* ⬆️ Update ggml-org/llama.cpp
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* fix(llama-cpp): track upstream rename checkpoint_every_nt -> checkpoint_min_step
Upstream llama.cpp renamed common_params::checkpoint_every_nt to
checkpoint_min_step and changed its default from 8192 to 256. The semantics
also shifted: it used to enforce a fixed checkpoint cadence during prefill,
now it sets a minimum spacing between context checkpoints. Track the new
field name in grpc-server.cpp and accept the old option names as backward-
compatible aliases for users with existing configs.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7
---------
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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Add a routing middleware stack and a cloud-proxy backend.
* cloud-proxy: a Go gRPC backend that forwards OpenAI- and
Anthropic-shaped chat requests to upstream providers, with an
optional translate mode (OpenAI request -> Anthropic /v1/messages
-> OpenAI response) and full tool-calling support.
* routing: admission control, content-aware model routing
(embedding cache + classifier + rerank + Arch-Router score),
PII detection/redaction (regex + NER) with streaming filter and
OpenAI/Anthropic adapters, and a per-user/per-key billing recorder
backed by GORM or in-memory storage.
* middleware: UsageMiddleware records usage via the billing recorder,
plus admission, route-model, usage-stamp and trace middlewares.
* observability: BackendTrace ring buffer stores full request bodies
(capped), MITM proxy emits structured trace events, and router
classifier decisions surface at /api/router/decide.
* gallery: Arch-Router-1.5B (Q4_K_M and Q8_0).
* UI: cloud-proxy model-editor fields, classifier system-prompt and
score-normalization config, and a Traces page rendering request
bodies.
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Aligns LocalAI's llama-cpp gRPC backend with upstream's auto-on prompt
cache path so repeated system prompts (agents, OpenAI/Anthropic-compatible
CLIs, coding assistants) skip prefill on subsequent calls without any
YAML changes. Reported in #9921.
Upstream's server enables `kv_unified=true` (and bumps `n_parallel` to 4)
when slot count is auto, which unlocks `cache_idle_slots`. LocalAI
hardcodes `n_parallel=1` and so far also hardcoded `kv_unified=false`,
which silently force-disables idle-slot saving at server init. The host
prompt cache was allocated but never written across requests.
Changes in backend/cpp/llama-cpp/grpc-server.cpp:
- params.kv_unified: false -> true (single-slot path now benefits from
the prompt cache; users can opt out with `kv_unified:false`)
- params.n_ctx_checkpoints: 8 -> 32 (match upstream default)
- params.cache_idle_slots = true initialized explicitly (upstream default)
- params.checkpoint_every_nt = 8192 initialized explicitly (upstream default)
- New option parsers: cache_idle_slots / idle_slots_cache,
checkpoint_every_nt / checkpoint_every_n_tokens
Docs:
- features/text-generation.md: fix misleading `cache_ram` description
(it's the host-side prompt cache, not the KV cache), document the
kv_unified + cache_ram + cache_idle_slots interaction, add rows for
the two newly-exposed options, and add a worked example for the
agent/CLI workload from the issue.
- advanced/model-configuration.md: mark the legacy `prompt_cache_path`
/ `prompt_cache_all` / `prompt_cache_ro` YAML fields as unused by the
llama-cpp gRPC backend (they target upstream's CLI completion tool
and are not consumed by grpc-server.cpp) and point readers at the
new prompt-cache explainer.
Closes#9921
Assisted-by: claude:opus-4.7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
llama.cpp's model loader asserts back().pattern == nullptr on
params.tensor_buft_overrides (and on params.kv_overrides.back().key[0]
== 0) before binding them into llama_model_params. PR #8560 attempted
to satisfy llama_params_fit's placeholder requirement by pre-filling
params.tensor_buft_overrides up to llama_max_tensor_buft_overrides()
*before* the option-parse loop. Any subsequent push_back from
override_tensor / draft_cpu_moe / draft_n_cpu_moe / draft_override_tensor
then appended real entries after the placeholders, leaving back() with
a real pattern and tripping the assert. The draft override vector
likewise had no terminator at all.
Mirror upstream common/arg.cpp:645-658 instead: real entries are
pushed during option parsing, and after parsing we pad the main vector
up to ntbo (placeholders land at the end, so back() is always nullptr)
and append a single {nullptr, nullptr} to the draft vector when it is
non-empty. The existing kv_overrides terminator block already matches
upstream and stays.
Verified against ggml-org/llama.cpp@5cbaa5e: only tensor_buft_overrides
(main + draft) and kv_overrides are sentinel-terminated common_params
fields; everything else is size-driven std::vector.
Assisted-by: claude-code:claude-opus-4-7
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* 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>
The llama.cpp backend already accepts a free-form options: array in the
model config that maps to common_params fields, but a coverage audit
against upstream pin 7f3f843c flagged 12 user-visible knobs that were
neither set via the typed proto fields nor reachable via options:.
Wire them up under the existing if/else chain in params_parse, before
the speculative section. Each new option follows the file's prevailing
patterns (try/catch around numeric parses, the same true/1/yes/on bool
form used elsewhere, hardware_concurrency() fallback for thread counts,
mirror of draft_override_tensor for override_tensor).
Top-level / batching / IO:
- n_ubatch (alias ubatch) -- physical batch size; was previously
force-aliased to n_batch at line 482, blocking embedding/rerank
workloads that need independent control
- threads_batch (alias n_threads_batch) -- main-model batch threads;
mirrors the existing draft_threads_batch
- direct_io (alias use_direct_io) -- O_DIRECT model loads
- verbosity -- llama.cpp log threshold (line 479 had this commented
out)
- override_tensor (alias tensor_buft_overrides) -- per-tensor buffer
overrides for the main model; mirrors draft_override_tensor
Embedding / multimodal:
- pooling_type (alias pooling) -- mean/cls/last/rank/none; previously
only auto-flipped to RANK for rerankers
- embd_normalize (alias embedding_normalize) -- and the embedding
handler now reads params_base.embd_normalize instead of a hardcoded
2 at the previous embd_normalize literal in Embedding()
- mmproj_use_gpu (alias mmproj_offload) -- mmproj on CPU vs GPU
- image_min_tokens / image_max_tokens -- per-image vision token budget
Reasoning surface (the audit-focus three; LocalAI's existing
ReasoningConfig.DisableReasoning only feeds the per-request
chat_template_kwargs.enable_thinking and does not touch any of these):
- reasoning_format -- none/auto/deepseek/deepseek-legacy parser
- enable_reasoning (alias reasoning_budget) -- -1/0/>0 thinking budget
- prefill_assistant -- trailing-assistant-message prefill toggle
All 14 referenced fields exist on both the upstream pin and the
turboquant fork's common.h, so no LOCALAI_LEGACY_LLAMA_CPP_SPEC guard
is needed.
Docs: extend model-configuration.md with new "Reasoning Models",
"Multimodal Backend Options", "Embedding & Reranking Backend Options",
and "Other Backend Tuning Options" subsections; also refresh the
Speculative Type Values table to show the new dash-separated canonical
names alongside the underscore aliases LocalAI still accepts.
Assisted-by: claude-code:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update ggml-org/llama.cpp
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(llama-cpp): adapt to upstream COMMON_SPECULATIVE_TYPE_DRAFT rename
ggml-org/llama.cpp#22964 ("spec: update CLI arguments for better
consistency") renamed the speculative type enum values:
COMMON_SPECULATIVE_TYPE_DRAFT -> COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE
COMMON_SPECULATIVE_TYPE_EAGLE3 -> COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3
and the registered name strings flipped from underscore- to dash-
separated form (e.g. ngram_simple -> ngram-simple), with the bare
draft/eagle3 aliases replaced by draft-simple/draft-eagle3.
This broke the build with the new LLAMA_VERSION on every variant
(vulkan/arm64, darwin and likely all the rest) at grpc-server.cpp:461.
Update the upstream branch of the speculative-type fallback to use the
new identifier (the LOCALAI_LEGACY_LLAMA_CPP_SPEC fork branch keeps the
old name), and normalize spec_type option tokens before passing them to
common_speculative_types_from_names so existing model configs that say
spec_type:draft / spec_type:ngram_simple keep working.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
