore is the revocation lever — keyless Fulcio certs are ephemeral so revocation is policy-side; advancing not_before in the gallery YAML invalidates every signature predating the cutoff. - TUF trusted root cached process-wide so N backends from one gallery do 1 fetch, not N. Plumbing: - pkg/downloader: ImageVerifier interface + WithImageVerifier option threaded through DownloadFileWithContext. Verification runs between oci.GetImage and oci.ExtractOCIImage, with digest pinning via pinnedImageRef to close the TOCTOU window. Skips the verifier's HEAD when the ref is already digest-pinned. - core/config: Gallery.Verification YAML block. - core/gallery: backendDownloadOptions builds the verifier from the policy; applied on initial URI, mirrors, and tag fallbacks. - core/gallery/upgrade: the upgrade path now routes through the same options builder. A regression Ginkgo spec pins this contract — without it, UpgradeBackend silently bypassed verification. - core/cli: --require-backend-integrity (LOCALAI_REQUIRE_BACKEND_INTEGRITY) escalates missing policy / empty SHA256 from warn to hard-fail. Producer (.github/workflows/backend_merge.yml): - id-token: write at job scope (PR-fork-safe via existing event gate). - sigstore/cosign-installer@v3 pinned to v2.4.1. - After each docker buildx imagetools create, resolve the manifest list digest and run cosign sign --recursive --new-bundle-format --registry-referrers-mode=oci-1-1 against repo@digest. --recursive signs the index and every per-arch entry, matching how the consumer resolves a tag to a platform-specific manifest before verifying. Rollout: backend/index.yaml has no `verification:` block yet, so this PR is backward-compatible — installs proceed with a warning until the gallery is populated. Strict mode is opt-in. Assisted-by: claude-code:claude-opus-4-7 [Bash] [Edit] [Read] [Write] [WebSearch] [WebFetch] Signed-off-by: Richard Palethorpe <io@richiejp.com> * refactor(gallery): plumb RequireBackendIntegrity through config instead of env The previous implementation re-exported the --require-backend-integrity CLI flag into LOCALAI_REQUIRE_BACKEND_INTEGRITY via os.Setenv, then re-read it in core/gallery via os.Getenv. This leaked process state into the gallery package and made the flag impossible to override per-call or test without touching the env. Add RequireBackendIntegrity to ApplicationConfig (with a matching WithRequireBackendIntegrity AppOption) and thread the bool through every install/upgrade path: InstallBackend, InstallBackendFromGallery, UpgradeBackend, InstallModelFromGallery, InstallExternalBackend, ApplyGalleryFromString/File, startup.InstallModels. Worker subcommands gain the same env-bound flag on WorkerFlags so distributed-worker installs honor it consistently with the worker daemon path. Add a forbidigo lint rule against os.Getenv / os.LookupEnv / os.Environ to keep the env-leak pattern from creeping back. Existing offenders (p2p, config loaders, etc.) are baseline-grandfathered by the existing new-from-merge-base: origin/master setting; targeted path exclusions cover the legitimate cases — kong CLI entry points, backend subprocesses, system capability probes, gRPC AUTH_TOKEN inheritance, test gating env vars. Assisted-by: claude-code:claude-opus-4-7 Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
||
|
LocalAI [bot]
|
d77a9137d8 |
feat(llama-cpp): bump to MTP-merge SHA and automatically set MTP defaults (#9852)
* feat(llama-cpp): bump to MTP-merge SHA and document draft-mtp spec type Update LLAMA_VERSION to 0253fb21 (post ggml-org/llama.cpp#22673 merge, 2026-05-16) to pick up Multi-Token Prediction support. No grpc-server.cpp changes are required: the existing `spec_type` option delegates to upstream's `common_speculative_types_from_names()`, which already accepts the new `draft-mtp` name. The `n_rs_seq` cparam needed by MTP is auto-derived inside `common_context_params_to_llama` from `params.speculative.need_n_rs_seq()`, and when no `draft_model` is set the upstream server builds the MTP context off the target model itself. Docs: extend the speculative-decoding section of the model-configuration guide with the new type, both load paths (MTP head embedded in the main GGUF vs. separate `mtp-*.gguf` sibling), the PR's recommended `spec_n_max:2-3`, and the chained `draft-mtp,ngram-mod` recipe. Also notes that the upstream `-hf` auto-discovery of `mtp-*.gguf` siblings is not wired through LocalAI's gRPC layer. Agent guide: short note explaining that new upstream spec types are picked up automatically and that MTP needs no gRPC plumbing. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(llama-cpp): auto-detect MTP heads and enable draft-mtp on import + load Detect upstream's `<arch>.nextn_predict_layers` GGUF metadata key (set by `convert_hf_to_gguf.py` for Qwen3.5/3.6 family models and similar) and, when present and the user has not configured a `spec_type` explicitly, auto-append the upstream-recommended speculative-decoding tuple: - spec_type:draft-mtp - spec_n_max:6 - spec_p_min:0.75 The 0.75 p_min is pinned defensively because upstream marks the current default with a "change to 0.0f" TODO; locking it here keeps acceptance thresholds stable across future llama.cpp bumps. Detection runs in two places: - The model importer (`POST /models/import-uri`, the `/import-model` UI) range-fetches the GGUF header for HuggingFace / direct-URL imports via `gguf.ParseGGUFFileRemote`, with a 30s timeout and non-fatal error handling. OCI/Ollama URIs are skipped because the artifact is not directly streamable; the load-time hook covers them once the file is on disk. - The llama-cpp load-time hook (`guessGGUFFromFile`) reads the local header on every model start and appends the same options if `spec_type` is not already set. Both paths share `ApplyMTPDefaults` and respect an explicit user-set `spec_type:` / `speculative_type:` so YAML overrides win. Ginkgo specs cover the append, preserve-user-choice, legacy alias, and nil safety paths. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(importer): resolve huggingface:// URIs before MTP header probe `gguf.ParseGGUFFileRemote` only speaks HTTP(S), but the importer was handing it the raw `huggingface://...` URI directly (and similarly for any other custom downloader scheme). Live-test against `huggingface://ggml-org/Qwen3.6-27B-MTP-GGUF/Qwen3.6-27B-MTP-Q8_0.gguf` exposed this: the probe failed with `unsupported protocol scheme "huggingface"`, was caught by the non-fatal error path, and the MTP options were silently never applied to the generated YAML. Route every candidate URI through `downloader.URI.ResolveURL()` and require the resolved form to be HTTP(S). After the fix the probe successfully reads `<arch>.nextn_predict_layers=1` from the real HF GGUF and the emitted ConfigFile carries spec_type:draft-mtp, spec_n_max:6, spec_p_min:0.75 as intended. Assisted-by: Claude:claude-opus-4-7 [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> |
||
|
Richard Palethorpe
|
0245b33eab |
feat(realtime): Add Liquid Audio s2s model and assistant mode on talk page (#9801)
* feat(liquid-audio): add LFM2.5-Audio any-to-any backend + realtime_audio usecase
Wires LiquidAI's LFM2.5-Audio-1.5B as a self-contained Realtime API model:
single engine handles VAD, transcription, LLM, and TTS in one bidirectional
stream — drop-in alternative to a VAD+STT+LLM+TTS pipeline.
Backend
- backend/python/liquid-audio/ — new Python gRPC backend wrapping the
`liquid-audio` package. Modes: chat / asr / tts / s2s, voice presets,
Load/Predict/PredictStream/AudioTranscription/TTS/VAD/AudioToAudioStream/
Free and StartFineTune/FineTuneProgress/StopFineTune. Runtime monkey-patch
on `liquid_audio.utils.snapshot_download` so absolute local paths from
LocalAI's gallery resolve without a HF round-trip. soundfile in place of
torchaudio.load/save (torchcodec drags NVIDIA NPP we don't bundle).
- backend/backend.proto + pkg/grpc/{backend,client,server,base,embed,
interface}.go — new AudioToAudioStream RPC mirroring AudioTransformStream
(config/frame/control oneof in; typed event+pcm+meta out).
- core/services/nodes/{health_mock,inflight}_test.go — add stubs for the
new RPC to the test fakes.
Config + capabilities
- core/config/backend_capabilities.go — UsecaseRealtimeAudio, MethodAudio
ToAudioStream, UsecaseInfoMap entry, liquid-audio BackendCapability row.
- core/config/model_config.go — FLAG_REALTIME_AUDIO bitmask, ModalityGroups
membership in both speech-input and audio-output groups so a lone flag
still reads as multimodal, GetAllModelConfigUsecases entry, GuessUsecases
branch.
Realtime endpoint
- core/http/endpoints/openai/realtime.go — extract prepareRealtimeConfig()
so the gate is unit-testable; accept realtime_audio models and self-fill
empty pipeline slots with the model's own name (user-pinned slots win).
- core/http/endpoints/openai/realtime_gate_test.go — six specs covering nil
cfg, empty pipeline, legacy pipeline, self-contained realtime_audio,
user-pinned VAD slot, and partial legacy pipeline.
UI + endpoints
- core/http/routes/ui.go — /api/pipeline-models accepts either a legacy
VAD+STT+LLM+TTS pipeline or a realtime_audio model; surfaces a
self_contained flag so the Talk page can collapse the four cards.
- core/http/routes/ui_api.go — realtime_audio in usecaseFilters.
- core/http/routes/ui_pipeline_models_test.go — covers both code paths.
- core/http/react-ui/src/pages/Talk.jsx — self-contained badge instead of
the four-slot grid; rename Edit Pipeline → Edit Model Config; less
pipeline-specific wording.
- core/http/react-ui/src/pages/Models.jsx + locales/en/models.json — new
realtime_audio filter button + i18n.
- core/http/react-ui/src/utils/capabilities.js — CAP_REALTIME_AUDIO.
- core/http/react-ui/src/pages/FineTune.jsx — voice + validation-dataset
fields, surfaced when backend === liquid-audio, plumbed via
extra_options on submit/export/import.
Gallery + importer
- gallery/liquid-audio.yaml — config template with known_usecases:
[realtime_audio, chat, tts, transcript, vad].
- gallery/index.yaml — four model entries (realtime/chat/asr/tts) keyed by
mode option. Fixed pre-existing `transcribe` typo on the asr entry
(loader silently dropped the unknown string → entry never surfaced as a
transcript model).
- gallery/lfm.yaml — function block for the LFM2 Pythonic tool-call format
`<|tool_call_start|>[name(k="v")]<|tool_call_end|>` matching
common_chat_params_init_lfm2 in vendored llama.cpp.
- core/gallery/importers/{liquid-audio,liquid-audio_test}.go — detector
matches LFM2-Audio HF repos (excludes -gguf mirrors); mode/voice
preferences plumbed through to options.
- core/gallery/importers/importers.go — register LiquidAudioImporter
before LlamaCPPImporter.
- pkg/functions/parse_lfm2_test.go — seven specs for the response/argument
regex pair on the LFM2 pythonic format.
Build matrix
- .github/backend-matrix.yml — seven liquid-audio targets (cuda12, cuda13,
l4t-cuda-13, hipblas, intel, cpu amd64, cpu arm64). Jetpack r36 cuda-12
is skipped (Ubuntu 22.04 / Python 3.10 incompatible with liquid-audio's
3.12 floor).
- backend/index.yaml — anchor + 13 image entries.
- Makefile — .NOTPARALLEL, prepare-test-extra, test-extra,
docker-build-liquid-audio.
Docs
- .agents/plans/liquid-audio-integration.md — phased plan; PR-D (real
any-to-any wiring via AudioToAudioStream), PR-E (mid-audio tool-call
detector), PR-G (GGUF entries once upstream llama.cpp PR #18641 lands)
remain.
- .agents/api-endpoints-and-auth.md — expand the capability-surface
checklist with every place a new FLAG_* needs to be registered.
Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): function calling + history cap for any-to-any models
Three pieces, all on the realtime_audio path that just landed:
1. liquid-audio backend (backend/python/liquid-audio/backend.py):
- _build_chat_state grows a `tools_prelude` arg.
- new _render_tools_prelude parses request.Tools (the OpenAI Chat
Completions function array realtime.go already serialises) and
emits an LFM2 `<|tool_list_start|>…<|tool_list_end|>` system turn
ahead of the user history. Mirrors gallery/lfm.yaml's `function:`
template so the model sees the same prompt shape whether served
via llama-cpp or here. Without this the backend silently dropped
tools — function calling was wired end-to-end on the Go side but
the model never saw a tool list.
2. Realtime history cap (core/http/endpoints/openai/realtime.go):
- Session grows MaxHistoryItems int; default picked by new
defaultMaxHistoryItems(cfg) — 6 for realtime_audio models (LFM2.5
1.5B degrades quickly past a handful of turns), 0/unlimited for
legacy pipelines composing larger LLMs.
- triggerResponse runs conv.Items through trimRealtimeItems before
building conversationHistory. Helper walks the cut left if it
would orphan a function_call_output, so tool result + call pairs
stay intact.
- realtime_gate_test.go: specs for defaultMaxHistoryItems and
trimRealtimeItems (zero cap, under cap, over cap, tool-call pair
preservation).
3. Talk page (core/http/react-ui/src/pages/Talk.jsx):
- Reuses the chat page's MCP plumbing — useMCPClient hook,
ClientMCPDropdown component, same auto-connect/disconnect effect
pattern. No bespoke tool registry, no new REST endpoints; tools
come from whichever MCP servers the user toggles on, exactly as
on the chat page.
- sendSessionUpdate now passes session.tools=getToolsForLLM(); the
update re-fires when the active server set changes mid-session.
- New response.function_call_arguments.done handler executes via
the hook's executeTool (which round-trips through the MCP client
SDK), then replies with conversation.item.create
{type:function_call_output} + response.create so the model
completes its turn with the tool output. Mirrors chat's
client-side agentic loop, translated to the realtime wire shape.
UI changes require a LocalAI image rebuild (Dockerfile:308-313 bakes
react-ui/dist into the runtime image). Backend.py changes can be
swapped live in /backends/<id>/backend.py + /backend/shutdown.
Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): LocalAI Assistant ("Manage Mode") for the Talk page
Mirrors the chat-page metadata.localai_assistant flow so users can ask the
realtime model what's loaded / installed / configured. Tools are run
server-side via the same in-process MCP holder that powers the chat
modality — no transport switch, no proxy, no new wire protocol.
Wire:
- core/http/endpoints/openai/realtime.go:
- RealtimeSessionOptions{LocalAIAssistant,IsAdmin}; isCurrentUserAdmin
helper mirrors chat.go's requireAssistantAccess (no-op when auth
disabled, else requires auth.RoleAdmin).
- Session grows AssistantExecutor mcpTools.ToolExecutor.
- runRealtimeSession, when opts.LocalAIAssistant is set: gate on admin,
fail closed if DisableLocalAIAssistant or the holder has no tools,
DiscoverTools and inject into session.Tools, prepend
holder.SystemPrompt() to instructions.
- Tool-call dispatch loop: when AssistantExecutor.IsTool(name), run
ExecuteTool inproc, append a FunctionCallOutput to conv.Items, skip
the function_call_arguments client emit (the client can't execute
these — it doesn't know about them). After the loop, if any
assistant tool ran, trigger another response so the model speaks the
result. Mirrors chat's agentic loop, driven server-side rather than
via client round-trip.
- core/http/endpoints/openai/realtime_webrtc.go: RealtimeCallRequest
gains `localai_assistant` (JSON omitempty). Handshake calls
isCurrentUserAdmin and builds RealtimeSessionOptions.
- core/http/react-ui/src/pages/Talk.jsx: admin-only "Manage Mode"
checkbox under the Tools dropdown; passes localai_assistant: true to
realtimeApi.call's body, captured in the connect callback's deps.
Mirroring chat's pattern means the in-process MCP tools surface "just
works" for the Talk page without exposing a Streamable-HTTP MCP endpoint
(which was the alternative). Clients with their own MCP servers can
still use the existing ClientMCPDropdown path in parallel; the realtime
handler distinguishes them by AssistantExecutor.IsTool() at dispatch
time.
Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): render Manage Mode tool calls in the Talk transcript
Previously the realtime endpoint only emitted response.output_item.added
for the FunctionCall item, and Talk.jsx's switch ignored the event — so
server-side tool runs were invisible in the UI. The model would speak
the result but the user had no way to see what tool was actually
called.
realtime.go: after executing an assistant tool inproc, emit a second
output_item.added/.done pair for the FunctionCallOutput item. Mirrors
the way the chat page displays tool_call + tool_result blocks.
Talk.jsx: handle both response.output_item.added and .done. Render
FunctionCall (with arguments) and FunctionCallOutput (pretty-printed
JSON when possible) as two transcript entries — `tool_call` with the
wrench icon, `tool_result` with the clipboard icon, both in mono-space
secondary-colour. Resets streamingRef after the result so the next
assistant text delta starts a fresh transcript entry instead of
appending to the previous turn.
Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* refactor(realtime): bound the Manage Mode tool-loop + preserve assistant tools
Fallout from a review pass on the Manage Mode patches:
- Bound the server-side agentic loop. triggerResponse used to recurse on
executedAssistantTool with no cap — a model that kept calling tools
would blow the goroutine stack. New maxAssistantToolTurns = 10 (mirrors
useChat.js's maxToolTurns). Public triggerResponse is now a thin shim
over triggerResponseAtTurn(toolTurn int); recursion increments the
counter and stops at the cap with an xlog.Warn.
- Preserve Manage Mode tools across client session.update. The handler
used to blindly overwrite session.Tools, so toggling a client MCP
server mid-session silently wiped the in-process admin tools. Session
now caches the original AssistantTools slice at session creation and
the session.update handler merges them back in (client names win on
collision — the client is explicit).
- strconv.ParseBool for the localai_assistant query param instead of
hand-rolled "1" || "true". Mirrors LocalAIAssistantFromMetadata.
- Talk.jsx: render both tool_call and tool_result on
response.output_item.done instead of splitting them across .added and
.done. The server's event pairing (added → done) stays correct; the
UI just doesn't need to inspect both phases of the same item. One
switch case instead of two, no behavioural change.
Out of scope (noted for follow-ups): extract a shared assistant-tools
helper between chat.go and realtime.go (duplication is small enough
that two parallel implementations stay readable for now), and an i18n
key for the Manage Mode helper text (Talk.jsx doesn't use i18n
anywhere else yet).
Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci(test-extra): wire liquid-audio backend smoke test
The backend ships test.py + a `make test` target and is listed in
backend-matrix.yml, so scripts/changed-backends.js already writes a
`liquid-audio=true|false` output when files under backend/python/liquid-audio/
change. The workflow just wasn't reading it.
- Expose the `liquid-audio` output on the detect-changes job
- Add a tests-liquid-audio job that runs `make` + `make test` in
backend/python/liquid-audio, gated on the per-backend detect flag
The smoke covers Health() and LoadModel(mode:finetune); fine-tune mode
short-circuits before any HuggingFace download (backend.py:192), so the
job needs neither weights nor a GPU. The full-inference path remains
gated on LIQUID_AUDIO_MODEL_ID, which CI doesn't set.
The four new Go test files (core/gallery/importers/liquid-audio_test.go,
core/http/endpoints/openai/realtime_gate_test.go,
core/http/routes/ui_pipeline_models_test.go, pkg/functions/parse_lfm2_test.go)
are already picked up by the existing test.yml workflow via `make test` →
`ginkgo -r ./pkg/... ./core/...`; their packages all carry RunSpecs entries.
Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
|
||
|
LocalAI [bot]
|
d892e4af80 |
feat: add ds4 backend (DeepSeek V4 Flash) with tool calls, thinking, KV cache (#9758)
* test(e2e-backends): allow BACKEND_BINARY for native-built backends
Adds an escape hatch for hardware-gated backends (e.g. ds4) where the
model is too large for Docker build context. When BACKEND_BINARY points
at a run.sh produced by 'make -C backend/cpp/<name> package', the suite
skips docker image extraction and drives the binary directly.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(e2e-backends): validate BACKEND_BINARY basename + log actual source
Two follow-ups from the
|
||
|
Ettore Di Giacinto
|
3568b2819d |
fix(gallery): keep auto-upgrade off non-dev backends when -development is installed (#9736)
A `-development` backend variant (e.g. `cuda12-llama-cpp-development`)
shares its `alias` with the stable counterpart and is meant to be a
drop-in replacement via ListSystemBackends alias resolution. Two paths
in the auto-upgrade flow let the stable variant slip back in on top of
the user's explicit dev pick:
1. ListSystemBackends emits a synthetic alias row keyed by the alias
name that re-uses the chosen concrete's metadata pointer. In
distributed mode, the worker's handleBackendList serialised that
row over NATS as `{Name: <alias>, URI: <dev URI>, Digest: <dev>}`
— the frontend can't reconstruct the alias relationship, and the
wire-rebuilt row then carried `Metadata.Name = <alias>` and
resolved against an unrelated gallery entry on the next upgrade
check.
2. CheckUpgradesAgainst happily iterated the synthetic row in
single-node too. Today the duplicate gallery lookup is harmless
because both rows share the same `Metadata.Name`, but any gallery
change that gives a meta backend a version, or any concrete
sharing its alias with a dev counterpart, would surface a phantom
non-dev upgrade and auto-upgrade would install it — shadowing the
dev one through alias-token preference.
Two layered fixes:
- `core/services/worker/lifecycle.go` (`handleBackendList`): drop
rows where the map key differs from `b.Metadata.Name`. Concrete
and meta entries always have `key == Metadata.Name`; only synthetic
aliases violate it. Workers now report only what's actually on disk;
the per-node UI listing and CheckUpgrades both stop seeing phantoms.
- `core/gallery/upgrade.go` (`CheckUpgradesAgainst`): iterate by key,
skip rows where `key != Metadata.Name` (belt-and-suspenders for any
caller-supplied installed set), and apply the dev-aware rule —
build a set of installed `Metadata.Name`s and drop any non-dev
candidate `X` whose `X-<devSuffix>` counterpart is installed. Uses
the configured dev suffix from `getFallbackTagValues(systemState)`.
Manual `POST /api/backends/upgrade/<name>` is unaffected: it goes
straight through `bm.UpgradeBackend(name)` without consulting the
suppression list, so users who genuinely want the stable variant
upgraded can still trigger it explicitly.
Tests in core/gallery/upgrade_test.go cover three cases under
"CheckUpgradesAgainst (distributed)": dev-only installed → only the
dev surfaces; both variants installed → dev still wins; synthetic
alias row is ignored. Generic backend names are used to avoid the
capability filter dropping cuda-prefixed entries on a CPU-only host.
Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
|
||
|
Richard Palethorpe
|
670259ce43 |
chore: Security hardening (#9719)
* fix(http): close 0.0.0.0/[::] SSRF bypass in /api/cors-proxy The CORS proxy carried its own private-network blocklist (RFC 1918 + a handful of IPv6 ranges) instead of using the same classification as pkg/utils/urlfetch.go. The hand-rolled list missed 0.0.0.0/8 and ::/128, both of which Linux routes to localhost — so any user with FeatureMCP (default-on for new users) could reach LocalAI's own listener and any other service bound to 0.0.0.0:port via: GET /api/cors-proxy?url=http://0.0.0.0:8080/... GET /api/cors-proxy?url=http://[::]:8080/... Replace the custom check with utils.IsPublicIP (Go stdlib IsLoopback / IsLinkLocalUnicast / IsPrivate / IsUnspecified, plus IPv4-mapped IPv6 unmasking) and add an upfront hostname rejection for localhost, *.local, and the cloud metadata aliases so split-horizon DNS can't paper over the IP check. The IP-pinning DialContext is unchanged: the validated IP from the single resolution is reused for the connection, so DNS rebinding still cannot swap a public answer for a private one between validate and dial. Regression tests cover 0.0.0.0, 0.0.0.0:PORT, [::], ::ffff:127.0.0.1, ::ffff:10.0.0.1, file://, gopher://, ftp://, localhost, 127.0.0.1, 10.0.0.1, 169.254.169.254, metadata.google.internal. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(downloader): verify SHA before promoting temp file to final path DownloadFileWithContext renamed the .partial file to its final name *before* checking the streamed SHA, so a hash mismatch returned an error but left the tampered file at filePath. Subsequent code that operated on filePath (a backend launcher, a YAML loader, a re-download that finds the file already present and skips) would consume the attacker-supplied bytes. Reorder: verify the streamed hash first, remove the .partial on mismatch, then rename. The streamed hash is computed during io.Copy so no second read is needed. While here, raise the empty-SHA case from a Debug log to a Warn so "this download had no integrity check" is visible at the default log level. Backend installs currently pass through with no digest; the warning makes that footprint observable without changing behaviour. Regression test asserts os.IsNotExist on the destination after a deliberate SHA mismatch. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(auth): require email_verified for OIDC admin promotion extractOIDCUserInfo read the ID token's "email" claim but never inspected "email_verified". With LOCALAI_ADMIN_EMAIL set, an attacker who could register on the configured OIDC IdP under that email (some IdPs accept self-supplied unverified emails) inherited admin role: - first login: AssignRole(tx, email, adminEmail) → RoleAdmin - re-login: MaybePromote(db, user, adminEmail) → flip to RoleAdmin Add EmailVerified to oauthUserInfo, parse email_verified from the OIDC claims (default false on absence so an IdP that omits the claim cannot short-circuit the gate), and substitute "" for the role-decision email when verified=false via emailForRoleDecision. The user record still stores the unverified email for display. GitHub's path defaults EmailVerified=true: GitHub only returns a public profile email after verification, and fetchGitHubPrimaryEmail explicitly filters to Verified=true. Regression tests cover both the helper contract and integration with AssignRole, including the bootstrap "first user" branch that would otherwise mask the gate. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(cli): refuse public bind when no auth backend is configured When neither an auth DB nor a static API key is set, the auth middleware passes every request through. That is fine for a developer laptop, a home LAN, or a Tailnet — the network itself is the trust boundary. It is not fine on a public IP, where every model install, settings change, and admin endpoint becomes reachable from the internet. Refuse to start in that exact configuration. Loopback, RFC 1918, RFC 4193 ULA, link-local, and RFC 6598 CGNAT (Tailscale's default range) all count as trusted; wildcard binds (`:port`, `0.0.0.0`, `[::]`) are accepted only when every host interface is in one of those ranges. Hostnames are resolved and treated as trusted only when every answer is. A new --allow-insecure-public-bind / LOCALAI_ALLOW_INSECURE_PUBLIC_BIND flag opts out for deployments that gate access externally (a reverse proxy enforcing auth, a mesh ACL, etc.). The error message lists this plus the three constructive alternatives (bind a private interface, enable --auth, set --api-keys). The interface enumeration goes through a package-level interfaceAddrsFn var so tests can simulate cloud-VM, home-LAN, Tailscale-only, and enumeration-failure topologies without poking at the real network stack. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * test(http): regression-test the localai_assistant admin gate ChatEndpoint already rejects metadata.localai_assistant=true from a non-admin caller, but the gate was open-coded inline with no direct test coverage. The chat route is FeatureChat-gated (default-on), and the assistant's in-process MCP server can install/delete models and edit configs — the wrong handler change would silently turn the LLM into a confused deputy. Extract the gate into requireAssistantAccess(c, authEnabled) and pin its behaviour: auth disabled is a no-op, unauthenticated is 403, RoleUser is 403, RoleAdmin and the synthetic legacy-key admin are admitted. No behaviour change in the production path. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * test(http): assert every API route is auth-classified The auth middleware classifies path prefixes (/api/, /v1/, /models/, etc.) as protected and treats anything else as a static-asset passthrough. A new endpoint shipped under a brand-new prefix — or a new path that simply isn't on the prefix allowlist — would be reachable anonymously. Walk every route registered by API() with auth enabled and a fresh in-memory database (no users, no keys), and assert each API-prefixed route returns 401 / 404 / 405 to an anonymous request. Public surfaces (/api/auth/*, /api/branding, /api/node/* token-authenticated routes, /healthz, branding asset server, generated-content server, static assets) are explicit allowlist entries with comments justifying them. Build-tagged 'auth' so it runs against the SQLite-backed auth DB (matches the existing auth suite). Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * test(http): pin agent endpoint per-user isolation contract agents.go's getUserID / effectiveUserID / canImpersonateUser / wantsAllUsers helpers are the single trust boundary for cross-user access on agent, agent-jobs, collections, and skills routes. A regression there is the difference between "regular user reads their own data" and "regular user reads anyone's data via ?user_id=victim". Lock in the contract: - effectiveUserID ignores ?user_id= for unauthenticated and RoleUser - effectiveUserID honours it for RoleAdmin and ProviderAgentWorker - wantsAllUsers requires admin AND the literal "true" string - canImpersonateUser is admin OR agent-worker, never plain RoleUser No production change — this commit only adds tests. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(downloader): drop redundant stat in removePartialFile The stat-then-remove pattern is a TOCTOU window and a wasted syscall — os.Remove already returns ErrNotExist for the missing-file case, so trust that and treat it as a no-op. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(http): redact secrets from trace buffer and distribution-token logs The /api/traces buffer captured Authorization, Cookie, Set-Cookie, and API-key headers verbatim from every request when tracing was enabled. The endpoint is admin-only but the buffer is reachable via any heap-style introspection and the captured tokens otherwise outlive the request. Strip those header values at capture time. Body redaction is left to a follow-up — the prompts are usually the operator's own and JSON-walking is invasive. Distribution tokens were also logged in plaintext from core/explorer/discovery.go; logs forward to syslog/journald and outlive the token. Redact those to a short prefix/suffix instead. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(auth): rate-limit OAuth callbacks separately from password endpoints The shared 5/min/IP limit on auth endpoints is right for password-style flows but too tight for OAuth callbacks: corporate SSO funnels many real users through one outbound IP and would trip the limit. Add a separate 60/min/IP limiter for /api/auth/{github,oidc}/callback so callbacks are bounded against floods without breaking shared-IP deployments. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(gallery): verify backend tarball sha256 when set in gallery entry GalleryBackend gained an optional sha256 field; the install path now threads it through to the existing downloader hash-verify (which already streams, verifies, and rolls back on mismatch). Galleries without sha256 keep working; the empty-SHA path still emits the existing "downloading without integrity check" warning. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * test(http): pin CSRF coverage on multipart endpoints The CSRF middleware in app.go is global (e.Use) so it covers every multipart upload route — branding assets, fine-tune datasets, audio transforms, agent collections. Pin that contract: cross-site multipart POSTs are rejected; same-origin / same-site / API-key clients are not. Also pins the SameSite=Lax fallback path the skipper relies on when Sec-Fetch-Site is absent. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(http): XSS hardening — CSP headers, safe href, base-href escape, SVG sandbox Several closely related XSS-prevention changes spanning the SPA shell, the React UI, and the branding asset server: - New SecurityHeaders middleware sets CSP, X-Content-Type-Options, X-Frame-Options, and Referrer-Policy on every response. The CSP keeps script-src permissive because the Vite bundle relies on inline + eval'd scripts; tightening that requires moving to a nonce-based policy. - The <base href> injection in the SPA shell escaped attacker-controllable Host / X-Forwarded-Host headers — a single quote in the host header broke out of the attribute. Pass through SecureBaseHref (html.EscapeString). - Three React sinks rendering untrusted content via dangerouslySetInnerHTML switch to text-node rendering with whiteSpace: pre-wrap: user message bodies in Chat.jsx and AgentChat.jsx, and the agent activity log in AgentChat.jsx. The hand-rolled escape on the agent user-message variant is replaced by the same plain-text path. - New safeHref util collapses non-allowlisted URI schemes (most importantly javascript:) to '#'. Applied to gallery `<a href={url}>` links in Models / Backends / Manage and to canvas artifact links — these come from gallery JSON or assistant tool calls and must be treated as untrusted. - The branding asset server attaches a sandbox CSP plus same-origin CORP to .svg responses. The React UI loads logos via <img>, but the same URL is also reachable via direct navigation; this prevents script execution if a hostile SVG slipped past upload validation. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(http): bound HTTP server with read-header and idle timeouts A net/http server with no timeouts is trivially Slowloris-able and leaks idle keep-alive connections. Set ReadHeaderTimeout (30s) to plug the slow-headers attack and IdleTimeout (120s) to cap keep-alive sockets. ReadTimeout and WriteTimeout stay at 0 because request bodies can be multi-GB model uploads and SSE / chat completions stream for many minutes; operators who need tighter per-request bounds should terminate slow clients at a reverse proxy. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * test(auth): pin PUT /api/auth/profile field-tampering contract The handler uses an explicit local body struct (only name and avatar_url) plus a gorm Updates(map) with a column allowlist, so an attacker posting {"role":"admin","email":"...","password_hash":"..."} can't mass-assign those fields. Lock that down with a regression test so a future "let's just c.Bind(&user)" refactor breaks loudly. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(services): strip directory components from multipart upload filenames UploadDataset and UploadToCollectionForUser took the raw multipart file.Filename and joined it into a destination path. The fine-tune upload was incidentally safe because of a UUID prefix that fused any leading '..' to a literal segment, but the protection is fragile. UploadToCollectionForUser handed the filename to a vendored backend without sanitising at all. Strip to filepath.Base at both boundaries and reject the trivial unsafe values ("", ".", "..", "/"). Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(react-ui): validate persisted MCP server entries on load localStorage is shared across same-origin pages; an XSS that lands once can poison persisted MCP server config to attempt header injection or to feed a non-http URL into the fetch path on subsequent loads. Validate every entry: types must match, URL must parse with http(s) scheme, header keys/values must be control-char-free. Drop anything that doesn't fit. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(http): close X-Forwarded-Prefix open redirect The reverse-proxy support concatenated X-Forwarded-Prefix into the redirect target without validation, so a forged header value of "//evil.com" turned the SPA-shell redirect helper at /, /browse, and /browse/* into a 301 to //evil.com/app. The path-strip middleware had the same shape on its prefix-trailing-slash redirect. Add SafeForwardedPrefix at the middleware boundary: must start with a single '/', no protocol-relative '//' opener, no scheme, no backslash, no control characters. Apply at both consumers; misconfig trips the validator and the header is dropped. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(http): refuse wildcard CORS when LOCALAI_CORS=true with empty allowlist When LOCALAI_CORS=true but LOCALAI_CORS_ALLOW_ORIGINS was empty, Echo's CORSWithConfig saw an empty allow-list and fell back to its default AllowOrigins=["*"]. An operator who flipped the strict-CORS feature flag without populating the list got the opposite of what they asked for. Echo never sets Allow-Credentials: true so this isn't directly exploitable (cookies aren't sent under wildcard CORS), but the misconfiguration trap is worth closing. Skip the registration and warn. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(auth): zxcvbn password strength check with user-acknowledged override The previous policy was len < 8, which let through "Password1" and the rest of the credential-stuffing corpus. LocalAI has no second factor yet, so the bar needs to sit higher. Add ValidatePasswordStrength using github.com/timbutler/zxcvbn (an actively-maintained fork of the trustelem port; v1.0.4, April 2024): - min 12 chars, max 72 (bcrypt's truncation point) - reject NUL bytes (some bcrypt callers truncate at the first NUL) - require zxcvbn score >= 3 ("safely unguessable, ~10^8 guesses to break"); the hint list ["localai", "local-ai", "admin"] penalises passwords built from the app's own branding zxcvbn produces false positives sometimes (a strong-looking password that happens to match a dictionary word) and operators occasionally need to set a known-weak password (kiosk demos, CI rigs). Add an acknowledgement path: PasswordPolicy{AllowWeak: true} skips the entropy check while still enforcing the hard rules. The structured PasswordErrorResponse marks weak-password rejections as Overridable so the UI can surface a "use this anyway" checkbox. Wired through register, self-service password change, and admin password reset on both the server and the React UI. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(react-ui): drop HTML5 minLength on new-password inputs minLength={12} on the new-password input let the browser block the form submit silently before any JS or network call ran. The browser focused the field, showed a brief native tooltip, and that was that — no toast, no fetch, no clue. Reproducible by typing fewer than 12 chars on the second password change of a session. The JS-level length check in handleSubmit already shows a toast and the server rejects with a structured error, so the HTML5 attribute was redundant defence anyway. Drop it. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(react-ui): bundle Geist fonts locally instead of fetching from Google The new CSP correctly refused to apply styles from fonts.googleapis.com because style-src is locked to 'self' and 'unsafe-inline'. Loosening the CSP would defeat its purpose; the right fix is to stop reaching out to a third-party CDN for fonts on every page load. Add @fontsource-variable/geist and @fontsource-variable/geist-mono as npm deps and import them once at boot. Drop the <link rel="preconnect"> and external stylesheet from index.html. Side benefit: no third-party tracking via Referer / IP on every UI load, no failure mode when offline / behind a captive portal. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(react-ui): refresh i18n strings to reflect 12-char password minimum The translations still said "at least 8 characters" everywhere — the client-side toast on a too-short password change told the user the wrong floor. Update tooShort and newPasswordPlaceholder / newPasswordDescription across all five locales (en, es, it, de, zh-CN) to match the real ValidatePasswordStrength rule. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(auth): make password length-floor overridable like the entropy check The 12-char minimum was a policy choice, not a technical invariant — only "non-empty", "<= 72 bytes", and "no NUL bytes" are real bcrypt constraints. Treating length-12 as a hard rule was inconsistent with the entropy check (already overridable) and friction for use cases where the account is just a name on a session, not a security boundary (single-user kiosk, CI rig, lab demo). Restructure ValidatePasswordStrength: - Hard rules (always enforced): non-empty, <= MaxPasswordLength, no NUL byte - Policy rules (skipped when AllowWeak=true): length >= 12, zxcvbn score >= 3 PasswordError now marks password_too_short as Overridable too. The React forms generalised from `error_code === 'password_too_weak'` to `overridable === true`, and the JS-side preflight length checks were removed (server is source of truth, returns the same checkbox flow). Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
||
|
Richard Palethorpe
|
969005b2a1 |
feat(gallery): Speed up load times and clean gallery entries (#9211)
* feat: Rework VRAM estimation and use known_usecases in gallery Signed-off-by: Richard Palethorpe <io@richiejp.com> Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code] * chore(gallery): regenerate gallery index and add known_usecases to model entries Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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|
LocalAI [bot]
|
6d56bf98fe |
feat(importers): add vibevoice-cpp importer for GGUF bundles (#9685)
Routes mudler/vibevoice.cpp-models and similar repos to the vibevoice-cpp
backend. Detects via repo name ("vibevoice.cpp"/"vibevoice-cpp"), file
listing (vibevoice-*.gguf + tokenizer.gguf), or preferences.backend
override. Defaults to the realtime TTS model; preferences.usecase=asr
selects the ASR/diarization variant. Bundles the required tokenizer.gguf
and (for TTS) a voice prompt, emitting the Options[] entries the backend
expects. Registered ahead of VibeVoiceImporter so the C++ bundles aren't
swallowed by the older Python-backend substring match.
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Write] [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
|
8452068f43 |
feat(importers): whisper.cpp HF repos pick a quant + nest under whisper/models (#9630)
The WhisperImporter's Import() switch ordered LooksLikeURL ahead of the HuggingFace branch, so any https://huggingface.co/<owner>/<repo> URI (e.g. LocalAI-io/whisper-large-v3-it-yodas-only-ggml) hijacked the URL path. FilenameFromUrl returned the repo slug, the gallery entry pointed at the HTML repo page, the SHA256 was empty, and the HF file listing was effectively dead code for HTTPS imports. The HF branch only fired for huggingface://owner/repo and hf://owner/repo references. Gate the URL case on a "ggml-*.bin" basename signal — mirroring how the llama-cpp importer gates on ".gguf" — so direct file URLs still take the URL path while HF repo URLs fall through to the HF branch. There the file listing is actually consulted: every ggml-*.bin entry is collected and one is picked by the new preferences.quantizations preference (default q5_0; comma-separated for fallback ordering). Pin the chosen file under whisper/models/<name>/<file> so a single repo can ship q4_0/q5_0/q8_0 side-by-side without colliding on disk, matching the llama-cpp/models/<name>/ layout. The fallback when no preference matches is the last available ggml file, mirroring llama-cpp's pickPreferredGroup behaviour. Tests: replace the previous probe spec with positive assertions against LocalAI-io/whisper-large-v3-it-yodas-only-ggml (default → ggml-model-q5_0.bin, quantizations=q4_0 → ggml-model-q4_0.bin) plus two offline specs that build a fake hfapi.ModelDetails to cover the fallback rule and non-ggml filtering without touching the network. Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit WebFetch] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
|
4906cbad04 |
feat: add biometrics UI (#9524)
* feat(react-ui): add Face & Voice Recognition pages
Expose the face and voice biometrics endpoints
(/v1/face/*, /v1/voice/*) through the React UI. Each page has four
tabs driving the six endpoints per modality: Analyze (demographics
with bounding boxes / waveform segments), Compare (verify with a
match gauge and live threshold slider), Enrollment (register /
identify / forget with a top-K matches view), Embedding (raw
vector inspector with sparkline + copy).
MediaInput supports file upload plus live capture: webcam
snap-to-canvas for face, MediaRecorder -> AudioContext ->
16-bit PCM mono WAV transcode for voice (libsndfile on the
backend only handles WAV/FLAC/OGG natively).
Sidebar gets a new Biometrics section feature-gated on
face_recognition / voice_recognition; routes are wrapped in
<RequireFeature>. No new dependencies -- Font Awesome icons
picked from the Free set.
Assisted-by: Claude:Opus 4.7
* fix(localai): accept data URI prefixes with codec/charset params
Browser MediaRecorder produces data URIs like
data:audio/webm;codecs=opus;base64,...
so the pre-';base64,' section can carry multiple parameter
segments. The `^data:([^;]+);base64,` regex in pkg/utils/base64.go
and core/http/endpoints/localai/audio.go only matched exactly one
segment, so recordings straight from the React UI's live-capture
tab failed the strip and then tripped the base64 decoder on the
leading 'data:' literal, surfacing as
"invalid audio base64: illegal base64 data at input byte 4"
Widened both regexes to `^data:[^,]+?;base64,` so any number of
';param=value' segments between the mime type and ';base64,' are
tolerated. Added a regression test covering the MediaRecorder
shape.
Assisted-by: Claude:Opus 4.7
* fix(insightface): scope pack ONNX loading to known manifests
LocalAI's gallery extracts buffalo_* zips flat into the models
directory, which inevitably mixes with ONNX files from other
backends (opencv face engine, MiniFASNet antispoof, WeSpeaker
voice embedding) and older buffalo pack installs. Feeding those
foreign files into insightface's model_zoo.get_model() blows up
inside the router -- it assumes a 4-D NCHW input and indexes
`input_shape[2]` on tensors that aren't shaped like a face model,
raising IndexError mid-load and leaving the backend unusable.
The router's dispatch isn't amenable to per-file try/except alone
(first-file-wins picks det_10g.onnx from buffalo_l even when the
user asked for buffalo_sc -- alphabetical order happens to favour
the wrong pack). Instead, ship an explicit manifest of the
upstream v0.7 pack contents and scope the glob to that when the
requested pack is known. The manifest is small and stable; future
packs can be added alongside or fall through to the tolerance
loop, which also swallows any remaining IndexError / ValueError
from foreign files with a clear `[insightface] skipped` stderr
line for diagnostics.
Assisted-by: Claude:Opus 4.7
* fix(speaker-recognition): extract FBank features for rank-3 ONNX encoders
Pre-exported speaker-encoder ONNX graphs come in two shapes:
rank-2 [batch, samples] -- some 3D-Speaker exports,
take raw waveform directly.
rank-3 [batch, frames, n_mels] -- WeSpeaker and most Kaldi-
lineage encoders, expect
pre-computed Kaldi FBank.
OnnxDirectEngine unconditionally fed `audio.reshape(1, -1)` --
correct for rank-2, IndexError-on-input_shape[3] on rank-3, which
surfaced to the UI as
"Invalid rank for input: feats Got: 2 Expected: 3"
Detect the input rank at session init and run Kaldi FBank
(80-dim, 25ms/10ms frames, dither=0.0, per-utterance CMN) before
the forward pass when rank>=3. All knobs are configurable via
backend options for encoders that deviate from defaults.
torchaudio.compliance.kaldi is already in the backend's
requirements (SpeechBrain pulls torchaudio in), so no new
dependency.
Assisted-by: Claude:Opus 4.7
* fix(biometrics): isolate face and voice vector stores
Face (ArcFace, 512-D) and voice (ECAPA-TDNN 192-D / WeSpeaker
256-D) biometric embeddings were colliding inside a single
in-memory local-store instance. Enrolling one after the other
failed with
"Try to add key with length N when existing length is M"
because local-store correctly refuses to mix dimensions in one
keyspace.
The registries were constructed with `storeName=""`, which in
StoreBackend() is just a WithModel() call. But ModelLoader's
cache is keyed on `modelID`, not `model` -- so both registries
collapsed to the same `modelID=""` slot and reused the same
backend process despite looking isolated on paper.
Three complementary fixes:
1. application.go -- give each registry a distinct default
namespace ("localai-face-biometrics" /
"localai-voice-biometrics"). The comment claimed
isolation, now it's actually enforced.
2. stores.go -- pass the storeName as both WithModelID and
WithModel so the ModelLoader cache key separates
namespaces and the loader spawns distinct processes.
3. local-store/store.go -- drop the Load() `opts.Model != ""`
guard. It was there to prevent generic model-loading loops
from picking up local-store by accident, but that auto-load
path is being retired; the guard now just blocks legitimate
namespace isolation. opts.Model is treated as a tag; the
per-tuple process isolation upstream handles discrimination.
Assisted-by: Claude:Opus 4.7
* fix(gallery): stale-file cleanup and upgrade-tmp directory safety
Two related robustness fixes for backend install/upgrade:
pkg/downloader/uri.go
OCI downloads passed through
if filepath.Ext(filePath) != "" ...
filePath = filepath.Dir(filePath)
which was intended to redirect file-shaped download targets
into their parent directory for OCI extraction. The heuristic
misfires on directory-shaped paths with a dot-suffix --
gallery.UpgradeBackend uses
tmpPath = "<backendsPath>/<name>.upgrade-tmp"
and Go's filepath.Ext treats ".upgrade-tmp" as an extension.
The rewrite landed the extraction at "<backendsPath>/", which
then **overwrote the real install** (backends/<name>/) with a
flat-layout file and left a stray run.sh at the top level. The
tmp dir itself stayed empty, so the validation step that
checked "<tmpPath>/run.sh" predictably failed with
"upgrade validation failed: run.sh not found in new backend"
Every manual upgrade silently corrupted the backends tree this
way. Guard the rewrite behind "target isn't already an existing
directory" -- InstallBackend / UpgradeBackend both pre-create
the target as a directory, so they get the correct behaviour;
existing file-path callers with a genuine dot-extension still
get the parent redirect.
core/gallery/backends.go
InstallBackend's MkdirAll returned ENOTDIR when something at
the target path was already a file (legacy dev builds dropped
golang backend binaries directly at `<backendsPath>/<name>`
instead of nesting them under their own subdir). That
permanently blocked reinstall and upgrade for anyone carrying
that state, since every retry hit the same error. Detect a
pre-existing non-directory, warn, and remove it before the
MkdirAll so the fresh install can write the correct nested
layout with metadata.json + run.sh.
Assisted-by: Claude:Opus 4.7
* fix(galleryop): refresh upgrade cache after backend ops
UpgradeChecker caches the last upgrade-check result and only
refreshes on the 6-hour tick or after an auto-upgrade cycle.
Manual upgrades (POST /api/backends/upgrade/:name) go through
the async galleryop worker, which completes the upgrade
correctly but never tells UpgradeChecker to re-check -- so
/api/backends/upgrades continued to list a just-upgraded backend
as upgradeable, indistinguishable from a failed upgrade, for up
to six hours.
Add an optional `OnBackendOpCompleted func()` hook on
GalleryService that fires after every successful install /
upgrade / delete on the backend channel (async, so a slow
callback doesn't stall the queue). startup.go wires it to
UpgradeChecker.TriggerCheck after both services exist. Result:
the upgrade banner clears within milliseconds of the worker
finishing.
Assisted-by: Claude:Opus 4.7
* build: prepend GOPATH/bin to PATH for protogen-go
install-go-tools runs `go install` for protoc-gen-go and
protoc-gen-go-grpc, which writes them into `go env GOPATH`/bin.
That directory isn't on every dev's PATH, and protoc resolves
its code-gen plugins via PATH, so the immediately-following
protoc invocation fails with
"protoc-gen-go: program not found"
which in turn blocks `make build` and any
`make backends/%` target that depends on build.
Prepend `go env GOPATH`/bin to PATH for the protoc invocation
so the freshly-installed plugins are found without requiring a
shell-profile change.
Assisted-by: Claude:Opus 4.7
* refactor(ui-api): non-blocking backend upgrade handler with opcache
POST /api/backends/upgrade/:name used to send the ManagementOp
directly onto the unbuffered BackendGalleryChannel, which blocked
the HTTP request whenever the galleryop worker was busy with a
prior operation. The op also didn't show up in /api/operations,
so the Backends UI couldn't reflect upgrade progress on the
affected row.
Register the op in opcache immediately, wrap it in a cancellable
context, store the cancellation function on the GalleryService,
and push onto the channel from a goroutine so the handler
returns right away. Response gains a `jobID` field and a
`message` string so clients have a consistent handle regardless
of whether the op is queued or running.
Pairs with the OnBackendOpCompleted hook added in the galleryop
commit — together the UI sees the upgrade start, watches
progress via /api/operations, and drops the "upgradeable" flag
the moment the worker finishes.
Assisted-by: Claude:Opus 4.7
|
||
|
Ettore Di Giacinto
|
c1f923b2bc |
fix(importer): emit all shards for multi-part GGUF models (#9513)
The llama-cpp HuggingFace importer iterated files one at a time and kept overwriting `lastGGUFFile`, so sharded repos such as `unsloth/Kimi-K2.6-GGUF` (14 `Q8_K_XL` parts) produced a gallery entry pointing only at the final shard — useless to llama.cpp's split loader, which needs shard 1 to discover the set. Group shards up front via new helpers in `pkg/huggingface-api` (`SplitShardSuffix`, `ShardGroup`, `GroupShards`). The llama-cpp importer now picks a group (preferred quant, then last-group fallback) and emits every shard, with `Model:` pointing at shard 1. `FindPreferredModelFile` returns shard 1 of the first matching group so the gallery agent's preview stays coherent for sharded repos. Adds unit coverage for the HuggingFace branch of the importer (which had none), plus shard-detection tests in the hfapi package. Assisted-by: Claude:Opus-4.7 [Read] [Edit] [Bash] |
||
|
Ettore Di Giacinto
|
f0c92610a1 |
feat(importer): expand importer flow to almost all backends (#9466)
* docs(agents): require importer integration when adding backends
Document the importer registry workflow so contributors know that adding
a new backend also requires updating the /import-model dropdown source:
either a new importer in core/gallery/importers/, extending an existing
one for drop-in replacements, or the pref-only slice for backends with
no reliable auto-detect signal. Always covered by a table-driven test.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for Batch 0 primitives
Introduce failing tests that drive Batch 0 of the importer expansion:
- pkg/huggingface-api: assert GetModelDetails populates PipelineTag and
LibraryName from /api/models/{repo}, and that a failing metadata
endpoint still returns file details (best-effort fetch).
- core/gallery/importers/helpers_test.go: new table-driven coverage for
HasFile, HasExtension, HasONNX, HasONNXConfigPair, HasGGMLFile.
- core/gallery/importers/importers_test.go: assert ErrAmbiguousImport
sentinel exists and round-trips through errors.Is.
- core/gallery/importers/local_test.go: extend with detection cases for
ggml-*.bin (whisper), silero_vad.onnx (silero-vad), and the piper
.onnx + .onnx.json pair.
- core/http/endpoints/localai/import_model_test.go: assert
ImportModelURIEndpoint returns HTTP 400 with a structured
{error, detail, hint} body when ErrAmbiguousImport surfaces.
All tests fail in the expected places (missing fields, missing
helpers, missing sentinel, endpoint still wraps as 500).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): Batch 0 foundation — helpers, sentinel, local detection
Implements the Batch 0 primitives that subsequent importer batches build on:
- pkg/huggingface-api: ModelDetails gains PipelineTag and LibraryName.
GetModelDetails now layers a best-effort GET /api/models/{repo} fetch
on top of ListFiles — a metadata outage leaves the fields empty but
still returns full file details. Uses a dedicated response struct
because the single-model endpoint uses snake_case keys while the list
endpoint historically returned camelCase.
- core/gallery/importers/helpers.go: generic HasFile, HasExtension,
HasONNX, HasONNXConfigPair, HasGGMLFile helpers working on
[]hfapi.ModelFile so per-backend importers can detect artefact
patterns without duplicating string wrangling.
- core/gallery/importers/importers.go: adds the ErrAmbiguousImport
sentinel. DiscoverModelConfig now returns it (wrapped with
fmt.Errorf("%w: ...")) when no importer matched AND the HF
pipeline_tag falls in a whitelist of narrow modalities (ASR, TTS,
sentence-similarity, text-classification, object-detection). The
whitelist is intentionally narrow — unknown tags keep the previous
"no importer matched" behaviour to avoid blocking rare repos.
- core/gallery/importers/local.go: three new local-path detections,
inserted before the existing merged-transformers branch:
* ggml-*.bin → whisper
* silero*.onnx → silero-vad
* *.onnx + *.onnx.json pair → piper
- core/http/endpoints/localai/import_model.go: ImportModelURIEndpoint
surfaces ErrAmbiguousImport as HTTP 400 with
{error, detail, hint} JSON, preserving existing behaviour for
unrelated errors.
Green tests:
go test ./core/gallery/importers/... ./pkg/huggingface-api/... \
./core/http/endpoints/localai/...
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(importers): red tests for KnownBackend endpoint and importer metadata
Add failing tests that drive Batch UI-Dropdown:
- importers_test.go: assert importers expose Name/Modality/AutoDetects
and that LlamaCPPImporter advertises drop-in replacements via a new
AdditionalBackendsProvider interface. A Registry() accessor is also
expected.
- backend_test.go (new): assert GET /backends/known returns
[]schema.KnownBackend, covers every importer, exposes drop-in
llama-cpp replacements, includes curated pref-only backends, has no
duplicates, and is sorted by Modality+Name.
These tests fail at compile time against master; they are intentionally
red so the follow-up green commit is reviewable.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery): add /backends/known endpoint for importer-aware backend list
Extend the Importer interface with Name/Modality/AutoDetects so the
import system can self-describe its registry, and introduce the
AdditionalBackendsProvider interface so importers can advertise drop-in
replacements (llama-cpp advertises ik-llama-cpp and turboquant).
Expose the new GET /backends/known endpoint that merges:
- the importer registry (auto-detect supported),
- drop-in replacements hosted by importers (preference-only),
- a curated knownPrefOnlyBackends slice for backends with no dedicated
importer (sglang, tinygrad, trl, mlx-vlm, whisperx, kokoros, Qwen TTS
variants, sam3-cpp) — kept at the top of backend.go so contributors
adding a new pref-only backend have one obvious place to edit,
- backends installed on disk but unknown to the importer (marked
AutoDetect=false, empty Modality).
The endpoint deliberately does NOT filter by gallery membership or host
capability (unlike /backends/available): LocalAI may auto-install a
backend that is not yet present, so the import form dropdown must show
everything the importer knows about.
Response is deduplicated (importer wins over pref-only) and sorted by
Modality+Name for deterministic output.
Registered in core/http/routes/localai.go next to /backends/available
under the same admin middleware.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui): source import form backend dropdown from /backends/known
Replace the hard-coded BACKENDS constant in ImportModel.jsx with a
live fetch of /backends/known on mount. Users now see every backend
the importer layer knows about (including preference-only entries)
grouped by modality, not a stale subset.
Changes:
- config.js: add backendsKnown endpoint constant next to
backendsAvailable.
- api.js: add backendsApi.listKnown() wrapper.
- ImportModel.jsx: remove BACKENDS constant, fetch the list via
useEffect, and derive grouped options via buildBackendOptions.
Preference-only entries render with a " (preference-only)" suffix.
Loading state disables the dropdown with a "Loading backends…"
placeholder; on fetch failure the form falls back to auto-detect
only and surfaces a non-blocking toast.
- SearchableSelect.jsx: accept items flagged isHeader=true and render
them as non-selectable section dividers. Keyboard navigation skips
headers and search queries hide them so filtered output stays
relevant.
Vitest is not set up in this project (devDependencies ship Playwright
only). Per the brief's guard-rail, no frontend test framework is
introduced; coverage is provided by the Go handler tests that assert
the /backends/known contract consumed by the React form.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for whisper importer
Asserts detection on ggerganov/whisper.cpp (via ggml-*.bin filename),
the preferences.backend=whisper override path for arbitrary URIs,
and the Importer interface metadata (name/modality/autodetect).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add whisper importer
Recognises whisper.cpp GGML models by the "ggml-*.bin" filename
convention (direct URL or HF repo member) and by the explicit
preferences.backend="whisper" override. Emits backend: whisper with
the transcript use-case. Registered before llama-cpp so the narrow
filename signal wins before any generic GGUF match is attempted.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for moonshine importer
Asserts detection on UsefulSensors/moonshine-tiny via owner + ONNX
files, the preferences.backend=moonshine override for arbitrary URIs,
and the Importer interface metadata (name/modality/autodetect).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add moonshine importer
Matches UsefulSensors-owned HF repos whose artefacts or metadata
identify them as ASR: on-disk .onnx files (the canonical Moonshine
packaging) OR pipeline_tag=automatic-speech-recognition (covers
transformers/safetensors-only sibling repos). preferences.backend=
moonshine overrides detection. Test uses the live moonshine-tiny
repo because the canonical UsefulSensors/moonshine repo currently
hits a recursive-subfolder bug in pkg/huggingface-api ListFiles.
Registered after WhisperImporter but before LlamaCPPImporter and
TransformersImporter so the narrower owner+ASR signal wins before
the generic tokenizer.json check routes the repo to transformers.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for nemo importer
Asserts detection on nvidia/parakeet-tdt-0.6b-v3 via owner + .nemo
file, the preferences.backend=nemo override for arbitrary URIs, and
the Importer interface metadata (name/modality/autodetect).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add nemo importer
Matches nvidia-owned HF repos that ship a .nemo checkpoint archive,
the canonical NeMo ASR packaging. preferences.backend=nemo forces
detection. Registered between moonshine and llama-cpp so the narrow
owner + extension signal wins before any downstream generic matcher.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for faster-whisper importer
Asserts detection on Systran/faster-whisper-large-v3 (owner +
model.bin + config.json + ASR pipeline), the preferences.backend=
faster-whisper override for arbitrary URIs, and the Importer
interface metadata.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add faster-whisper importer
Recognises CTranslate2-packaged whisper checkpoints distributed for
the faster-whisper runtime: model.bin + config.json + ASR
pipeline_tag, narrowed to Systran-owned repos or repo names
containing "faster-whisper" to avoid falsely claiming vanilla
OpenAI whisper HF repos. preferences.backend=faster-whisper
overrides detection. Registered before llama-cpp and transformers
so the narrow signal wins before tokenizer.json routes the repo to
the generic transformers importer.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for qwen-asr importer
Asserts detection on Qwen/Qwen3-ASR-1.7B via owner + ASR substring
in the repo name, the preferences.backend=qwen-asr override for
arbitrary URIs, and the Importer interface metadata.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add qwen-asr importer
Matches Qwen-owned HF repos whose name contains "ASR"
(case-insensitive), routing them to the qwen-asr backend rather
than the generic transformers/vllm path. The substring check scans
the repo portion only so the owner field cannot leak a false match.
preferences.backend=qwen-asr forces detection. Registered before
llama-cpp and transformers so the narrow owner+name signal wins.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): ASR ambiguity surfaces ErrAmbiguousImport
Locks in the behaviour added in Batch 0: an HF repo whose pipeline_tag
marks it as automatic-speech-recognition but whose artefacts match no
ASR importer (and no generic importer) must fail with
ErrAmbiguousImport so callers know to pass preferences.backend rather
than silently guess. pyannote/voice-activity-detection is the fixture
— its file list is only config.yaml + README, leaving every importer's
artefact check negative.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for piper importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add piper importer
Detects piper TTS voices by the canonical <voice>.onnx + <voice>.onnx.json
pair packaging (via HasONNXConfigPair). Narrow enough to skip generic
ONNX repos used by other backends (Moonshine ASR, sentence-transformers).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for bark importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add bark importer
Detects Suno's Bark TTS checkpoints by HF owner "suno" + repo name
prefix "bark". Adds HFOwnerRepoFromURI() helper so importers can fall
back to URI parsing when pkg/huggingface-api's recursive tree listing
errors on repos with nested subdirectories (suno/bark ships a
speaker_embeddings/v2 subtree that trips a pre-existing path-doubling
bug in the listFilesInPath recursion).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for fish-speech importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add fish-speech importer
Detects Fish Audio TTS releases by HF owner "fishaudio" with a URI-based
fallback for repos whose tree recursion trips the pre-existing hfapi
path-doubling bug.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for outetts importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add outetts importer
Detects OuteAI's OuteTTS releases by HF owner "OuteAI" or a case-
insensitive "OuteTTS" substring in the repo name, with a URI-based
fallback for recursion-bugged repos.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for voxcpm importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add voxcpm importer
Detects OpenBMB's VoxCPM TTS family by repo-name substring (community
mirrors re-host the weights under many owners — mlx-community,
bluryar, callgg, etc).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for kokoro importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add kokoro importer
Detects hexgrad's Kokoro TTS by the "Kokoro" repo-name substring paired
with a PyTorch .pth/.pt checkpoint — the pairing excludes ONNX-only
mirrors (handled by the pref-only `kokoros` Rust runtime) and GGUF
mirrors (handled by llama-cpp).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for kitten-tts importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add kitten-tts importer
Detects KittenML's kitten-tts releases by owner or "kitten-tts" repo-name
substring, with URI-parsing fallback.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for neutts importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add neutts importer
Detects Neuphonic's NeuTTS releases by owner "neuphonic" or "neutts"
repo-name substring, with URI-parsing fallback.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for chatterbox importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add chatterbox importer
Detects Resemble AI's Chatterbox TTS by owner "ResembleAI" or
"chatterbox" repo-name substring, with URI-parsing fallback.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for vibevoice importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add vibevoice importer
Detects Microsoft's VibeVoice TTS by "vibevoice" repo-name substring
(case-insensitive) so community mirrors still route here.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for coqui importer
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add coqui importer
Detects Coqui AI's TTS releases (XTTS-v2, YourTTS, …) by the
authoritative `coqui` HF owner, with URI-parsing fallback.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): TTS ambiguity surfaces ErrAmbiguousImport
Adds a Ginkgo spec that imports nari-labs/Dia-1.6B — a real HF repo
carrying pipeline_tag="text-to-speech" whose artefacts (*.pth, one
safetensors shard, preprocessor_config.json, config.json) match none of
the Batch-2 TTS importers nor the generic text/image importers — and
asserts DiscoverModelConfig wraps ErrAmbiguousImport via errors.Is.
Also pivots the endpoint-level ambiguity fixture from hexgrad/Kokoro-82M
to nari-labs/Dia-1.6B. Batch 2 added a dedicated kokoro importer that
now claims the original fixture; Dia remains genuinely unclaimed and
so exercises the same ambiguity code path at the HTTP layer.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for stablediffusion-ggml importer
Covers HF repo detection (city96/FLUX.1-dev-gguf), raw .gguf URL matching on
filename arch tokens, preference override, and Importer interface metadata.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add stablediffusion-ggml importer
Detects GGUF-packed Stable Diffusion and FLUX checkpoints (leejet owner,
city96 FLUX mirrors, second-state SD dumps, raw .gguf URLs with arch
tokens) and routes them to the stablediffusion-ggml backend. Registered
BEFORE LlamaCPPImporter so .gguf image checkpoints are not stolen by
llama-cpp's generic .gguf match. Reuses HFOwnerRepoFromURI for the
hfapi-recursion-bug fallback. preferences.backend overrides detection.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for ace-step importer
Covers HF repo-name detection (ACE-Step/ACE-Step-v1-3.5B), preference
override, and Importer interface metadata.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add ace-step importer
Routes ACE-Step music generation checkpoints (ACE-Step/ACE-Step-v1-3.5B,
ACE-Step/Ace-Step1.5, community mirrors) to the ace-step backend.
Matching is case-insensitive on the "ace-step" repo-name substring and
owner, with an HFOwnerRepoFromURI fallback for the hfapi recursion bug.
KnownUsecaseStrings mirrors the gallery's ace-step-turbo entry
(sound_generation, tts). preferences.backend overrides.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): surface ErrAmbiguousImport on text-to-image misses
Adds text-to-image to ambiguousModalities whitelist and covers the
h94/IP-Adapter-FaceID case — pipeline_tag=text-to-image but ships only
.bin/.safetensors so diffusers, stablediffusion-ggml, llama-cpp,
transformers, vllm, mlx, and ace-step all miss. DiscoverModelConfig now
surfaces ErrAmbiguousImport for that shape instead of the opaque
"no importer matched" error.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for vllm-omni importer
Introduces the test surface for the forthcoming VLLMOmniImporter:
detection via preferences.backend, Qwen owner + Omni repo token,
URI-only fallback, negative cases (plain Qwen, random OmniX repo), and
Import() emitting backend: vllm-omni with chat + multimodal usecases.
Includes a registration-order assertion via DiscoverModelConfig to pin
the requirement that vllm-omni wins over vllm for Qwen Omni repos
(tokenizer files are usually present too).
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add vllm-omni importer
Adds VLLMOmniImporter for Qwen Omni-style multimodal checkpoints
(Qwen3-Omni, Qwen2.5-Omni, …). Detection is narrow: HF owner "Qwen"
combined with "omni" in the repo name, or a repo name matching the
-Omni-/Omni- naming pattern. preferences.backend="vllm-omni" always
wins; HFOwnerRepoFromURI provides a URI-only fallback for the hfapi
recursion-bug edge case.
Emitted YAML sets backend: vllm-omni and known_usecases: [chat,
multimodal], matching the gallery/index.yaml vllm-omni entries. The
importer is registered ahead of VLLMImporter so Qwen Omni repos —
which also carry tokenizer files — route to vllm-omni rather than the
plain vllm backend.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for llama-cpp drop-in preferences
Pins the expected drop-in replacement behaviour: preferences.backend
of ik-llama-cpp or turboquant must swap the emitted YAML backend
field while keeping the llama-cpp file layout identical. Also covers
the unknown-backend case (must stay llama-cpp) and re-asserts
AdditionalBackends() returns the two curated entries with non-empty
descriptions.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): llama-cpp honours ik-llama-cpp and turboquant drop-in preferences
preferences.backend set to ik-llama-cpp or turboquant now swaps the
emitted YAML backend field while leaving the file layout, model path,
mmproj handling and everything else in the llama-cpp Import pipeline
untouched. Unknown values are ignored and fall back to backend:
llama-cpp so arbitrary input can't leak into the config.
Aligns the AdditionalBackends() descriptions with the user-facing
naming conventions surfaced via /backends/known. No changes to the
pref-only curated list in endpoints/localai/backend.go: the two
drop-in names have always lived on the importer side via
AdditionalBackends.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for silero-vad importer
Add the SileroVADImporter test fixtures covering metadata, preference
overrides, snakers4 + onnx detection, silero_vad.onnx canonical filename,
URI fallback, and live HF discovery. Implementation follows in the next
commit.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add silero-vad importer
Recognise the Silero VAD ONNX packaging: the canonical silero_vad.onnx
filename or any ONNX file under the snakers4 owner. Emits a
backend: silero-vad config with the vad known_usecase, and attaches the
canonical file entry when present so the weights download on import.
Registered before the generic importers so the unique-filename signal
takes precedence over any downstream tokenizer-based matcher.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for rerankers importer
Cover the RerankersImporter contract: interface metadata, preference
override, cross-encoder owner detection, case-insensitive 'reranker'
substring match (BAAI/bge-reranker, Alibaba-NLP/gte-reranker), URI
fallback, and the full-discovery ordering check that a BAAI reranker
repo must route to the rerankers importer rather than transformers.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add rerankers importer
Recognise reranker repositories — cross-encoder owner or any repo whose
name contains 'reranker' (case-insensitive). Emits backend: rerankers
with reranking: true and the rerank known_usecase.
Registered ahead of sentencetransformers and transformers so reranker
repos that happen to ship tokenizer.json or modules.json still route
here.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for sentencetransformers importer
Cover the SentenceTransformersImporter contract: interface metadata,
preference override, modules.json marker file, sentence_bert_config.json
marker file, sentence-transformers owner, URI fallback, and the
full-discovery ordering check that ensures a sentence-transformers HF
URI routes here rather than transformers.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add sentencetransformers importer
Recognise sentence-transformers embedding repos by modules.json,
sentence_bert_config.json, or the sentence-transformers owner. Emits
backend: sentencetransformers with embeddings: true and the embeddings
known_usecase.
Registered ahead of transformers so ST repos that carry tokenizer.json
still route here.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): add failing tests for rfdetr importer
Cover the RFDetrImporter contract: interface metadata, preference
override, case-insensitive rf-detr and rfdetr substring matches, URI
fallback, and negative cases. Implementation follows in the next
commit.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(gallery/importers): add rfdetr importer
Recognise RF-DETR object-detection repositories by a case-insensitive
'rf-detr' / 'rfdetr' substring in the repo name. Emits backend: rfdetr
with the detection known_usecase.
Registered ahead of transformers so RF-DETR repos with tokenizer
artefacts still route here.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(gallery/importers): surface ErrAmbiguousImport on sentence-similarity misses
Add an ambiguity fixture covering the embeddings/rerankers modality.
Qdrant/bm25 carries pipeline_tag=sentence-similarity but ships only
config.json + stopword .txt files — none of the Batch 5 importers
(silero-vad, rerankers, sentencetransformers, rfdetr) or the generic
vllm/transformers/llama-cpp/mlx/diffusers importers match. Because the
modality is in the ambiguous whitelist, DiscoverModelConfig must
surface ErrAmbiguousImport.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(localai/backend): red tests for KnownBackend.Installed flag
Extend the /backends/known suite with three failing cases that pin down
the forthcoming Installed field: JSON field presence on every entry,
flipping to true when an importer-registered backend is also present on
disk (and staying false for non-installed pref-only entries), and
surfacing system-only backends with empty modality and AutoDetect=false.
A small writeFakeSystemBackend helper plants a run.sh under the backends
dir so gallery.ListSystemBackends recognises the fixture.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(schema,localai/backend): add Installed flag to KnownBackend
Add an Installed bool to schema.KnownBackend and populate it from the
/backends/known handler so the React import form can warn users that
picking a not-yet-installed backend will trigger an automatic download
on submit.
Computation: after merging the importer registry, additional backends
provider entries and the curated pref-only slice, the handler walks
gallery.ListSystemBackends(systemState) and either flips the existing
map entry's Installed flag to true (preserving modality / autodetect /
description metadata) or inserts a bare {Installed:true} entry for
system-only backends the importer layer doesn't know about.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(localai/import_model): structured ambiguous-import response
Add red tests covering the extended ambiguity shape the React import
form needs:
- ImportModelURIEndpoint must return an HTTP 400 body that exposes the
detected `modality` (normalised to the importer modality key, e.g.
"tts" for pipeline_tag=text-to-speech) and a list of `candidates`
(backend names filtered by modality, excluding text-LLM backends).
- The importers package must surface a typed AmbiguousImportError so
HTTP consumers can read Modality + Candidates without parsing the
error string. errors.Is against the existing sentinel keeps working.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(localai/import_model): structured ambiguity response with modality + candidates
DiscoverModelConfig now returns a typed AmbiguousImportError that
carries the importer modality key, candidate backend names, the
original URI, and the raw HF pipeline_tag. Its Is() preserves
errors.Is(err, ErrAmbiguousImport) for legacy callers.
The importer modality is pre-mapped from the HF pipeline_tag
(automatic-speech-recognition → asr, text-to-speech → tts, etc) via
PipelineTagToModality — surfaced as an exported helper so downstream
consumers can avoid duplicating the table. CandidatesForModality
filters the default importer registry plus AdditionalBackendsProvider
drop-ins by modality, sorts deterministically, and is the single
source of truth used by ImportModelURIEndpoint.
ImportModelURIEndpoint now returns HTTP 400 with
{ error, detail, modality, candidates, hint }
when ambiguity fires, letting the React form render a modality-scoped
picker inline instead of a generic toast.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): manual pick badge + tooltip
Red Playwright coverage for the preference-only → manual pick rename:
- The Backend dropdown renders a "manual pick" badge on every option
whose KnownBackend.auto_detect is false.
- The badge carries a title attribute with hover-tooltip copy that
explains auto-detect won't route to this backend.
- Auto-detectable backends must NOT carry the badge.
- The legacy " (preference-only)" suffix is gone from every label.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* ui(import): replace preference-only suffix with manual pick badge
SearchableSelect option rows now support an optional badge field — a
muted pill rendered to the right of the label with an optional title
attribute for native hover tooltips. Plain text so screen readers read
it alongside the option name.
buildBackendOptions in ImportModel stops appending " (preference-only)"
to the label and instead sets badge="manual pick" plus a descriptive
tooltip on every option whose auto_detect is false. The Backend help
text explains what "manual pick" means so users aren't left wondering
about the badge.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): inline ambiguity picker
Red Playwright coverage for Batch A2 — when the server returns a 400
ambiguity body, the form must render an inline alert instead of a
toast, expose one clickable chip per candidate backend, and support
both auto-resubmit on pick and silent dismiss.
- Mocks /api/models/import-uri with the structured ambiguity body
(error, detail, modality, candidates, hint).
- On first click of Import, the alert is visible, carries
modality-specific copy, and shows a chip per candidate.
- Clicking a chip clears the alert, sets the Backend dropdown, and
triggers a second POST to /api/models/import-uri.
- Dismissing the alert leaves the Backend dropdown on Auto-detect —
no implicit backend assignment.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): inline ambiguity alert with candidate chips
Adds AmbiguityAlert — a soft, info-coloured card rendered above the URI
input when the server returns a structured 400 with { modality,
candidates }. Message is modality-aware (tts/asr/embeddings/image/
reranker/detection get purpose-written copy, everything else falls back
to a generic template). Each candidate is a clickable chip that shows a
download icon when /backends/known marks the backend as not yet
installed, so users aren't surprised by an implicit install.
ImportModel wires the alert to handleSimpleImport's error path:
- api.handleResponse now attaches { status, body } to the thrown Error
so pages can pattern-match on structured responses instead of string
error messages.
- handleSimpleImport detects `status === 400 && body.error === 'ambiguous
import'` and flips into the inline-picker mode instead of toasting.
- Clicking a chip sets prefs.backend and auto-resubmits (passing the
picked backend as an override so setPrefs's asynchrony doesn't leak
a stale value).
- Dismissing clears the alert; changing the URI or the backend also
clears it so a stale alert never sticks around.
Test fixtures mock GET /backends/known + POST /models/import-uri so the
Playwright specs don't depend on real network reachability.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): auto-install warning
Red Playwright coverage for Batch A3 — when the user picks a backend
whose KnownBackend.installed is false, the form must render a muted
inline note under the Backend dropdown warning that submitting will
download the backend first. Picking an installed backend or leaving
Auto-detect selected must keep the note hidden.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): auto-install warning under backend dropdown
When the user picks a backend whose KnownBackend.installed is false,
render a muted inline note under the Backend dropdown's help text
warning that submitting will download the backend first. The note
lives inside the same form-group so it lines up with the existing
hint text; it's hidden when Auto-detect is selected (the selected
backend is unknowable at that point) or when the chosen backend is
already on disk.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* ui(import): drop redundant section header, adjust icons, rename HF shortcut
- Remove the "Import from URI" card-level <h2> — the page title already
says "Import New Model" one row up, so the secondary header was
duplicating information.
- Swap the fa-star on "Common Preferences" for fa-sliders (stars imply
favourites/ratings; this is just a preferences block) and move the
Custom Preferences fa-sliders-h to fa-plus-circle so the two blocks
read as distinct rather than as two sliders.
- Rename the HF shortcut from "Search GGUF on HF" → "Browse models on
HF" and drop the `search=gguf` filter on the linked URL. The import
form now supports ~40 backends; hard-coding GGUF in the copy no
longer matches the form's actual reach.
- Pure polish — no behaviour change, covered by the existing Batch A
Playwright suite.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): batch B — simple/power switch, options, tabs, dialog
Adds a failing Playwright suite covering the full Batch B surface ahead
of implementation:
- B1: SimplePowerSwitch segmented control renders, toggles, persists to
localStorage across reloads.
- B2: Simple-mode Options disclosure is collapsed by default; expanding
exposes only Backend, Model Name, Description (no quantizations,
mmproj, model type, or custom prefs).
- B3: Power mode has Preferences and YAML tabs with a persistent
selection across reloads; URI/name/description typed in Simple carry
over to Power; YAML tab swaps the primary action to Create.
- B4: Switching Power -> Simple with a custom preference set triggers
the 3-button confirmation dialog (Keep / Discard / Cancel) with the
documented semantics.
Tests fail against master — implementation lands in the following
commits.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): add SimplePowerSwitch segmented control
Replaces the previous "Advanced Mode / Simple Mode" toggle button in the
page header with a two-segment control that flips between Simple and
Power. The control reuses the existing .segmented CSS shared with the
Sound page for visual consistency.
Mode state is persisted to localStorage under `import-form-mode` so
reloads land on the same view (default: simple). The boolean alias
`isAdvancedMode` is retained internally to minimise diff — subsequent
commits reshape the Simple and Power surfaces independently.
Closes B1 from the Batch B Playwright suite.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): simple mode collapsible options, power tabs, switch dialog
Completes the Batch B surface in a single structural pass so Simple and
Power mode can evolve independently:
Simple mode
- URI input + Ambiguity alert + Import button, plus a collapsible
"Options" disclosure that exposes ONLY Backend, Model Name,
Description. Quantizations / MMProj / Model Type / Diffusers fields
/ Custom Preferences are no longer rendered in Simple mode.
Power mode
- In-page segmented "Preferences · YAML" tab strip. Active tab
persists to localStorage under `import-form-power-tab`.
- Preferences tab = the full existing preferences + custom prefs
panel (no progressive disclosure yet — that's Batch D).
- YAML tab = the existing CodeEditor. Primary button reads "Create"
here, "Import Model" everywhere else.
Switch dialog
- Power -> Simple with non-default prefs (advanced pref keys set,
any custom-pref key non-empty, or YAML edited away from the
template) opens a 3-button dialog: Keep & switch / Discard &
switch / Cancel.
- Keep preserves all state. Discard resets prefs + customPrefs + YAML
to defaults. Cancel leaves the user in Power mode.
Page subtitle reflects the current surface (Simple, Power/Preferences,
Power/YAML). Estimate banner renders everywhere except Power/YAML.
Closes B2/B3/B4 from the Batch B Playwright suite.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): expand Options disclosure in Batch A tests
Batch B hid the Backend dropdown behind a collapsible Options disclosure
in Simple mode. The Batch A tests that exercise the dropdown directly
(manual-pick badge, ambiguity chip sets the selected backend, auto-
install warning) now click the disclosure toggle before asserting on
dropdown contents. Test intent is unchanged.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* ui(import): strip decorative icons from field labels
The preference panel had 12 Font Awesome icons decorating field labels
(Backend, Model Name, Description, Quantizations, MMProj Quantizations,
Model Type, Pipeline Type, Scheduler Type, Enable Parameters, Embeddings,
CUDA, plus fa-link on Model URI). Every label screamed equally, flattening
the visual hierarchy.
Remove them. Keep icons where they carry meaning: page-level section
headers, URI format guide entries, primary buttons, the Simple-mode
Options disclosure, the ambiguity alert's fa-lightbulb, the auto-install
note's fa-download, and the Estimated-requirements banner's
fa-memory / fa-microchip / fa-download.
No new behaviour, no layout / spacing changes beyond removing the
orphaned icon margin. Playwright suite green.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): progressive disclosure of preference fields
Cover the Batch D visibility matrix for Power > Preferences: Quantizations,
MMProj Quantizations, and Model Type each render only for the backends that
can consume them, stay visible when the backend is unset, and preserve any
value the user already typed when toggled off and back on. Also pin the
shrunk Description textarea at rows=2.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): progressive disclosure + shorter description textarea
Gate Quantizations, MMProj Quantizations, and Model Type in the Power >
Preferences tab so each field only renders for the backends that can
actually consume it. Backend unset keeps everything visible. Hidden
fields' state is preserved (the JSX wrapper is guarded, not the
underlying prefs state) so users flipping backends back and forth don't
lose input.
Also shrink the Description textarea from rows=3 to rows=2 — it's
shared between Simple Options and Power Preferences so the change
applies to both.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): enter-to-submit in Simple mode
Red test for Batch F3 — pressing Enter in the URI input must POST
/models/import-uri, and Enter in the Description textarea must insert
a newline without submitting the form.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): enter-to-submit in Simple mode
Wrap the Simple-mode URI input + ambiguity alert + Options disclosure
in a <form> whose onSubmit calls handleSimpleImport. Pressing Enter in
the URI input (or any Simple-mode text input) now submits the import
without having to move the mouse to the header button. The Description
textarea keeps its native behaviour — Enter inserts a newline.
A hidden submit button is included because the visible Import button
lives outside the form in the page header; some browsers only fire
implicit Enter-submit when the form contains a submit-capable element.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* ui(import,SearchableSelect,components): aria-hidden on decorative icons
Every Font Awesome icon in the import form is decorative — its meaning
is already conveyed by adjacent visible text. Adding aria-hidden="true"
prevents screen readers from announcing the unicode glyph point as
content. Covers ImportModel.jsx (all remaining <i> glyphs) and
SearchableSelect.jsx (the trigger chevron).
AmbiguityAlert and SimplePowerSwitch already set aria-hidden on their
icons when the components landed in Batches A and B — no change needed
there.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* ui(SearchableSelect): responsive dropdown maxHeight + hover focus guard
F2 — replace fixed pixel heights with min(pixel, vh) so the dropdown
and its inner scroll region don't overflow short viewports. Outer
container: 260px -> min(260px, 60vh); inner listbox: 200px ->
min(200px, 50vh). Tall viewports still get the original pixel caps.
F5 — short-circuit onMouseEnter when the hovered row is already the
focused row. Avoids queueing a setFocusIndex call (and a render) for
every mousemove inside the same item — the state would be identical.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* ui(import): aria-label on custom preference rows
The Key / Value inputs and trash button in each Custom Preferences row
previously relied on placeholder text alone. Placeholders are not
accessible names — they vanish on input and screen readers do not
announce them consistently. Add row-indexed aria-labels so assistive
tech can distinguish "Preference key for row 1" from "row 2", and give
the trash button an explicit "Remove this preference" label.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* test(ui/import): modality chip row
Red tests for Batch E — a horizontal modality chip row that filters the
Backend dropdown by modality. Covers visibility in Simple-mode Options
and Power/Preferences (and absence in Power/YAML), filter behaviour,
mismatched-backend clearing with toast, ambiguity-alert auto-selection,
and radiogroup keyboard navigation.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* feat(ui/import): add ModalityChips component + filter integration
Horizontal chip row (Any, Text, Speech, TTS, Image, Embeddings,
Rerankers, Detection, VAD) filters the Backend dropdown options to the
selected modality. Default is Any — no filter, current behaviour.
- New ModalityChips component (radiogroup pattern, roving tabindex,
arrow-key navigation, Home/End).
- buildBackendOptions now accepts an optional modalityFilter so grouped
output is narrowed before rendering.
- Chips render inside Simple-mode Options disclosure and Power >
Preferences tab. Power > YAML stays unaffected.
- Switching the filter drops a mismatched backend selection and
surfaces a toast so the auto-clear is visible.
- Ambiguity alerts auto-activate the matching chip so users see only
relevant backends even if they dismiss the alert.
Tightens the Batch E tests' option-matching to the label <span> so the
"↵" keybind hint on the focused row doesn't break accessible-name
lookups.
Assisted-by: Claude:claude-opus-4-7[1m] [Agent]
* fix(ui/import): rename Power to Advanced + stop URI-formats toggle from submitting form
The "Supported URI Formats" disclosure button inside the Simple-mode form
lacked an explicit type attribute, so it defaulted to type="submit". Every
click triggered the form's onSubmit and surfaced the empty-URI validation
toast ("Please enter a model URI"). Marking it type="button" lets it
behave as a pure toggle.
While here, rename the user-visible "Power" label to "Advanced" in the
mode switch (button text + tooltip) and the Power-mode tab's aria-label,
matching the term users actually expect. The internal mode key stays
'power' so tests, localStorage, and data-testid selectors are untouched.
Assisted-by: Claude:claude-opus-4-7
* fix(system): fall back to cpu when meta backend lacks default capability
Meta backends like vllm and sglang enumerate concrete variants for
nvidia/amd/intel/cpu but omit a default: catch-all entry. On a no-GPU
host the reported capability is "default", so the previous Capability()
returned "default" unconditionally on a miss — IsCompatibleWith then saw
no "default" key and filtered the meta out of AvailableBackends. The
import flow's auto-install step then failed with "no backend found with
name <meta>", contradicting the UI's promise that the backend would be
downloaded on demand.
Try the explicit "default" key first, then fall back to "cpu" before
giving up. vllm now resolves to cpu-vllm on CPU-only Linux without
touching the gallery YAML.
Assisted-by: Claude:claude-opus-4-7
|
||
|
Ettore Di Giacinto
|
372eb08dcf |
fix(gallery): allow uninstalling orphaned meta backends + force reinstall (#9434)
Two interrelated bugs that combined to make a meta backend impossible to uninstall once its concrete had been removed from disk (partial install, earlier crash, manual cleanup). 1. DeleteBackendFromSystem returned "meta backend %q not found" and bailed out early when the concrete directory didn't exist, preventing the orphaned meta dir from ever being removed. Treat a missing concrete as idempotent success — log a warning and continue to remove the orphan meta. 2. InstallBackendFromGallery's "already installed, skip" short-circuit only checked that the name was known (`backends.Exists(name)`); an orphaned meta whose RunFile points at a missing concrete still satisfies that check, so every reinstall returned nil without doing anything. Afterwards the worker's findBackend returned empty and we kept looping with "backend %q not found after install attempt". Require the entry to be actually runnable (run.sh stat-able, not a directory) before skipping. New helper isBackendRunnable centralises the runnability test so both the install guard and future callers stay in sync. Tests cover the orphaned-meta delete path and the non-runnable short-circuit case. |
||
|
Ettore Di Giacinto
|
75a63f87d8 |
feat(distributed): sync state with frontends, better backend management reporting (#9426)
* fix(distributed): detect backend upgrades across worker nodes
Before this change `DistributedBackendManager.CheckUpgrades` delegated to the
local manager, which read backends from the frontend filesystem. In
distributed deployments the frontend has no backends installed locally —
they live on workers — so the upgrade-detection loop never ran and the UI
silently never surfaced upgrades even when the gallery advertised newer
versions or digests.
Worker-side: NATS backend.list reply now carries Version, URI and Digest
for each installed backend (read from metadata.json).
Frontend-side: DistributedBackendManager.ListBackends aggregates per-node
refs (name, status, version, digest) instead of deduping, and CheckUpgrades
feeds that aggregation into gallery.CheckUpgradesAgainst — a new entrypoint
factored out of CheckBackendUpgrades so both paths share the same core
logic.
Cluster drift policy: when per-node version/digest tuples disagree, the
backend is flagged upgradeable regardless of whether any single node
matches the gallery, and UpgradeInfo.NodeDrift enumerates the outliers so
operators can see *why* it is out of sync. The next upgrade-all realigns
the cluster.
Tests cover: drift detection, unanimous-match (no upgrade), and the
empty-installed-version path that the old distributed code silently
missed.
* feat(ui): surface backend upgrades in the System page
The System page (Manage.jsx) only showed updates as a tiny inline arrow,
so operators routinely missed them. Port the Backend Gallery's upgrade UX
so System speaks the same visual language:
- Yellow banner at the top of the Backends tab when upgrades are pending,
with an "Upgrade all" button (serial fan-out, matches the gallery) and a
"Updates only" filter toggle.
- Warning pill (↑ N) next to the tab label so the count is glanceable even
when the banner is scrolled out of view.
- Per-row labeled "Upgrade to vX.Y" button (replaces the icon-only button
that silently flipped semantics between Reinstall and Upgrade), plus an
"Update available" badge in the new Version column.
- New columns: Version (with upgrade + drift chips), Nodes (per-node
attribution badges for distributed mode, degrading to a compact
"on N nodes · M offline" chip above three nodes), Installed (relative
time).
- System backends render a "Protected" chip instead of a bare "—" so rows
still align and the reason is obvious.
- Delete uses the softer btn-danger-ghost so rows don't scream red; the
ConfirmDialog still owns the "are you sure".
The upgrade checker also needed the same per-worker fix as the previous
commit: NewUpgradeChecker now takes a BackendManager getter so its
periodic runs call the distributed CheckUpgrades (which asks workers)
instead of the empty frontend filesystem. Without this the /api/backends/
upgrades endpoint stayed empty in distributed mode even with the protocol
change in place.
New CSS primitives — .upgrade-banner, .tab-pill, .badge-row, .cell-stack,
.cell-mono, .cell-muted, .row-actions, .btn-danger-ghost — all live in
App.css so other pages can adopt them without duplicating styles.
* feat(ui): polish the Nodes page so it reads like a product
The Nodes page was the biggest visual liability in distributed mode.
Rework the main dashboard surfaces in place without changing behavior:
StatCards: uniform height (96px min), left accent bar colored by the
metric's semantic (success/warning/error/primary), icon lives in a
36x36 soft-tinted chip top-right, value is left-aligned and large.
Grid auto-fills so the row doesn't collapse on narrow viewports. This
replaces the previous thin-bordered boxes with inconsistent heights.
Table rows: expandable rows now show a chevron cue on the left (rotates
on expand) so users know rows open. Status cell became a dedicated chip
with an LED-style halo dot instead of a bare bullet. Action buttons gained
labels — "Approve", "Resume", "Drain" — so the icons aren't doing all
the semantic work; the destructive remove action uses the softer
btn-danger-ghost variant so rows don't scream red, with the ConfirmDialog
still owning the real "are you sure". Applied cell-mono/cell-muted
utility classes so label chips and addresses share one spacing/font
grammar instead of re-declaring inline styles everywhere.
Expanded drawer: empty states for Loaded Models and Installed Backends
now render as a proper drawer-empty card (dashed border, icon, one-line
hint) instead of a plain muted string that read like broken formatting.
Tabs: three inline-styled buttons became the shared .tab class so they
inherit focus ring, hover state, and the rest of the design system —
matches the System page.
"Add more workers" toggle turned into a .nodes-add-worker dashed-border
button labelled "Register a new worker" (action voice) instead of a
chevron + muted link that operators kept mistaking for broken text.
New shared CSS primitives carry over to other pages:
.stat-grid + .stat-card, .row-chevron, .node-status, .drawer-empty,
.nodes-add-worker.
* feat(distributed): durable backend fan-out + state reconciliation
Two connected problems handled together:
1) Backend delete/install/upgrade used to silently skip non-healthy nodes,
so a delete during an outage left a zombie on the offline node once it
returned. The fan-out now records intent in a new pending_backend_ops
table before attempting the NATS round-trip. Currently-healthy nodes
get an immediate attempt; everyone else is queued. Unique index on
(node_id, backend, op) means reissuing the same operation refreshes
next_retry_at instead of stacking duplicates.
2) Loaded-model state could drift from reality: a worker OOM'd, got
killed, or restarted a backend process would leave a node_models row
claiming the model was still loaded, feeding ghost entries into the
/api/nodes/models listing and the router's scheduling decisions.
The existing ReplicaReconciler gains two new passes that run under a
fresh KeyStateReconciler advisory lock (non-blocking, so one wedged
frontend doesn't freeze the cluster):
- drainPendingBackendOps: retries queued ops whose next_retry_at has
passed on currently-healthy nodes. Success deletes the row; failure
bumps attempts and pushes next_retry_at out with exponential backoff
(30s → 15m cap). ErrNoResponders also marks the node unhealthy.
- probeLoadedModels: gRPC-HealthChecks addresses the DB thinks are
loaded but hasn't seen touched in the last probeStaleAfter (2m).
Unreachable addresses are removed from the registry. A pluggable
ModelProber lets tests substitute a fake without standing up gRPC.
DistributedBackendManager exposes DeleteBackendDetailed so the HTTP
handler can surface per-node outcomes ("2 succeeded, 1 queued") to the
UI in a follow-up commit; the existing DeleteBackend still returns
error-only for callers that don't care about node breakdown.
Multi-frontend safety: the state pass uses advisorylock.TryWithLockCtx
on a new key so N frontends coordinate — the same pattern the health
monitor and replica reconciler already rely on. Single-node mode runs
both passes inline (adapter is nil, state drain is a no-op).
Tests cover the upsert semantics, backoff math, the probe removing an
unreachable model but keeping a reachable one, and filtering by
probeStaleAfter.
* feat(ui): show cluster distribution of models in the System page
When a frontend restarted in distributed mode, models that workers had
already loaded weren't visible until the operator clicked into each node
manually — the /api/models/capabilities endpoint only knew about
configs on the frontend's filesystem, not the registry-backed truth.
/api/models/capabilities now joins in ListAllLoadedModels() when the
registry is active, returning loaded_on[] with node id/name/state/status
for each model. Models that live in the registry but lack a local config
(the actual ghosts, not recovered from the frontend's file cache) still
surface with source="registry-only" so operators can see and persist
them; without that emission they'd be invisible to this frontend.
Manage → Models replaces the old Running/Idle pill with a distribution
cell that lists the first three nodes the model is loaded on as chips
colored by state (green loaded, blue loading, amber anything else). On
wider clusters the remaining count collapses into a +N chip with a
title-attribute breakdown. Disabled / single-node behavior unchanged.
Adopted models get an extra "Adopted" ghost-icon chip with hover copy
explaining what it means and how to make it permanent.
Distributed mode also enables a 10s auto-refresh and a "Last synced Xs
ago" indicator next to the Update button so ghost rows drop off within
one reconcile tick after their owning process dies. Non-distributed
mode is untouched — no polling, no cell-stack, same old Running/Idle.
* feat(ui): NodeDistributionChip — shared per-node attribution component
Large clusters were going to break the Manage → Backends Nodes column:
the old inline logic rendered every node as a badge and would shred the
layout at >10 workers, plus the Manage → Models distribution cell had
copy-pasted its own slightly-different version.
NodeDistributionChip handles any cluster size with two render modes:
- small (≤3 nodes): inline chips of node names, colored by health.
- large: a single "on N nodes · M offline · K drift" summary chip;
clicking opens a Popover with a per-node table (name, status,
version, digest for backends; name, status, state for models).
Drift counting mirrors the backend's summarizeNodeDrift so the UI
number matches UpgradeInfo.NodeDrift. Digests are truncated to the
docker-style 12-char form with the full value preserved in the title.
Popover is a new general-purpose primitive: fixed positioning anchored
to the trigger, flips above when there's no room below, closes on
outside-click or Escape, returns focus to the trigger. Uses .card as
its surface so theming is inherited. Also useful for a future
labels-editor popup and the user menu.
Manage.jsx drops its duplicated inline Nodes-column + loaded_on cell
and uses the shared chip with context="backends" / "models"
respectively. Delete code removes ~40 lines of ad-hoc logic.
* feat(ui): shared FilterBar across the System page tabs
The Backends gallery had a nice search + chip + toggle strip; the System
page had nothing, so the two surfaces felt like different apps. Lift the
pattern into a reusable FilterBar and wire both System tabs through it.
New component core/http/react-ui/src/components/FilterBar.jsx renders a
search input, a role="tablist" chip row (aria-selected for a11y), and
optional toggles / right slot. Chips support an optional `count` which
the System page uses to show "User 3", "Updates 1" etc.
System Models tab: search by id or backend; chips for
All/Running/Idle/Disabled/Pinned plus a conditional Distributed chip in
distributed mode. "Last synced" + Update button live in the right slot.
System Backends tab: search by name/alias/meta-backend-for; chips for
All/User/System/Meta plus conditional Updates / Offline-nodes chips
when relevant. The old ad-hoc "Updates only" toggle from the upgrade
banner folded into the Updates chip — one source of truth for that
filter. Offline chip only appears in distributed mode when at least
one backend has an unhealthy node, so the chip row stays quiet on
healthy clusters.
Filter state persists in URL query params (mq/mf/bq/bf) so deep links
and tab switches keep the operator's filter context instead of
resetting every time.
Also adds an "Adopted" distribution path: when a model in
/api/models/capabilities carries source="registry-only" (discovered on
a worker but not configured locally), the Models tab shows a ghost chip
labelled "Adopted" with hover copy explaining how to persist it — this
is what closes the loop on the ghost-model story end-to-end.
|
||
|
Ettore Di Giacinto
|
7c5d6162f7 |
fix(ui): rename model config files on save to prevent duplicates (#9388)
Editing a model's YAML and changing the `name:` field previously wrote the new body to the original `<oldName>.yaml`. On reload the config loader indexed that file under the new name while the old key lingered in memory, producing two entries in the system UI that shared a single underlying file — deleting either removed both. Detect the rename in EditModelEndpoint and rename the on-disk `<name>.yaml` and `._gallery_<name>.yaml` to match, drop the stale in-memory key before the reload, and redirect the editor URL in the React UI so it tracks the new name. Reject conflicts (409) and names containing path separators (400). Fixes #9294 |
||
|
Ettore Di Giacinto
|
016da02845 |
feat: refactor shared helpers and enhance MLX backend functionality (#9335)
* refactor(backends): extract python_utils + add mlx_utils shared helpers
Move parse_options() and messages_to_dicts() out of vllm_utils.py into a
new framework-agnostic python_utils.py, and re-export them from vllm_utils
so existing vllm / vllm-omni imports keep working.
Add mlx_utils.py with split_reasoning() and parse_tool_calls() — ported
from mlx_vlm/server.py's process_tool_calls. These work with any
mlx-lm / mlx-vlm tool module (anything exposing tool_call_start,
tool_call_end, parse_tool_call). Used by the mlx and mlx-vlm backends in
later commits to emit structured ChatDelta.tool_calls without
reimplementing per-model parsing.
Shared smoke tests confirm:
- parse_options round-trips bool/int/float/string
- vllm_utils re-exports are identity-equal to python_utils originals
- mlx_utils parse_tool_calls handles <tool_call>...</tool_call> with a
shim module and produces a correctly-indexed list with JSON arguments
- mlx_utils split_reasoning extracts <think> blocks and leaves clean
content
* feat(mlx): wire native tool parsers + ChatDelta + token usage + logprobs
Bring the MLX backend up to the same structured-output contract as vLLM
and llama.cpp: emit Reply.chat_deltas so the OpenAI HTTP layer sees
tool_calls and reasoning_content, not just raw text.
Key insight: mlx_lm.load() returns a TokenizerWrapper that already auto-
detects the right tool parser from the model's chat template
(_infer_tool_parser in mlx_lm/tokenizer_utils.py). The wrapper exposes
has_tool_calling, has_thinking, tool_parser, tool_call_start,
tool_call_end, think_start, think_end — no user configuration needed,
unlike vLLM.
Changes in backend/python/mlx/backend.py:
- Imports: replace inline parse_options / messages_to_dicts with the
shared helpers from python_utils. Pull split_reasoning / parse_tool_calls
from the new mlx_utils shared module.
- LoadModel: log the auto-detected has_tool_calling / has_thinking /
tool_parser_type for observability. Drop the local is_float / is_int
duplicates.
- _prepare_prompt: run request.Messages through messages_to_dicts so
tool_call_id / tool_calls / reasoning_content survive the conversion,
and pass tools=json.loads(request.Tools) + enable_thinking=True (when
request.Metadata says so) to apply_chat_template. Falls back on
TypeError for tokenizers whose template doesn't accept those kwargs.
- _build_generation_params: return an additional (logits_params,
stop_words) pair. Maps RepetitionPenalty / PresencePenalty /
FrequencyPenalty to mlx_lm.sample_utils.make_logits_processors and
threads StopPrompts through to post-decode truncation.
- New _tool_module_from_tokenizer / _finalize_output / _truncate_at_stop
helpers. _finalize_output runs split_reasoning when has_thinking is
true and parse_tool_calls (using a SimpleNamespace shim around the
wrapper's tool_parser callable) when has_tool_calling is true, then
extracts prompt_tokens, generation_tokens and (best-effort) logprobs
from the last GenerationResponse chunk.
- Predict: use make_logits_processors, accumulate text + last_response,
finalize into a structured Reply carrying chat_deltas,
prompt_tokens, tokens, logprobs. Early-stops on user stop sequences.
- PredictStream: per-chunk Reply still carries raw message bytes for
back-compat but now also emits chat_deltas=[ChatDelta(content=delta)].
On loop exit, emit a terminal Reply with structured
reasoning_content / tool_calls / token counts / logprobs — so the Go
side sees tool calls without needing the regex fallback.
- TokenizeString RPC: uses the TokenizerWrapper's encode(); returns
length + tokens or FAILED_PRECONDITION if the model isn't loaded.
- Free RPC: drops model / tokenizer / lru_cache, runs gc.collect(),
calls mx.metal.clear_cache() when available, and best-effort clears
torch.cuda as a belt-and-suspenders.
* feat(mlx-vlm): mirror MLX parity (tool parsers + ChatDelta + samplers)
Same treatment as the MLX backend: emit structured Reply.chat_deltas,
tool_calls, reasoning_content, token counts and logprobs, and extend
sampling parameter coverage beyond the temp/top_p pair the backend
used to handle.
- Imports: drop the inline is_float/is_int helpers, pull parse_options /
messages_to_dicts from python_utils and split_reasoning /
parse_tool_calls from mlx_utils. Also import make_sampler and
make_logits_processors from mlx_lm.sample_utils — mlx-vlm re-uses them.
- LoadModel: use parse_options; call mlx_vlm.tool_parsers._infer_tool_parser
/ load_tool_module to auto-detect a tool module from the processor's
chat_template. Stash think_start / think_end / has_thinking so later
finalisation can split reasoning blocks without duck-typing on each
call. Logs the detected parser type.
- _prepare_prompt: convert proto Messages via messages_to_dicts (so
tool_call_id / tool_calls survive), pass tools=json.loads(request.Tools)
and enable_thinking=True to apply_chat_template when present, fall
back on TypeError for older mlx-vlm versions. Also handle the
prompt-only + media and empty-prompt + media paths consistently.
- _build_generation_params: return (max_tokens, sampler_params,
logits_params, stop_words). Maps repetition_penalty / presence_penalty /
frequency_penalty and passes them through make_logits_processors.
- _finalize_output / _truncate_at_stop: common helper used by Predict
and PredictStream to split reasoning, run parse_tool_calls against the
auto-detected tool module, build ToolCallDelta list, and extract token
counts + logprobs from the last GenerationResult.
- Predict / PredictStream: switch from mlx_vlm.generate to mlx_vlm.stream_generate
in both paths, accumulate text + last_response, pass sampler and
logits_processors through, emit content-only ChatDelta per streaming
chunk followed by a terminal Reply carrying reasoning_content,
tool_calls, prompt_tokens, tokens and logprobs. Non-streaming Predict
returns the same structured Reply shape.
- New helper _collect_media extracted from the duplicated base64 image /
audio decode loop.
- New TokenizeString RPC using the processor's tokenizer.encode and
Free RPC that drops model/processor/config, runs gc + Metal cache
clear + best-effort torch.cuda cache clear.
* feat(importer/mlx): auto-set tool_parser/reasoning_parser on import
Mirror what core/gallery/importers/vllm.go does: after applying the
shared inference defaults, look up the model URI in parser_defaults.json
and append matching tool_parser:/reasoning_parser: entries to Options.
The MLX backends auto-detect tool parsers from the chat template at
runtime so they don't actually consume these options — but surfacing
them in the generated YAML:
- keeps the import experience consistent with vllm
- gives users a single visible place to override
- documents the intended parser for a given model family
* test(mlx): add helper unit tests + TokenizeString/Free + e2e make targets
- backend/python/mlx/test.py: add TestSharedHelpers with server-less
unit tests for parse_options, messages_to_dicts, split_reasoning and
parse_tool_calls (using a SimpleNamespace shim to fake a tool module
without requiring a model). Plus test_tokenize_string and test_free
RPC tests that load a tiny MLX-quantized Llama and exercise the new
RPCs end-to-end.
- backend/python/mlx-vlm/test.py: same helper unit tests + cleanup of
the duplicated import block at the top of the file.
- Makefile: register BACKEND_MLX and BACKEND_MLX_VLM (they were missing
from the docker-build-target eval list — only mlx-distributed had a
generated target before). Add test-extra-backend-mlx and
test-extra-backend-mlx-vlm convenience targets that build the
respective image and run tests/e2e-backends with the tools capability
against mlx-community/Qwen2.5-0.5B-Instruct-4bit. The MLX backend
auto-detects the tool parser from the chat template so no
BACKEND_TEST_OPTIONS is needed (unlike vllm).
* fix(libbackend): don't pass --copies to venv unless PORTABLE_PYTHON=true
backend/python/common/libbackend.sh:ensureVenv() always invoked
'python -m venv --copies', but macOS system python (and some other
builds) refuses with:
Error: This build of python cannot create venvs without using symlinks
--copies only matters when _makeVenvPortable later relocates the venv,
which only happens when PORTABLE_PYTHON=true. Make --copies conditional
on that flag and fall back to default (symlinked) venv otherwise.
Caught while bringing up the mlx backend on Apple Silicon — the same
build path is used by every Python backend with USE_PIP=true.
* fix(mlx): support mlx-lm 0.29.x tool calling + drop deprecated clear_cache
The released mlx-lm 0.29.x ships a much simpler tool-calling API than
HEAD: TokenizerWrapper detects the <tool_call>...</tool_call> markers
from the tokenizer vocab and exposes has_tool_calling /
tool_call_start / tool_call_end, but does NOT expose a tool_parser
callable on the wrapper and does NOT ship a mlx_lm.tool_parsers
subpackage at all (those only exist on main).
Caught while running the smoke test on Apple Silicon with the
released mlx-lm 0.29.1: tokenizer.tool_parser raised AttributeError
(falling through to the underlying HF tokenizer), so
_tool_module_from_tokenizer always returned None and tool calls slipped
through as raw <tool_call>...</tool_call> text in Reply.message instead
of being parsed into ChatDelta.tool_calls.
Fix: when has_tool_calling is True but tokenizer.tool_parser is missing,
default the parse_tool_call callable to json.loads(body.strip()) — that's
exactly what mlx_lm.tool_parsers.json_tools.parse_tool_call does on HEAD
and covers the only format 0.29 detects (<tool_call>JSON</tool_call>).
Future mlx-lm releases that ship more parsers will be picked up
automatically via the tokenizer.tool_parser attribute when present.
Also tighten the LoadModel logging — the old log line read
init_kwargs.get('tool_parser_type') which doesn't exist on 0.29 and
showed None even when has_tool_calling was True. Log the actual
tool_call_start / tool_call_end markers instead.
While here, switch Free()'s Metal cache clear from the deprecated
mx.metal.clear_cache to mx.clear_cache (mlx >= 0.30), with a
fallback for older releases. Mirrored to the mlx-vlm backend.
* feat(mlx-distributed): mirror MLX parity (tool calls + ChatDelta + sampler)
Same treatment as the mlx and mlx-vlm backends: emit Reply.chat_deltas
with structured tool_calls / reasoning_content / token counts /
logprobs, expand sampling parameter coverage beyond temp+top_p, and
add the missing TokenizeString and Free RPCs.
Notes specific to mlx-distributed:
- Rank 0 is the only rank that owns a sampler — workers participate in
the pipeline-parallel forward pass via mx.distributed and don't
re-implement sampling. So the new logits_params (repetition_penalty,
presence_penalty, frequency_penalty) and stop_words apply on rank 0
only; we don't need to extend coordinator.broadcast_generation_params,
which still ships only max_tokens / temperature / top_p to workers
(everything else is a rank-0 concern).
- Free() now broadcasts CMD_SHUTDOWN to workers when a coordinator is
active, so they release the model on their end too. The constant is
already defined and handled by the existing worker loop in
backend.py:633 (CMD_SHUTDOWN = -1).
- Drop the locally-defined is_float / is_int / parse_options trio in
favor of python_utils.parse_options, re-exported under the module
name for back-compat with anything that imported it directly.
- _prepare_prompt: route through messages_to_dicts so tool_call_id /
tool_calls / reasoning_content survive, pass tools=json.loads(
request.Tools) and enable_thinking=True to apply_chat_template, fall
back on TypeError for templates that don't accept those kwargs.
- New _tool_module_from_tokenizer (with the json.loads fallback for
mlx-lm 0.29.x), _finalize_output, _truncate_at_stop helpers — same
contract as the mlx backend.
- LoadModel logs the auto-detected has_tool_calling / has_thinking /
tool_call_start / tool_call_end so users can see what the wrapper
picked up for the loaded model.
- backend/python/mlx-distributed/test.py: add the same TestSharedHelpers
unit tests (parse_options, messages_to_dicts, split_reasoning,
parse_tool_calls) that exist for mlx and mlx-vlm.
|
||
|
Ettore Di Giacinto
|
d67623230f |
feat(vllm): parity with llama.cpp backend (#9328)
* fix(schema): serialize ToolCallID and Reasoning in Messages.ToProto
The ToProto conversion was dropping tool_call_id and reasoning_content
even though both proto and Go fields existed, breaking multi-turn tool
calling and reasoning passthrough to backends.
* refactor(config): introduce backend hook system and migrate llama-cpp defaults
Adds RegisterBackendHook/runBackendHooks so each backend can register
default-filling functions that run during ModelConfig.SetDefaults().
Migrates the existing GGUF guessing logic into hooks_llamacpp.go,
registered for both 'llama-cpp' and the empty backend (auto-detect).
Removes the old guesser.go shim.
* feat(config): add vLLM parser defaults hook and importer auto-detection
Introduces parser_defaults.json mapping model families to vLLM
tool_parser/reasoning_parser names, with longest-pattern-first matching.
The vllmDefaults hook auto-fills tool_parser and reasoning_parser
options at load time for known families, while the VLLMImporter writes
the same values into generated YAML so users can review and edit them.
Adds tests covering MatchParserDefaults, hook registration via
SetDefaults, and the user-override behavior.
* feat(vllm): wire native tool/reasoning parsers + chat deltas + logprobs
- Use vLLM's ToolParserManager/ReasoningParserManager to extract structured
output (tool calls, reasoning content) instead of reimplementing parsing
- Convert proto Messages to dicts and pass tools to apply_chat_template
- Emit ChatDelta with content/reasoning_content/tool_calls in Reply
- Extract prompt_tokens, completion_tokens, and logprobs from output
- Replace boolean GuidedDecoding with proper GuidedDecodingParams from Grammar
- Add TokenizeString and Free RPC methods
- Fix missing `time` import used by load_video()
* feat(vllm): CPU support + shared utils + vllm-omni feature parity
- Split vllm install per acceleration: move generic `vllm` out of
requirements-after.txt into per-profile after files (cublas12, hipblas,
intel) and add CPU wheel URL for cpu-after.txt
- requirements-cpu.txt now pulls torch==2.7.0+cpu from PyTorch CPU index
- backend/index.yaml: register cpu-vllm / cpu-vllm-development variants
- New backend/python/common/vllm_utils.py: shared parse_options,
messages_to_dicts, setup_parsers helpers (used by both vllm backends)
- vllm-omni: replace hardcoded chat template with tokenizer.apply_chat_template,
wire native parsers via shared utils, emit ChatDelta with token counts,
add TokenizeString and Free RPCs, detect CPU and set VLLM_TARGET_DEVICE
- Add test_cpu_inference.py: standalone script to validate CPU build with
a small model (Qwen2.5-0.5B-Instruct)
* fix(vllm): CPU build compatibility with vllm 0.14.1
Validated end-to-end on CPU with Qwen2.5-0.5B-Instruct (LoadModel, Predict,
TokenizeString, Free all working).
- requirements-cpu-after.txt: pin vllm to 0.14.1+cpu (pre-built wheel from
GitHub releases) for x86_64 and aarch64. vllm 0.14.1 is the newest CPU
wheel whose torch dependency resolves against published PyTorch builds
(torch==2.9.1+cpu). Later vllm CPU wheels currently require
torch==2.10.0+cpu which is only available on the PyTorch test channel
with incompatible torchvision.
- requirements-cpu.txt: bump torch to 2.9.1+cpu, add torchvision/torchaudio
so uv resolves them consistently from the PyTorch CPU index.
- install.sh: add --index-strategy=unsafe-best-match for CPU builds so uv
can mix the PyTorch index and PyPI for transitive deps (matches the
existing intel profile behaviour).
- backend.py LoadModel: vllm >= 0.14 removed AsyncLLMEngine.get_model_config
so the old code path errored out with AttributeError on model load.
Switch to the new get_tokenizer()/tokenizer accessor with a fallback
to building the tokenizer directly from request.Model.
* fix(vllm): tool parser constructor compat + e2e tool calling test
Concrete vLLM tool parsers override the abstract base's __init__ and
drop the tools kwarg (e.g. Hermes2ProToolParser only takes tokenizer).
Instantiating with tools= raised TypeError which was silently caught,
leaving chat_deltas.tool_calls empty.
Retry the constructor without the tools kwarg on TypeError — tools
aren't required by these parsers since extract_tool_calls finds tool
syntax in the raw model output directly.
Validated with Qwen/Qwen2.5-0.5B-Instruct + hermes parser on CPU:
the backend correctly returns ToolCallDelta{name='get_weather',
arguments='{"location": "Paris, France"}'} in ChatDelta.
test_tool_calls.py is a standalone smoke test that spawns the gRPC
backend, sends a chat completion with tools, and asserts the response
contains a structured tool call.
* ci(backend): build cpu-vllm container image
Add the cpu-vllm variant to the backend container build matrix so the
image registered in backend/index.yaml (cpu-vllm / cpu-vllm-development)
is actually produced by CI.
Follows the same pattern as the other CPU python backends
(cpu-diffusers, cpu-chatterbox, etc.) with build-type='' and no CUDA.
backend_pr.yml auto-picks this up via its matrix filter from backend.yml.
* test(e2e-backends): add tools capability + HF model name support
Extends tests/e2e-backends to cover backends that:
- Resolve HuggingFace model ids natively (vllm, vllm-omni) instead of
loading a local file: BACKEND_TEST_MODEL_NAME is passed verbatim as
ModelOptions.Model with no download/ModelFile.
- Parse tool calls into ChatDelta.tool_calls: new "tools" capability
sends a Predict with a get_weather function definition and asserts
the Reply contains a matching ToolCallDelta. Uses UseTokenizerTemplate
with OpenAI-style Messages so the backend can wire tools into the
model's chat template.
- Need backend-specific Options[]: BACKEND_TEST_OPTIONS lets a test set
e.g. "tool_parser:hermes,reasoning_parser:qwen3" at LoadModel time.
Adds make target test-extra-backend-vllm that:
- docker-build-vllm
- loads Qwen/Qwen2.5-0.5B-Instruct
- runs health,load,predict,stream,tools with tool_parser:hermes
Drops backend/python/vllm/test_{cpu_inference,tool_calls}.py — those
standalone scripts were scaffolding used while bringing up the Python
backend; the e2e-backends harness now covers the same ground uniformly
alongside llama-cpp and ik-llama-cpp.
* ci(test-extra): run vllm e2e tests on CPU
Adds tests-vllm-grpc to the test-extra workflow, mirroring the
llama-cpp and ik-llama-cpp gRPC jobs. Triggers when files under
backend/python/vllm/ change (or on run-all), builds the local-ai
vllm container image, and runs the tests/e2e-backends harness with
BACKEND_TEST_MODEL_NAME=Qwen/Qwen2.5-0.5B-Instruct, tool_parser:hermes,
and the tools capability enabled.
Uses ubuntu-latest (no GPU) — vllm runs on CPU via the cpu-vllm
wheel we pinned in requirements-cpu-after.txt. Frees disk space
before the build since the docker image + torch + vllm wheel is
sizeable.
* fix(vllm): build from source on CI to avoid SIGILL on prebuilt wheel
The prebuilt vllm 0.14.1+cpu wheel from GitHub releases is compiled with
SIMD instructions (AVX-512 VNNI/BF16 or AMX-BF16) that not every CPU
supports. GitHub Actions ubuntu-latest runners SIGILL when vllm spawns
the model_executor.models.registry subprocess for introspection, so
LoadModel never reaches the actual inference path.
- install.sh: when FROM_SOURCE=true on a CPU build, temporarily hide
requirements-cpu-after.txt so installRequirements installs the base
deps + torch CPU without pulling the prebuilt wheel, then clone vllm
and compile it with VLLM_TARGET_DEVICE=cpu. The resulting binaries
target the host's actual CPU.
- backend/Dockerfile.python: accept a FROM_SOURCE build-arg and expose
it as an ENV so install.sh sees it during `make`.
- Makefile docker-build-backend: forward FROM_SOURCE as --build-arg
when set, so backends that need source builds can opt in.
- Makefile test-extra-backend-vllm: call docker-build-vllm via a
recursive $(MAKE) invocation so FROM_SOURCE flows through.
- .github/workflows/test-extra.yml: set FROM_SOURCE=true on the
tests-vllm-grpc job. Slower but reliable — the prebuilt wheel only
works on hosts that share the build-time SIMD baseline.
Answers 'did you test locally?': yes, end-to-end on my local machine
with the prebuilt wheel (CPU supports AVX-512 VNNI). The CI runner CPU
gap was not covered locally — this commit plugs that gap.
* ci(vllm): use bigger-runner instead of source build
The prebuilt vllm 0.14.1+cpu wheel requires SIMD instructions (AVX-512
VNNI/BF16) that stock ubuntu-latest GitHub runners don't support —
vllm.model_executor.models.registry SIGILLs on import during LoadModel.
Source compilation works but takes 30-40 minutes per CI run, which is
too slow for an e2e smoke test. Instead, switch tests-vllm-grpc to the
bigger-runner self-hosted label (already used by backend.yml for the
llama-cpp CUDA build) — that hardware has the required SIMD baseline
and the prebuilt wheel runs cleanly.
FROM_SOURCE=true is kept as an opt-in escape hatch:
- install.sh still has the CPU source-build path for hosts that need it
- backend/Dockerfile.python still declares the ARG + ENV
- Makefile docker-build-backend still forwards the build-arg when set
Default CI path uses the fast prebuilt wheel; source build can be
re-enabled by exporting FROM_SOURCE=true in the environment.
* ci(vllm): install make + build deps on bigger-runner
bigger-runner is a bare self-hosted runner used by backend.yml for
docker image builds — it has docker but not the usual ubuntu-latest
toolchain. The make-based test target needs make, build-essential
(cgo in 'go test'), and curl/unzip (the Makefile protoc target
downloads protoc from github releases).
protoc-gen-go and protoc-gen-go-grpc come via 'go install' in the
install-go-tools target, which setup-go makes possible.
* ci(vllm): install libnuma1 + libgomp1 on bigger-runner
The vllm 0.14.1+cpu wheel ships a _C C++ extension that dlopens
libnuma.so.1 at import time. When the runner host doesn't have it,
the extension silently fails to register its torch ops, so
EngineCore crashes on init_device with:
AttributeError: '_OpNamespace' '_C_utils' object has no attribute
'init_cpu_threads_env'
Also add libgomp1 (OpenMP runtime, used by torch CPU kernels) to be
safe on stripped-down runners.
* feat(vllm): bundle libnuma/libgomp via package.sh
The vllm CPU wheel ships a _C extension that dlopens libnuma.so.1 at
import time; torch's CPU kernels in turn use libgomp.so.1 (OpenMP).
Without these on the host, vllm._C silently fails to register its
torch ops and EngineCore crashes with:
AttributeError: '_OpNamespace' '_C_utils' object has no attribute
'init_cpu_threads_env'
Rather than asking every user to install libnuma1/libgomp1 on their
host (or every LocalAI base image to ship them), bundle them into
the backend image itself — same pattern fish-speech and the GPU libs
already use. libbackend.sh adds ${EDIR}/lib to LD_LIBRARY_PATH at
run time so the bundled copies are picked up automatically.
- backend/python/vllm/package.sh (new): copies libnuma.so.1 and
libgomp.so.1 from the builder's multilib paths into ${BACKEND}/lib,
preserving soname symlinks. Runs during Dockerfile.python's
'Run backend-specific packaging' step (which already invokes
package.sh if present).
- backend/Dockerfile.python: install libnuma1 + libgomp1 in the
builder stage so package.sh has something to copy (the Ubuntu
base image otherwise only has libgomp in the gcc dep chain).
- test-extra.yml: drop the workaround that installed these libs on
the runner host — with the backend image self-contained, the
runner no longer needs them, and the test now exercises the
packaging path end-to-end the way a production host would.
* ci(vllm): disable tests-vllm-grpc job (heterogeneous runners)
Both ubuntu-latest and bigger-runner have inconsistent CPU baselines:
some instances support the AVX-512 VNNI/BF16 instructions the prebuilt
vllm 0.14.1+cpu wheel was compiled with, others SIGILL on import of
vllm.model_executor.models.registry. The libnuma packaging fix doesn't
help when the wheel itself can't be loaded.
FROM_SOURCE=true compiles vllm against the actual host CPU and works
everywhere, but takes 30-50 minutes per run — too slow for a smoke
test on every PR.
Comment out the job for now. The test itself is intact and passes
locally; run it via 'make test-extra-backend-vllm' on a host with the
required SIMD baseline. Re-enable when:
- we have a self-hosted runner label with guaranteed AVX-512 VNNI/BF16, or
- vllm publishes a CPU wheel with a wider baseline, or
- we set up a docker layer cache that makes FROM_SOURCE acceptable
The detect-changes vllm output, the test harness changes (tests/
e2e-backends + tools cap), the make target (test-extra-backend-vllm),
the package.sh and the Dockerfile/install.sh plumbing all stay in
place.
|
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|
Ettore Di Giacinto
|
2865f0f8d3 |
feat(ux): backend management enhancement (#9325)
* feat: add PreferDevelopmentBackends setting, expose isMeta/isDevelopment in API - Add PreferDevelopmentBackends config field, CLI flag, runtime setting - Add IsDevelopment() method to GalleryBackend - Use AvailableBackendsUnfiltered in UI API to show all backends - Expose isMeta, isDevelopment, preferDevelopmentBackends in backend API response * feat: upgrade banner with Upgrade All button, detect pre-existing backends - Add upgrade banner on Backends page showing count and Upgrade All button - Fix upgrade detection for backends installed before version tracking: flag as upgradeable when gallery has a version but installed has none - Fix OCI digest check to flag backends with no stored digest as upgradeable |
||
|
Ettore Di Giacinto
|
8ab0744458 |
feat: backend versioning, upgrade detection and auto-upgrade (#9315)
* feat: add backend versioning data model foundation Add Version, URI, and Digest fields to BackendMetadata for tracking installed backend versions and enabling upgrade detection. Add Version field to GalleryBackend. Add UpgradeAvailable/AvailableVersion fields to SystemBackend. Implement GetImageDigest() for lightweight OCI digest lookups via remote.Head. Record version, URI, and digest at install time in InstallBackend() and propagate version through meta backends. * feat: add backend upgrade detection and execution logic Add CheckBackendUpgrades() to compare installed backend versions/digests against gallery entries, and UpgradeBackend() to perform atomic upgrades with backup-based rollback on failure. Includes Agent A's data model changes (Version/URI/Digest fields, GetImageDigest). * feat: add AutoUpgradeBackends config and runtime settings Add configuration and runtime settings for backend auto-upgrade: - RuntimeSettings field for dynamic config via API/JSON - ApplicationConfig field, option func, and roundtrip conversion - CLI flag with LOCALAI_AUTO_UPGRADE_BACKENDS env var - Config file watcher support for runtime_settings.json - Tests for ToRuntimeSettings, ApplyRuntimeSettings, and roundtrip * feat(ui): add backend version display and upgrade support - Add upgrade check/trigger API endpoints to config and api module - Backends page: version badge, upgrade indicator, upgrade button - Manage page: version in metadata, context-aware upgrade/reinstall button - Settings page: auto-upgrade backends toggle * feat: add upgrade checker service, API endpoints, and CLI command - UpgradeChecker background service: checks every 6h, auto-upgrades when enabled - API endpoints: GET /backends/upgrades, POST /backends/upgrades/check, POST /backends/upgrade/:name - CLI: `localai backends upgrade` command, version display in `backends list` - BackendManager interface: add UpgradeBackend and CheckUpgrades methods - Wire upgrade op through GalleryService backend handler - Distributed mode: fan-out upgrade to worker nodes via NATS * fix: use advisory lock for upgrade checker in distributed mode In distributed mode with multiple frontend instances, use PostgreSQL advisory lock (KeyBackendUpgradeCheck) so only one instance runs periodic upgrade checks and auto-upgrades. Prevents duplicate upgrade operations across replicas. Standalone mode is unchanged (simple ticker loop). * test: add e2e tests for backend upgrade API - Test GET /api/backends/upgrades returns 200 (even with no upgrade checker) - Test POST /api/backends/upgrade/:name accepts request and returns job ID - Test full upgrade flow: trigger upgrade via API, wait for job completion, verify run.sh updated to v2 and metadata.json has version 2.0.0 - Test POST /api/backends/upgrades/check returns 200 - Fix nil check for applicationInstance in upgrade API routes |
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|
Ettore Di Giacinto
|
e00ce981f0 |
fix: try to add whisperx and faster-whisper for more variants (#9278)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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|
Ettore Di Giacinto
|
223deb908d |
fix(nats): improve error handling (#9222)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
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> |
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|
Ettore Di Giacinto
|
5d410e5a03 |
fix(download): do not remove dst dir until we try all fallbacks (#9100)
This actually caused fallbacks to be compeletely no-op as we were removing the destination dir before calling containerd.Apply Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |