chore(deps): bump torch in /backend/python/coqui

Bumps torch from 2.4.1 to 2.12.0+xpu.

---
updated-dependencies:
- dependency-name: torch
  dependency-version: 2.12.0+xpu
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

.agents/adding-backends.md

@@ -28,13 +28,61 @@ For Rust backends, you'll typically need (see `backend/rust/kokoros/` as a refer
 - `run.sh` - Sets `LD_LIBRARY_PATH`/`SSL_CERT_DIR` and execs the binary via the bundled `lib/ld.so`
 - `sources/<UpstreamProject>/` - Git submodule with the upstream Rust crate
 
-## 2. Add Build Configurations to `.github/workflows/backend.yml`
+## 2. Add Build Configurations to `.github/backend-matrix.yml`
 
-Add build matrix entries for each platform/GPU type you want to support. Look at similar backends for reference — `chatterbox`/`faster-whisper` for Python, `piper`/`silero-vad` for Go, `kokoros` for Rust.
+The build matrix is data-only YAML at `.github/backend-matrix.yml` (not inside `backend.yml` itself). `backend.yml` (master push) and `backend_pr.yml` (PR) load it via `scripts/changed-backends.js`, which also handles per-file path filtering so only touched backends rebuild on PRs and master pushes alike. Add build matrix entries to `.github/backend-matrix.yml` for each platform/GPU type you want to support. Look at similar backends for reference — `chatterbox`/`faster-whisper` for Python, `piper`/`silero-vad` for Go, `kokoros` for Rust.
 
 **Without an entry here no image is ever built or pushed, and the gallery entry in `backend/index.yaml` will point at a tag that does not exist.** The `dockerfile:` field must point at `./backend/Dockerfile.<lang>` matching the language bucket from step 1 (e.g. `Dockerfile.python`, `Dockerfile.golang`, `Dockerfile.rust`). The `tag-suffix` must match the `uri:` in the corresponding `backend/index.yaml` image entry exactly.
 
-If you add a new language bucket, `scripts/changed-backends.js` also needs a branch in `inferBackendPath` so PR change-detection routes file edits correctly.
+**`scripts/changed-backends.js` registration — REQUIRED for any new dockerfile suffix.** This is the single most common omission, because it has no effect on the PR that adds the backend (when no prior path filter could catch it anyway) — it only breaks the *next* PR that touches your backend's directory, which then gets zero CI jobs and looks broken for unrelated reasons. Edit `scripts/changed-backends.js:inferBackendPath` and add a branch BEFORE the more-generic suffixes:
+
+```js
+if (item.dockerfile.endsWith("<your-dockerfile-suffix>")) {
+    return `backend/cpp/<your-backend>/`;   // or backend/python|go|rust/...
+}
+```
+
+The `endsWith()` test is against the matrix entry's `dockerfile:` value (e.g. `./backend/Dockerfile.ds4` → `endsWith("ds4")`). Specificity order matters here just like it does for importers: more-specific suffixes go BEFORE more-generic ones (e.g. `ds4` before `llama-cpp` even though both end with letters, because some upstream might one day call itself `super-ds4-llama-cpp`). Verify locally before pushing:
+
+```bash
+# Confirm your dockerfile suffix is unique enough
+node -e "
+const yaml = require('js-yaml'); const fs = require('fs');
+const m = yaml.load(fs.readFileSync('.github/backend-matrix.yml','utf8'));
+for (const e of m.include.filter(e => e.backend === '<your-backend>')) {
+  console.log(e.dockerfile, '->', e.dockerfile.endsWith('<suffix>'));
+}"
+```
+
+A quick way to find the right insertion point: `grep -n 'item.dockerfile.endsWith' scripts/changed-backends.js`.
+
+**`bump_deps.yaml` registration — REQUIRED for any backend pinning an upstream commit.** If your backend's Makefile has a `*_VERSION?=<sha>` pin to a third-party repo, the daily auto-bump bot at `.github/workflows/bump_deps.yaml` won't notice it unless you register the backend in its matrix. The bot runs `.github/bump_deps.sh` which `grep`s for `^$VAR?=` in the Makefile you list — so the pin MUST live in the Makefile (not in a separate shell script). The bump for ds4 (#9761) had to walk this back because the original landed the pin in `prepare.sh`, which the bot can't see. Pattern (for `antirez/ds4`):
+
+```yaml
+# .github/workflows/bump_deps.yaml
+matrix:
+  include:
+    - repository: "antirez/ds4"
+      variable: "DS4_VERSION"
+      branch: "main"
+      file: "backend/cpp/ds4/Makefile"
+```
+
+And the corresponding Makefile shape (mirror `backend/cpp/llama-cpp/Makefile`):
+
+```makefile
+DS4_VERSION?=ae302c2fa18cc6d9aefc021d0f27ae03c9ad2fc0
+DS4_REPO?=https://github.com/antirez/ds4
+...
+ds4:
+	mkdir -p ds4
+	cd ds4 && git init -q && \
+	git remote add origin $(DS4_REPO) && \
+	git fetch --depth 1 origin $(DS4_VERSION) && \
+	git checkout FETCH_HEAD
+```
+
+If you have a `prepare.sh` doing the clone, delete it — the recipe belongs in the Makefile target so `make purge && make` works as a clean-and-rebuild and so the bump bot finds the pin.
 
 **Placement in file:**
 - CPU builds: Add after other CPU builds (e.g., after `cpu-chatterbox`)
@@ -46,6 +94,14 @@ If you add a new language bucket, `scripts/changed-backends.js` also needs a bra
 - Intel/SYCL: Use `build-type: 'intel'` or `build-type: 'sycl_f16'`/`sycl_f32` with `base-image: "intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04"`
 - L4T (ARM): Use `build-type: 'l4t'` with `platforms: 'linux/arm64'` and `runs-on: 'ubuntu-24.04-arm'`
 
+**Per-arch native builds (`linux/amd64` + `linux/arm64`):**
+
+Multi-arch backends are NOT a single matrix entry with `platforms: 'linux/amd64,linux/arm64'`. Instead, add **two** entries — one with `platforms: 'linux/amd64'` + `platform-tag: 'amd64'` + `runs-on: 'ubuntu-latest'`, one with `platforms: 'linux/arm64'` + `platform-tag: 'arm64'` + `runs-on: 'ubuntu-24.04-arm'` — both sharing the same `tag-suffix`. The script detects the shared `tag-suffix` and emits a `merge-matrix` entry, so `backend-merge-jobs` (in `backend.yml`/`backend_pr.yml`) automatically assembles the manifest list from per-arch digest artifacts. See `-cpu-faster-whisper` in `.github/backend-matrix.yml` for a reference shape.
+
+**llama-cpp / ik-llama-cpp / turboquant variants only — `builder-base-image`:**
+
+Entries whose `dockerfile` is `./backend/Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}` must also set a `builder-base-image` field pointing at a prebuilt base from `quay.io/go-skynet/ci-cache:base-grpc-*` (CI builds these via `.github/workflows/base-images.yml`). The mapping is by `(build-type, platforms)` — see existing entries for the pattern. CI uses these prebuilt bases to skip the gRPC compile (~25–35 min cold). Local `make backends/<name>` ignores `builder-base-image` and uses the from-source path inside the Dockerfile, so you don't need quay access for local builds.
+
 ## 3. Add Backend Metadata to `backend/index.yaml`
 
 **Step 3a: Add Meta Definition**
@@ -56,6 +112,8 @@ Add a YAML anchor definition in the `## metas` section (around line 2-300). Look
 
 Add image entries at the end of the file, following the pattern of similar backends such as `diffusers` or `chatterbox`. Include both `latest` (production) and `master` (development) tags.
 
+**Note on integrity:** OCI backends installed from a gallery whose `verification:` block is set are verified against a keyless-cosign policy before extraction; tarball/HTTP backends use the optional `sha256:` field. New backends do not need any extra YAML — the gallery-level `verification:` block covers every entry. See [.agents/backend-signing.md](backend-signing.md) for the producer-side CI step.
+
 ## 4. Update the Makefile
 
 The Makefile needs to be updated in several places to support building and testing the new backend:
@@ -145,7 +203,7 @@ docker-build-backends: ... docker-build-<backend-name>
 After adding a new backend, verify:
 
 - [ ] Backend directory structure is complete with all necessary files
-- [ ] Build configurations added to `.github/workflows/backend.yml` for all desired platforms
+- [ ] Build configurations added to `.github/backend-matrix.yml` for all desired platforms (per-arch entries with `platform-tag` for multi-arch; `builder-base-image` for llama-cpp / ik-llama-cpp / turboquant)
 - [ ] Meta definition added to `backend/index.yaml` in the `## metas` section
 - [ ] Image entries added to `backend/index.yaml` for all build variants (latest + development)
 - [ ] Tag suffixes match between workflow file and index.yaml

.agents/api-endpoints-and-auth.md

@@ -284,7 +284,17 @@ Also bump the expected-length count in `api_instructions_test.go` and add the na
 
 ### 3. `capabilities.js` symbol (for new model-config FLAG_* flags)
 
-If your feature needs a new `FLAG_*` usecase flag in `core/config/model_config.go` (so users can filter gallery models by it, and so `/v1/models` surfaces it), also declare the matching symbol in `core/http/react-ui/src/utils/capabilities.js`:
+If your feature needs a new `FLAG_*` usecase flag in `core/config/model_config.go` (so users can filter gallery models by it, and so `/v1/models` surfaces it), you need to update **all** of:
+
+- `Usecase<Name>` string constant in `core/config/backend_capabilities.go`
+- `UsecaseInfoMap` entry mapping the string to its flag + gRPC method
+- `FLAG_<NAME>` bitmask in `core/config/model_config.go`
+- `GetAllModelConfigUsecases()` map entry (otherwise the YAML loader silently ignores the string)
+- `ModalityGroups` membership if the flag should affect `IsMultimodal()` (e.g. realtime_audio is in both speech-input and audio-output groups so a lone flag still reads as multimodal)
+- `GuessUsecases()` branch listing the backends that own this capability
+- `usecaseFilters` in `core/http/routes/ui_api.go` (drives the gallery filter dropdown)
+- `Models.jsx` `FILTERS` array + matching `filters.<camelCase>` i18n key in `core/http/react-ui/public/locales/en/models.json`
+- `core/http/react-ui/src/utils/capabilities.js`:
 
 ```js
 export const CAP_MY_CAPABILITY = 'FLAG_MY_CAPABILITY'

.agents/backend-signing.md

@@ -0,0 +1,120 @@
+# Backend image signing & verification
+
+LocalAI verifies backend OCI images against a per-gallery keyless-cosign
+policy. This page documents the trust model, the producer side
+(`.github/workflows/backend_merge.yml` in this repo), and the consumer
+side (`pkg/oci/cosignverify` plus the gallery YAML).
+
+## Trust model
+
+- **Producer:** `.github/workflows/backend_merge.yml` signs each pushed
+  manifest list with `cosign sign --recursive` in keyless mode after
+  `docker buildx imagetools create`. The signing cert is issued by
+  Fulcio bound to the workflow's OIDC identity. There is no long-lived
+  signing key. `--recursive` signs both the manifest list and every
+  per-arch entry — needed because our consumer resolves a tag to a
+  per-arch manifest before checking signatures.
+- **Storage:** Signatures are written as OCI 1.1 referrers
+  (`--registry-referrers-mode=oci-1-1`) in the new Sigstore bundle format
+  (`--new-bundle-format`). No `:sha256-<hex>.sig` tag clutter.
+- **Consumer:** `pkg/oci/cosignverify` discovers the bundle via the
+  referrers API, hands it to `sigstore-go`, and verifies it against the
+  policy declared in the gallery YAML (`Gallery.Verification`).
+- **Revocation:** Keyless cosign certs are ephemeral (10-minute Fulcio
+  validity), so revocation is policy-side, not CA-side. The gallery's
+  `verification.not_before` (RFC3339) is the kill-switch — advance it to
+  invalidate every signature produced before a known compromise window.
+
+## Producer setup
+
+`backend_merge.yml` is the workflow that joins per-arch digests into the
+multi-arch manifest list users actually pull, so it's also the right place
+to sign. The job needs:
+
+- `permissions: { id-token: write, contents: read }` at the job level so
+  the runner can exchange its GitHub OIDC token for a Fulcio cert.
+- `sigstore/cosign-installer@v3` step (cosign ≥ 2.2 for
+  `--new-bundle-format`).
+- After each `docker buildx imagetools create`, resolve the resulting
+  list digest with `docker buildx imagetools inspect <tag> --format
+  '{{.Manifest.Digest}}'` and sign:
+
+```sh
+cosign sign --yes --recursive \
+  --new-bundle-format \
+  --registry-referrers-mode=oci-1-1 \
+  "${REGISTRY_REPO}@${DIGEST}"
+```
+
+Sign by digest, never by tag — signing by tag binds the signature to
+whatever the tag points at *now*, and a subsequent tag push orphans it.
+
+`backend_build_darwin.yml` builds and pushes single-arch darwin images
+that bypass the manifest-list merge. If/when those entries get a gallery
+`verification:` policy, the equivalent cosign step has to land there
+too.
+
+## Consumer setup (in `mudler/LocalAI` gallery YAML)
+
+Once CI is signing, add a `verification:` block to the backend gallery
+entry (`backend/index.yaml`):
+
+```yaml
+- name: localai
+  url: github:mudler/LocalAI/backend/index.yaml@master
+  verification:
+    issuer: "https://token.actions.githubusercontent.com"
+    identity_regex: "^https://github\\.com/mudler/LocalAI/\\.github/workflows/backend_merge\\.yml@refs/heads/master$"
+    # Optional revocation cutoff; advance during incident response.
+    # not_before: "2026-06-01T00:00:00Z"
+```
+
+Identity matching pins the OIDC subject Fulcio issued the signing cert
+to. Without this, any image signed by *anyone* with a Fulcio cert would
+pass — the regex is what makes a signature mean "produced by our CI".
+
+## Strict mode
+
+Default behaviour: OCI backends without a `verification:` block install
+with a warning (logs include `installing OCI backend without signature
+verification`). Tarball/HTTP backends without a `sha256` field log a
+similar warning.
+
+For production, set `LOCALAI_REQUIRE_BACKEND_INTEGRITY=1` (or pass
+`--require-backend-integrity` to `local-ai run` / `local-ai backends
+install` / `local-ai models install`). The warning becomes a hard error
+and unverifiable backends refuse to install.
+
+## Revocation playbook
+
+If `backend_merge.yml` (or any workflow with `id-token: write`) is
+compromised and we've shipped malicious signed images:
+
+1. **Identify the compromise window.** Find the earliest IntegratedTime
+   from the bad signatures (Rekor search by `subject` filter).
+2. **Set `verification.not_before`** in `backend/index.yaml` to a
+   timestamp just *after* that window's start.
+3. **Push the YAML.** Deployed LocalAI instances pick it up on next
+   gallery refresh (1-hour cache in `core/gallery/gallery.go`).
+4. **Fix the underlying compromise** in the workflow and re-sign images
+   with the new build, which will have IntegratedTime > `not_before`.
+5. **Optional:** for absolute decisiveness, also rotate to a new
+   workflow path (`backend_merge_v2.yml`) and update `identity_regex`.
+
+## Where the code lives
+
+- `pkg/oci/cosignverify/` — verifier, policy, OCI referrer fetch, NotBefore enforcement.
+- `pkg/downloader/uri.go` — `WithImageVerifier` option threaded through `DownloadFileWithContext`.
+- `core/gallery/backends.go` — `backendDownloadOptions` builds the verifier from the gallery's policy.
+- `core/config/gallery.go` — `Gallery.Verification` YAML schema.
+- `core/cli/run.go`, `core/cli/backends.go`, `core/cli/models.go` — `--require-backend-integrity` flag propagation.
+- `.github/workflows/backend_merge.yml` — producer-side `cosign sign --recursive` after each multi-arch manifest list push.
+
+## Out of scope (follow-ups)
+
+- **Signing the gallery YAML itself.** The index is fetched over HTTPS
+  from GitHub; we trust the host. A cosign blob signature on the YAML
+  would close that gap but adds key-management overhead. Revisit this
+  page if/when added.
+- **Tarball/HTTP backend signing.** Cosign can sign arbitrary blobs, but
+  for now non-OCI backends keep using the `sha256:` field in YAML.

.agents/building-and-testing.md

@@ -8,8 +8,9 @@ Let's say the user wants to build a particular backend for a given platform. For
 
 - The Makefile has targets like `docker-build-coqui` created with `generate-docker-build-target` at the time of writing. Recently added backends may require a new target.
 - At a minimum we need to set the BUILD_TYPE, BASE_IMAGE build-args
-  - Use .github/workflows/backend.yml as a reference it lists the needed args in the `include` job strategy matrix
-  - l4t and cublas also requires the CUDA major and minor version
+  - Use `.github/backend-matrix.yml` as a reference — it's the data-only YAML that lists every backend variant's `build-type`, `base-image`, `platforms`, etc. (`backend.yml` and `backend_pr.yml` consume it via `scripts/changed-backends.js`).
+  - l4t and cublas also require the CUDA major and minor version.
+  - For llama-cpp / ik-llama-cpp / turboquant the matrix also sets `builder-base-image` pointing at a prebuilt `quay.io/go-skynet/ci-cache:base-grpc-*` tag. Local `make backends/<name>` defaults to `BUILDER_TARGET=builder-fromsource` and doesn't need it — the Dockerfile's from-source stage installs everything itself.
 - You can pretty print a command like `DOCKER_MAKEFLAGS=-j$(nproc --ignore=1) BUILD_TYPE=hipblas BASE_IMAGE=rocm/dev-ubuntu-24.04:7.2.1 make docker-build-coqui`
 - Unless the user specifies that they want you to run the command, then just print it because not all agent frontends handle long running jobs well and the output may overflow your context
 - The user may say they want to build AMD or ROCM instead of hipblas, or Intel instead of SYCL or NVIDIA insted of l4t or cublas. Ask for confirmation if there is ambiguity.

.agents/ci-caching.md

@@ -1,33 +1,120 @@
 # CI Build Caching
 
-Container builds — both the root LocalAI image (`Dockerfile`) and the per-backend images (`backend/Dockerfile.*`) — share a registry-backed BuildKit cache. This file explains how that cache is laid out, what invalidates it, and how to bypass it.
+Container builds — both the root LocalAI image (`Dockerfile`) and the per-backend images (`backend/Dockerfile.*`) — share a registry-backed BuildKit cache plus a layered set of prebuilt base images. This file explains how the cache is laid out, what invalidates it, and how to bypass it.
+
+## Workflow surfaces
+
+| Workflow | Purpose | Triggers |
+|---|---|---|
+| `.github/workflows/backend.yml` | Backend container images on master | `push` to master + tags, weekly Sunday cron, `workflow_dispatch` |
+| `.github/workflows/backend_pr.yml` | Backend container images on PRs | `pull_request` |
+| `.github/workflows/backend_build.yml` | Reusable: builds one backend (one arch) by digest | `workflow_call` from above |
+| `.github/workflows/backend_merge.yml` | Reusable: assembles per-arch digests into a multi-arch manifest list | `workflow_call` |
+| `.github/workflows/backend_build_darwin.yml` | Reusable: macOS-native backend builds | `workflow_call` |
+| `.github/workflows/image.yml` / `image-pr.yml` | Root LocalAI image (push / PR) | push / PR |
+| `.github/workflows/image_build.yml` / `image_merge.yml` | Reusable: per-arch root-image build + merge | `workflow_call` |
+| `.github/workflows/base-images.yml` | Builds the prebuilt `base-grpc-*` builder bases | Saturdays 05:00 UTC cron, `workflow_dispatch`, master push touching `Dockerfile.base-grpc-builder`, `.docker/install-base-deps.sh`, `.docker/apt-mirror.sh`, or this workflow |
+
+The matrix that drives `backend.yml` / `backend_pr.yml` lives in **`.github/backend-matrix.yml`** (data-only YAML, not embedded in the workflow). `scripts/changed-backends.js` parses it, applies path-filter logic against the PR diff (PR events) or the GitHub Compare API (push events), and emits the filtered matrix plus a `merge-matrix` for backends with multiple per-arch entries.
 
 ## Cache layout
 
 - **Cache registry**: `quay.io/go-skynet/ci-cache`
-- **One tag per matrix entry**, derived from the existing `tag-suffix`:
-  - Backend builds (`backend_build.yml`): `cache<tag-suffix>`
-    - e.g. `cache-gpu-nvidia-cuda-12-llama-cpp`, `cache-cpu-vllm`, `cache-nvidia-l4t-cuda-13-arm64-vllm`
-  - Root image builds (`image_build.yml`): `cache-localai<tag-suffix>`
-    - e.g. `cache-localai-gpu-nvidia-cuda-12`, `cache-localai-gpu-vulkan`
+- **One tag per matrix entry per arch**, derived from `tag-suffix` and `platform-tag`:
+  - Backend builds (`backend_build.yml`): `cache<tag-suffix>-<platform-tag>`
+    - e.g. `cache-cpu-faster-whisper-amd64`, `cache-cpu-faster-whisper-arm64`, `cache-gpu-nvidia-cuda-13-llama-cpp-amd64`
+  - Root image builds (`image_build.yml`): `cache-localai<tag-suffix>-<platform-tag>` (with a `-core` placeholder when `tag-suffix` is empty, so `cache-localai-core-amd64` for the core image)
+  - Pre-built base images (`base-images.yml`): `cache-base-grpc-<variant>` (one per `(BUILD_TYPE, arch)` permutation)
 - Each tag stores a multi-arch BuildKit cache manifest (`mode=max`), so every intermediate stage is re-usable, not just the final image.
 
+The per-arch suffix exists because amd64 and arm64 builds produce different intermediate content; sharing one cache key would thrash on every cross-arch rebuild.
+
 ## Read/write semantics
 
 | Trigger | `cache-from` | `cache-to` |
 |---|---|---|
-| `push` to `master` / tag | yes | yes (`mode=max,ignore-error=true`) |
+| `push` to `master` / tag / cron / dispatch | yes | yes (`mode=max,ignore-error=true`) |
 | `pull_request` | yes | **no** |
 
 PR builds read master's warm cache but never write — this prevents PRs from polluting the shared cache with their experimental state. After merge, the master build for that matrix entry refreshes the cache.
 
 `ignore-error=true` on the write side means a transient quay push failure does not fail the build; the next master push retries.
 
-## Self-warming, no separate populator
+## Pre-built base images (`base-grpc-*`)
 
-There is no cron job that pre-warms the cache. The production builds *are* the populator. The first master build of a given matrix entry pays the cold cost; subsequent same-entry master builds reuse everything that hasn't changed (apt installs, gRPC compile in `Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}`, Python wheel installs, etc.).
+The C++ backend Dockerfiles (`Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}`) compile gRPC from source. On a cold build that's ~25–35 min before any LocalAI source compiles. To skip that on CI, `.github/workflows/base-images.yml` builds and pushes a set of pre-prepped builder bases:
 
-Historically there was a `generate_grpc_cache.yaml` cron that targeted a `grpc` stage in the root Dockerfile. That stage was removed in July 2025 and the cron silently failed every night for 9 months without writing anything. It was deleted along with the registry-cache rollout.
+| Tag | Contents |
+|---|---|
+| `base-grpc-amd64` / `base-grpc-arm64` | Ubuntu 24.04 + apt build deps + protoc + cmake + gRPC at `/opt/grpc` |
+| `base-grpc-cuda-12-amd64` | the above + CUDA 12.8 toolkit |
+| `base-grpc-cuda-13-amd64` | the above + CUDA 13.0 toolkit (Ubuntu 22.04 base) |
+| `base-grpc-cuda-13-arm64` | the above + CUDA 13.0 sbsa toolkit (Ubuntu 24.04 base) |
+| `base-grpc-l4t-cuda-12-arm64` | JetPack r36.4.0 base (CUDA preinstalled, `SKIP_DRIVERS=true`) + gRPC |
+| `base-grpc-rocm-amd64` | rocm/dev-ubuntu-24.04:7.2.1 base + hipblas/hipblaslt/rocblas + gRPC |
+| `base-grpc-vulkan-amd64` / `base-grpc-vulkan-arm64` | Ubuntu 24.04 + Vulkan SDK 1.4.335 + gRPC |
+| `base-grpc-intel-amd64` | intel/oneapi-basekit:2025.3.2 base + gRPC |
+
+**Single source of truth**: the install logic for all 10 variants lives in `.docker/install-base-deps.sh`. Both `Dockerfile.base-grpc-builder` AND each variant Dockerfile's `builder-fromsource` stage bind-mount and execute the same script — so the prebuilt CI base and the local from-source path are bit-equivalent by construction.
+
+### How variant Dockerfiles consume the base
+
+`Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}` are multi-target. Three stages plus a final aliasing stage:
+
+- `builder-fromsource` — `FROM ${BASE_IMAGE}` then runs `install-base-deps.sh` and the per-backend compile script. Used when `BUILDER_TARGET=builder-fromsource` (the default; local `make backends/<name>`).
+- `builder-prebuilt` — `FROM ${BUILDER_BASE_IMAGE}` (one of the prebuilt `base-grpc-*` tags) and runs only the per-backend compile script. Used when `BUILDER_TARGET=builder-prebuilt` (CI when the matrix entry sets `builder-base-image`).
+- `FROM ${BUILDER_TARGET} AS builder` — alias resolves the ARG-selected stage to a fixed name (BuildKit doesn't allow ARG expansion in `COPY --from=`).
+- `FROM scratch` + `COPY --from=builder ...package/. ./` — emits the final scratch image with just the package contents.
+
+BuildKit prunes the unreferenced builder stage, so each build only runs the path it needs. `backend_build.yml` derives `BUILDER_TARGET=builder-prebuilt` automatically when the matrix entry has a non-empty `builder-base-image`; otherwise it defaults to `builder-fromsource`.
+
+The matrix `(build-type, platforms)` → `builder-base-image` mapping for llama-cpp / ik-llama-cpp / turboquant entries:
+
+| `build-type` | `platforms` | tag |
+|---|---|---|
+| `''` | `linux/amd64` | `base-grpc-amd64` |
+| `''` | `linux/arm64` | `base-grpc-arm64` |
+| `cublas` cuda 12 | `linux/amd64` | `base-grpc-cuda-12-amd64` |
+| `cublas` cuda 13 | `linux/amd64` | `base-grpc-cuda-13-amd64` |
+| `cublas` cuda 13 | `linux/arm64` | `base-grpc-cuda-13-arm64` |
+| `cublas` cuda 12 + JetPack base | `linux/arm64` | `base-grpc-l4t-cuda-12-arm64` |
+| `hipblas` | `linux/amd64` | `base-grpc-rocm-amd64` |
+| `vulkan` | `linux/amd64` | `base-grpc-vulkan-amd64` |
+| `vulkan` | `linux/arm64` | `base-grpc-vulkan-arm64` |
+| `sycl_*` | `linux/amd64` | `base-grpc-intel-amd64` |
+
+### Bootstrap order when adding a new variant
+
+If you add a new entry to `base-images.yml`'s matrix, the new tag does not exist on quay until the workflow runs. To consume it from a variant entry safely, dispatch the base-images workflow on the branch first:
+
+```bash
+gh workflow run base-images.yml --ref <feature-branch>
+```
+
+Wait for the new variant to push, then merge the consumer change. Otherwise the consumer's CI fails with "image not found."
+
+## Per-arch native builds + manifest merge
+
+Multi-arch backends (and the core LocalAI image) build natively per arch instead of running both arches under QEMU emulation on a single x86 runner. The pattern:
+
+- The matrix has TWO entries per multi-arch backend, sharing the same `tag-suffix` but distinct `platforms` + `platform-tag` + `runs-on`. Example: `-cpu-faster-whisper` has one amd64 entry on `ubuntu-latest` and one arm64 entry on `ubuntu-24.04-arm`.
+- Each per-arch build pushes by **canonical digest only** (no tags) via `outputs: type=image,push-by-digest=true,name-canonical=true,push=true`. The digest is uploaded as an artifact named `digests<tag-suffix>-<platform-tag>` (or `digests-localai<...>` for root-image builds).
+- `scripts/changed-backends.js` detects shared `tag-suffix` and emits a `merge-matrix` output. `backend.yml` / `backend_pr.yml` have a `backend-merge-jobs` job that consumes it and calls `backend_merge.yml`.
+- `backend_merge.yml` downloads all matching digest artifacts and runs `docker buildx imagetools create` to publish the final tagged manifest list pointing at both per-arch digests. Same `docker/metadata-action` config as the original monolithic build, so consumers see no tag-shape change.
+- `image_merge.yml` is the equivalent for the root LocalAI image (`-core` placeholder when `tag-suffix` is empty so the artifact-name glob doesn't over-match across `core` and `gpu-vulkan`).
+
+**`provenance: false` is required on multi-registry digest pushes**: with the default `mode=max` provenance attestation, BuildKit bundles a per-registry attestation manifest into each registry's manifest list, making the resulting list digest diverge across registries. `steps.build.outputs.digest` only matches one of them and the merge step's `imagetools create <reg>@sha256:<digest>` lookup fails on the other. Setting `provenance: false` keeps the digest content-only and identical across registries.
+
+## Path filter on master push
+
+Both `backend.yml` (push) and `backend_pr.yml` (PR) generate their matrix dynamically through `scripts/changed-backends.js`:
+
+- **PR events**: paginated `pulls/{n}/files` API → filter the matrix to entries whose `dockerfile` path prefix matches the PR diff.
+- **Push events**: GitHub Compare API (`/repos/{owner}/{repo}/compare/{before}...{after}`) → same path-filter logic. Falls back to "run everything" on first-branch push (`event.before` zero), API truncation (≥300 changed files), missing API token, or any thrown error.
+- **Tag pushes**: `FORCE_ALL=true` is set from the workflow side (`startsWith(github.ref, 'refs/tags/')`) — releases rebuild every backend regardless of diff.
+- **Schedule / `workflow_dispatch`**: no `event.before`, falls through to "run everything" automatically.
+
+The Sunday 06:00 UTC cron on `backend.yml` exists specifically because path filtering can leave Python backends frozen on stale wheels. `DEPS_REFRESH` (below) only fires when the build actually runs, so an untouched Python backend would never re-resolve its unpinned deps. The weekly cron is the safety net.
 
 ## The `DEPS_REFRESH` cache-buster (Python backends)
 
@@ -42,18 +129,57 @@ Most Python backends ship `requirements*.txt` files that **do not pin every tran
 
 `DEPS_REFRESH` defends against that:
 
-- `backend_build.yml` computes `date -u +%Y-W%V` (ISO week, e.g. `2026-W17`) before each build and passes it as a build-arg.
+- `backend_build.yml` computes `date -u +%Y-W%V` (ISO week, e.g. `2026-W19`) before each build and passes it as a build-arg.
 - The `RUN ... make` layer's BuildKit hash now includes that string, so the layer invalidates **at most once per week**, automatically picking up newer wheels.
 - Within a week, builds stay warm.
 
 This applies only to `Dockerfile.python` because:
 - Go (`Dockerfile.golang`) pins versions in `go.mod` / `go.sum`.
 - Rust (`Dockerfile.rust`) pins via `Cargo.lock`.
-- C++ backends (`Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}`) clone gRPC at a pinned tag (`v1.65.0`) and llama.cpp at a pinned commit; their inputs don't drift between rebuilds.
+- C++ backends pin gRPC (`v1.65.0`) and llama.cpp at a specific commit; their inputs don't drift between rebuilds.
 
 ### Adjusting the cadence
 
-If you need a faster refresh (e.g. while debugging an upstream flake), bump the format to daily (`+%Y-%m-%d`) or hourly (`+%Y-%m-%d-%H`). If you need a one-shot rebuild for a specific backend without changing the schedule, append a marker to the tag-suffix in the matrix or temporarily delete that backend's cache tag in quay.
+Bump the format to daily (`+%Y-%m-%d`) or hourly (`+%Y-%m-%d-%H`) for faster refreshes. For one-shot rebuilds without changing the schedule, append a marker to the tag-suffix in the matrix or temporarily delete that backend's cache tag in quay.
+
+## ccache for C++ backend builds
+
+`Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}` declare a BuildKit cache mount on `/root/.ccache`:
+
+```dockerfile
+RUN --mount=type=cache,target=/root/.ccache,id=<backend>-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
+```
+
+The compile script exports `CMAKE_C/CXX/CUDA_COMPILER_LAUNCHER=ccache` so CMake threads ccache through gcc/g++/nvcc. `cache-to: type=registry,mode=max` exports the cache mount data into the registry cache, so subsequent builds restore it.
+
+On a `LLAMA_VERSION` bump, most translation units are byte-identical to the previous version's preprocessed source — ccache returns the previous `.o` and skips the real compile. Same for LocalAI source changes that don't actually touch llama.cpp's CMake inputs. Cache scope is per `(TARGETARCH, BUILD_TYPE)` so e.g. cublas-12 doesn't share with cublas-13 (their CUDA headers differ; cross-pollination would just be cache misses anyway).
+
+## Composite actions
+
+Two composite actions handle runner-side prep:
+
+- **`.github/actions/free-disk-space/action.yml`** — wraps `jlumbroso/free-disk-space@main` plus an explicit apt purge of dotnet/android/ghc/mono/etc. Reclaims ~6–10 GB on `ubuntu-latest`. No-op on self-hosted runners. Used by `backend_build.yml`, `image_build.yml`, `test.yml`, `tests-aio.yml`, etc.
+- **`.github/actions/setup-build-disk/action.yml`** — relocates Docker's data-root to `/mnt` on hosted X64 runners. GHA hosted `ubuntu-latest` ships ~75 GB of unused space at `/mnt`; combined with the free-disk-space cleanup this gives ~100 GB working space — enough for ROCm dev image + vLLM torch install + flash-attn intermediate layers. No-op on self-hosted and on non-X64 hosted runners. Used by `backend_build.yml`, `image_build.yml`, `base-images.yml`.
+
+Both actions run before any docker buildx step.
+
+## Concurrency
+
+All `backend.yml` / `image.yml` / `test.yml` / etc. workflows use:
+
+```yaml
+concurrency:
+  group: ci-<workflow>-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
+```
+
+- **PR events** group by PR number → newer pushes to the same PR cancel old runs (intended).
+- **Push events** group by `github.sha` → each master commit gets its own run; rapid-fire merges don't cancel each other (this was a real issue prior — two master pushes 11 seconds apart would cancel the first's CI).
+
+## Self-warming, no separate populator
+
+There is no cron job that pre-warms the BuildKit cache for individual backends. The production builds *are* the populators. The first master build of a given matrix entry pays the cold cost; subsequent same-entry master builds reuse everything that hasn't changed (apt installs, gRPC compile in the variant `builder-fromsource` stage or skipped entirely when consuming `base-grpc-*`, Python wheel installs, etc.). The base-images workflow's weekly cron is the closest thing to a populator and only refreshes the prebuilt builder bases.
 
 ## Manually evicting cache
 
@@ -63,19 +189,19 @@ To force a fully cold build for one backend or the whole image:
 # Delete a single tag (requires quay credentials with admin on the repo)
 curl -X DELETE \
   -H "Authorization: Bearer ${QUAY_TOKEN}" \
-  https://quay.io/api/v1/repository/go-skynet/ci-cache/tag/cache-gpu-nvidia-cuda-12-vllm
+  https://quay.io/api/v1/repository/go-skynet/ci-cache/tag/cache-gpu-nvidia-cuda-12-vllm-amd64
 
 # List all tags
 curl -s -H "Authorization: Bearer ${QUAY_TOKEN}" \
   "https://quay.io/api/v1/repository/go-skynet/ci-cache/tag/?limit=100" | jq '.tags[].name'
 ```
 
-Eviction is rarely needed in normal operation — `DEPS_REFRESH` handles weekly drift, source changes invalidate naturally, and `mode=max` keeps the cache scoped per matrix entry so a stale tag never bleeds into a different build.
+Eviction is rarely needed in normal operation — `DEPS_REFRESH` handles weekly drift, source changes invalidate naturally, and `mode=max` keeps the cache scoped per matrix entry per arch so a stale tag never bleeds into a different build.
 
-## What the cache **does not** cover
+## What the cache does **not** cover
 
-- The "Free Disk Space" / "Release space from worker" steps run on every job — these reclaim ~6 GB on `ubuntu-latest` runners. They are runner-state cleanup, not Docker, and BuildKit caches don't apply.
-- Intermediate artifacts of `Build and push (PR)` are not pushed anywhere — PRs only build for verification.
+- The `free-disk-space` and `setup-build-disk` composite actions run on every job — these reclaim runner-state, not Docker layers, so BuildKit caches don't apply.
+- Intermediate artifacts of `Build (PR)` are not pushed anywhere — PRs only build for verification.
 - Darwin builds (see below) — macOS runners have no Docker daemon, so the registry-backed BuildKit cache cannot apply.
 
 ## Darwin native caches
@@ -95,17 +221,30 @@ The Python wheel cache uses the same ISO-week cache-buster as the Linux `DEPS_RE
 
 The brew Cellar cache requires `HOMEBREW_NO_AUTO_UPDATE=1` and `HOMEBREW_NO_INSTALL_CLEANUP=1` (set as job-level env). Without those, `brew install` would mutate the very directories that were just restored, defeating the cache.
 
+**Force-link after cache restore**: `actions/cache` restores `/opt/homebrew/Cellar/*` but NOT the `/opt/homebrew/bin/*` symlinks. After a cache hit, `brew install` sees the Cellar entries and decides "already installed" without re-running its link step, leaving the formulas off PATH. The Dependencies step explicitly runs `brew link --overwrite` for every cached formula afterwards to ensure the symlinks exist.
+
 For ccache, the workflow exports `CMAKE_ARGS=… -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache` via `$GITHUB_ENV` before running `make build-darwin-go-backend`. The Makefile in `backend/cpp/llama-cpp/` already forwards `CMAKE_ARGS` through to each variant build (`fallback`, `grpc`, `rpc-server`), so no script changes are needed. The three variants share most TUs, so ccache dedupes object files across them.
 
+`backend_build_darwin.yml` also has a llama-cpp-specific build-step branch that runs `make backends/llama-cpp-darwin` (the bespoke script that compiles three CMake variants and bundles dylibs via `otool`), distinct from the generic `make build-darwin-${lang}-backend` path. This was consolidated from a previously-bespoke top-level `llama-cpp-darwin` job in `backend.yml` so llama-cpp on Darwin honors the same path filter as the other 34 Darwin backends.
+
 ### Cache budget on Darwin
 
 GitHub Actions caches are limited to 10 GB per repo. Steady-state worst case: ~800 MB Go cache + ~2 GB brew Cellar + up to 2 GB ccache + ~1.5 GB × 5 python backends. If the cap is hit, prefer collapsing the per-backend Python keys into a shared `pyenv-darwin-shared-<week>` key (accepts more cross-backend churn for a smaller footprint) before reducing other caches.
 
+## Self-hosted runners
+
+`.github/backend-matrix.yml` has zero references to `arc-runner-set` or `bigger-runner` — all backends run on GHA free-tier hosted runners (`ubuntu-latest` for amd64, `ubuntu-24.04-arm` for arm64 native, `macos-14` for Darwin). The migration off self-hosted relied on the per-arch native split (no QEMU emulation) plus `setup-build-disk`'s `/mnt` relocation (~100 GB working space, enough for ROCm dev image + vLLM/torch installs).
+
+One residual self-hosted reference remains in `test-extra.yml` (`tests-vibevoice-cpp-grpc-transcription` uses `bigger-runner` for the 30s JFK-decode timeout headroom). That's a separate concern.
+
 ## Touching the cache pipeline
 
-When changing `image_build.yml`, `backend_build.yml`, or any of the `backend/Dockerfile.*` files:
+When changing `image_build.yml`, `backend_build.yml`, any of the `backend/Dockerfile.*` files, `Dockerfile.base-grpc-builder`, `.docker/install-base-deps.sh`, `.docker/<backend>-compile.sh`, or `scripts/changed-backends.js`:
 
 1. **Don't drop `DEPS_REFRESH=...` from the build-args** without a replacement strategy (lockfiles, pinned requirements). Otherwise master will silently freeze on whichever versions were cached at the time.
-2. **Keep `tag-suffix` unique per matrix entry** — it's the cache namespace. Two matrix entries sharing a tag-suffix would clobber each other's cache.
+2. **Keep `(tag-suffix, platform-tag)` unique per matrix entry** — together they're the cache namespace. Two matrix entries sharing a key would clobber each other's cache.
 3. **Keep `cache-to` gated on `github.event_name != 'pull_request'`** — PRs must not write.
 4. **Keep `ignore-error=true` on `cache-to`** — quay registry hiccups must not fail builds.
+5. **Keep `provenance: false` on push-by-digest steps** — multi-registry digest divergence is the Bug We Already Fixed; reintroducing provenance attestation re-breaks the merge.
+6. **`install-base-deps.sh` is the single source of truth for base contents.** Both `Dockerfile.base-grpc-builder` (CI) and the variant Dockerfiles' `builder-fromsource` (local) bind-mount and execute it. If you add a package to one path, add it to the script — don't fork the logic into a Dockerfile RUN.
+7. **After adding a `base-images.yml` matrix variant, run the workflow on your branch before merging consumer changes** that depend on the new tag — otherwise the consumer's CI fails "image not found."

.agents/ds4-backend.md

@@ -0,0 +1,84 @@
+# Working on the ds4 Backend
+
+`antirez/ds4` is a single-model inference engine for DeepSeek V4 Flash.
+LocalAI wraps the engine's C API (`ds4/ds4.h`) with a fresh C++ gRPC server at
+`backend/cpp/ds4/` - NOT a fork of llama-cpp's grpc-server.cpp.
+
+## Pin
+
+`backend/cpp/ds4/Makefile` pins `DS4_VERSION?=<sha>` at the top. The `ds4`
+target in the Makefile clones `antirez/ds4` at that commit (mirroring the
+llama-cpp / ik-llama-cpp / turboquant pattern). The bump-deps bot
+(`.github/workflows/bump_deps.yaml`) finds this pin via grep and opens a
+daily PR to update it. To bump manually: edit the `DS4_VERSION?=` line,
+then `make purge && make` (or rely on CI's clean build).
+
+## Wire shape
+
+| RPC | Implementation |
+|---|---|
+| Health, Free, Status | Trivial; no engine dependency for Health |
+| LoadModel | `ds4_engine_open` + `ds4_session_create`; backend is compile-time (DS4_NO_GPU → CPU, __APPLE__ → Metal, otherwise CUDA) |
+| TokenizeString | `ds4_tokenize_text` |
+| Predict | `ds4_engine_generate_argmax` + `DsmlParser` → one ChatDelta with content / reasoning_content / tool_calls[] |
+| PredictStream | Same, per-token ChatDelta writes |
+
+## DSML
+
+ds4 emits tool calls as literal text markers (`<｜DSML｜tool_calls>` etc.) -
+NOT special tokens. `dsml_parser.{h,cpp}` is our streaming state machine that
+classifies token bytes into CONTENT / REASONING / TOOL_START / TOOL_ARGS / TOOL_END
+events. `dsml_renderer.{h,cpp}` does the prompt direction: turns
+OpenAI tool_calls + role=tool messages back into DSML for the next turn.
+
+## Thinking modes
+
+`PredictOptions.Metadata["enable_thinking"]` gates thinking on/off (default ON).
+`["reasoning_effort"] == "max" | "xhigh"` selects `DS4_THINK_MAX`; anything else
+maps to `DS4_THINK_HIGH`. We pass the chosen mode to `ds4_chat_append_assistant_prefix`.
+
+## Disk KV cache
+
+`kv_cache.{h,cpp}` implements an SHA1-keyed file cache using ds4's public
+`ds4_session_save_payload` / `ds4_session_load_payload` API. Enable per request
+via `ModelOptions.Options[] = "kv_cache_dir:/some/path"`. Format is **our own** -
+NOT bit-compatible with ds4-server's KVC files (interop is a follow-up plan).
+
+## Build matrix
+
+| Build | Where | Notes |
+|---|---|---|
+| `cpu-ds4` (amd64 + arm64) | Linux GHA | ds4 considers CPU debug-only; useful only for wiring tests |
+| `cuda13-ds4` (amd64 + arm64) | Linux GHA + DGX Spark validation | Primary production path on Linux |
+| `ds4-darwin` (arm64) | macOS GHA runners | Metal; uses `scripts/build/ds4-darwin.sh` like llama-cpp-darwin |
+
+cuda12 is intentionally omitted. ROCm / Vulkan / SYCL are not applicable.
+
+## Hardware-gated validation
+
+`tests/e2e-backends/backend_test.go` in `BACKEND_BINARY` mode:
+
+```
+BACKEND_BINARY=$(pwd)/backend/cpp/ds4/package/run.sh \
+BACKEND_TEST_MODEL_FILE=/path/to/ds4flash.gguf \
+BACKEND_TEST_CAPS=health,load,predict,stream,tools \
+BACKEND_TEST_TOOL_PROMPT="What's the weather in Paris?" \
+go test -count=1 -timeout=30m -v ./tests/e2e-backends/...
+```
+
+CI does not load the model; the suite is opt-in via env vars.
+
+## Importer
+
+`core/gallery/importers/ds4.go` (`DS4Importer`) auto-detects ds4 weights by
+matching the `antirez/deepseek-v4-gguf` repo URI or the
+`DeepSeek-V4-Flash-*.gguf` filename pattern. **Registered BEFORE
+`LlamaCPPImporter`** in `defaultImporters` - both match `.gguf` but ds4 is more
+specific, and first-match-wins. The importer emits `backend: ds4`, uses
+`ds4flash.gguf` as the local filename (matches ds4's own CLI default), and
+disables the Go-side automatic tool-parsing fallback (the C++ backend emits
+ChatDelta.tool_calls natively via `DsmlParser`).
+
+ds4 is also listed in `core/http/endpoints/localai/backend.go`'s pref-only
+slice so the `/import-model` UI surfaces it as a manual choice for users who
+want to force the backend on a non-canonical URI.

.agents/llama-cpp-backend.md

@@ -61,6 +61,12 @@ Always check `llama.cpp` for new model configuration options that should be supp
    - `reasoning_format` - Reasoning format options
    - Any new flags or parameters
 
+### Speculative Decoding Types
+
+The `spec_type` option in `grpc-server.cpp` delegates to upstream's `common_speculative_types_from_names()`, so new speculative types added to the `common_speculative_type_from_name` map in `common/speculative.cpp` are picked up automatically with no code changes - only docs need an entry in `docs/content/advanced/model-configuration.md`. Current values: `none`, `draft-simple`, `draft-eagle3`, `draft-mtp`, `ngram-simple`, `ngram-map-k`, `ngram-map-k4v`, `ngram-mod`, `ngram-cache`.
+
+`draft-mtp` (Multi-Token Prediction, [ggml-org/llama.cpp#22673](https://github.com/ggml-org/llama.cpp/pull/22673)) does not need a separate draft GGUF: when `spec_type` includes `draft-mtp` and `draftmodel` is empty, the upstream server creates an MTP context off the target model itself. LocalAI's gRPC layer needs no changes for this — it works through the existing `params.speculative.types` plumbing and the derived `cparams.n_rs_seq = params.speculative.need_n_rs_seq()` in `common_context_params_to_llama`.
+
 ### Implementation Guidelines
 
 1. **Feature Parity**: Always aim for feature parity with llama.cpp's implementation

.agents/sglang-backend.md

@@ -0,0 +1,62 @@
+# Working on the SGLang Backend
+
+The SGLang backend lives at `backend/python/sglang/backend.py` (async gRPC). It wraps SGLang's `Engine` (`sglang.srt.entrypoints.engine.Engine`) and translates LocalAI's gRPC `PredictOptions` into SGLang sampling params + outputs into `Reply.chat_deltas`. Structurally it mirrors `backend/python/vllm/backend.py` — keep them shaped the same so changes in one have an obvious analog in the other.
+
+## `engine_args` is the universal escape hatch
+
+A small fixed set of fields on `ModelOptions` is mapped to typed SGLang kwargs in `LoadModel` (model, quantization, load_format, gpu_memory_utilization → mem_fraction_static, trust_remote_code, enforce_eager → disable_cuda_graph, tensor_parallel_size → tp_size, max_model_len → context_length, dtype). **Everything else** flows through the `engine_args:` YAML map.
+
+Validation happens in `_apply_engine_args`. Keys are checked against `dataclasses.fields(ServerArgs)` (`sglang.srt.server_args.ServerArgs` is a flat `@dataclass` with ~380 fields). Unknown keys raise `ValueError` at LoadModel time with a `difflib.get_close_matches` suggestion — same shape as the vLLM backend.
+
+**Precedence:** typed `ModelOptions` fields populate `engine_kwargs` first, then `engine_args` overrides them. So a YAML that sets both `gpu_memory_utilization: 0.9` and `engine_args.mem_fraction_static: 0.5` ends up at `0.5`. Document this when answering "why didn't my YAML field stick?".
+
+**ServerArgs is flat.** Unlike vLLM, where speculative decoding is nested under `engine_args.speculative_config: {...}`, SGLang exposes flat top-level fields: `speculative_algorithm`, `speculative_draft_model_path`, `speculative_num_steps`, `speculative_eagle_topk`, `speculative_num_draft_tokens`, `speculative_dflash_block_size`, etc. There is no `speculative_config:` dict. Same goes for compilation, kv-transfer, attention — all flat.
+
+The canonical reference is `python/sglang/srt/server_args.py:ServerArgs` (line ~304). When SGLang adds new flags, no LocalAI code change is needed — they're automatically available via `engine_args:`. The validator picks them up because it introspects the live dataclass.
+
+## Speculative decoding cheatsheet
+
+`--speculative-algorithm` accepts `EAGLE`, `EAGLE3`, `NEXTN`, `STANDALONE`, `NGRAM`, `DFLASH`. `NEXTN` is silently rewritten to `EAGLE` in `ServerArgs.__post_init__` (`server_args.py:3286-3287`). MTP (Multi-Token Prediction) is the same EAGLE path with `num_steps=1, eagle_topk=1, num_draft_tokens=2` against a target whose architecture has multi-token heads (e.g. MiMo-7B-RL, DeepSeek-V3-MTP).
+
+| Algorithm | Drafter requirement | Gallery demo target | Gallery demo drafter |
+|-----------|--------------------|---------------------|----------------------|
+| `NEXTN` / `EAGLE` (MTP) | Assistant drafter or built-in heads | google/gemma-4-E2B-it, google/gemma-4-E4B-it | google/gemma-4-E2B-it-assistant, google/gemma-4-E4B-it-assistant |
+| `EAGLE3` | EAGLE3 draft head | (no gallery entry yet) | e.g. jamesliu1/sglang-EAGLE3-Llama-3.1-Instruct-8B |
+| `DFLASH` | Block-diffusion drafter | (no gallery entry yet) | e.g. z-lab/Qwen3-4B-DFlash-b16 |
+| `STANDALONE` | Smaller LLM as drafter | (no gallery entry yet) | any smaller chat-tuned LLM in the same family |
+| `NGRAM` | None — uses prefix history | (no gallery entry yet) | n/a |
+
+The Gemma 4 demos use `mem_fraction_static: 0.85` (cookbook default) and the cookbook's `num_steps=5, num_draft_tokens=6, eagle_topk=1` parameters. Other algorithms are reachable from any user YAML via `engine_args:` but don't have shipped demos yet — that's a deliberate gallery scope choice, not a backend limitation.
+
+Gemma 4 support requires sglang built from a commit that includes [PR #21952](https://github.com/sgl-project/sglang/pull/21952). LocalAI's pinned release for cublas12 / cublas13 includes it. The `l4t13` (JetPack 7 / sbsa cu130) build floors at `sglang>=0.5.0` because the `pypi.jetson-ai-lab.io` mirror still ships only `0.5.1.post2` as of 2026-05-06 — Gemma 4 / MTP recipes are therefore not available on l4t13 until that mirror catches up. `backend.py` keeps backward compat with the 0.5.x → 0.5.11 `SamplingParams.seed` → `sampling_seed` rename via runtime detection.
+
+Compatibility caveats per the SGLang docs: DFLASH and NGRAM are incompatible with `enable_dp_attention`; DFLASH requires `pp_size == 1`; STANDALONE is incompatible with `enable_dp_attention`; NGRAM is CUDA-only and disables the overlap scheduler.
+
+### `mem_fraction_static` + quantization + MTP on consumer GPUs
+
+When combining online weight quantization (`engine_args.quantization: fp8` / `awq` / etc.) with built-in-head MTP (`speculative_algorithm: EAGLE`/`NEXTN`) on a tight VRAM budget, sglang's default `mem_fraction_static: 0.85` will OOM during draft-worker init. The reason: sglang quantizes the **target** model's transformer blocks but loads the **MTP draft worker's vocab embedding** at the source dtype (typically bf16). For a 7 B-class model with a 150k-token vocab × 4096 hidden, that's another ~1.2 GiB allocated *after* the static pool is reserved. At 0.85 fraction on a 16 GB card there's no room left.
+
+Workaround: drop `mem_fraction_static` to ~0.7 so the post-static heap can absorb the MTP embedding alloc + CUDA graph private pools. Verified end-to-end on MiMo-7B-RL + fp8 + MTP on a 16 GB RTX 5070 Ti (`gallery/sglang-mimo-7b-mtp.yaml`) at ~88 tok/s. Models with larger vocabs or more MTP layers (e.g. DeepSeek-V3-MTP) need an even smaller fraction.
+
+This isn't documented anywhere upstream as of 2026-05-06 — the SGLang Gemma 4 cookbook uses 0.85 because their MTP path doesn't go through `eagle_worker_v2.py` for an embedding-bearing draft module. Don't blanket-apply 0.7 across all sglang YAMLs; only when MTP-with-built-in-heads + quantization combine.
+
+## Tool-call and reasoning parsers stay on `Options[]`
+
+ServerArgs has `tool_call_parser` and `reasoning_parser` fields, and the backend does pass them through to `Engine` so SGLang's own HTTP/OAI surface keeps working. But for the **LocalAI** request path the backend constructs fresh per-request parser instances in `_make_parsers` (`backend.py:286`) because the parsers are stateful — the streaming and non-streaming paths each need their own.
+
+So the user-facing knob stays on `Options[]`:
+
+```yaml
+options:
+  - tool_parser:hermes
+  - reasoning_parser:deepseek_r1
+```
+
+Putting these in `engine_args:` will set them on `ServerArgs` but the LocalAI-level streaming `ChatDelta` will not pick them up. Don't recommend that path.
+
+## What's missing today (out of scope, but worth tracking)
+
+- `core/config/hooks_sglang.go` — there is no SGLang equivalent of `hooks_vllm.go`. The vLLM hook auto-selects parsers for known model families from `parser_defaults.json` and seeds production engine_args defaults. A symmetric hook for SGLang could reuse the same `parser_defaults.json` (the SGLang parser names are different but the family detection is shared) and seed defaults like `enable_metrics: true` or attention-backend choices.
+- `core/gallery/importers/sglang.go` — vLLM has an importer that resolves model architecture → parser defaults at gallery-import time. A matching importer for SGLang would let `local-ai install` populate sensible parsers automatically.
+
+These should be a follow-up PR, not a blocker for the engine_args feature.

.docker/ik-llama-cpp-compile.sh

@@ -0,0 +1,30 @@
+#!/usr/bin/env bash
+# Shared compile logic for backend/Dockerfile.ik-llama-cpp.
+# Sourced (via bind mount) from both builder-fromsource and builder-prebuilt stages.
+
+set -euxo pipefail
+
+export CCACHE_DIR=/root/.ccache
+ccache --max-size=5G || true
+ccache -z || true
+
+export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache"
+
+if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
+  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
+  export CMAKE_ARGS="${CMAKE_ARGS} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
+  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
+  rm -rf /LocalAI/backend/cpp/ik-llama-cpp-*-build
+fi
+
+cd /LocalAI/backend/cpp/ik-llama-cpp
+
+if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
+  # ARM64 / ROCm: build without x86 SIMD
+  make ik-llama-cpp-fallback
+else
+  # ik_llama.cpp's IQK kernels require at least AVX2
+  make ik-llama-cpp-avx2
+fi
+
+ccache -s || true

.docker/install-base-deps.sh

@@ -0,0 +1,244 @@
+#!/usr/bin/env bash
+# Single source of truth for builder-base contents.
+#
+# Used by:
+#   - backend/Dockerfile.base-grpc-builder        (CI prebuilt-base source of truth)
+#   - backend/Dockerfile.llama-cpp                (builder-fromsource stage)
+#   - backend/Dockerfile.ik-llama-cpp             (builder-fromsource stage)
+#   - backend/Dockerfile.turboquant               (builder-fromsource stage)
+#
+# All four files invoke this script via
+#   RUN --mount=type=bind,source=.docker/install-base-deps.sh,target=/usr/local/sbin/install-base-deps \
+#       --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
+#       bash /usr/local/sbin/install-base-deps
+#
+# so the prebuilt CI base image and the from-source local-dev path are
+# bit-equivalent by construction.
+#
+# Inputs (env, populated from Dockerfile ARG/ENV):
+#   BUILD_TYPE                ("cublas"|"l4t"|"hipblas"|"vulkan"|"sycl"|"clblas"|"")
+#   CUDA_MAJOR_VERSION        ("12" | "13" | "")
+#   CUDA_MINOR_VERSION        ("8" | "0" | "")
+#   TARGETARCH                ("amd64" | "arm64")
+#   UBUNTU_VERSION            ("2204" | "2404")
+#   SKIP_DRIVERS              ("false" | "true")
+#   CMAKE_FROM_SOURCE         ("false" | "true")
+#   CMAKE_VERSION             ("3.31.10")
+#   GRPC_VERSION              ("v1.65.0")
+#   GRPC_MAKEFLAGS            ("-j4 -Otarget")
+#   APT_MIRROR / APT_PORTS_MIRROR  (optional; consumed by /usr/local/sbin/apt-mirror)
+#   AMDGPU_TARGETS            (optional; only relevant for hipblas downstream)
+#
+# IMPORTANT: install logic is copied verbatim from the prior in-Dockerfile
+# RUN blocks. Do not paraphrase apt invocations / version pins / sed line
+# numbers / deb URLs — the bit-equivalence guarantee depends on it.
+
+set -eux
+
+# --- 0. apt mirror rewrite (no-op when APT_MIRROR / APT_PORTS_MIRROR unset) ---
+if [ -x /usr/local/sbin/apt-mirror ]; then
+    APT_MIRROR="${APT_MIRROR:-}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR:-}" \
+        sh /usr/local/sbin/apt-mirror
+fi
+
+export DEBIAN_FRONTEND=noninteractive
+export MAKEFLAGS="${GRPC_MAKEFLAGS:-}"
+
+# --- 1. Base apt build deps ---
+apt-get update
+apt-get install -y --no-install-recommends \
+    build-essential \
+    ccache git \
+    ca-certificates \
+    make \
+    pkg-config libcurl4-openssl-dev \
+    curl unzip \
+    libssl-dev wget
+apt-get clean
+rm -rf /var/lib/apt/lists/*
+
+# --- 2. Vulkan SDK (BUILD_TYPE=vulkan) ---
+# NB: this block intentionally installs `cmake` via apt as part of the
+# Vulkan tooling — must run before the dedicated CMake step below.
+if [ "${BUILD_TYPE:-}" = "vulkan" ] && [ "${SKIP_DRIVERS:-false}" = "false" ]; then
+    apt-get update
+    apt-get install -y  --no-install-recommends \
+        software-properties-common pciutils wget gpg-agent
+    apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
+        libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
+        libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
+        git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
+        ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
+        clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
+    if [ "amd64" = "${TARGETARCH:-}" ]; then
+        wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz"
+        tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz
+        rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz
+        mkdir -p /opt/vulkan-sdk
+        mv 1.4.335.0 /opt/vulkan-sdk/
+        ( cd /opt/vulkan-sdk/1.4.335.0 && \
+          ./vulkansdk --no-deps --maxjobs \
+              vulkan-loader \
+              vulkan-validationlayers \
+              vulkan-extensionlayer \
+              vulkan-tools \
+              shaderc )
+        cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/
+        cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/
+        cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/
+        cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/
+        rm -rf /opt/vulkan-sdk
+    fi
+    if [ "arm64" = "${TARGETARCH:-}" ]; then
+        mkdir vulkan
+        ( cd vulkan && \
+          curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
+          tar -xvf vulkan-sdk.tar.xz && \
+          rm vulkan-sdk.tar.xz && \
+          cd 1.4.335.0 && \
+          cp -rfv aarch64/bin/* /usr/bin/ && \
+          cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
+          cp -rfv aarch64/include/* /usr/include/ && \
+          cp -rfv aarch64/share/* /usr/share/ )
+        rm -rf vulkan
+    fi
+    ldconfig
+    apt-get clean
+    rm -rf /var/lib/apt/lists/*
+fi
+
+# --- 3. CUDA toolkit (BUILD_TYPE=cublas|l4t) ---
+if { [ "${BUILD_TYPE:-}" = "cublas" ] || [ "${BUILD_TYPE:-}" = "l4t" ]; } && [ "${SKIP_DRIVERS:-false}" = "false" ]; then
+    apt-get update
+    apt-get install -y  --no-install-recommends \
+        software-properties-common pciutils
+    if [ "amd64" = "${TARGETARCH:-}" ]; then
+        curl -O "https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb"
+    fi
+    if [ "arm64" = "${TARGETARCH:-}" ]; then
+        if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
+            curl -O "https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb"
+        else
+            curl -O "https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb"
+        fi
+    fi
+    dpkg -i cuda-keyring_1.1-1_all.deb
+    rm -f cuda-keyring_1.1-1_all.deb
+    apt-get update
+    apt-get install -y --no-install-recommends \
+        "cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+        "libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+        "libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+        "libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+        "libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+        "libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}"
+    if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "${TARGETARCH:-}" ]; then
+        apt-get install -y --no-install-recommends \
+            "libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+            "libcudnn9-cuda-${CUDA_MAJOR_VERSION}" \
+            "cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}" \
+            "libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}"
+    fi
+    apt-get clean
+    rm -rf /var/lib/apt/lists/*
+fi
+
+# --- 4. cuDSS / NVPL on arm64 + cublas (legacy JetPack / Tegra) ---
+# https://github.com/NVIDIA/Isaac-GR00T/issues/343
+if [ "${BUILD_TYPE:-}" = "cublas" ] && [ "${TARGETARCH:-}" = "arm64" ]; then
+    wget "https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb"
+    dpkg -i "cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb"
+    cp /var/cudss-local-tegra-repo-ubuntu"${UBUNTU_VERSION}"-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/
+    apt-get update
+    apt-get -y install cudss "cudss-cuda-${CUDA_MAJOR_VERSION}"
+    wget "https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb"
+    dpkg -i "nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb"
+    cp /var/nvpl-local-repo-ubuntu"${UBUNTU_VERSION}"-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/
+    apt-get update
+    apt-get install -y nvpl
+fi
+
+# --- 5. clBLAS (BUILD_TYPE=clblas) ---
+# Present in variant Dockerfiles' from-source path but not in master's
+# Dockerfile.base-grpc-builder. No CI matrix entry currently uses this,
+# but keep parity so a future BUILD_TYPE=clblas build doesn't drift.
+if [ "${BUILD_TYPE:-}" = "clblas" ] && [ "${SKIP_DRIVERS:-false}" = "false" ]; then
+    apt-get update
+    apt-get install -y --no-install-recommends \
+        libclblast-dev
+    apt-get clean
+    rm -rf /var/lib/apt/lists/*
+fi
+
+# --- 6. ROCm / HIP build deps (BUILD_TYPE=hipblas) ---
+if [ "${BUILD_TYPE:-}" = "hipblas" ] && [ "${SKIP_DRIVERS:-false}" = "false" ]; then
+    apt-get update
+    apt-get install -y --no-install-recommends \
+        hipblas-dev \
+        hipblaslt-dev \
+        rocblas-dev
+    apt-get clean
+    rm -rf /var/lib/apt/lists/*
+    # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install,
+    # which results in local-ai and others not being able to locate the libraries.
+    # We run ldconfig ourselves to work around this packaging deficiency.
+    ldconfig
+    # Log which GPU architectures have rocBLAS kernel support
+    echo "rocBLAS library data architectures:"
+    (ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
+        echo "WARNING: No rocBLAS kernel data found"
+fi
+
+echo "TARGETARCH: ${TARGETARCH:-}"
+
+# --- 7. protoc (always) ---
+# The version in 22.04 is too old. We will create one as part of installing
+# the GRPC build below but that will also bring in a newer version of absl
+# which stablediffusion cannot compile with. This version of protoc is only
+# here so that we can generate the grpc code for the stablediffusion build.
+if [ "amd64" = "${TARGETARCH:-}" ]; then
+    curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip
+    unzip -j -d /usr/local/bin protoc.zip bin/protoc
+    rm protoc.zip
+fi
+if [ "arm64" = "${TARGETARCH:-}" ]; then
+    curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip
+    unzip -j -d /usr/local/bin protoc.zip bin/protoc
+    rm protoc.zip
+fi
+
+# --- 8. CMake (apt or compiled from source) ---
+# The version in 22.04 is too old. Vulkan path above already pulled cmake
+# via apt; the from-source branch here will install over it which is fine.
+if [ "${CMAKE_FROM_SOURCE:-false}" = "true" ]; then
+    curl -L -s "https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz" -o cmake.tar.gz
+    tar xvf cmake.tar.gz
+    ( cd "cmake-${CMAKE_VERSION}" && ./configure && make && make install )
+else
+    apt-get update
+    apt-get install -y \
+        cmake
+    apt-get clean
+    rm -rf /var/lib/apt/lists/*
+fi
+
+# --- 9. gRPC compile + install at /opt/grpc ---
+# We install GRPC to a different prefix here so that we can copy in only
+# the build artifacts later — saves several hundred MB on the final docker
+# image size vs copying in the entire GRPC source tree and running
+# `make install` in the target container.
+#
+# The TESTONLY abseil sed patch and /opt/grpc prefix are load-bearing —
+# downstream Dockerfiles `COPY` /opt/grpc to /usr/local (or rely on the
+# prebuilt base having it at /opt/grpc).
+mkdir -p /build
+cd /build
+git clone --recurse-submodules --jobs 4 -b "${GRPC_VERSION}" --depth 1 --shallow-submodules https://github.com/grpc/grpc
+mkdir -p /build/grpc/cmake/build
+cd /build/grpc/cmake/build
+sed -i "216i\\  TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt"
+cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../..
+make
+make install
+cd /
+rm -rf /build

.docker/llama-cpp-compile.sh

@@ -0,0 +1,35 @@
+#!/usr/bin/env bash
+# Shared compile logic for backend/Dockerfile.llama-cpp.
+# Sourced (via bind mount) from both builder-fromsource and builder-prebuilt stages.
+
+set -euxo pipefail
+
+export CCACHE_DIR=/root/.ccache
+ccache --max-size=5G || true
+ccache -z || true
+
+export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache"
+
+if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
+  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
+  export CMAKE_ARGS="${CMAKE_ARGS} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
+  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
+  rm -rf /LocalAI/backend/cpp/llama-cpp-*-build
+fi
+
+if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
+  cd /LocalAI/backend/cpp/llama-cpp
+  make llama-cpp-fallback
+  make llama-cpp-grpc
+  make llama-cpp-rpc-server
+else
+  cd /LocalAI/backend/cpp/llama-cpp
+  make llama-cpp-avx
+  make llama-cpp-avx2
+  make llama-cpp-avx512
+  make llama-cpp-fallback
+  make llama-cpp-grpc
+  make llama-cpp-rpc-server
+fi
+
+ccache -s || true

.docker/turboquant-compile.sh

@@ -0,0 +1,35 @@
+#!/usr/bin/env bash
+# Shared compile logic for backend/Dockerfile.turboquant.
+# Sourced (via bind mount) from both builder-fromsource and builder-prebuilt stages.
+
+set -euxo pipefail
+
+export CCACHE_DIR=/root/.ccache
+ccache --max-size=5G || true
+ccache -z || true
+
+export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache"
+
+if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
+  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
+  export CMAKE_ARGS="${CMAKE_ARGS} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
+  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
+  rm -rf /LocalAI/backend/cpp/turboquant-*-build
+fi
+
+cd /LocalAI/backend/cpp/turboquant
+
+if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
+  make turboquant-fallback
+  make turboquant-grpc
+  make turboquant-rpc-server
+else
+  make turboquant-avx
+  make turboquant-avx2
+  make turboquant-avx512
+  make turboquant-fallback
+  make turboquant-grpc
+  make turboquant-rpc-server
+fi
+
+ccache -s || true

.github/actions/free-disk-space/action.yml

@@ -0,0 +1,65 @@
+name: 'Free disk space on hosted runners'
+description: |
+  Aggressively clean GitHub-hosted ubuntu-latest runners to reclaim ~6-10 GB
+  of working space before docker buildx steps. Combines jlumbroso/free-disk-space
+  with explicit apt purges of large packages we never use (dotnet, ghc, mono,
+  android, jdk, ...).
+
+  No-op on self-hosted runners; pass mode=skip to force-disable.
+
+inputs:
+  mode:
+    description: 'hosted (default — clean) or skip (no-op)'
+    required: false
+    default: 'hosted'
+
+runs:
+  using: 'composite'
+  steps:
+    - name: Free Disk Space (Ubuntu)
+      if: inputs.mode == 'hosted' && runner.environment == 'github-hosted'
+      uses: jlumbroso/free-disk-space@main
+      with:
+        tool-cache: true
+        android: true
+        dotnet: true
+        haskell: true
+        large-packages: true
+        docker-images: true
+        swap-storage: true
+
+    - name: Release space from worker
+      if: inputs.mode == 'hosted' && runner.environment == 'github-hosted'
+      shell: bash
+      run: |
+        echo "Listing top largest packages"
+        pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
+        head -n 30 <<< "${pkgs}"
+        df -h
+        sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
+        sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
+        sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
+        sudo rm -rf /usr/local/lib/android
+        sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
+        sudo rm -rf /usr/share/dotnet
+        sudo apt-get remove -y '^mono-.*' || true
+        sudo apt-get remove -y '^ghc-.*' || true
+        sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
+        sudo apt-get remove -y 'php.*' || true
+        sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
+        sudo apt-get remove -y '^google-.*' || true
+        sudo apt-get remove -y azure-cli || true
+        sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
+        sudo apt-get remove -y '^gfortran-.*' || true
+        sudo apt-get remove -y microsoft-edge-stable || true
+        sudo apt-get remove -y firefox || true
+        sudo apt-get remove -y powershell || true
+        sudo apt-get remove -y r-base-core || true
+        sudo apt-get autoremove -y
+        sudo apt-get clean
+        sudo rm -rfv build || true
+        sudo rm -rf /usr/share/dotnet || true
+        sudo rm -rf /opt/ghc || true
+        sudo rm -rf "/usr/local/share/boost" || true
+        sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
+        df -h

.github/actions/setup-build-disk/action.yml

@@ -0,0 +1,59 @@
+name: 'Set up build disk on hosted runners'
+description: |
+  Relocate Docker's data-root to /mnt (which has ~75 GB free, vs ~20 GB
+  on / after free-disk-space). Combined with the apt cleanup, gives
+  ~100 GB working space for buildx — enough for ROCm dev image + vLLM
+  torch install + flash-attn build.
+
+  No-op on:
+    - self-hosted runners (no /mnt expectation)
+    - non-X64 runners (verify /mnt shape on ubuntu-24.04-arm separately
+      before enabling there — see Task 3.2 in the migration plan)
+    - mode=skip (force-disable from caller)
+
+  Must run after free-disk-space (which removes large packages — would
+  fail mid-uninstall if Docker were stopped) and before any Docker
+  operation (setup-qemu, setup-buildx, login, build) so the relocated
+  data-root catches all subsequent docker activity.
+
+inputs:
+  mode:
+    description: 'auto (default — relocate on hosted X64 only) or skip'
+    required: false
+    default: 'auto'
+
+runs:
+  using: 'composite'
+  steps:
+    - name: Relocate Docker data-root to /mnt
+      if: inputs.mode == 'auto' && runner.environment == 'github-hosted' && runner.arch == 'X64'
+      shell: bash
+      run: |
+        set -euo pipefail
+        echo "Before relocation:"
+        df -h / /mnt || true
+        sudo systemctl stop docker docker.socket
+        sudo mkdir -p /mnt/docker-data /mnt/docker-tmp
+        # buildx CLI runs as the unprivileged runner user and creates
+        # config dirs under TMPDIR before binding them into the buildkit
+        # container. /mnt is owned by root by default; mirror /tmp's
+        # 1777 (world-writable + sticky) so non-root processes can write.
+        sudo chmod 1777 /mnt/docker-tmp
+        if [ -d /var/lib/docker ] && [ ! -L /var/lib/docker ]; then
+          sudo rsync -a /var/lib/docker/ /mnt/docker-data/
+          sudo rm -rf /var/lib/docker
+          sudo ln -s /mnt/docker-data /var/lib/docker
+        fi
+        # daemon.json may not exist; merge data-root in or create minimal.
+        if [ -f /etc/docker/daemon.json ]; then
+          sudo jq '."data-root" = "/mnt/docker-data"' /etc/docker/daemon.json | sudo tee /etc/docker/daemon.json.new >/dev/null
+          sudo mv /etc/docker/daemon.json.new /etc/docker/daemon.json
+        else
+          echo '{"data-root":"/mnt/docker-data"}' | sudo tee /etc/docker/daemon.json
+        fi
+        sudo systemctl start docker
+        # Make TMPDIR persist for subsequent steps in the same job.
+        echo "TMPDIR=/mnt/docker-tmp" >> "$GITHUB_ENV"
+        echo "After relocation:"
+        df -h / /mnt
+        docker info | grep -i 'docker root dir' || true

.github/scripts/anchor-digest-in-cache.sh

@@ -0,0 +1,46 @@
+#!/usr/bin/env bash
+# Anchor a backend per-arch digest in quay.io/go-skynet/ci-cache so quay's
+# garbage collector won't reap the manifest before backend_merge.yml runs.
+#
+# Context: backend_build.yml pushes by canonical digest only
+# (push-by-digest=true). Unreferenced manifests on quay can be reaped within
+# ~1-2h, but backend-merge-jobs runs only after the *entire* per-arch build
+# matrix drains (max-parallel: 8 × dozens of entries → ~2h+). Without an
+# anchoring tag, the earliest digests are gone by the time `imagetools create`
+# tries to read them, producing "manifest not found" merge failures.
+#
+# We tag the digest under our internal ci-cache image; quay does not GC tagged
+# manifests. The user-facing manifest list still references the original
+# digest in local-ai-backends. backend_merge.yml deletes the anchor tag after
+# the user-facing manifest is published — see cleanup-keepalive-tags.sh.
+#
+# Required env:
+#   GITHUB_RUN_ID  - current workflow run id (set automatically by GHA)
+#   TAG_SUFFIX     - matrix entry's tag-suffix (e.g. -gpu-nvidia-cuda-12-vllm)
+#   PLATFORM_TAG   - amd64 / arm64 / single (single = singleton matrix entry)
+#   DIGEST         - canonical content digest from build step (sha256:...)
+#
+# Optional env:
+#   ANCHOR_IMAGE   - target image (default: quay.io/go-skynet/ci-cache)
+#   SOURCE_IMAGE   - source image (default: quay.io/go-skynet/local-ai-backends)
+#   GITHUB_STEP_SUMMARY - if set, an anchored-by line is appended to it
+set -euo pipefail
+
+: "${GITHUB_RUN_ID:?}"
+: "${TAG_SUFFIX:?}"
+: "${PLATFORM_TAG:?}"
+: "${DIGEST:?}"
+
+anchor_image="${ANCHOR_IMAGE:-quay.io/go-skynet/ci-cache}"
+source_image="${SOURCE_IMAGE:-quay.io/go-skynet/local-ai-backends}"
+
+tag="keepalive-${GITHUB_RUN_ID}${TAG_SUFFIX}-${PLATFORM_TAG}"
+
+docker buildx imagetools create \
+  -t "${anchor_image}:${tag}" \
+  "${source_image}@${DIGEST}"
+
+echo "anchored ${DIGEST} as ${anchor_image}:${tag}"
+if [[ -n "${GITHUB_STEP_SUMMARY:-}" ]]; then
+  echo "anchored \`${DIGEST}\` as \`${anchor_image}:${tag}\`" >> "${GITHUB_STEP_SUMMARY}"
+fi

.github/scripts/cleanup-keepalive-tags.sh

@@ -0,0 +1,49 @@
+#!/usr/bin/env bash
+# Best-effort cleanup of the keepalive anchor tags written by
+# anchor-digest-in-cache.sh. Called from backend_merge.yml after the
+# user-facing manifest list has been published.
+#
+# Quay's docker registry v2 doesn't allow tag deletes — only digest deletes.
+# The proper delete is the quay REST API, which requires an OAuth-scoped
+# token. We try QUAY_TOKEN as a bearer token: if the secret is an OAuth app
+# token (typical for service accounts) the delete succeeds; otherwise this
+# is a soft no-op and the tag persists until manually pruned.
+#
+# Cleanup failure MUST NOT fail the merge — the merge has already produced
+# the user-facing manifest list at this point and the keepalive tags are
+# pure overhead. We always exit 0.
+#
+# Required env:
+#   GITHUB_RUN_ID  - current workflow run id (set automatically by GHA)
+#   TAG_SUFFIX     - matrix entry's tag-suffix (e.g. -gpu-nvidia-cuda-12-vllm)
+#   QUAY_TOKEN     - bearer token for quay's REST API
+#
+# Optional env:
+#   QUAY_REPO      - target repo (default: go-skynet/ci-cache)
+#   PLATFORM_TAGS  - space-separated list of platform-tag values to try
+#                    (default: "amd64 arm64 single")
+#                    We don't know which platform-tag(s) exist for this
+#                    tag-suffix without an extra API call, so we just try
+#                    all three and ignore 404s for the ones that don't.
+set -uo pipefail
+
+: "${GITHUB_RUN_ID:?}"
+: "${TAG_SUFFIX:?}"
+: "${QUAY_TOKEN:?}"
+
+quay_repo="${QUAY_REPO:-go-skynet/ci-cache}"
+platform_tags="${PLATFORM_TAGS:-amd64 arm64 single}"
+
+for plat in $platform_tags; do
+  tag="keepalive-${GITHUB_RUN_ID}${TAG_SUFFIX}-${plat}"
+  url="https://quay.io/api/v1/repository/${quay_repo}/tag/${tag}"
+  http=$(curl -sS -o /dev/null -w '%{http_code}' \
+    -X DELETE -H "Authorization: Bearer ${QUAY_TOKEN}" "$url" || echo "000")
+  case "$http" in
+    204|200) echo "deleted $tag" ;;
+    404)     echo "not present: $tag" ;;
+    401|403) echo "auth not OAuth-scoped (http $http) for $tag - skipping; orphan tag will persist" ;;
+    *)       echo "unexpected http $http deleting $tag - skipping" ;;
+  esac
+done
+exit 0

.github/workflows/backend_build.yml

@@ -24,6 +24,17 @@ on:
         description: 'Platforms'
         default: ''
         type: string
+      platform-tag:
+        description: |
+          Short tag identifying the platform leg, e.g. "amd64" or "arm64".
+          Used to scope the per-arch registry cache and the digest artifact name.
+          Required for split-and-merge multi-arch builds; pass "amd64" for
+          single-arch amd64 builds too. Optional (default '') during the
+          migration to per-arch matrix expansion; will be flipped to
+          required: true in Phase 6 once all callers pass an explicit value.
+        required: false
+        default: ''
+        type: string
       tag-latest:
         description: 'Tag latest'
         default: ''
@@ -63,6 +74,15 @@ on:
         required: false
         default: ''
         type: string
+      builder-base-image:
+        description: |
+          Pre-built builder base image (e.g. quay.io/go-skynet/ci-cache:base-grpc-cuda-13-amd64).
+          When set, the variant Dockerfile uses its `builder-prebuilt` stage which FROMs this
+          image directly instead of running its own gRPC stage + apt installs. Empty for
+          backends whose Dockerfile doesn't support a prebuilt base.
+        required: false
+        default: ''
+        type: string
     secrets:
       dockerUsername:
         required: false
@@ -89,63 +109,13 @@ jobs:
         id: apt_mirror
         uses: ./.github/actions/configure-apt-mirror
 
-      - name: Free Disk Space (Ubuntu)
-        if: inputs.runs-on == 'ubuntu-latest'
-        uses: jlumbroso/free-disk-space@main
+      - name: Free disk space
+        uses: ./.github/actions/free-disk-space
         with:
-          # this might remove tools that are actually needed,
-          # if set to "true" but frees about 6 GB
-          tool-cache: true
-          # all of these default to true, but feel free to set to
-          # "false" if necessary for your workflow
-          android: true
-          dotnet: true
-          haskell: true
-          large-packages: true
-          docker-images: true
-          swap-storage: true
+          mode: ${{ inputs.runs-on == 'ubuntu-latest' && 'hosted' || 'skip' }}
 
-      - name: Release space from worker
-        if: inputs.runs-on == 'ubuntu-latest'
-        run: |
-          echo "Listing top largest packages"
-          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-          head -n 30 <<< "${pkgs}"
-          echo
-          df -h
-          echo
-          sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
-          sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
-          sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
-          sudo rm -rf /usr/local/lib/android
-          sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
-          sudo rm -rf /usr/share/dotnet
-          sudo apt-get remove -y '^mono-.*' || true
-          sudo apt-get remove -y '^ghc-.*' || true
-          sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
-          sudo apt-get remove -y 'php.*' || true
-          sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
-          sudo apt-get remove -y '^google-.*' || true
-          sudo apt-get remove -y azure-cli || true
-          sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
-          sudo apt-get remove -y '^gfortran-.*' || true
-          sudo apt-get remove -y microsoft-edge-stable || true
-          sudo apt-get remove -y firefox || true
-          sudo apt-get remove -y powershell || true
-          sudo apt-get remove -y r-base-core || true
-          sudo apt-get autoremove -y
-          sudo apt-get clean
-          echo
-          echo "Listing top largest packages"
-          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-          head -n 30 <<< "${pkgs}"
-          echo
-          sudo rm -rfv build || true
-          sudo rm -rf /usr/share/dotnet || true
-          sudo rm -rf /opt/ghc || true
-          sudo rm -rf "/usr/local/share/boost" || true
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
-          df -h
+      - name: Set up build disk
+        uses: ./.github/actions/setup-build-disk
 
       - name: Docker meta
         id: meta
@@ -211,7 +181,8 @@ jobs:
         id: deps_refresh
         run: echo "key=$(date -u +%Y-W%V)" >> "$GITHUB_OUTPUT"
 
-      - name: Build and push
+      - name: Build and push by digest
+        id: build
         uses: docker/build-push-action@v7
         if: github.event_name != 'pull_request'
         with:
@@ -228,16 +199,62 @@ jobs:
             APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
             APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
             DEPS_REFRESH=${{ steps.deps_refresh.outputs.key }}
+            BUILDER_BASE_IMAGE=${{ inputs.builder-base-image }}
+            BUILDER_TARGET=${{ inputs.builder-base-image != '' && 'builder-prebuilt' || 'builder-fromsource' }}
           context: ${{ inputs.context }}
           file: ${{ inputs.dockerfile }}
-          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}
-          cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }},mode=max,ignore-error=true
+          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}-${{ inputs.platform-tag }}
+          cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}-${{ inputs.platform-tag }},mode=max,ignore-error=true
           platforms: ${{ inputs.platforms }}
-          push: ${{ github.event_name != 'pull_request' }}
-          tags: ${{ steps.meta.outputs.tags }}
+          outputs: |
+            type=image,name=quay.io/go-skynet/local-ai-backends,push-by-digest=true,name-canonical=true,push=true
+            type=image,name=localai/localai-backends,push-by-digest=true,name-canonical=true,push=true
+          # Disable provenance: with mode=max (the default for push:true)
+          # buildx bundles a per-registry attestation manifest into each
+          # registry's manifest list, which makes the resulting list digest
+          # diverge across registries. steps.build.outputs.digest then
+          # only matches one of them, and the merge job's
+          # `imagetools create <reg>@sha256:<digest>` lookup fails on the
+          # other. Disabling provenance keeps the digest content-only and
+          # identical across both registries — required for digest-based
+          # cross-registry merge.
+          provenance: false
           labels: ${{ steps.meta.outputs.labels }}
 
-      - name: Build and push (PR)
+      - name: Export digest
+        if: github.event_name != 'pull_request'
+        run: |
+          mkdir -p /tmp/digests
+          digest="${{ steps.build.outputs.digest }}"
+          touch "/tmp/digests/${digest#sha256:}"
+
+      # See .github/scripts/anchor-digest-in-cache.sh for why this is needed
+      # and how it interacts with backend_merge.yml's cleanup step.
+      - name: Anchor digest in ci-cache so quay GC won't reap before merge
+        if: github.event_name != 'pull_request'
+        env:
+          TAG_SUFFIX: ${{ inputs.tag-suffix }}
+          PLATFORM_TAG: ${{ inputs.platform-tag || 'single' }}
+          DIGEST: ${{ steps.build.outputs.digest }}
+        run: .github/scripts/anchor-digest-in-cache.sh
+
+      # Artifact name uses a `--` separator between tag-suffix and platform-tag
+      # to avoid prefix collisions during the merge job's pattern-based download.
+      # Tag-suffixes are not prefix-disjoint (e.g. -gpu-nvidia-cuda-12-vllm is a
+      # prefix of -gpu-nvidia-cuda-12-vllm-omni); a single `-` separator plus the
+      # merge-side `digests<tag-suffix>-*` glob would let one merge over-match
+      # the other backend's artifacts. The `-single` placeholder for empty
+      # platform-tag (single-arch entries) keeps the artifact name non-trailing.
+      - name: Upload digest artifact
+        if: github.event_name != 'pull_request'
+        uses: actions/upload-artifact@v7
+        with:
+          name: digests${{ inputs.tag-suffix }}--${{ inputs.platform-tag || 'single' }}
+          path: /tmp/digests/*
+          if-no-files-found: error
+          retention-days: 1
+
+      - name: Build (PR)
         uses: docker/build-push-action@v7
         if: github.event_name == 'pull_request'
         with:
@@ -254,9 +271,11 @@ jobs:
             APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
             APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
             DEPS_REFRESH=${{ steps.deps_refresh.outputs.key }}
+            BUILDER_BASE_IMAGE=${{ inputs.builder-base-image }}
+            BUILDER_TARGET=${{ inputs.builder-base-image != '' && 'builder-prebuilt' || 'builder-fromsource' }}
           context: ${{ inputs.context }}
           file: ${{ inputs.dockerfile }}
-          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}
+          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}-${{ inputs.platform-tag }}
           platforms: ${{ inputs.platforms }}
           push: ${{ env.quay_username != '' }}
           tags: ${{ steps.meta_pull_request.outputs.tags }}

.github/workflows/backend_build_darwin.yml

@@ -93,6 +93,11 @@ jobs:
             /opt/homebrew/Cellar/libomp
             /opt/homebrew/Cellar/llvm
             /opt/homebrew/Cellar/ccache
+            /opt/homebrew/Cellar/blake3
+            /opt/homebrew/Cellar/fmt
+            /opt/homebrew/Cellar/hiredis
+            /opt/homebrew/Cellar/xxhash
+            /opt/homebrew/Cellar/zstd
           key: brew-${{ runner.os }}-${{ runner.arch }}-v1-${{ hashFiles('.github/workflows/backend_build_darwin.yml') }}
 
       - name: Dependencies
@@ -100,7 +105,30 @@ jobs:
           # ccache is always installed (used by the llama-cpp variant build) so
           # the brew cache content stays stable across every backend in the
           # matrix — they all share one cache key.
-          brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm ccache
+          # blake3, fmt, hiredis, xxhash, zstd are ccache's runtime dylib deps.
+          # Without explicitly installing them, a brew cache-hit run restores
+          # ccache's Cellar dir but skips installing those transitive deps,
+          # and ccache fails at runtime with `dyld: Library not loaded`.
+          brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm ccache blake3 fmt hiredis xxhash zstd
+          # Force-reinstall ccache so brew re-validates its full runtime-dep
+          # closure on every run. This is the durable fix: when the upstream
+          # ccache formula gains a new transitive dep (as it has multiple times
+          # already), we don't have to chase missing dylibs one at a time.
+          # The downloads cache makes the reinstall fast (~5s on a hit).
+          brew reinstall ccache
+          # Same pattern for grpc: its CMake config (used by the llama-cpp
+          # `grpc-server` target) does find_package(absl). The cache restores
+          # /opt/homebrew/Cellar/grpc so brew above no-ops the install, but
+          # abseil isn't in our Cellar cache list and never gets installed
+          # alongside, leaving grpc's CMake unable to resolve it. Reinstalling
+          # grpc re-validates and pulls abseil in, mirroring the ccache fix.
+          brew reinstall grpc
+          # The brew cache restores the Cellar dirs but NOT the bin symlinks
+          # at /opt/homebrew/bin/*. brew install above sees the Cellar present
+          # and decides "already installed" without re-linking, so on a cache-
+          # hit run the formulas aren't on PATH. Force-link them; --overwrite
+          # tolerates pre-existing symlinks from earlier installs.
+          brew link --overwrite protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm ccache blake3 fmt hiredis xxhash zstd 2>/dev/null || true
 
       - name: Save Homebrew cache
         if: github.event_name != 'pull_request' && steps.brew-cache.outputs.cache-hit != 'true'
@@ -115,6 +143,11 @@ jobs:
             /opt/homebrew/Cellar/libomp
             /opt/homebrew/Cellar/llvm
             /opt/homebrew/Cellar/ccache
+            /opt/homebrew/Cellar/blake3
+            /opt/homebrew/Cellar/fmt
+            /opt/homebrew/Cellar/hiredis
+            /opt/homebrew/Cellar/xxhash
+            /opt/homebrew/Cellar/zstd
           key: brew-${{ runner.os }}-${{ runner.arch }}-v1-${{ hashFiles('.github/workflows/backend_build_darwin.yml') }}
 
       # ---- ccache for llama.cpp CMake builds ----
@@ -175,7 +208,23 @@ jobs:
           restore-keys: |
             pyenv-darwin-${{ inputs.backend }}-
 
+      # llama-cpp on Darwin uses a bespoke build script (scripts/build/llama-cpp-darwin.sh)
+      # that compiles three CMake variants from backend/cpp/llama-cpp and bundles dylibs
+      # via otool — it doesn't fit the build-darwin-go-backend / build-darwin-python-backend
+      # mold. Drive it via its dedicated `backends/llama-cpp-darwin` make target instead.
+      - name: Build ${{ inputs.backend }}-darwin (llama-cpp)
+        if: inputs.backend == 'llama-cpp'
+        run: |
+          make protogen-go
+          make backends/llama-cpp-darwin
+
+      - name: Build ds4 backend (Darwin Metal)
+        if: inputs.backend == 'ds4'
+        run: |
+          make backends/ds4-darwin
+
       - name: Build ${{ inputs.backend }}-darwin
+        if: inputs.backend != 'llama-cpp' && inputs.backend != 'ds4'
         run: |
           make protogen-go
           BACKEND=${{ inputs.backend }} BUILD_TYPE=${{ inputs.build-type }} USE_PIP=${{ inputs.use-pip }} make build-darwin-${{ inputs.lang }}-backend

.github/workflows/backend_merge.yml

@@ -0,0 +1,213 @@
+---
+name: 'merge backend manifest list (reusable)'
+
+# Reusable workflow that joins per-arch digest artifacts (uploaded by
+# backend_build.yml when called with platform-tag) into a single tagged
+# multi-arch manifest list. Called once per backend by backend.yml after
+# both per-arch build jobs succeed.
+
+on:
+  workflow_call:
+    inputs:
+      tag-latest:
+        description: 'Whether the manifest list should also be tagged latest (auto/false/true)'
+        required: false
+        type: string
+        default: ''
+      tag-suffix:
+        description: 'Backend tag suffix (e.g. -cpu-faster-whisper). Used to compute the artifact pattern and the final tag suffix.'
+        required: true
+        type: string
+    secrets:
+      dockerUsername:
+        required: false
+      dockerPassword:
+        required: false
+      quayUsername:
+        required: true
+      quayPassword:
+        required: true
+
+jobs:
+  merge:
+    runs-on: ubuntu-latest
+    # id-token: write is required for keyless cosign — the workflow
+    # exchanges the GitHub OIDC token for a short-lived Fulcio cert that
+    # signs each pushed manifest. Without this permission the runner
+    # cannot mint the token, and `cosign sign` fails with "no token".
+    permissions:
+      contents: read
+      id-token: write
+    env:
+      quay_username: ${{ secrets.quayUsername }}
+    steps:
+      # Sparse checkout: the merge job needs `.github/scripts/` (for the
+      # keepalive cleanup script) but none of the source tree.
+      - name: Checkout (.github/scripts only)
+        uses: actions/checkout@v6
+        with:
+          sparse-checkout: |
+            .github/scripts
+          sparse-checkout-cone-mode: false
+
+      # `--` separator anchors the glob so we don't over-match sibling
+      # backends whose tag-suffix happens to be a prefix of ours
+      # (e.g. -cpu-vllm vs -cpu-vllm-omni). Must stay in sync with the
+      # upload-artifact name in backend_build.yml.
+      - name: Download digests
+        uses: actions/download-artifact@v8
+        with:
+          pattern: digests${{ inputs.tag-suffix }}--*
+          merge-multiple: true
+          path: /tmp/digests
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@master
+
+      # cosign signs each pushed manifest list with --recursive so the
+      # index and every per-arch entry get an attached Sigstore bundle.
+      # 2.2+ is required for --new-bundle-format.
+      - name: Install cosign
+        if: github.event_name != 'pull_request'
+        uses: sigstore/cosign-installer@v3
+        with:
+          cosign-release: 'v2.4.1'
+
+      - name: Login to DockerHub
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v4
+        with:
+          username: ${{ secrets.dockerUsername }}
+          password: ${{ secrets.dockerPassword }}
+
+      - name: Login to Quay.io
+        if: ${{ env.quay_username != '' }}
+        uses: docker/login-action@v4
+        with:
+          registry: quay.io
+          username: ${{ secrets.quayUsername }}
+          password: ${{ secrets.quayPassword }}
+
+      - name: Docker meta
+        id: meta
+        if: github.event_name != 'pull_request'
+        uses: docker/metadata-action@v6
+        with:
+          images: |
+            quay.io/go-skynet/local-ai-backends
+            localai/localai-backends
+          tags: |
+            type=ref,event=branch
+            type=semver,pattern={{raw}}
+            type=sha
+          flavor: |
+            latest=${{ inputs.tag-latest }}
+            suffix=${{ inputs.tag-suffix }},onlatest=true
+
+      # Source from ci-cache, not local-ai-backends.
+      #
+      # The build job pushes per-arch manifests to local-ai-backends with
+      # push-by-digest=true (no tag), then anchors a tagged copy into
+      # ci-cache so the manifest can be retrieved hours later when this
+      # merge runs. Quay's manifest GC, however, is per-repository: the
+      # anchor tag in ci-cache protects the manifest there, but the same
+      # digest in local-ai-backends has no tag in *that* repo and gets
+      # reaped independently. Sourcing local-ai-backends@<digest> here
+      # then fails with "manifest not found" — exactly the regression
+      # we hit on v4.2.2 (19/37 multiarch merges failed).
+      #
+      # ci-cache@<digest> resolves because we anchored it there. buildx
+      # imagetools create copies the manifest into local-ai-backends
+      # (cross-repo within the same registry, blobs already cross-mounted
+      # from the original push so no transfer needed) and publishes the
+      # manifest list with the user-facing tags. The resulting manifest
+      # list is fully self-contained in local-ai-backends — child digests
+      # only, no embedded references to ci-cache.
+      - name: Create manifest list and push (quay)
+        if: github.event_name != 'pull_request'
+        working-directory: /tmp/digests
+        run: |
+          set -euo pipefail
+          tags=$(jq -cr '
+            .tags
+            | map(select(startswith("quay.io/")))
+            | map("-t " + .)
+            | join(" ")
+          ' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          if [ -z "$tags" ]; then
+            echo "No quay.io tags from docker/metadata-action; skipping quay merge"
+            exit 0
+          fi
+          # shellcheck disable=SC2086
+          docker buildx imagetools create $tags \
+            $(printf 'quay.io/go-skynet/ci-cache@sha256:%s ' *)
+          # Resolve the manifest-list digest (any tag points at it) so
+          # cosign can sign by digest. Signing by tag would leave the
+          # signature orphaned the next time the tag moves.
+          first_tag=$(jq -cr '
+            .tags | map(select(startswith("quay.io/"))) | .[0]
+          ' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          digest=$(docker buildx imagetools inspect "$first_tag" --format '{{.Manifest.Digest}}')
+          # --recursive walks the list and signs every per-arch entry
+          # too — clients that resolve a tag to a platform-specific
+          # manifest before checking signatures need the per-arch
+          # signatures, not just the list-level one.
+          cosign sign --yes --recursive \
+            --new-bundle-format \
+            --registry-referrers-mode=oci-1-1 \
+            "quay.io/go-skynet/local-ai-backends@${digest}"
+
+      - name: Create manifest list and push (dockerhub)
+        if: github.event_name != 'pull_request'
+        working-directory: /tmp/digests
+        run: |
+          set -euo pipefail
+          tags=$(jq -cr '
+            .tags
+            | map(select(startswith("localai/")))
+            | map("-t " + .)
+            | join(" ")
+          ' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          if [ -z "$tags" ]; then
+            echo "No dockerhub tags from docker/metadata-action; skipping dockerhub merge"
+            exit 0
+          fi
+          # shellcheck disable=SC2086
+          docker buildx imagetools create $tags \
+            $(printf 'localai/localai-backends@sha256:%s ' *)
+          first_tag=$(jq -cr '
+            .tags | map(select(startswith("localai/"))) | .[0]
+          ' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          digest=$(docker buildx imagetools inspect "$first_tag" --format '{{.Manifest.Digest}}')
+          cosign sign --yes --recursive \
+            --new-bundle-format \
+            --registry-referrers-mode=oci-1-1 \
+            "localai/localai-backends@${digest}"
+
+      - name: Inspect manifest
+        if: github.event_name != 'pull_request'
+        run: |
+          set -euo pipefail
+          first_tag=$(jq -cr '.tags[0]' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          if [ -n "$first_tag" ] && [ "$first_tag" != "null" ]; then
+            docker buildx imagetools inspect "$first_tag"
+          fi
+
+      # See .github/scripts/cleanup-keepalive-tags.sh for why this is
+      # best-effort and what the failure modes are.
+      - name: Cleanup keepalive tags in ci-cache
+        if: github.event_name != 'pull_request' && success()
+        env:
+          TAG_SUFFIX: ${{ inputs.tag-suffix }}
+          QUAY_TOKEN: ${{ secrets.quayPassword }}
+        run: .github/scripts/cleanup-keepalive-tags.sh
+
+      - name: Job summary
+        if: github.event_name != 'pull_request'
+        run: |
+          set -euo pipefail
+          echo "Merged manifest tags:" >> "$GITHUB_STEP_SUMMARY"
+          jq -r '.tags[]' <<< "$DOCKER_METADATA_OUTPUT_JSON" | sed 's/^/- /' >> "$GITHUB_STEP_SUMMARY"
+          echo >> "$GITHUB_STEP_SUMMARY"
+          echo "Per-arch digests:" >> "$GITHUB_STEP_SUMMARY"
+          ls -1 /tmp/digests | sed 's/^/- sha256:/' >> "$GITHUB_STEP_SUMMARY"

.github/workflows/backend_pr.yml

@@ -4,17 +4,23 @@ on:
   pull_request:
 
 concurrency:
-  group: ci-backends-pr-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-backends-pr-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   generate-matrix:
     runs-on: ubuntu-latest
     outputs:
-      matrix: ${{ steps.set-matrix.outputs.matrix }}
-      matrix-darwin: ${{ steps.set-matrix.outputs.matrix-darwin }}
-      has-backends: ${{ steps.set-matrix.outputs.has-backends }}
-      has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
+      matrix-singlearch: ${{ steps.set-matrix.outputs['matrix-singlearch'] }}
+      matrix-multiarch: ${{ steps.set-matrix.outputs['matrix-multiarch'] }}
+      matrix-darwin: ${{ steps.set-matrix.outputs['matrix-darwin'] }}
+      merge-matrix-multiarch: ${{ steps.set-matrix.outputs['merge-matrix-multiarch'] }}
+      merge-matrix-singlearch: ${{ steps.set-matrix.outputs['merge-matrix-singlearch'] }}
+      has-backends-singlearch: ${{ steps.set-matrix.outputs['has-backends-singlearch'] }}
+      has-backends-multiarch: ${{ steps.set-matrix.outputs['has-backends-multiarch'] }}
+      has-backends-darwin: ${{ steps.set-matrix.outputs['has-backends-darwin'] }}
+      has-merges-multiarch: ${{ steps.set-matrix.outputs['has-merges-multiarch'] }}
+      has-merges-singlearch: ${{ steps.set-matrix.outputs['has-merges-singlearch'] }}
     steps:
       - name: Checkout repository
         uses: actions/checkout@v6
@@ -27,7 +33,9 @@ jobs:
           bun add js-yaml
           bun add @octokit/core
 
-      # filters the matrix in backend.yml
+      # filters the matrix in backend.yml; splits into single-arch and
+      # multi-arch groups so backend-merge-jobs can `needs:` only the latter
+      # (matches backend.yml's structure).
       - name: Filter matrix for changed backends
         id: set-matrix
         env:
@@ -35,10 +43,10 @@ jobs:
           GITHUB_EVENT_PATH: ${{ github.event_path }}
         run: bun run scripts/changed-backends.js
 
-  backend-jobs:
+  backend-jobs-multiarch:
     needs: generate-matrix
     uses: ./.github/workflows/backend_build.yml
-    if: needs.generate-matrix.outputs.has-backends == 'true'
+    if: needs.generate-matrix.outputs['has-backends-multiarch'] == 'true'
     with:
       tag-latest: ${{ matrix.tag-latest }}
       tag-suffix: ${{ matrix.tag-suffix }}
@@ -46,7 +54,9 @@ jobs:
       cuda-major-version: ${{ matrix.cuda-major-version }}
       cuda-minor-version: ${{ matrix.cuda-minor-version }}
       platforms: ${{ matrix.platforms }}
+      platform-tag: ${{ matrix.platform-tag || '' }}
       runs-on: ${{ matrix.runs-on }}
+      builder-base-image: ${{ matrix.builder-base-image || '' }}
       base-image: ${{ matrix.base-image }}
       backend: ${{ matrix.backend }}
       dockerfile: ${{ matrix.dockerfile }}
@@ -59,7 +69,68 @@ jobs:
       quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
     strategy:
       fail-fast: true
-      matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
+      max-parallel: 8
+      matrix: ${{ fromJson(needs.generate-matrix.outputs['matrix-multiarch']) }}
+  backend-jobs-singlearch:
+    needs: generate-matrix
+    uses: ./.github/workflows/backend_build.yml
+    if: needs.generate-matrix.outputs['has-backends-singlearch'] == 'true'
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      platform-tag: ${{ matrix.platform-tag || '' }}
+      runs-on: ${{ matrix.runs-on }}
+      builder-base-image: ${{ matrix.builder-base-image || '' }}
+      base-image: ${{ matrix.base-image }}
+      backend: ${{ matrix.backend }}
+      dockerfile: ${{ matrix.dockerfile }}
+      skip-drivers: ${{ matrix.skip-drivers }}
+      context: ${{ matrix.context }}
+      ubuntu-version: ${{ matrix.ubuntu-version }}
+      amdgpu-targets: ${{ matrix.amdgpu-targets || 'gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1151,gfx1200,gfx1201' }}
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: true
+      max-parallel: 8
+      matrix: ${{ fromJson(needs.generate-matrix.outputs['matrix-singlearch']) }}
+  backend-merge-jobs-multiarch:
+    needs: [generate-matrix, backend-jobs-multiarch]
+    # backend_merge.yml's push-side steps are all gated on
+    # github.event_name != 'pull_request', so on a PR the merge job would
+    # do nothing. Skip it entirely to avoid spinning up an empty runner.
+    # !cancelled() lets the merge run even when a few build legs fail —
+    # see the matching note in backend.yml.
+    if: ${{ !cancelled() && github.event_name != 'pull_request' && needs.generate-matrix.outputs['has-merges-multiarch'] == 'true' }}
+    uses: ./.github/workflows/backend_merge.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: false
+      matrix: ${{ fromJson(needs.generate-matrix.outputs['merge-matrix-multiarch']) }}
+
+  backend-merge-jobs-singlearch:
+    needs: [generate-matrix, backend-jobs-singlearch]
+    if: ${{ !cancelled() && github.event_name != 'pull_request' && needs.generate-matrix.outputs['has-merges-singlearch'] == 'true' }}
+    uses: ./.github/workflows/backend_merge.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: false
+      matrix: ${{ fromJson(needs.generate-matrix.outputs['merge-matrix-singlearch']) }}
   backend-jobs-darwin:
     needs: generate-matrix
     uses: ./.github/workflows/backend_build_darwin.yml
@@ -67,7 +138,7 @@ jobs:
     with:
       backend: ${{ matrix.backend }}
       build-type: ${{ matrix.build-type }}
-      go-version: "1.24.x"
+      go-version: "1.25.x"
       tag-suffix: ${{ matrix.tag-suffix }}
       lang: ${{ matrix.lang || 'python' }}
       use-pip: ${{ matrix.backend == 'diffusers' }}

.github/workflows/base-images.yml

@@ -0,0 +1,161 @@
+---
+name: 'build base-grpc images'
+
+# Builds + pushes pre-compiled builder base images that downstream
+# llama-cpp / ik-llama-cpp / turboquant variant Dockerfiles will FROM
+# (PR 2). Each base contains apt deps + protoc + cmake + gRPC at
+# /opt/grpc + (conditionally) CUDA / ROCm / Vulkan toolchains.
+#
+# Triggers:
+#   - schedule (Saturdays 05:00 UTC) - picks up Ubuntu/CUDA/ROCm
+#     security updates and re-runs ahead of the backend.yml weekly
+#     cron (Sundays 06:00 UTC).
+#   - workflow_dispatch - manual one-off rebuild.
+#   - push to master that touches Dockerfile.base-grpc-builder or
+#     this workflow itself - keeps bases in sync with their inputs.
+#
+# Bootstrap (one-time after this PR merges):
+#   gh workflow run base-images.yml --ref master
+# Wait ~30 min for all 9 matrix variants to push to
+# quay.io/go-skynet/ci-cache:base-grpc-* before merging PR 2.
+
+on:
+  schedule:
+    - cron: '0 5 * * 6'
+  workflow_dispatch:
+  push:
+    branches: [master]
+    paths:
+      - 'backend/Dockerfile.base-grpc-builder'
+      - '.github/workflows/base-images.yml'
+      # The install logic and apt-mirror helper are bind-mounted into
+      # Dockerfile.base-grpc-builder at build time — changes to either
+      # affect the produced base images and must trigger a rebuild.
+      - '.docker/install-base-deps.sh'
+      - '.docker/apt-mirror.sh'
+
+concurrency:
+  group: ci-base-images-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
+
+jobs:
+  build:
+    if: github.repository == 'mudler/LocalAI'
+    runs-on: ${{ matrix.runs-on }}
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - tag: 'base-grpc-amd64'
+            runs-on: 'ubuntu-latest'
+            base-image: 'ubuntu:24.04'
+            build-type: ''
+            cuda-major-version: ''
+            cuda-minor-version: ''
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-arm64'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: 'ubuntu:24.04'
+            build-type: ''
+            cuda-major-version: ''
+            cuda-minor-version: ''
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-cuda-12-amd64'
+            runs-on: 'ubuntu-latest'
+            base-image: 'ubuntu:24.04'
+            build-type: 'cublas'
+            cuda-major-version: '12'
+            cuda-minor-version: '8'
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-cuda-13-amd64'
+            runs-on: 'ubuntu-latest'
+            base-image: 'ubuntu:22.04'
+            build-type: 'cublas'
+            cuda-major-version: '13'
+            cuda-minor-version: '0'
+            ubuntu-version: '2204'
+          - tag: 'base-grpc-cuda-13-arm64'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: 'ubuntu:24.04'
+            build-type: 'cublas'
+            cuda-major-version: '13'
+            cuda-minor-version: '0'
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-rocm-amd64'
+            runs-on: 'ubuntu-latest'
+            base-image: 'rocm/dev-ubuntu-24.04:7.2.1'
+            build-type: 'hipblas'
+            cuda-major-version: ''
+            cuda-minor-version: ''
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-vulkan-amd64'
+            runs-on: 'ubuntu-latest'
+            base-image: 'ubuntu:24.04'
+            build-type: 'vulkan'
+            cuda-major-version: ''
+            cuda-minor-version: ''
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-vulkan-arm64'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: 'ubuntu:24.04'
+            build-type: 'vulkan'
+            cuda-major-version: ''
+            cuda-minor-version: ''
+            ubuntu-version: '2404'
+          - tag: 'base-grpc-intel-amd64'
+            runs-on: 'ubuntu-latest'
+            base-image: 'intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04'
+            build-type: 'sycl'
+            cuda-major-version: ''
+            cuda-minor-version: ''
+            ubuntu-version: '2404'
+          # Legacy JetPack r36.4.0 base for older Jetson devices (CUDA 12).
+          # Distinct from base-grpc-cuda-13-arm64 (Ubuntu 24.04 + CUDA 13 sbsa)
+          # which targets newer Jetsons. Some matrix entries
+          # (-nvidia-l4t-arm64-llama-cpp / -turboquant) still build against
+          # the JetPack image, so we need a matching base.
+          - tag: 'base-grpc-l4t-cuda-12-arm64'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: 'nvcr.io/nvidia/l4t-jetpack:r36.4.0'
+            build-type: 'l4t'
+            cuda-major-version: '12'
+            cuda-minor-version: '0'
+            ubuntu-version: '2204'
+            # JetPack r36.4.0 already ships CUDA preinstalled at /usr/local/cuda;
+            # apt-installing cuda-nvcc-12-0 from the public repos fails because
+            # those packages aren't published for the JetPack apt feed. Match
+            # the original l4t matrix entry which set skip-drivers: 'true'.
+            skip-drivers: 'true'
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          submodules: false
+      - name: Free disk space
+        uses: ./.github/actions/free-disk-space
+      - name: Set up build disk
+        uses: ./.github/actions/setup-build-disk
+      - uses: docker/setup-qemu-action@master
+        with:
+          platforms: all
+      - uses: docker/setup-buildx-action@master
+      - uses: docker/login-action@v4
+        with:
+          registry: quay.io
+          username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+          password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+      - uses: docker/build-push-action@v7
+        with:
+          context: .
+          file: ./backend/Dockerfile.base-grpc-builder
+          build-args: |
+            BASE_IMAGE=${{ matrix.base-image }}
+            BUILD_TYPE=${{ matrix.build-type }}
+            CUDA_MAJOR_VERSION=${{ matrix.cuda-major-version }}
+            CUDA_MINOR_VERSION=${{ matrix.cuda-minor-version }}
+            UBUNTU_VERSION=${{ matrix.ubuntu-version }}
+            SKIP_DRIVERS=${{ matrix.skip-drivers || 'false' }}
+          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-${{ matrix.tag }}
+          cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache-${{ matrix.tag }},mode=max,ignore-error=true
+          provenance: false
+          tags: quay.io/go-skynet/ci-cache:${{ matrix.tag }}
+          push: true

.github/workflows/bump_deps.yaml

@@ -22,6 +22,10 @@ jobs:
             variable: "TURBOQUANT_VERSION"
             branch: "feature/turboquant-kv-cache"
             file: "backend/cpp/turboquant/Makefile"
+          - repository: "antirez/ds4"
+            variable: "DS4_VERSION"
+            branch: "main"
+            file: "backend/cpp/ds4/Makefile"
           - repository: "ggml-org/whisper.cpp"
             variable: "WHISPER_CPP_VERSION"
             branch: "master"
@@ -50,7 +54,7 @@ jobs:
             variable: "QWEN3TTS_CPP_VERSION"
             branch: "main"
             file: "backend/go/qwen3-tts-cpp/Makefile"
-          - repository: "mudler/vibevoice.cpp"
+          - repository: "localai-org/vibevoice.cpp"
             variable: "VIBEVOICE_CPP_VERSION"
             branch: "master"
             file: "backend/go/vibevoice-cpp/Makefile"

.github/workflows/generate_intel_image.yaml

@@ -7,8 +7,8 @@ on:
       - master
 
 concurrency:
-  group: intel-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: intel-cache-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   generate_caches:

.github/workflows/image-pr.yml

@@ -5,8 +5,8 @@
     pull_request:
   
   concurrency:
-    group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
-    cancel-in-progress: true
+    group: ci-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+    cancel-in-progress: ${{ github.event_name == 'pull_request' }}
   
   jobs:
     image-build:
@@ -18,6 +18,7 @@
         cuda-major-version: ${{ matrix.cuda-major-version }}
         cuda-minor-version: ${{ matrix.cuda-minor-version }}
         platforms: ${{ matrix.platforms }}
+        platform-tag: ${{ matrix.platform-tag || '' }}
         runs-on: ${{ matrix.runs-on }}
         base-image: ${{ matrix.base-image }}
         makeflags: ${{ matrix.makeflags }}
@@ -71,13 +72,23 @@
               makeflags: "--jobs=3 --output-sync=target"
               ubuntu-version: '2404'
             - build-type: 'vulkan'
-              platforms: 'linux/amd64,linux/arm64'
+              platforms: 'linux/amd64'
+              platform-tag: 'amd64'
               tag-latest: 'false'
               tag-suffix: '-vulkan-core'
               runs-on: 'ubuntu-latest'
               base-image: "ubuntu:24.04"
               makeflags: "--jobs=4 --output-sync=target"
               ubuntu-version: '2404'
+            - build-type: 'vulkan'
+              platforms: 'linux/arm64'
+              platform-tag: 'arm64'
+              tag-latest: 'false'
+              tag-suffix: '-vulkan-core'
+              runs-on: 'ubuntu-24.04-arm'
+              base-image: "ubuntu:24.04"
+              makeflags: "--jobs=4 --output-sync=target"
+              ubuntu-version: '2404'
             - build-type: 'cublas'
               cuda-major-version: "13"
               cuda-minor-version: "0"

.github/workflows/image.yml

@@ -9,8 +9,8 @@
         - '*'
   
   concurrency:
-    group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
-    cancel-in-progress: true
+    group: ci-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+    cancel-in-progress: ${{ github.event_name == 'pull_request' }}
   
   jobs:
     hipblas-jobs:
@@ -56,6 +56,7 @@
         cuda-major-version: ${{ matrix.cuda-major-version }}
         cuda-minor-version: ${{ matrix.cuda-minor-version }}
         platforms: ${{ matrix.platforms }}
+        platform-tag: ${{ matrix.platform-tag || '' }}
         runs-on: ${{ matrix.runs-on }}
         base-image: ${{ matrix.base-image }}
         makeflags: ${{ matrix.makeflags }}
@@ -72,7 +73,8 @@
         matrix:
           include:
             - build-type: ''
-              platforms: 'linux/amd64,linux/arm64'
+              platforms: 'linux/amd64'
+              platform-tag: 'amd64'
               tag-latest: 'auto'
               tag-suffix: ''
               base-image: "ubuntu:24.04"
@@ -81,6 +83,17 @@
               skip-drivers: 'false'
               ubuntu-version: '2404'
               ubuntu-codename: 'noble'
+            - build-type: ''
+              platforms: 'linux/arm64'
+              platform-tag: 'arm64'
+              tag-latest: 'auto'
+              tag-suffix: ''
+              base-image: "ubuntu:24.04"
+              runs-on: 'ubuntu-24.04-arm'
+              makeflags: "--jobs=4 --output-sync=target"
+              skip-drivers: 'false'
+              ubuntu-version: '2404'
+              ubuntu-codename: 'noble'
             - build-type: 'cublas'
               cuda-major-version: "12"
               cuda-minor-version: "8"
@@ -106,7 +119,8 @@
               ubuntu-version: '2404'
               ubuntu-codename: 'noble'
             - build-type: 'vulkan'
-              platforms: 'linux/amd64,linux/arm64'
+              platforms: 'linux/amd64'
+              platform-tag: 'amd64'
               tag-latest: 'auto'
               tag-suffix: '-gpu-vulkan'
               runs-on: 'ubuntu-latest'
@@ -115,6 +129,17 @@
               makeflags: "--jobs=4 --output-sync=target"
               ubuntu-version: '2404'
               ubuntu-codename: 'noble'
+            - build-type: 'vulkan'
+              platforms: 'linux/arm64'
+              platform-tag: 'arm64'
+              tag-latest: 'auto'
+              tag-suffix: '-gpu-vulkan'
+              runs-on: 'ubuntu-24.04-arm'
+              base-image: "ubuntu:24.04"
+              skip-drivers: 'false'
+              makeflags: "--jobs=4 --output-sync=target"
+              ubuntu-version: '2404'
+              ubuntu-codename: 'noble'
             - build-type: 'intel'
               platforms: 'linux/amd64'
               tag-latest: 'auto'
@@ -124,7 +149,121 @@
               makeflags: "--jobs=3 --output-sync=target"
               ubuntu-version: '2404'
               ubuntu-codename: 'noble'
-  
+
+    core-image-merge:
+      # !cancelled(): without it, GHA's default `needs:` cascade skips the
+      # merge whenever any matrix cell of the parent build fails or is
+      # cancelled. Same fix as backend.yml's merge jobs — we still want to
+      # publish the manifest list for tag-suffixes whose legs all succeeded.
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: core-image-build
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: ''
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    gpu-vulkan-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: core-image-build
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-gpu-vulkan'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    # Single-arch server-image merges. Same conceptual fix as the backend
+    # singletons in PR #9781: image_build.yml pushes by canonical digest
+    # only, so without a downstream merge step there's no tag for consumers
+    # (no :latest-gpu-nvidia-cuda-12, no :v<X>-gpu-nvidia-cuda-12, etc.).
+    # Each merge job needs only its parent build matrix and is filtered by
+    # tag-suffix in image_merge.yml's artifact-download pattern.
+    gpu-nvidia-cuda-12-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: core-image-build
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-gpu-nvidia-cuda-12'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    gpu-nvidia-cuda-13-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: core-image-build
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-gpu-nvidia-cuda-13'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    gpu-intel-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: core-image-build
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-gpu-intel'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    gpu-hipblas-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: hipblas-jobs
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-gpu-hipblas'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    nvidia-l4t-arm64-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: gh-runner
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-nvidia-l4t-arm64'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
+    nvidia-l4t-arm64-cuda-13-image-merge:
+      if: ${{ !cancelled() && github.repository == 'mudler/LocalAI' }}
+      needs: gh-runner
+      uses: ./.github/workflows/image_merge.yml
+      with:
+        tag-latest: 'auto'
+        tag-suffix: '-nvidia-l4t-arm64-cuda-13'
+      secrets:
+        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+
     gh-runner:
       if: github.repository == 'mudler/LocalAI'
       uses: ./.github/workflows/image_build.yml

.github/workflows/image_build.yml

@@ -24,6 +24,15 @@ on:
         description: 'Platforms'
         default: ''
         type: string
+      platform-tag:
+        description: |
+          Short tag identifying the platform leg, e.g. "amd64" or "arm64".
+          Used to scope the per-arch registry cache and the digest artifact name.
+          Optional during the migration; will be flipped to required: true once
+          every caller passes an explicit value.
+        required: false
+        default: ''
+        type: string
       tag-latest:
         description: 'Tag latest'
         default: ''
@@ -77,63 +86,13 @@ jobs:
         id: apt_mirror
         uses: ./.github/actions/configure-apt-mirror
 
-      - name: Free Disk Space (Ubuntu)
-        if: inputs.runs-on == 'ubuntu-latest'
-        uses: jlumbroso/free-disk-space@main
+      - name: Free disk space
+        uses: ./.github/actions/free-disk-space
         with:
-          # this might remove tools that are actually needed,
-          # if set to "true" but frees about 6 GB
-          tool-cache: true
-          # all of these default to true, but feel free to set to
-          # "false" if necessary for your workflow
-          android: true
-          dotnet: true
-          haskell: true
-          large-packages: true
-          docker-images: true
-          swap-storage: true
+          mode: ${{ inputs.runs-on == 'ubuntu-latest' && 'hosted' || 'skip' }}
 
-      - name: Release space from worker
-        if: inputs.runs-on == 'ubuntu-latest'
-        run: |
-          echo "Listing top largest packages"
-          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-          head -n 30 <<< "${pkgs}"
-          echo
-          df -h
-          echo
-          sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
-          sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
-          sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
-          sudo rm -rf /usr/local/lib/android
-          sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
-          sudo rm -rf /usr/share/dotnet
-          sudo apt-get remove -y '^mono-.*' || true
-          sudo apt-get remove -y '^ghc-.*' || true
-          sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
-          sudo apt-get remove -y 'php.*' || true
-          sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
-          sudo apt-get remove -y '^google-.*' || true
-          sudo apt-get remove -y azure-cli || true
-          sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
-          sudo apt-get remove -y '^gfortran-.*' || true
-          sudo apt-get remove -y microsoft-edge-stable || true
-          sudo apt-get remove -y firefox || true
-          sudo apt-get remove -y powershell || true
-          sudo apt-get remove -y r-base-core || true
-          sudo apt-get autoremove -y
-          sudo apt-get clean
-          echo
-          echo "Listing top largest packages"
-          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-          head -n 30 <<< "${pkgs}"
-          echo
-          sudo rm -rfv build || true
-          sudo rm -rf /usr/share/dotnet || true
-          sudo rm -rf /opt/ghc || true
-          sudo rm -rf "/usr/local/share/boost" || true
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
-          df -h
+      - name: Set up build disk
+        uses: ./.github/actions/setup-build-disk
 
       - name: Docker meta
         id: meta
@@ -188,7 +147,8 @@ jobs:
           username: ${{ secrets.quayUsername }}
           password: ${{ secrets.quayPassword }}
 
-      - name: Build and push
+      - name: Build and push by digest
+        id: build
         uses: docker/build-push-action@v7
         if: github.event_name != 'pull_request'
         with:
@@ -206,12 +166,50 @@ jobs:
             APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
           context: .
           file: ./Dockerfile
-          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}
-          cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }},mode=max,ignore-error=true
+          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}-${{ inputs.platform-tag }}
+          cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}-${{ inputs.platform-tag }},mode=max,ignore-error=true
           platforms: ${{ inputs.platforms }}
-          push: ${{ github.event_name != 'pull_request' }}
-          tags: ${{ steps.meta.outputs.tags }}
+          outputs: |
+            type=image,name=quay.io/go-skynet/local-ai,push-by-digest=true,name-canonical=true,push=true
+            type=image,name=localai/localai,push-by-digest=true,name-canonical=true,push=true
+          # See backend_build.yml for the rationale — provenance=mode=max
+          # diverges the manifest-list digest per registry, breaking the
+          # downstream imagetools create lookup.
+          provenance: false
           labels: ${{ steps.meta.outputs.labels }}
+
+      - name: Export digest
+        if: github.event_name != 'pull_request'
+        run: |
+          mkdir -p /tmp/digests
+          digest="${{ steps.build.outputs.digest }}"
+          touch "/tmp/digests/${digest#sha256:}"
+
+      # See .github/scripts/anchor-digest-in-cache.sh for why this is needed
+      # and how it interacts with image_merge.yml's cleanup step. Mirrors the
+      # same anchor in backend_build.yml — quay's per-repo manifest GC reaps
+      # untagged manifests in local-ai before the merge runs.
+      - name: Anchor digest in ci-cache so quay GC won't reap before merge
+        if: github.event_name != 'pull_request'
+        env:
+          TAG_SUFFIX: ${{ inputs.tag-suffix == '' && '-core' || inputs.tag-suffix }}
+          PLATFORM_TAG: ${{ inputs.platform-tag || 'single' }}
+          DIGEST: ${{ steps.build.outputs.digest }}
+          SOURCE_IMAGE: quay.io/go-skynet/local-ai
+        run: .github/scripts/anchor-digest-in-cache.sh
+
+      - name: Upload digest artifact
+        if: github.event_name != 'pull_request'
+        uses: actions/upload-artifact@v7
+        with:
+          # `--` separator + 'single' placeholder for empty platform-tag —
+          # same pattern as backend_build.yml. Prevents prefix collisions
+          # in the merge-side glob (e.g. -nvidia-l4t-arm64 is a prefix of
+          # -nvidia-l4t-arm64-cuda-13).
+          name: digests-localai${{ inputs.tag-suffix == '' && '-core' || inputs.tag-suffix }}--${{ inputs.platform-tag || 'single' }}
+          path: /tmp/digests/*
+          if-no-files-found: error
+          retention-days: 1
 ### Start testing image
       - name: Build and push
         uses: docker/build-push-action@v7
@@ -231,7 +229,7 @@ jobs:
             APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
           context: .
           file: ./Dockerfile
-          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}
+          cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}-${{ inputs.platform-tag }}
           platforms: ${{ inputs.platforms }}
           #push: true
           tags: ${{ steps.meta_pull_request.outputs.tags }}

.github/workflows/image_merge.yml

@@ -0,0 +1,145 @@
+---
+name: 'merge LocalAI image manifest list (reusable)'
+
+# Reusable workflow that joins per-arch digest artifacts (uploaded by
+# image_build.yml when called with platform-tag) into a single tagged
+# multi-arch manifest list.
+
+on:
+  workflow_call:
+    inputs:
+      tag-latest:
+        description: 'Whether the manifest list should also be tagged latest (auto/false/true)'
+        required: false
+        type: string
+        default: ''
+      tag-suffix:
+        description: 'Image tag suffix (empty for core image). Used in artifact pattern with a -core placeholder for empty.'
+        required: true
+        type: string
+    secrets:
+      dockerUsername:
+        required: false
+      dockerPassword:
+        required: false
+      quayUsername:
+        required: true
+      quayPassword:
+        required: true
+
+jobs:
+  merge:
+    runs-on: ubuntu-latest
+    env:
+      quay_username: ${{ secrets.quayUsername }}
+    steps:
+      # Sparse checkout: needed for .github/scripts/ (the keepalive cleanup
+      # script). Skips the rest of the source tree.
+      - name: Checkout (.github/scripts only)
+        uses: actions/checkout@v6
+        with:
+          sparse-checkout: |
+            .github/scripts
+          sparse-checkout-cone-mode: false
+
+      - name: Download digests
+        uses: actions/download-artifact@v8
+        with:
+          # `--` separator anchors the glob so we don't over-match sibling
+          # tag-suffixes (e.g. -nvidia-l4t-arm64 vs -nvidia-l4t-arm64-cuda-13).
+          # Must stay in sync with image_build.yml's upload-artifact name.
+          pattern: digests-localai${{ inputs.tag-suffix == '' && '-core' || inputs.tag-suffix }}--*
+          merge-multiple: true
+          path: /tmp/digests
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@master
+
+      - name: Login to DockerHub
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v4
+        with:
+          username: ${{ secrets.dockerUsername }}
+          password: ${{ secrets.dockerPassword }}
+
+      - name: Login to Quay.io
+        uses: docker/login-action@v4
+        with:
+          registry: quay.io
+          username: ${{ secrets.quayUsername }}
+          password: ${{ secrets.quayPassword }}
+
+      - name: Docker meta
+        id: meta
+        uses: docker/metadata-action@v6
+        with:
+          images: |
+            quay.io/go-skynet/local-ai
+            localai/localai
+          tags: |
+            type=ref,event=branch
+            type=semver,pattern={{raw}}
+            type=sha
+          flavor: |
+            latest=${{ inputs.tag-latest }}
+            suffix=${{ inputs.tag-suffix }},onlatest=true
+
+      # Source from ci-cache, not local-ai. See backend_merge.yml for the
+      # detailed rationale — quay's manifest GC is per-repository, so the
+      # untagged digest in local-ai gets reaped while the same content lives
+      # tagged under ci-cache (anchored by image_build.yml). buildx imagetools
+      # create copies the manifest into local-ai (blobs already cross-mounted)
+      # and publishes the manifest list with user-facing tags. End state in
+      # local-ai is self-contained; no embedded reference to ci-cache.
+      - name: Create manifest list and push (quay)
+        working-directory: /tmp/digests
+        run: |
+          set -euo pipefail
+          tags=$(jq -cr '.tags | map(select(startswith("quay.io/"))) | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          if [ -z "$tags" ]; then
+            echo "No quay.io tags from docker/metadata-action; skipping quay merge"
+          else
+            # shellcheck disable=SC2086
+            docker buildx imagetools create $tags \
+              $(printf 'quay.io/go-skynet/ci-cache@sha256:%s ' *)
+          fi
+
+      - name: Create manifest list and push (dockerhub)
+        if: github.event_name != 'pull_request'
+        working-directory: /tmp/digests
+        run: |
+          set -euo pipefail
+          tags=$(jq -cr '.tags | map(select(startswith("localai/"))) | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          if [ -z "$tags" ]; then
+            echo "No dockerhub tags from docker/metadata-action; skipping dockerhub merge"
+          else
+            # shellcheck disable=SC2086
+            docker buildx imagetools create $tags \
+              $(printf 'localai/localai@sha256:%s ' *)
+          fi
+
+      - name: Inspect manifest
+        run: |
+          set -euo pipefail
+          first_tag=$(jq -cr '.tags[0]' <<< "$DOCKER_METADATA_OUTPUT_JSON")
+          if [ -n "$first_tag" ] && [ "$first_tag" != "null" ]; then
+            docker buildx imagetools inspect "$first_tag"
+          fi
+
+      # See .github/scripts/cleanup-keepalive-tags.sh for the best-effort
+      # semantics — fails soft when the registry credential isn't OAuth-scoped.
+      - name: Cleanup keepalive tags in ci-cache
+        if: github.event_name != 'pull_request' && success()
+        env:
+          TAG_SUFFIX: ${{ inputs.tag-suffix == '' && '-core' || inputs.tag-suffix }}
+          QUAY_TOKEN: ${{ secrets.quayPassword }}
+        run: .github/scripts/cleanup-keepalive-tags.sh
+
+      - name: Job summary
+        run: |
+          set -euo pipefail
+          echo "Merged manifest tags:" >> "$GITHUB_STEP_SUMMARY"
+          jq -r '.tags[]' <<< "$DOCKER_METADATA_OUTPUT_JSON" | sed 's/^/- /' >> "$GITHUB_STEP_SUMMARY"
+          echo >> "$GITHUB_STEP_SUMMARY"
+          echo "Per-arch digests:" >> "$GITHUB_STEP_SUMMARY"
+          ls -1 /tmp/digests | sed 's/^/- sha256:/' >> "$GITHUB_STEP_SUMMARY"

.github/workflows/lint.yml

@@ -13,8 +13,8 @@ on:
       - master
 
 concurrency:
-  group: ci-lint-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-lint-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   golangci-lint:

.github/workflows/test-extra.yml

@@ -10,8 +10,8 @@ on:
       - '*'
 
 concurrency:
-  group: ci-tests-extra-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-tests-extra-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   detect-changes:
@@ -28,6 +28,7 @@ jobs:
       qwen-asr: ${{ steps.detect.outputs.qwen-asr }}
       nemo: ${{ steps.detect.outputs.nemo }}
       voxcpm: ${{ steps.detect.outputs.voxcpm }}
+      liquid-audio: ${{ steps.detect.outputs.liquid-audio }}
       llama-cpp-quantization: ${{ steps.detect.outputs.llama-cpp-quantization }}
       llama-cpp: ${{ steps.detect.outputs.llama-cpp }}
       ik-llama-cpp: ${{ steps.detect.outputs.ik-llama-cpp }}
@@ -43,6 +44,7 @@ jobs:
       insightface: ${{ steps.detect.outputs.insightface }}
       speaker-recognition: ${{ steps.detect.outputs.speaker-recognition }}
       sherpa-onnx: ${{ steps.detect.outputs.sherpa-onnx }}
+      whisper: ${{ steps.detect.outputs.whisper }}
     steps:
       - name: Checkout repository
         uses: actions/checkout@v6
@@ -446,6 +448,32 @@ jobs:
         run: |
           make --jobs=5 --output-sync=target -C backend/python/voxcpm
           make --jobs=5 --output-sync=target -C backend/python/voxcpm test
+  # liquid-audio: LFM2.5-Audio any-to-any backend. The CI smoke test
+  # exercises Health() and LoadModel(mode:finetune) — fine-tune mode
+  # short-circuits before pulling weights (backend.py:192), so no
+  # HuggingFace download or GPU is needed. The full-inference path is
+  # gated on LIQUID_AUDIO_MODEL_ID, which we don't set here.
+  tests-liquid-audio:
+    needs: detect-changes
+    if: needs.detect-changes.outputs.liquid-audio == 'true' || needs.detect-changes.outputs.run-all == 'true'
+    runs-on: ubuntu-latest
+    steps:
+      - name: Clone
+        uses: actions/checkout@v6
+        with:
+          submodules: true
+      - name: Dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y build-essential ffmpeg
+          sudo apt-get install -y ca-certificates cmake curl patch python3-pip
+          # Install UV
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          pip install --user --no-cache-dir grpcio-tools==1.64.1
+      - name: Test liquid-audio
+        run: |
+          make --jobs=5 --output-sync=target -C backend/python/liquid-audio
+          make --jobs=5 --output-sync=target -C backend/python/liquid-audio test
   tests-llama-cpp-quantization:
     needs: detect-changes
     if: needs.detect-changes.outputs.llama-cpp-quantization == 'true' || needs.detect-changes.outputs.run-all == 'true'
@@ -583,6 +611,27 @@ jobs:
       - name: Build sherpa-onnx backend image and run streaming ASR gRPC e2e tests
         run: |
           make test-extra-backend-sherpa-onnx-transcription
+  # End-to-end transcription via the e2e-backends gRPC harness against
+  # the whisper.cpp backend. Drives AudioTranscription (offline) and
+  # AudioTranscriptionStream (real, segment-callback-driven deltas) on
+  # ggml-base.en + the JFK 11s clip.
+  tests-whisper-grpc-transcription:
+    needs: detect-changes
+    if: needs.detect-changes.outputs.whisper == 'true' || needs.detect-changes.outputs.run-all == 'true'
+    runs-on: ubuntu-latest
+    timeout-minutes: 90
+    steps:
+      - name: Clone
+        uses: actions/checkout@v6
+        with:
+          submodules: true
+      - name: Setup Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: '1.25.4'
+      - name: Build whisper backend image and run transcription gRPC e2e tests
+        run: |
+          make test-extra-backend-whisper-transcription
   # VITS TTS via the sherpa-onnx backend. Drives both TTS (file write) and
   # TTSStream (PCM chunks) on the e2e-backends harness.
   tests-sherpa-onnx-grpc-tts:

.github/workflows/test.yml

@@ -3,12 +3,6 @@ name: 'tests'
 
 on:
   pull_request:
-    paths-ignore:
-      - 'docs/**'
-      - 'examples/**'
-      - 'README.md'
-      - '**/*.md'
-      - 'backend/**'
   push:
     branches:
       - master
@@ -16,8 +10,8 @@ on:
       - '*'
 
 concurrency:
-  group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-tests-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   tests-linux:
@@ -26,56 +20,12 @@ jobs:
       matrix:
         go-version: ['1.26.x']
     steps:
-      - name: Free Disk Space (Ubuntu)
-        uses: jlumbroso/free-disk-space@main
-        with:
-          # this might remove tools that are actually needed,
-          # if set to "true" but frees about 6 GB
-          tool-cache: true
-          # all of these default to true, but feel free to set to
-          # "false" if necessary for your workflow
-          android: true
-          dotnet: true
-          haskell: true
-          large-packages: true
-          docker-images: true
-          swap-storage: true
-      - name: Release space from worker
-        run: |
-          echo "Listing top largest packages"
-          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-          head -n 30 <<< "${pkgs}"
-          echo
-          df -h
-          echo
-          sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
-          sudo apt-get remove --auto-remove android-sdk-platform-tools || true
-          sudo apt-get purge --auto-remove android-sdk-platform-tools || true
-          sudo rm -rf /usr/local/lib/android
-          sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
-          sudo rm -rf /usr/share/dotnet
-          sudo apt-get remove -y '^mono-.*' || true
-          sudo apt-get remove -y '^ghc-.*' || true
-          sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
-          sudo apt-get remove -y 'php.*' || true
-          sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
-          sudo apt-get remove -y '^google-.*' || true
-          sudo apt-get remove -y azure-cli || true
-          sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
-          sudo apt-get remove -y '^gfortran-.*' || true
-          sudo apt-get autoremove -y
-          sudo apt-get clean
-          echo
-          echo "Listing top largest packages"
-          pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
-          head -n 30 <<< "${pkgs}"
-          echo
-          sudo rm -rfv build || true
-          df -h
       - name: Clone
         uses: actions/checkout@v6
         with:
           submodules: true
+      - name: Free disk space
+        uses: ./.github/actions/free-disk-space
       - name: Setup Go ${{ matrix.go-version }}
         uses: actions/setup-go@v5
         with:

.github/workflows/tests-aio.yml

@@ -22,8 +22,8 @@ on:
       - '*'
 
 concurrency:
-  group: ci-tests-aio-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-tests-aio-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   tests-aio:

.github/workflows/tests-e2e.yml

@@ -3,12 +3,6 @@ name: 'E2E Backend Tests'
 
 on:
   pull_request:
-    paths-ignore:
-      - 'docs/**'
-      - 'examples/**'
-      - 'README.md'
-      - '**/*.md'
-      - 'backend/**'
   push:
     branches:
       - master
@@ -16,8 +10,8 @@ on:
       - '*'
 
 concurrency:
-  group: ci-tests-e2e-backend-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-tests-e2e-backend-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   tests-e2e-backend:

.github/workflows/tests-ui-e2e.yml

@@ -12,8 +12,8 @@ on:
       - master
 
 concurrency:
-  group: ci-tests-ui-e2e-${{ github.head_ref || github.ref }}-${{ github.repository }}
-  cancel-in-progress: true
+  group: ci-tests-ui-e2e-${{ github.event.pull_request.number || github.sha }}-${{ github.repository }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 jobs:
   tests-ui-e2e:

.golangci.yml

@@ -46,8 +46,52 @@ linters:
           msg: 'LocalAI tests must use Ginkgo/Gomega; use Fail(...) instead of t.Fail. See .agents/coding-style.md.'
         - pattern: '^t\.FailNow$'
           msg: 'LocalAI tests must use Ginkgo/Gomega; use Fail(...) instead of t.FailNow. See .agents/coding-style.md.'
+        # In-process config should flow through ApplicationConfig / kong-bound
+        # CLI flags, not via os.Getenv. The CLI layer is the legitimate
+        # env→struct boundary (kong's `env:"..."` tag); anything deeper that
+        # reads env directly leaks process state into business logic and
+        # makes flags impossible to test or override per-request. Backend
+        # subprocesses, the system/capabilities probe, and a few places that
+        # read non-LocalAI env vars (HOME, PATH, AUTH_TOKEN passed by parent)
+        # are exempt — see linters.exclusions.rules below.
+        - pattern: '^os\.(Getenv|LookupEnv|Environ)$'
+          msg: 'Plumb config through ApplicationConfig (or the relevant CLI struct) instead of reading env directly. CLI entry points (core/cli/) bind env vars via kong''s `env:` tag — that is the only sanctioned env→struct boundary. See .agents/coding-style.md.'
   exclusions:
     paths:
       # Upstream whisper.cpp source tree fetched by the whisper backend Makefile.
       - 'backend/go/whisper/sources'
       - 'docs/'
+    rules:
+      # CLI entry points: kong's `env:"..."` tag is the legitimate env→struct
+      # boundary, and a handful of subcommands legitimately propagate values
+      # to spawned subprocesses (LLAMACPP_GRPC_SERVERS, MLX hostfile, ...).
+      - path: ^core/cli/
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]
+      # Backend subprocesses are independent binaries with their own env
+      # surface; they're not "in-process config" of the LocalAI server.
+      - path: ^backend/
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]
+      # System capability probe reads HOME, PATH-style vars to discover
+      # GPUs, default paths, etc. — not LocalAI config.
+      - path: ^pkg/system/
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]
+      # gRPC server reads AUTH_TOKEN passed in by the parent process at spawn
+      # time; model.Loader sets/inherits env to communicate with subprocesses.
+      - path: ^pkg/grpc/
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]
+      - path: ^pkg/model/
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]
+      # Top-level main binaries (local-ai, launcher) are entry points.
+      - path: ^cmd/
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]
+      # Tests legitimately read $HOME, $TMPDIR, and gating env vars
+      # (LOCALAI_COSIGN_LIVE, etc.) to skip live-network specs.
+      - path: _test\.go$
+        text: 'os\.(Getenv|LookupEnv|Environ)'
+        linters: [forbidigo]

AGENTS.md

@@ -19,16 +19,19 @@ LocalAI follows the Linux kernel project's [guidelines for AI coding assistants]
 |------|-------------|
 | [.agents/ai-coding-assistants.md](.agents/ai-coding-assistants.md) | Policy for AI-assisted contributions — licensing, DCO, attribution |
 | [.agents/building-and-testing.md](.agents/building-and-testing.md) | Building the project, running tests, Docker builds for specific platforms |
-| [.agents/ci-caching.md](.agents/ci-caching.md) | CI build cache layout (registry-backed BuildKit cache on quay.io/go-skynet/ci-cache), `DEPS_REFRESH` weekly cache-buster for unpinned Python deps, manual eviction |
+| [.agents/ci-caching.md](.agents/ci-caching.md) | CI build cache layout (registry-backed BuildKit cache on quay.io/go-skynet/ci-cache, per-arch keys), `DEPS_REFRESH` weekly cache-buster for unpinned Python deps, prebuilt `base-grpc-*` images for llama.cpp variants, per-arch native + manifest-merge pattern, `setup-build-disk` `/mnt` relocation, path filter on master push, manual eviction |
 | [.agents/adding-backends.md](.agents/adding-backends.md) | Adding a new backend (Python, Go, or C++) — full step-by-step checklist, including importer integration (the `/import-model` dropdown is server-driven from `GET /backends/known`) |
 | [.agents/coding-style.md](.agents/coding-style.md) | Code style, editorconfig, logging, documentation conventions |
 | [.agents/llama-cpp-backend.md](.agents/llama-cpp-backend.md) | Working on the llama.cpp backend — architecture, updating, tool call parsing |
 | [.agents/vllm-backend.md](.agents/vllm-backend.md) | Working on the vLLM / vLLM-omni backends — native parsers, ChatDelta, CPU build, libnuma packaging, backend hooks |
+| [.agents/sglang-backend.md](.agents/sglang-backend.md) | Working on the SGLang backend — `engine_args` validation against ServerArgs, speculative-decoding (EAGLE/EAGLE3/DFLASH/MTP) recipes, parser handling |
+| [.agents/ds4-backend.md](.agents/ds4-backend.md) | Working on the ds4 backend - DSML state machine, thinking modes, KV cache, Metal+CUDA matrix |
 | [.agents/testing-mcp-apps.md](.agents/testing-mcp-apps.md) | Testing MCP Apps (interactive tool UIs) in the React UI |
 | [.agents/api-endpoints-and-auth.md](.agents/api-endpoints-and-auth.md) | Adding API endpoints, auth middleware, feature permissions, user access control |
 | [.agents/debugging-backends.md](.agents/debugging-backends.md) | Debugging runtime backend failures, dependency conflicts, rebuilding backends |
 | [.agents/adding-gallery-models.md](.agents/adding-gallery-models.md) | Adding GGUF models from HuggingFace to the model gallery |
 | [.agents/localai-assistant-mcp.md](.agents/localai-assistant-mcp.md) | LocalAI Assistant chat modality — adding admin tools to the in-process MCP server, editing skill prompts, keeping REST + MCP + skills in sync |
+| [.agents/backend-signing.md](.agents/backend-signing.md) | Backend OCI image signing (keyless cosign + sigstore-go) — producer-side CI setup, consumer-side gallery `verification:` block, strict mode (`LOCALAI_REQUIRE_BACKEND_INTEGRITY`), revocation via `not_before` |
 
 ## Quick Reference
 

Dockerfile

@@ -305,7 +305,7 @@ EOT
 ###################################
 
 # Build React UI
-FROM node:25-slim AS react-ui-builder
+FROM node:26-slim AS react-ui-builder
 WORKDIR /app
 COPY core/http/react-ui/package*.json ./
 RUN npm install

Makefile

@@ -1,5 +1,5 @@
 # Disable parallel execution for backend builds
-.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/turboquant backends/outetts backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/insightface backends/speaker-recognition backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/mlx-distributed backends/stablediffusion-ggml-darwin backends/vllm backends/vllm-omni backends/sglang backends/moonshine backends/pocket-tts backends/qwen-tts backends/faster-qwen3-tts backends/qwen-asr backends/nemo backends/voxcpm backends/whisperx backends/ace-step backends/acestep-cpp backends/fish-speech backends/voxtral backends/opus backends/trl backends/llama-cpp-quantization backends/kokoros backends/sam3-cpp backends/qwen3-tts-cpp backends/vibevoice-cpp backends/localvqe backends/tinygrad backends/sherpa-onnx
+.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/turboquant backends/outetts backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/insightface backends/speaker-recognition backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/mlx-distributed backends/stablediffusion-ggml-darwin backends/vllm backends/vllm-omni backends/sglang backends/moonshine backends/pocket-tts backends/qwen-tts backends/faster-qwen3-tts backends/qwen-asr backends/nemo backends/voxcpm backends/whisperx backends/ace-step backends/acestep-cpp backends/fish-speech backends/voxtral backends/opus backends/trl backends/llama-cpp-quantization backends/kokoros backends/sam3-cpp backends/qwen3-tts-cpp backends/vibevoice-cpp backends/localvqe backends/tinygrad backends/sherpa-onnx backends/ds4 backends/ds4-darwin backends/liquid-audio
 
 GOCMD=go
 GOTEST=$(GOCMD) test
@@ -463,6 +463,7 @@ prepare-test-extra: protogen-python
 	$(MAKE) -C backend/python/vllm-omni
 	$(MAKE) -C backend/python/sglang
 	$(MAKE) -C backend/python/vibevoice
+	$(MAKE) -C backend/python/liquid-audio
 	$(MAKE) -C backend/python/moonshine
 	$(MAKE) -C backend/python/pocket-tts
 	$(MAKE) -C backend/python/qwen-tts
@@ -488,6 +489,7 @@ test-extra: prepare-test-extra
 	$(MAKE) -C backend/python/vllm test
 	$(MAKE) -C backend/python/vllm-omni test
 	$(MAKE) -C backend/python/vibevoice test
+	$(MAKE) -C backend/python/liquid-audio test
 	$(MAKE) -C backend/python/moonshine test
 	$(MAKE) -C backend/python/pocket-tts test
 	$(MAKE) -C backend/python/qwen-tts test
@@ -594,6 +596,7 @@ test-extra-backend-llama-cpp-transcription: docker-build-llama-cpp
 	BACKEND_TEST_MMPROJ_URL=https://huggingface.co/ggml-org/Qwen3-ASR-0.6B-GGUF/resolve/main/mmproj-Qwen3-ASR-0.6B-Q8_0.gguf \
 	BACKEND_TEST_AUDIO_URL=https://github.com/ggml-org/whisper.cpp/raw/master/samples/jfk.wav \
 	BACKEND_TEST_CAPS=health,load,transcription \
+	BACKEND_TEST_CTX_SIZE=2048 \
 	$(MAKE) test-extra-backend
 
 ## vllm is resolved from a HuggingFace model id (no file download) and
@@ -896,6 +899,18 @@ test-extra-backend-vibevoice-cpp-transcription: docker-build-vibevoice-cpp
 	BACKEND_TEST_CAPS=health,load,transcription \
 	$(MAKE) test-extra-backend
 
+## Audio transcription wrapper for the whisper.cpp backend.
+## Drives the AudioTranscription / AudioTranscriptionStream RPCs against
+## ggml-base.en (~145 MB) using the JFK 11s clip. The streaming spec
+## asserts len(deltas) >= 1 and concat(deltas) == final.Text - whisper-
+## specific multi-segment assertions live in backend/go/whisper/gowhisper_test.go.
+test-extra-backend-whisper-transcription: docker-build-whisper
+	BACKEND_IMAGE=local-ai-backend:whisper \
+	BACKEND_TEST_MODEL_URL=https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin \
+	BACKEND_TEST_AUDIO_URL=https://github.com/ggml-org/whisper.cpp/raw/master/samples/jfk.wav \
+	BACKEND_TEST_CAPS=health,load,transcription \
+	$(MAKE) test-extra-backend
+
 ## LocalVQE audio transform (joint AEC + noise suppression + dereverb).
 ## Exercises the audio_transform capability end-to-end: batch transform
 ## of a real WAV fixture and bidi streaming of synthetic silent frames.
@@ -996,6 +1011,10 @@ backends/llama-cpp-darwin: build
 	bash ./scripts/build/llama-cpp-darwin.sh
 	./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
 
+backends/ds4-darwin: build
+	bash ./scripts/build/ds4-darwin.sh
+	./local-ai backends install "ocifile://$(abspath ./backend-images/ds4.tar)"
+
 build-darwin-python-backend: build
 	bash ./scripts/build/python-darwin.sh
 
@@ -1037,6 +1056,10 @@ BACKEND_IK_LLAMA_CPP = ik-llama-cpp|ik-llama-cpp|.|false|false
 # turboquant is a llama.cpp fork with TurboQuant KV-cache quantization.
 # Reuses backend/cpp/llama-cpp grpc-server sources via a thin wrapper Makefile.
 BACKEND_TURBOQUANT = turboquant|turboquant|.|false|false
+# ds4 is antirez/ds4, a DeepSeek V4 Flash-specific inference engine.
+# Single-model; hardware-only validation lives at tests/e2e-backends/
+# (BACKEND_BINARY mode); see docs/superpowers/plans/2026-05-11-ds4-backend.md.
+BACKEND_DS4 = ds4|ds4|.|false|false
 
 # Golang backends
 BACKEND_PIPER = piper|golang|.|false|true
@@ -1071,6 +1094,7 @@ BACKEND_SGLANG = sglang|python|.|false|true
 BACKEND_DIFFUSERS = diffusers|python|.|--progress=plain|true
 BACKEND_CHATTERBOX = chatterbox|python|.|false|true
 BACKEND_VIBEVOICE = vibevoice|python|.|--progress=plain|true
+BACKEND_LIQUID_AUDIO = liquid-audio|python|.|--progress=plain|true
 BACKEND_MOONSHINE = moonshine|python|.|false|true
 BACKEND_POCKET_TTS = pocket-tts|python|.|false|true
 BACKEND_QWEN_TTS = qwen-tts|python|.|false|true
@@ -1122,6 +1146,7 @@ endef
 $(eval $(call generate-docker-build-target,$(BACKEND_LLAMA_CPP)))
 $(eval $(call generate-docker-build-target,$(BACKEND_IK_LLAMA_CPP)))
 $(eval $(call generate-docker-build-target,$(BACKEND_TURBOQUANT)))
+$(eval $(call generate-docker-build-target,$(BACKEND_DS4)))
 $(eval $(call generate-docker-build-target,$(BACKEND_PIPER)))
 $(eval $(call generate-docker-build-target,$(BACKEND_LOCAL_STORE)))
 $(eval $(call generate-docker-build-target,$(BACKEND_HUGGINGFACE)))
@@ -1147,6 +1172,7 @@ $(eval $(call generate-docker-build-target,$(BACKEND_SGLANG)))
 $(eval $(call generate-docker-build-target,$(BACKEND_DIFFUSERS)))
 $(eval $(call generate-docker-build-target,$(BACKEND_CHATTERBOX)))
 $(eval $(call generate-docker-build-target,$(BACKEND_VIBEVOICE)))
+$(eval $(call generate-docker-build-target,$(BACKEND_LIQUID_AUDIO)))
 $(eval $(call generate-docker-build-target,$(BACKEND_MOONSHINE)))
 $(eval $(call generate-docker-build-target,$(BACKEND_POCKET_TTS)))
 $(eval $(call generate-docker-build-target,$(BACKEND_QWEN_TTS)))
@@ -1175,7 +1201,7 @@ $(eval $(call generate-docker-build-target,$(BACKEND_SHERPA_ONNX)))
 docker-save-%: backend-images
 	docker save local-ai-backend:$* -o backend-images/$*.tar
 
-docker-build-backends: docker-build-llama-cpp docker-build-ik-llama-cpp docker-build-turboquant docker-build-rerankers docker-build-vllm docker-build-vllm-omni docker-build-sglang docker-build-transformers docker-build-outetts docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-chatterbox docker-build-vibevoice docker-build-moonshine docker-build-pocket-tts docker-build-qwen-tts docker-build-fish-speech docker-build-faster-qwen3-tts docker-build-qwen-asr docker-build-nemo docker-build-voxcpm docker-build-whisperx docker-build-ace-step docker-build-acestep-cpp docker-build-voxtral docker-build-mlx-distributed docker-build-trl docker-build-llama-cpp-quantization docker-build-tinygrad docker-build-kokoros docker-build-sam3-cpp docker-build-qwen3-tts-cpp docker-build-vibevoice-cpp docker-build-localvqe docker-build-insightface docker-build-speaker-recognition docker-build-sherpa-onnx
+docker-build-backends: docker-build-llama-cpp docker-build-ik-llama-cpp docker-build-turboquant docker-build-ds4 docker-build-rerankers docker-build-vllm docker-build-vllm-omni docker-build-sglang docker-build-transformers docker-build-outetts docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-chatterbox docker-build-vibevoice docker-build-liquid-audio docker-build-moonshine docker-build-pocket-tts docker-build-qwen-tts docker-build-fish-speech docker-build-faster-qwen3-tts docker-build-qwen-asr docker-build-nemo docker-build-voxcpm docker-build-whisperx docker-build-ace-step docker-build-acestep-cpp docker-build-voxtral docker-build-mlx-distributed docker-build-trl docker-build-llama-cpp-quantization docker-build-tinygrad docker-build-kokoros docker-build-sam3-cpp docker-build-qwen3-tts-cpp docker-build-vibevoice-cpp docker-build-localvqe docker-build-insightface docker-build-speaker-recognition docker-build-sherpa-onnx
 
 ########################################################
 ### Mock Backend for E2E Tests

backend/Dockerfile.base-grpc-builder

@@ -0,0 +1,98 @@
+# syntax=docker/dockerfile:1.7
+#
+# Pre-built builder base image for LocalAI's C++ backends.
+#
+# This Dockerfile is the source of truth for the
+# `quay.io/go-skynet/ci-cache:base-grpc-*` images that
+# `.github/workflows/base-images.yml` builds and pushes. The output of a
+# build is a fully-prepped builder layer containing:
+#
+#   - apt build deps (build-essential, ccache, git, make, pkg-config,
+#     libcurl4-openssl-dev, libssl-dev, curl, unzip, wget, ca-certificates)
+#   - cmake (apt or, when CMAKE_FROM_SOURCE=true, compiled from
+#     ${CMAKE_VERSION})
+#   - protoc v27.1 at /usr/local/bin/protoc
+#   - gRPC ${GRPC_VERSION} compiled and installed at /opt/grpc
+#   - Conditional CUDA toolkit (BUILD_TYPE=cublas|l4t, SKIP_DRIVERS=false)
+#     including the cuda-13 + arm64 cudss/nvpl special case
+#   - Conditional ROCm/HIP build deps (BUILD_TYPE=hipblas)
+#   - Conditional Vulkan SDK 1.4.335.0 (BUILD_TYPE=vulkan)
+#
+# Variants built by the workflow (matrix in base-images.yml):
+#
+#   base-grpc-amd64                 ubuntu:24.04, CPU-only
+#   base-grpc-arm64                 ubuntu:24.04, CPU-only
+#   base-grpc-cuda-12-amd64         ubuntu:24.04 + CUDA 12.8
+#   base-grpc-cuda-13-amd64         ubuntu:22.04 + CUDA 13.0
+#   base-grpc-cuda-13-arm64         ubuntu:24.04 + CUDA 13.0 (sbsa)
+#   base-grpc-l4t-cuda-12-arm64     ubuntu:22.04 + CUDA 12.x (legacy JetPack)
+#   base-grpc-rocm-amd64            rocm/dev-ubuntu-24.04:7.2.1 + hipblas
+#   base-grpc-vulkan-amd64          ubuntu:24.04 + Vulkan SDK 1.4.335
+#   base-grpc-vulkan-arm64          ubuntu:24.04 + Vulkan SDK ARM 1.4.335
+#   base-grpc-intel-amd64           intel/oneapi-basekit:2025.3.2 (sycl)
+#
+# This is a SINGLE-stage Dockerfile by design: the final image IS the
+# builder base. The intermediate gRPC compile happens inside this same
+# stage so consumer Dockerfiles in PR 2 can simply
+# `FROM quay.io/go-skynet/ci-cache:base-grpc-<variant>` without needing a
+# COPY --from=grpc step. /opt/grpc is the canonical install prefix and
+# downstream builds will add it to CMAKE_PREFIX_PATH (or copy to
+# /usr/local) the same way Dockerfile.llama-cpp does today.
+#
+# Install logic lives in .docker/install-base-deps.sh, which is also
+# bind-mounted by the variant Dockerfiles' builder-fromsource stage.
+# This guarantees bit-equivalence between the prebuilt CI base and the
+# from-source local-dev path — both invoke the same script with the
+# same env inputs.
+
+ARG BASE_IMAGE=ubuntu:24.04
+
+FROM ${BASE_IMAGE}
+
+ARG BASE_IMAGE=ubuntu:24.04
+ARG BUILD_TYPE=""
+ARG CUDA_MAJOR_VERSION=""
+ARG CUDA_MINOR_VERSION=""
+ARG CMAKE_FROM_SOURCE=false
+# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain
+# detection / arch table issues.
+ARG CMAKE_VERSION=3.31.10
+ARG GRPC_VERSION=v1.65.0
+ARG GRPC_MAKEFLAGS="-j4 -Otarget"
+ARG SKIP_DRIVERS=false
+ARG TARGETARCH
+ARG UBUNTU_VERSION=2404
+ARG APT_MIRROR=""
+ARG APT_PORTS_MIRROR=""
+ARG AMDGPU_TARGETS=""
+
+ENV BUILD_TYPE=${BUILD_TYPE} \
+    CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} \
+    CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION} \
+    CMAKE_FROM_SOURCE=${CMAKE_FROM_SOURCE} \
+    CMAKE_VERSION=${CMAKE_VERSION} \
+    GRPC_VERSION=${GRPC_VERSION} \
+    GRPC_MAKEFLAGS=${GRPC_MAKEFLAGS} \
+    SKIP_DRIVERS=${SKIP_DRIVERS} \
+    TARGETARCH=${TARGETARCH} \
+    UBUNTU_VERSION=${UBUNTU_VERSION} \
+    APT_MIRROR=${APT_MIRROR} \
+    APT_PORTS_MIRROR=${APT_PORTS_MIRROR} \
+    AMDGPU_TARGETS=${AMDGPU_TARGETS} \
+    MAKEFLAGS=${GRPC_MAKEFLAGS} \
+    DEBIAN_FRONTEND=noninteractive
+
+# CUDA on PATH (no-op when CUDA isn't installed)
+ENV PATH=/usr/local/cuda/bin:${PATH}
+# HipBLAS / ROCm on PATH (no-op when ROCm isn't installed)
+ENV PATH=/opt/rocm/bin:${PATH}
+
+WORKDIR /build
+
+# Single RUN that delegates to .docker/install-base-deps.sh — the same
+# script the variant Dockerfiles' builder-fromsource stage runs.
+RUN --mount=type=bind,source=.docker/install-base-deps.sh,target=/usr/local/sbin/install-base-deps \
+    --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
+    bash /usr/local/sbin/install-base-deps
+
+WORKDIR /

backend/Dockerfile.ds4

@@ -0,0 +1,41 @@
+ARG BASE_IMAGE=ubuntu:24.04
+ARG APT_MIRROR=""
+ARG APT_PORTS_MIRROR=""
+
+# BASE_IMAGE is either ubuntu:24.04 (for cpu builds) or nvidia/cuda:13.0.0-devel-ubuntu24.04
+# (for cublas builds). Both ship apt + Ubuntu Noble packages; the nvidia/cuda base
+# additionally provides /usr/local/cuda. Darwin (Metal) builds bypass this Dockerfile
+# entirely via scripts/build/ds4-darwin.sh.
+FROM ${BASE_IMAGE} AS builder
+ARG BUILD_TYPE
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+ENV BUILD_TYPE=${BUILD_TYPE} \
+    DEBIAN_FRONTEND=noninteractive \
+    PATH=/usr/local/cuda/bin:${PATH}
+
+WORKDIR /build
+
+# Install build-time deps via plain apt - install-base-deps.sh's full pipeline
+# (CUDA keyring + from-source gRPC) is unnecessary here:
+#   - CUDA: when BASE_IMAGE=nvidia/cuda:*, /usr/local/cuda is already populated;
+#     for the cpu build we don't need CUDA at all.
+#   - gRPC/Protobuf: system apt packages are sufficient; ds4's wrapper only links
+#     against them, it doesn't ship the gRPC source tree.
+#   - nlohmann-json: dsml_renderer's only third-party dep.
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        git cmake build-essential pkg-config ca-certificates \
+        libgrpc++-dev libprotobuf-dev protobuf-compiler protobuf-compiler-grpc \
+        nlohmann-json3-dev && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+COPY . /LocalAI
+
+RUN --mount=type=cache,target=/root/.ccache,id=ds4-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    make -C /LocalAI/backend/cpp/ds4 BUILD_TYPE=${BUILD_TYPE} NATIVE=false grpc-server package
+
+FROM scratch
+COPY --from=builder /LocalAI/backend/cpp/ds4/package/. ./

backend/Dockerfile.ik-llama-cpp

@@ -1,290 +1,149 @@
 ARG BASE_IMAGE=ubuntu:24.04
-ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
+# BUILDER_BASE_IMAGE defaults to BASE_IMAGE so the Dockerfile parses even
+# when no prebuilt base is supplied. The builder-prebuilt stage is only
+# entered when BUILDER_TARGET=builder-prebuilt, so a "wrong" fallback
+# content here is harmless — BuildKit prunes the unreferenced builder.
+ARG BUILDER_BASE_IMAGE=${BASE_IMAGE}
+# BUILDER_TARGET selects which builder stage the final scratch image copies
+# package output from. Declared at global scope (before any FROM) so it's
+# usable in `FROM ${BUILDER_TARGET}` below. Default keeps local
+# `make backends/ik-llama-cpp` on the from-source path.
+ARG BUILDER_TARGET=builder-fromsource
 ARG APT_MIRROR=""
 ARG APT_PORTS_MIRROR=""
 
 
-# The grpc target does one thing, it builds and installs GRPC.  This is in it's own layer so that it can be effectively cached by CI.
-# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
-FROM ${GRPC_BASE_IMAGE} AS grpc
-
-# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
-ARG GRPC_MAKEFLAGS="-j4 -Otarget"
-ARG GRPC_VERSION=v1.65.0
+# ============================================================================
+# Stage: builder-fromsource — self-contained build path.
+# Runs .docker/install-base-deps.sh (apt deps + cmake + protoc + gRPC +
+# conditional CUDA/ROCm/Vulkan), copies /opt/grpc to /usr/local, then
+# compiles the variant. Used when BUILDER_TARGET=builder-fromsource (the
+# default; local `make backends/ik-llama-cpp`).
+#
+# The install script is the same one that backend/Dockerfile.base-grpc-builder
+# runs, so the result is bit-equivalent to the prebuilt-base path
+# (builder-prebuilt below).
+# ============================================================================
+FROM ${BASE_IMAGE} AS builder-fromsource
+ARG BUILD_TYPE
+ARG CUDA_MAJOR_VERSION
+ARG CUDA_MINOR_VERSION
 ARG CMAKE_FROM_SOURCE=false
 # CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
 ARG CMAKE_VERSION=3.31.10
-ARG APT_MIRROR
-ARG APT_PORTS_MIRROR
-
-ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
-
-WORKDIR /build
-
-RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
-    APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends \
-        ca-certificates \
-        build-essential curl libssl-dev \
-        git wget && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
-
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
-# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
-# and running make install in the target container
-RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-    mkdir -p /build/grpc/cmake/build && \
-    cd /build/grpc/cmake/build && \
-    sed -i "216i\  TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
-    cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
-    make && \
-    make install && \
-    rm -rf /build
-
-FROM ${BASE_IMAGE} AS builder
-ARG CMAKE_FROM_SOURCE=false
-ARG CMAKE_VERSION=3.31.10
-# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
-ARG CUDA_DOCKER_ARCH
-ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
-ARG CMAKE_ARGS
-ENV CMAKE_ARGS=${CMAKE_ARGS}
-ARG BACKEND=rerankers
-ARG BUILD_TYPE
-ENV BUILD_TYPE=${BUILD_TYPE}
-ARG CUDA_MAJOR_VERSION
-ARG CUDA_MINOR_VERSION
+ARG GRPC_VERSION=v1.65.0
+ARG GRPC_MAKEFLAGS="-j4 -Otarget"
 ARG SKIP_DRIVERS=false
-ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
-ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
-ENV DEBIAN_FRONTEND=noninteractive
 ARG TARGETARCH
 ARG TARGETVARIANT
 ARG GO_VERSION=1.25.4
 ARG UBUNTU_VERSION=2404
 ARG APT_MIRROR
 ARG APT_PORTS_MIRROR
+ARG AMDGPU_TARGETS=""
+ARG BACKEND=rerankers
+# CUDA target archs, e.g. --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
+ARG CUDA_DOCKER_ARCH
+ARG CMAKE_ARGS
 
-RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
-    APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends \
-        build-essential \
-        ccache git \
-        ca-certificates \
-        make \
-        pkg-config libcurl4-openssl-dev \
-        curl unzip \
-        libssl-dev wget && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
+ENV BUILD_TYPE=${BUILD_TYPE} \
+    CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} \
+    CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION} \
+    CMAKE_FROM_SOURCE=${CMAKE_FROM_SOURCE} \
+    CMAKE_VERSION=${CMAKE_VERSION} \
+    GRPC_VERSION=${GRPC_VERSION} \
+    GRPC_MAKEFLAGS=${GRPC_MAKEFLAGS} \
+    SKIP_DRIVERS=${SKIP_DRIVERS} \
+    TARGETARCH=${TARGETARCH} \
+    UBUNTU_VERSION=${UBUNTU_VERSION} \
+    APT_MIRROR=${APT_MIRROR} \
+    APT_PORTS_MIRROR=${APT_PORTS_MIRROR} \
+    AMDGPU_TARGETS=${AMDGPU_TARGETS} \
+    CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} \
+    CMAKE_ARGS=${CMAKE_ARGS} \
+    DEBIAN_FRONTEND=noninteractive
 
-# Cuda
+# CUDA on PATH (no-op when CUDA isn't installed)
 ENV PATH=/usr/local/cuda/bin:${PATH}
-
-# HipBLAS requirements
+# HipBLAS / ROCm on PATH (no-op when ROCm isn't installed)
 ENV PATH=/opt/rocm/bin:${PATH}
 
+WORKDIR /build
 
-# Vulkan requirements
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y  --no-install-recommends \
-            software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# CuBLAS requirements
-RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y  --no-install-recommends \
-            software-properties-common pciutils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
-        fi
-        dpkg -i cuda-keyring_1.1-1_all.deb && \
-        rm -f cuda-keyring_1.1-1_all.deb && \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
-    fi
-EOT
-
-# If we are building with clblas support, we need the libraries for the builds
-RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            libclblast-dev && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* \
-    ; fi
-
-RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            hipblas-dev \
-            hipblaslt-dev \
-            rocblas-dev && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* && \
-        # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
-        # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
-        ldconfig \
-    ; fi
-
-RUN echo "TARGETARCH: $TARGETARCH"
-
-# We need protoc installed, and the version in 22.04 is too old.  We will create one as part installing the GRPC build below
-# but that will also being in a newer version of absl which stablediffusion cannot compile with.  This version of protoc is only
-# here so that we can generate the grpc code for the stablediffusion build
-RUN <<EOT bash
-    if [ "amd64" = "$TARGETARCH" ]; then
-        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
-        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-        rm protoc.zip
-    fi
-    if [ "arm64" = "$TARGETARCH" ]; then
-        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
-        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-        rm protoc.zip
-    fi
-EOT
-
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-COPY --from=grpc /opt/grpc /usr/local
+# Install everything via the shared script — the same one that
+# backend/Dockerfile.base-grpc-builder runs, so the prebuilt CI base and
+# this from-source path are bit-equivalent.
+RUN --mount=type=bind,source=.docker/install-base-deps.sh,target=/usr/local/sbin/install-base-deps \
+    --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
+    bash /usr/local/sbin/install-base-deps
 
+# Mirror builder-prebuilt: copy gRPC from /opt/grpc to /usr/local so
+# CMake's find_package finds it at the canonical prefix the Makefile expects.
+RUN cp -a /opt/grpc/. /usr/local/
 
 COPY . /LocalAI
 
-RUN <<'EOT' bash
-set -euxo pipefail
-
-if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
-  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
-  export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
-  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
-  rm -rf /LocalAI/backend/cpp/ik-llama-cpp-*-build
-fi
-
-cd /LocalAI/backend/cpp/ik-llama-cpp
-
-if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
-  # ARM64 / ROCm: build without x86 SIMD
-  make ik-llama-cpp-fallback
-else
-  # ik_llama.cpp's IQK kernels require at least AVX2
-  make ik-llama-cpp-avx2
-fi
-EOT
+# BuildKit cache mount for ccache. See Dockerfile.llama-cpp (commit 9228e5b4)
+# for the rationale. Distinct mount id so ik-llama-cpp's cache doesn't
+# overlap with llama-cpp's — ik_llama.cpp is a different fork with
+# different source.
+#
+# The compile body is shared with builder-prebuilt via .docker/ik-llama-cpp-compile.sh.
+RUN --mount=type=bind,source=.docker/ik-llama-cpp-compile.sh,target=/usr/local/sbin/compile.sh \
+    --mount=type=cache,target=/root/.ccache,id=ik-llama-cpp-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
 
 
 # Copy libraries using a script to handle architecture differences
 RUN make -BC /LocalAI/backend/cpp/ik-llama-cpp package
 
 
+# ============================================================================
+# Stage: builder-prebuilt — uses the pre-built base from
+# quay.io/go-skynet/ci-cache:base-grpc-* (built by .github/workflows/base-images.yml).
+# That image already has gRPC at /opt/grpc + apt deps + CUDA/ROCm/Vulkan
+# pre-installed, so we just copy gRPC to /usr/local and compile. Used when
+# BUILDER_TARGET=builder-prebuilt (CI when the matrix entry sets
+# builder-base-image).
+# ============================================================================
+FROM ${BUILDER_BASE_IMAGE} AS builder-prebuilt
+
+ARG BUILD_TYPE
+ENV BUILD_TYPE=${BUILD_TYPE}
+ARG CUDA_DOCKER_ARCH
+ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
+ARG CMAKE_ARGS
+ENV CMAKE_ARGS=${CMAKE_ARGS}
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+# The base-grpc-* image installs gRPC to /opt/grpc but doesn't copy it to
+# /usr/local. Mirror what the from-source path does so the compile step
+# can find gRPC at the canonical prefix the Makefile expects.
+RUN cp -a /opt/grpc/. /usr/local/
+
+COPY . /LocalAI
+
+RUN --mount=type=bind,source=.docker/ik-llama-cpp-compile.sh,target=/usr/local/sbin/compile.sh \
+    --mount=type=cache,target=/root/.ccache,id=ik-llama-cpp-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
+
+RUN make -BC /LocalAI/backend/cpp/ik-llama-cpp package
+
+
+# ============================================================================
+# Final stage — copies package output from one of the two builders.
+# BUILDER_TARGET selects which one. BuildKit prunes the unreferenced builder.
+#
+# BuildKit doesn't support variable expansion in `COPY --from=` directly,
+# so we resolve the ARG by aliasing the chosen builder to a fixed stage
+# name via `FROM ${BUILDER_TARGET} AS builder` and then COPY --from=builder.
+# BUILDER_TARGET itself is declared as a global ARG at the top of this
+# file (required for use in FROM), so we just re-import it into this
+# stage's scope before the FROM directive.
+# ============================================================================
+FROM ${BUILDER_TARGET} AS builder
+
 FROM scratch
 
 

backend/Dockerfile.llama-cpp

@@ -1,301 +1,155 @@
 ARG BASE_IMAGE=ubuntu:24.04
-ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
+# BUILDER_BASE_IMAGE defaults to BASE_IMAGE so the Dockerfile parses even
+# when no prebuilt base is supplied. The builder-prebuilt stage is only
+# entered when BUILDER_TARGET=builder-prebuilt, so a "wrong" fallback
+# content here is harmless — BuildKit prunes the unreferenced builder.
+ARG BUILDER_BASE_IMAGE=${BASE_IMAGE}
+# BUILDER_TARGET selects which builder stage the final scratch image copies
+# package output from. Declared at global scope (before any FROM) so it's
+# usable in `FROM ${BUILDER_TARGET}` below. Default keeps local
+# `make backends/llama-cpp` on the from-source path.
+ARG BUILDER_TARGET=builder-fromsource
 ARG APT_MIRROR=""
 ARG APT_PORTS_MIRROR=""
 
 
-# The grpc target does one thing, it builds and installs GRPC.  This is in it's own layer so that it can be effectively cached by CI.
-# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
-FROM ${GRPC_BASE_IMAGE} AS grpc
-
-# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
-ARG GRPC_MAKEFLAGS="-j4 -Otarget"
-ARG GRPC_VERSION=v1.65.0
+# ============================================================================
+# Stage: builder-fromsource — self-contained build path.
+# Runs .docker/install-base-deps.sh (apt deps + cmake + protoc + gRPC +
+# conditional CUDA/ROCm/Vulkan), copies /opt/grpc to /usr/local, then
+# compiles the variant. Used when BUILDER_TARGET=builder-fromsource (the
+# default; local `make backends/llama-cpp`).
+#
+# The install script is the same one that backend/Dockerfile.base-grpc-builder
+# runs, so the result is bit-equivalent to the prebuilt-base path
+# (builder-prebuilt below).
+# ============================================================================
+FROM ${BASE_IMAGE} AS builder-fromsource
+ARG BUILD_TYPE
+ARG CUDA_MAJOR_VERSION
+ARG CUDA_MINOR_VERSION
 ARG CMAKE_FROM_SOURCE=false
 # CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
 ARG CMAKE_VERSION=3.31.10
-ARG APT_MIRROR
-ARG APT_PORTS_MIRROR
-
-ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
-
-WORKDIR /build
-
-RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
-    APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends \
-        ca-certificates \
-        build-essential curl libssl-dev \
-        git wget && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
-
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
-# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
-# and running make install in the target container
-RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-    mkdir -p /build/grpc/cmake/build && \
-    cd /build/grpc/cmake/build && \
-    sed -i "216i\  TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
-    cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
-    make && \
-    make install && \
-    rm -rf /build
-
-FROM ${BASE_IMAGE} AS builder
-ARG CMAKE_FROM_SOURCE=false
-ARG CMAKE_VERSION=3.31.10
-# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
-ARG CUDA_DOCKER_ARCH
-ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
-ARG CMAKE_ARGS
-ENV CMAKE_ARGS=${CMAKE_ARGS}
-ARG AMDGPU_TARGETS
-ENV AMDGPU_TARGETS=${AMDGPU_TARGETS}
-ARG BACKEND=rerankers
-ARG BUILD_TYPE
-ENV BUILD_TYPE=${BUILD_TYPE}
-ARG CUDA_MAJOR_VERSION
-ARG CUDA_MINOR_VERSION
+ARG GRPC_VERSION=v1.65.0
+ARG GRPC_MAKEFLAGS="-j4 -Otarget"
 ARG SKIP_DRIVERS=false
-ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
-ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
-ENV DEBIAN_FRONTEND=noninteractive
 ARG TARGETARCH
 ARG TARGETVARIANT
 ARG GO_VERSION=1.25.4
 ARG UBUNTU_VERSION=2404
 ARG APT_MIRROR
 ARG APT_PORTS_MIRROR
+ARG AMDGPU_TARGETS
+# CUDA target archs, e.g. --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
+ARG CUDA_DOCKER_ARCH
+ARG CMAKE_ARGS
 
-RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
-    APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends \
-        build-essential \
-        ccache git \
-        ca-certificates \
-        make \
-        pkg-config libcurl4-openssl-dev \
-        curl unzip \
-        libssl-dev wget && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
+ENV BUILD_TYPE=${BUILD_TYPE} \
+    CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} \
+    CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION} \
+    CMAKE_FROM_SOURCE=${CMAKE_FROM_SOURCE} \
+    CMAKE_VERSION=${CMAKE_VERSION} \
+    GRPC_VERSION=${GRPC_VERSION} \
+    GRPC_MAKEFLAGS=${GRPC_MAKEFLAGS} \
+    SKIP_DRIVERS=${SKIP_DRIVERS} \
+    TARGETARCH=${TARGETARCH} \
+    UBUNTU_VERSION=${UBUNTU_VERSION} \
+    APT_MIRROR=${APT_MIRROR} \
+    APT_PORTS_MIRROR=${APT_PORTS_MIRROR} \
+    AMDGPU_TARGETS=${AMDGPU_TARGETS} \
+    CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} \
+    CMAKE_ARGS=${CMAKE_ARGS} \
+    DEBIAN_FRONTEND=noninteractive
 
-# Cuda
+# CUDA on PATH (no-op when CUDA isn't installed)
 ENV PATH=/usr/local/cuda/bin:${PATH}
-
-# HipBLAS requirements
+# HipBLAS / ROCm on PATH (no-op when ROCm isn't installed)
 ENV PATH=/opt/rocm/bin:${PATH}
 
+WORKDIR /build
 
-# Vulkan requirements
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y  --no-install-recommends \
-            software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# CuBLAS requirements
-RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y  --no-install-recommends \
-            software-properties-common pciutils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
-        fi
-        dpkg -i cuda-keyring_1.1-1_all.deb && \
-        rm -f cuda-keyring_1.1-1_all.deb && \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
-    fi
-EOT
-
-# If we are building with clblas support, we need the libraries for the builds
-RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            libclblast-dev && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* \
-    ; fi
-
-RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            hipblas-dev \
-            hipblaslt-dev \
-            rocblas-dev && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* && \
-        # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
-        # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
-        ldconfig && \
-        # Log which GPU architectures have rocBLAS kernel support
-        echo "rocBLAS library data architectures:" && \
-        (ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
-        echo "WARNING: No rocBLAS kernel data found" \
-    ; fi
-
-RUN echo "TARGETARCH: $TARGETARCH"
-
-# We need protoc installed, and the version in 22.04 is too old.  We will create one as part installing the GRPC build below
-# but that will also being in a newer version of absl which stablediffusion cannot compile with.  This version of protoc is only
-# here so that we can generate the grpc code for the stablediffusion build
-RUN <<EOT bash
-    if [ "amd64" = "$TARGETARCH" ]; then
-        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
-        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-        rm protoc.zip
-    fi
-    if [ "arm64" = "$TARGETARCH" ]; then
-        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
-        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-        rm protoc.zip
-    fi
-EOT
-
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-COPY --from=grpc /opt/grpc /usr/local
+# Install everything via the shared script — the same one that
+# backend/Dockerfile.base-grpc-builder runs, so the prebuilt CI base and
+# this from-source path are bit-equivalent.
+RUN --mount=type=bind,source=.docker/install-base-deps.sh,target=/usr/local/sbin/install-base-deps \
+    --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
+    bash /usr/local/sbin/install-base-deps
 
+# Mirror builder-prebuilt: copy gRPC from /opt/grpc to /usr/local so
+# CMake's find_package finds it at the canonical prefix the Makefile expects.
+RUN cp -a /opt/grpc/. /usr/local/
 
 COPY . /LocalAI
 
-RUN <<'EOT' bash
-set -euxo pipefail
-
-if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
-  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
-  export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
-  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
-  rm -rf /LocalAI/backend/cpp/llama-cpp-*-build
-fi
-
-if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
-  cd /LocalAI/backend/cpp/llama-cpp
-  make llama-cpp-fallback
-  make llama-cpp-grpc
-  make llama-cpp-rpc-server
-else
-  cd /LocalAI/backend/cpp/llama-cpp
-  make llama-cpp-avx
-  make llama-cpp-avx2
-  make llama-cpp-avx512
-  make llama-cpp-fallback
-  make llama-cpp-grpc
-  make llama-cpp-rpc-server
-fi
-EOT
+# BuildKit cache mount for ccache. Persists compiler outputs across builds
+# via the registry cache (cache-to: type=registry,mode=max in CI). On a
+# LLAMA_VERSION bump most TUs are byte-identical to the previous version's
+# preprocessed source — ccache returns the previous .o file and skips the
+# real compile. Same for LocalAI source changes that don't touch llama.cpp.
+# CMAKE_*_COMPILER_LAUNCHER threads ccache through CMake to wrap gcc/g++/nvcc.
+# sharing=locked serializes concurrent writes if multiple matrix variants
+# share the same cache mount id.
+#
+# The compile body is shared with builder-prebuilt via .docker/llama-cpp-compile.sh.
+RUN --mount=type=bind,source=.docker/llama-cpp-compile.sh,target=/usr/local/sbin/compile.sh \
+    --mount=type=cache,target=/root/.ccache,id=llama-cpp-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
 
 
 # Copy libraries using a script to handle architecture differences
 RUN make -BC /LocalAI/backend/cpp/llama-cpp package
 
 
+# ============================================================================
+# Stage: builder-prebuilt — uses the pre-built base from
+# quay.io/go-skynet/ci-cache:base-grpc-* (built by .github/workflows/base-images.yml).
+# That image already has gRPC at /opt/grpc + apt deps + CUDA/ROCm/Vulkan
+# pre-installed, so we just copy gRPC to /usr/local and compile. Used when
+# BUILDER_TARGET=builder-prebuilt (CI when the matrix entry sets
+# builder-base-image).
+# ============================================================================
+FROM ${BUILDER_BASE_IMAGE} AS builder-prebuilt
+
+ARG BUILD_TYPE
+ENV BUILD_TYPE=${BUILD_TYPE}
+ARG CUDA_DOCKER_ARCH
+ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
+ARG CMAKE_ARGS
+ENV CMAKE_ARGS=${CMAKE_ARGS}
+ARG AMDGPU_TARGETS
+ENV AMDGPU_TARGETS=${AMDGPU_TARGETS}
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+# The base-grpc-* image installs gRPC to /opt/grpc but doesn't copy it to
+# /usr/local. The variant Dockerfile's from-source path does that too;
+# mirror it here so the compile step can find gRPC at the canonical
+# prefix the Makefile expects.
+RUN cp -a /opt/grpc/. /usr/local/
+
+COPY . /LocalAI
+
+RUN --mount=type=bind,source=.docker/llama-cpp-compile.sh,target=/usr/local/sbin/compile.sh \
+    --mount=type=cache,target=/root/.ccache,id=llama-cpp-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
+
+RUN make -BC /LocalAI/backend/cpp/llama-cpp package
+
+
+# ============================================================================
+# Final stage — copies package output from one of the two builders.
+# BUILDER_TARGET selects which one. BuildKit prunes the unreferenced builder.
+#
+# BuildKit doesn't support variable expansion in `COPY --from=` directly,
+# so we resolve the ARG by aliasing the chosen builder to a fixed stage
+# name via `FROM ${BUILDER_TARGET} AS builder` and then COPY --from=builder.
+# BUILDER_TARGET itself is declared as a global ARG at the top of this
+# file (required for use in FROM), so we just re-import it into this
+# stage's scope before the FROM directive.
+# ============================================================================
+FROM ${BUILDER_TARGET} AS builder
+
 FROM scratch
 
 

backend/Dockerfile.turboquant

@@ -1,299 +1,158 @@
 ARG BASE_IMAGE=ubuntu:24.04
-ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
+# BUILDER_BASE_IMAGE defaults to BASE_IMAGE so the Dockerfile parses even
+# when no prebuilt base is supplied. The builder-prebuilt stage is only
+# entered when BUILDER_TARGET=builder-prebuilt, so a "wrong" fallback
+# content here is harmless — BuildKit prunes the unreferenced builder.
+ARG BUILDER_BASE_IMAGE=${BASE_IMAGE}
+# BUILDER_TARGET selects which builder stage the final scratch image copies
+# package output from. Declared at global scope (before any FROM) so it's
+# usable in `FROM ${BUILDER_TARGET}` below. Default keeps local
+# `make backends/turboquant` on the from-source path.
+ARG BUILDER_TARGET=builder-fromsource
 ARG APT_MIRROR=""
 ARG APT_PORTS_MIRROR=""
 
 
-# The grpc target does one thing, it builds and installs GRPC.  This is in it's own layer so that it can be effectively cached by CI.
-# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
-FROM ${GRPC_BASE_IMAGE} AS grpc
-
-# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
-ARG GRPC_MAKEFLAGS="-j4 -Otarget"
-ARG GRPC_VERSION=v1.65.0
+# ============================================================================
+# Stage: builder-fromsource — self-contained build path.
+# Runs .docker/install-base-deps.sh (apt deps + cmake + protoc + gRPC +
+# conditional CUDA/ROCm/Vulkan), copies /opt/grpc to /usr/local, then
+# compiles the variant. Used when BUILDER_TARGET=builder-fromsource (the
+# default; local `make backends/turboquant`).
+#
+# The install script is the same one that backend/Dockerfile.base-grpc-builder
+# runs, so the result is bit-equivalent to the prebuilt-base path
+# (builder-prebuilt below).
+# ============================================================================
+FROM ${BASE_IMAGE} AS builder-fromsource
+ARG BUILD_TYPE
+ARG CUDA_MAJOR_VERSION
+ARG CUDA_MINOR_VERSION
 ARG CMAKE_FROM_SOURCE=false
 # CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
 ARG CMAKE_VERSION=3.31.10
-ARG APT_MIRROR
-ARG APT_PORTS_MIRROR
-
-ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
-
-WORKDIR /build
-
-RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
-    APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends \
-        ca-certificates \
-        build-essential curl libssl-dev \
-        git wget && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
-
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
-# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
-# and running make install in the target container
-RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
-    mkdir -p /build/grpc/cmake/build && \
-    cd /build/grpc/cmake/build && \
-    sed -i "216i\  TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
-    cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
-    make && \
-    make install && \
-    rm -rf /build
-
-FROM ${BASE_IMAGE} AS builder
-ARG CMAKE_FROM_SOURCE=false
-ARG CMAKE_VERSION=3.31.10
-# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
-ARG CUDA_DOCKER_ARCH
-ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
-ARG CMAKE_ARGS
-ENV CMAKE_ARGS=${CMAKE_ARGS}
-ARG BACKEND=rerankers
-ARG BUILD_TYPE
-ENV BUILD_TYPE=${BUILD_TYPE}
-ARG CUDA_MAJOR_VERSION
-ARG CUDA_MINOR_VERSION
+ARG GRPC_VERSION=v1.65.0
+ARG GRPC_MAKEFLAGS="-j4 -Otarget"
 ARG SKIP_DRIVERS=false
-ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
-ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
-ENV DEBIAN_FRONTEND=noninteractive
 ARG TARGETARCH
 ARG TARGETVARIANT
 ARG GO_VERSION=1.25.4
 ARG UBUNTU_VERSION=2404
 ARG APT_MIRROR
 ARG APT_PORTS_MIRROR
+ARG AMDGPU_TARGETS=""
+ARG BACKEND=rerankers
+# CUDA target archs, e.g. --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
+ARG CUDA_DOCKER_ARCH
+ARG CMAKE_ARGS
 
-RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
-    APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
-    apt-get update && \
-    apt-get install -y --no-install-recommends \
-        build-essential \
-        ccache git \
-        ca-certificates \
-        make \
-        pkg-config libcurl4-openssl-dev \
-        curl unzip \
-        libssl-dev wget && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
+ENV BUILD_TYPE=${BUILD_TYPE} \
+    CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} \
+    CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION} \
+    CMAKE_FROM_SOURCE=${CMAKE_FROM_SOURCE} \
+    CMAKE_VERSION=${CMAKE_VERSION} \
+    GRPC_VERSION=${GRPC_VERSION} \
+    GRPC_MAKEFLAGS=${GRPC_MAKEFLAGS} \
+    SKIP_DRIVERS=${SKIP_DRIVERS} \
+    TARGETARCH=${TARGETARCH} \
+    UBUNTU_VERSION=${UBUNTU_VERSION} \
+    APT_MIRROR=${APT_MIRROR} \
+    APT_PORTS_MIRROR=${APT_PORTS_MIRROR} \
+    AMDGPU_TARGETS=${AMDGPU_TARGETS} \
+    CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} \
+    CMAKE_ARGS=${CMAKE_ARGS} \
+    DEBIAN_FRONTEND=noninteractive
 
-# Cuda
+# CUDA on PATH (no-op when CUDA isn't installed)
 ENV PATH=/usr/local/cuda/bin:${PATH}
-
-# HipBLAS requirements
+# HipBLAS / ROCm on PATH (no-op when ROCm isn't installed)
 ENV PATH=/opt/rocm/bin:${PATH}
 
+WORKDIR /build
 
-# Vulkan requirements
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y  --no-install-recommends \
-            software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-# CuBLAS requirements
-RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y  --no-install-recommends \
-            software-properties-common pciutils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
-        fi
-        dpkg -i cuda-keyring_1.1-1_all.deb && \
-        rm -f cuda-keyring_1.1-1_all.deb && \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
-    fi
-EOT
-
-# If we are building with clblas support, we need the libraries for the builds
-RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            libclblast-dev && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* \
-    ; fi
-
-RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            hipblas-dev \
-            hipblaslt-dev \
-            rocblas-dev && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/* && \
-        # I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
-        # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
-        ldconfig && \
-        # Log which GPU architectures have rocBLAS kernel support
-        echo "rocBLAS library data architectures:" && \
-        (ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
-        echo "WARNING: No rocBLAS kernel data found" \
-    ; fi
-
-RUN echo "TARGETARCH: $TARGETARCH"
-
-# We need protoc installed, and the version in 22.04 is too old.  We will create one as part installing the GRPC build below
-# but that will also being in a newer version of absl which stablediffusion cannot compile with.  This version of protoc is only
-# here so that we can generate the grpc code for the stablediffusion build
-RUN <<EOT bash
-    if [ "amd64" = "$TARGETARCH" ]; then
-        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
-        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-        rm protoc.zip
-    fi
-    if [ "arm64" = "$TARGETARCH" ]; then
-        curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
-        unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-        rm protoc.zip
-    fi
-EOT
-
-# Install CMake (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
-        curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
-    else
-        apt-get update && \
-        apt-get install -y \
-            cmake && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
-COPY --from=grpc /opt/grpc /usr/local
+# Install everything via the shared script — the same one that
+# backend/Dockerfile.base-grpc-builder runs, so the prebuilt CI base and
+# this from-source path are bit-equivalent.
+RUN --mount=type=bind,source=.docker/install-base-deps.sh,target=/usr/local/sbin/install-base-deps \
+    --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
+    bash /usr/local/sbin/install-base-deps
 
+# Mirror builder-prebuilt: copy gRPC from /opt/grpc to /usr/local so
+# CMake's find_package finds it at the canonical prefix the Makefile expects.
+RUN cp -a /opt/grpc/. /usr/local/
 
 COPY . /LocalAI
 
-RUN <<'EOT' bash
-set -euxo pipefail
-
-if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
-  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
-  export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
-  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
-  rm -rf /LocalAI/backend/cpp/turboquant-*-build
-fi
-
-cd /LocalAI/backend/cpp/turboquant
-
-if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
-  make turboquant-fallback
-  make turboquant-grpc
-  make turboquant-rpc-server
-else
-  make turboquant-avx
-  make turboquant-avx2
-  make turboquant-avx512
-  make turboquant-fallback
-  make turboquant-grpc
-  make turboquant-rpc-server
-fi
-EOT
+# BuildKit cache mount for ccache. See Dockerfile.llama-cpp (commit 9228e5b4)
+# for rationale. turboquant is a llama.cpp fork that reuses
+# backend/cpp/llama-cpp source via a thin wrapper Makefile, so MOST TUs
+# are content-identical to the upstream llama-cpp build. Sharing a cache
+# id with llama-cpp could give cross-fork hits — but for now keep them
+# separate so a regression in one doesn't poison the other. Revisit
+# sharing after measuring the actual hit rate.
+#
+# The compile body is shared with builder-prebuilt via .docker/turboquant-compile.sh.
+RUN --mount=type=bind,source=.docker/turboquant-compile.sh,target=/usr/local/sbin/compile.sh \
+    --mount=type=cache,target=/root/.ccache,id=turboquant-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
 
 
 # Copy libraries using a script to handle architecture differences
 RUN make -BC /LocalAI/backend/cpp/turboquant package
 
 
+# ============================================================================
+# Stage: builder-prebuilt — uses the pre-built base from
+# quay.io/go-skynet/ci-cache:base-grpc-* (built by .github/workflows/base-images.yml).
+# That image already has gRPC at /opt/grpc + apt deps + CUDA/ROCm/Vulkan
+# pre-installed, so we just copy gRPC to /usr/local and compile. Used when
+# BUILDER_TARGET=builder-prebuilt (CI when the matrix entry sets
+# builder-base-image).
+# ============================================================================
+FROM ${BUILDER_BASE_IMAGE} AS builder-prebuilt
+
+ARG BUILD_TYPE
+ENV BUILD_TYPE=${BUILD_TYPE}
+ARG CUDA_DOCKER_ARCH
+ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
+ARG CMAKE_ARGS
+ENV CMAKE_ARGS=${CMAKE_ARGS}
+# AMDGPU_TARGETS must be forwarded into the env here too — backend/cpp/llama-cpp/Makefile
+# (which the turboquant Makefile reuses via a sibling build dir) errors out when the var
+# is empty on a hipblas build, and the prebuilt path is what CI exercises most of the
+# time. The builder-fromsource stage above already does this; mirror it here.
+ARG AMDGPU_TARGETS
+ENV AMDGPU_TARGETS=${AMDGPU_TARGETS}
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+# The base-grpc-* image installs gRPC to /opt/grpc but doesn't copy it to
+# /usr/local. Mirror what the from-source path does so the compile step
+# can find gRPC at the canonical prefix the Makefile expects.
+RUN cp -a /opt/grpc/. /usr/local/
+
+COPY . /LocalAI
+
+RUN --mount=type=bind,source=.docker/turboquant-compile.sh,target=/usr/local/sbin/compile.sh \
+    --mount=type=cache,target=/root/.ccache,id=turboquant-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
+    bash /usr/local/sbin/compile.sh
+
+RUN make -BC /LocalAI/backend/cpp/turboquant package
+
+
+# ============================================================================
+# Final stage — copies package output from one of the two builders.
+# BUILDER_TARGET selects which one. BuildKit prunes the unreferenced builder.
+#
+# BuildKit doesn't support variable expansion in `COPY --from=` directly,
+# so we resolve the ARG by aliasing the chosen builder to a fixed stage
+# name via `FROM ${BUILDER_TARGET} AS builder` and then COPY --from=builder.
+# BUILDER_TARGET itself is declared as a global ARG at the top of this
+# file (required for use in FROM), so we just re-import it into this
+# stage's scope before the FROM directive.
+# ============================================================================
+FROM ${BUILDER_TARGET} AS builder
+
 FROM scratch
 
 

backend/backend.proto

@@ -48,6 +48,11 @@ service Backend {
 
   rpc AudioTransform(AudioTransformRequest) returns (AudioTransformResult) {}
   rpc AudioTransformStream(stream AudioTransformFrameRequest) returns (stream AudioTransformFrameResponse) {}
+  // AudioToAudioStream is the bidirectional any-to-any S2S RPC. Backends
+  // that load a speech-to-speech model consume input audio frames and emit
+  // interleaved audio + transcript + tool-call deltas as typed events.
+  // Backends without S2S support return UNIMPLEMENTED.
+  rpc AudioToAudioStream(stream AudioToAudioRequest) returns (stream AudioToAudioResponse) {}
 
   rpc ModelMetadata(ModelOptions) returns (ModelMetadataResponse) {}
 
@@ -768,6 +773,93 @@ message AudioTransformFrameResponse {
   int64 frame_index = 2;
 }
 
+// === AudioToAudioStream messages =========================================
+//
+// Bidirectional stream between the LocalAI core and an any-to-any audio
+// model. The client opens the stream with a Config payload, then alternates
+// Frame (input audio) and Control (turn boundaries, function-call results,
+// session updates) payloads. The server streams back typed events: audio
+// frames carry PCM in `pcm`; transcript / tool-call deltas carry JSON in
+// `meta`; the stream ends with a `response.done` (success) or `error` event.
+
+message AudioToAudioRequest {
+  oneof payload {
+    AudioToAudioConfig  config  = 1;
+    AudioToAudioFrame   frame   = 2;
+    AudioToAudioControl control = 3;
+  }
+}
+
+message AudioToAudioConfig {
+  // PCM format for client→server audio. 0 => backend default
+  // (16 kHz for the LFM2-Audio Conformer encoder).
+  int32 input_sample_rate = 1;
+  // Preferred server→client audio rate. 0 => backend default
+  // (24 kHz for the LFM2-Audio vocoder).
+  int32 output_sample_rate = 2;
+  // Optional system prompt override. Empty => backend chooses based on
+  // mode (e.g. "Respond with interleaved text and audio.").
+  string system_prompt = 3;
+  // Optional baked-voice id. Models that only ship a fixed set of
+  // voices (e.g. LFM2-Audio: us_male/us_female/uk_male/uk_female) match
+  // this against their voice table; an empty string keeps the default.
+  string voice = 4;
+  // JSON-encoded array of tool definitions in OpenAI Chat Completions
+  // format. Empty => no tools.
+  string tools = 5;
+  // Free-form sampling / decoding parameters (temperature, top_k,
+  // max_new_tokens, audio_top_k, etc).
+  map<string, string> params = 6;
+  // True => reset any session-scoped state before processing further
+  // frames on this stream. The first Config implicitly resets.
+  bool reset = 7;
+}
+
+message AudioToAudioFrame {
+  // Raw PCM s16le mono at config.input_sample_rate. Empty pcm + end_of_input
+  // is a valid "user finished speaking" marker without trailing audio.
+  bytes pcm = 1;
+  // Marks the last frame of a user turn. The backend may begin emitting
+  // a response immediately after seeing this.
+  bool end_of_input = 2;
+}
+
+message AudioToAudioControl {
+  // Free-form control event names. Initial set:
+  //   "input_audio_buffer.commit"     — user finished speaking
+  //   "response.cancel"               — abort in-flight generation
+  //   "conversation.item.create"      — inject a non-audio item (e.g.
+  //                                     function_call_output as JSON in
+  //                                     `payload`)
+  //   "session.update"                — re-configure mid-stream
+  string event = 1;
+  // Event-specific JSON payload.
+  bytes payload = 2;
+}
+
+message AudioToAudioResponse {
+  // Event identifies what this frame carries. Mirrors the OpenAI Realtime
+  // API server-event names where applicable. Initial set:
+  //   "response.audio.delta"
+  //   "response.audio_transcript.delta"
+  //   "response.function_call_arguments.delta"
+  //   "response.function_call_arguments.done"
+  //   "response.done"
+  //   "error"
+  string event = 1;
+  // Populated when event = response.audio.delta.
+  bytes pcm = 2;
+  // Populated alongside pcm to identify its rate. 0 => same as the
+  // session's negotiated output_sample_rate.
+  int32 sample_rate = 3;
+  // JSON payload for non-PCM events (transcript chunk, tool args, error
+  // body).
+  bytes meta = 4;
+  // Monotonic per-stream counter, useful for client reordering and
+  // debugging.
+  int64 sequence = 5;
+}
+
 message ModelMetadataResponse {
   bool supports_thinking = 1;
   string rendered_template = 2;  // The rendered chat template with enable_thinking=true (empty if not applicable)

backend/cpp/ds4/.gitignore

@@ -0,0 +1,9 @@
+ds4/
+build/
+package/
+grpc-server
+*.o
+backend.pb.cc
+backend.pb.h
+backend.grpc.pb.cc
+backend.grpc.pb.h

backend/cpp/ds4/CMakeLists.txt

@@ -0,0 +1,101 @@
+cmake_minimum_required(VERSION 3.15)
+project(ds4-grpc-server LANGUAGES CXX C)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
+set(TARGET grpc-server)
+
+option(DS4_NATIVE "Compile with -march=native / -mcpu=native" ON)
+set(DS4_GPU "cpu" CACHE STRING "GPU backend: cpu, cuda, or metal")
+set(DS4_DIR "${CMAKE_CURRENT_SOURCE_DIR}/ds4" CACHE PATH "Path to cloned ds4 source")
+
+find_package(Threads REQUIRED)
+find_package(Protobuf CONFIG QUIET)
+if(NOT Protobuf_FOUND)
+    find_package(Protobuf REQUIRED)
+endif()
+find_package(gRPC CONFIG QUIET)
+if(NOT gRPC_FOUND)
+    # Ubuntu's apt-installed grpc++ does not ship a CMake config - fall back.
+    find_library(GRPCPP_LIB grpc++ REQUIRED)
+    find_library(GRPCPP_REFLECTION_LIB grpc++_reflection REQUIRED)
+    add_library(gRPC::grpc++ INTERFACE IMPORTED)
+    set_target_properties(gRPC::grpc++ PROPERTIES INTERFACE_LINK_LIBRARIES "${GRPCPP_LIB}")
+    add_library(gRPC::grpc++_reflection INTERFACE IMPORTED)
+    set_target_properties(gRPC::grpc++_reflection PROPERTIES INTERFACE_LINK_LIBRARIES "${GRPCPP_REFLECTION_LIB}")
+endif()
+
+find_program(_PROTOC NAMES protoc REQUIRED)
+find_program(_GRPC_CPP_PLUGIN NAMES grpc_cpp_plugin REQUIRED)
+
+get_filename_component(HW_PROTO "${CMAKE_CURRENT_SOURCE_DIR}/../../backend.proto" ABSOLUTE)
+get_filename_component(HW_PROTO_PATH "${HW_PROTO}" PATH)
+
+set(HW_PROTO_SRCS "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.cc")
+set(HW_PROTO_HDRS "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.h")
+set(HW_GRPC_SRCS  "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.cc")
+set(HW_GRPC_HDRS  "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.h")
+
+add_custom_command(
+    OUTPUT "${HW_PROTO_SRCS}" "${HW_PROTO_HDRS}" "${HW_GRPC_SRCS}" "${HW_GRPC_HDRS}"
+    COMMAND ${_PROTOC}
+    ARGS --grpc_out "${CMAKE_CURRENT_BINARY_DIR}"
+         --cpp_out  "${CMAKE_CURRENT_BINARY_DIR}"
+         -I "${HW_PROTO_PATH}"
+         --plugin=protoc-gen-grpc="${_GRPC_CPP_PLUGIN}"
+         "${HW_PROTO}"
+    DEPENDS "${HW_PROTO}")
+
+add_library(hw_grpc_proto STATIC
+    ${HW_GRPC_SRCS} ${HW_GRPC_HDRS}
+    ${HW_PROTO_SRCS} ${HW_PROTO_HDRS})
+target_include_directories(hw_grpc_proto PUBLIC ${CMAKE_CURRENT_BINARY_DIR})
+
+set(DS4_OBJS "${DS4_DIR}/ds4.o")
+if(DS4_GPU STREQUAL "cuda")
+    list(APPEND DS4_OBJS "${DS4_DIR}/ds4_cuda.o")
+elseif(DS4_GPU STREQUAL "metal")
+    list(APPEND DS4_OBJS "${DS4_DIR}/ds4_metal.o")
+elseif(DS4_GPU STREQUAL "cpu")
+    set(DS4_OBJS "${DS4_DIR}/ds4_cpu.o")
+endif()
+
+add_executable(${TARGET}
+    grpc-server.cpp
+    dsml_parser.cpp
+    dsml_renderer.cpp
+    kv_cache.cpp)
+
+target_include_directories(${TARGET} PRIVATE ${DS4_DIR})
+
+foreach(obj ${DS4_OBJS})
+    target_sources(${TARGET} PRIVATE ${obj})
+    set_source_files_properties(${obj} PROPERTIES EXTERNAL_OBJECT TRUE GENERATED TRUE)
+endforeach()
+
+target_link_libraries(${TARGET} PRIVATE
+    hw_grpc_proto
+    gRPC::grpc++
+    gRPC::grpc++_reflection
+    protobuf::libprotobuf
+    Threads::Threads
+    m)
+
+if(DS4_GPU STREQUAL "cuda")
+    find_package(CUDAToolkit REQUIRED)
+    target_link_libraries(${TARGET} PRIVATE CUDA::cudart CUDA::cublas)
+elseif(DS4_GPU STREQUAL "metal")
+    find_library(FOUNDATION_LIB Foundation REQUIRED)
+    find_library(METAL_LIB Metal REQUIRED)
+    target_link_libraries(${TARGET} PRIVATE ${FOUNDATION_LIB} ${METAL_LIB})
+elseif(DS4_GPU STREQUAL "cpu")
+    target_compile_definitions(${TARGET} PRIVATE DS4_NO_GPU)
+endif()
+
+if(DS4_NATIVE)
+    if(APPLE)
+        target_compile_options(${TARGET} PRIVATE -mcpu=native)
+    else()
+        target_compile_options(${TARGET} PRIVATE -march=native)
+    endif()
+endif()

backend/cpp/ds4/Makefile

@@ -0,0 +1,78 @@
+# ds4 backend Makefile.
+#
+# Upstream pin lives below as DS4_VERSION?=c9dd9499bfa57c1bbfbb4446eff963330ab5329b
+# (.github/bump_deps.sh) can find and update it - matches the
+# llama-cpp / ik-llama-cpp / turboquant convention.
+
+DS4_VERSION?=c9dd9499bfa57c1bbfbb4446eff963330ab5329b
+DS4_REPO?=https://github.com/antirez/ds4
+
+CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
+BUILD_DIR := build
+
+BUILD_TYPE ?=
+NATIVE ?= false
+JOBS ?= $(shell nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 4)
+
+UNAME_S := $(shell uname -s)
+
+CMAKE_ARGS ?= -DCMAKE_BUILD_TYPE=Release
+
+ifeq ($(BUILD_TYPE),cublas)
+    CMAKE_ARGS += -DDS4_GPU=cuda
+    DS4_OBJ_TARGET := ds4.o ds4_cuda.o
+else ifeq ($(UNAME_S),Darwin)
+    CMAKE_ARGS += -DDS4_GPU=metal
+    DS4_OBJ_TARGET := ds4.o ds4_metal.o
+else
+    # CPU reference path (Linux only - macOS CPU path is broken by VM bug per ds4 README).
+    CMAKE_ARGS += -DDS4_GPU=cpu
+    DS4_OBJ_TARGET := ds4_cpu.o
+endif
+
+ifneq ($(NATIVE),true)
+    CMAKE_ARGS += -DDS4_NATIVE=OFF
+endif
+
+.PHONY: grpc-server package clean purge test all
+all: grpc-server
+
+# Clone the upstream ds4 source at the pinned commit. Directory acts as the
+# target so make only re-clones when missing. After a DS4_VERSION bump,
+# run 'make purge && make' to refetch (or rely on CI's clean build).
+ds4:
+	mkdir -p ds4
+	cd ds4 && \
+	git init -q && \
+	git remote add origin $(DS4_REPO) && \
+	git fetch --depth 1 origin $(DS4_VERSION) && \
+	git checkout FETCH_HEAD
+
+# Build ds4's engine object files via its own Makefile, which already encodes
+# the right per-platform compile flags (Objective-C/Metal on Darwin, nvcc on Linux+CUDA).
+ds4/ds4.o: ds4
+ifeq ($(BUILD_TYPE),cublas)
+	+$(MAKE) -C ds4 ds4.o ds4_cuda.o
+else ifeq ($(UNAME_S),Darwin)
+	+$(MAKE) -C ds4 ds4.o ds4_metal.o
+else
+	+$(MAKE) -C ds4 ds4_cpu.o
+endif
+
+grpc-server: ds4/ds4.o
+	mkdir -p $(BUILD_DIR)
+	cd $(BUILD_DIR) && cmake $(CMAKE_ARGS) $(CURRENT_MAKEFILE_DIR) && cmake --build . --config Release -j $(JOBS)
+	cp $(BUILD_DIR)/grpc-server grpc-server
+
+package: grpc-server
+	bash package.sh
+
+test:
+	@echo "ds4 backend: e2e coverage at tests/e2e-backends/ (BACKEND_BINARY mode)"
+
+clean:
+	rm -rf $(BUILD_DIR) grpc-server package
+	if [ -d ds4 ]; then $(MAKE) -C ds4 clean; fi
+
+purge: clean
+	rm -rf ds4

backend/cpp/ds4/dsml_parser.cpp

@@ -0,0 +1,359 @@
+#include "dsml_parser.h"
+
+#include <algorithm>
+#include <cstdio>
+#include <cstring>
+#include <chrono>
+#include <random>
+#include <string>
+#include <vector>
+
+namespace ds4cpp {
+
+namespace {
+
+constexpr const char *kThinkOpen      = "<think>";
+constexpr const char *kThinkClose     = "</think>";
+constexpr const char *kToolsOpen      = "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>";   // <｜DSML｜tool_calls>
+constexpr const char *kToolsClose     = "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>"; // </｜DSML｜tool_calls>
+constexpr const char *kInvokeOpenPfx  = "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke name=\""; // <｜DSML｜invoke name="
+constexpr const char *kInvokeClose    = "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke>";       // </｜DSML｜invoke>
+constexpr const char *kParamOpenPfx   = "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter name=\""; // <｜DSML｜parameter name="
+constexpr const char *kParamClose     = "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter>";       // </｜DSML｜parameter>
+
+// All structural markers the parser might encounter - used to detect "buf
+// might be a partial marker, don't drain yet" conditions.
+const std::vector<std::string> &all_markers() {
+    static const std::vector<std::string> v = {
+        kThinkOpen, kThinkClose,
+        kToolsOpen, kToolsClose,
+        kInvokeOpenPfx, kInvokeClose,
+        kParamOpenPfx, kParamClose,
+    };
+    return v;
+}
+
+// Returns true if `buf` could be a *prefix* of any marker (i.e., we should
+// wait for more text before draining as plain content). The marker-prefix
+// loop handles fixed markers exactly. For markers with variable-length
+// internal data (kInvokeOpenPfx, kParamOpenPfx have an open quote, then the
+// tool/param name, then a closing quote and `>`), we also wait while buf
+// starts with `<` and has not yet seen a `>`: the leading `<` could be the
+// start of one of those open markers, or a literal that we can confirm only
+// once we know what follows. Anything after the first `>` arrives is either
+// consumed by TryConsumeMarker or emitted as a literal `<` by the caller.
+bool looks_like_prefix(const std::string &buf) {
+    for (const auto &m : all_markers()) {
+        if (m.size() > buf.size() && m.compare(0, buf.size(), buf) == 0) return true;
+    }
+    if (!buf.empty() && buf[0] == '<' && buf.find('>') == std::string::npos) {
+        return true;
+    }
+    return false;
+}
+
+bool consume_literal(std::string &buf, const std::string &lit) {
+    if (buf.compare(0, lit.size(), lit) == 0) {
+        buf.erase(0, lit.size());
+        return true;
+    }
+    return false;
+}
+
+// Find the next '<' in buf starting at offset; returns std::string::npos if none.
+size_t next_tag(const std::string &buf, size_t off = 0) {
+    return buf.find('<', off);
+}
+
+std::string json_escape(const std::string &in) {
+    std::string out;
+    out.reserve(in.size() + 2);
+    for (char c : in) {
+        switch (c) {
+            case '"':  out += "\\\""; break;
+            case '\\': out += "\\\\"; break;
+            case '\b': out += "\\b"; break;
+            case '\f': out += "\\f"; break;
+            case '\n': out += "\\n"; break;
+            case '\r': out += "\\r"; break;
+            case '\t': out += "\\t"; break;
+            default:
+                if (static_cast<unsigned char>(c) < 0x20) {
+                    char tmp[8];
+                    std::snprintf(tmp, sizeof(tmp), "\\u%04x", c);
+                    out += tmp;
+                } else {
+                    out += c;
+                }
+        }
+    }
+    return out;
+}
+
+} // namespace
+
+DsmlParser::DsmlParser() = default;
+
+bool DsmlParser::IsInDsmlStructural() const {
+    switch (state_) {
+        case State::TOOL_CALLS:
+        case State::INVOKE:
+            return true;
+        case State::PARAM_VALUE:  // payload bytes; user sampling applies
+        case State::TEXT:
+        case State::THINK:
+            return false;
+    }
+    return false;
+}
+
+void DsmlParser::EmitArgsChunk(const std::string &chunk, std::vector<ParserEvent> &out) {
+    if (chunk.empty()) return;
+    ParserEvent e;
+    e.type = ParserEvent::TOOL_ARGS;
+    e.text = chunk;
+    e.index = tool_index_;
+    out.push_back(std::move(e));
+}
+
+void DsmlParser::FinishCurrentToolCall(std::vector<ParserEvent> &out) {
+    if (tool_index_ < 0) return;
+    // Close the JSON object that was opened on the first parameter.
+    if (args_emitted_open_brace_) {
+        EmitArgsChunk("}", out);
+    } else {
+        EmitArgsChunk("{}", out);
+    }
+    ParserEvent e;
+    e.type = ParserEvent::TOOL_END;
+    e.index = tool_index_;
+    out.push_back(std::move(e));
+    current_tool_name_.clear();
+    args_emitted_open_brace_ = false;
+    args_param_count_ = 0;
+}
+
+bool DsmlParser::TryConsumeMarker(std::vector<ParserEvent> &out) {
+    switch (state_) {
+    case State::TEXT: {
+        if (consume_literal(buf_, kThinkOpen))   { state_ = State::THINK;       return true; }
+        if (consume_literal(buf_, kToolsOpen))   { state_ = State::TOOL_CALLS;  return true; }
+        return false;
+    }
+    case State::THINK: {
+        if (consume_literal(buf_, kThinkClose))  { state_ = State::TEXT;        return true; }
+        return false;
+    }
+    case State::TOOL_CALLS: {
+        if (consume_literal(buf_, kToolsClose))  { state_ = State::TEXT;        return true; }
+        // <｜DSML｜invoke name="X">
+        if (buf_.compare(0, std::strlen(kInvokeOpenPfx), kInvokeOpenPfx) == 0) {
+            size_t close_q = buf_.find('"', std::strlen(kInvokeOpenPfx));
+            if (close_q == std::string::npos) return false; // need more bytes
+            size_t close_gt = buf_.find('>', close_q);
+            if (close_gt == std::string::npos) return false;
+            current_tool_name_ = buf_.substr(std::strlen(kInvokeOpenPfx),
+                                             close_q - std::strlen(kInvokeOpenPfx));
+            tool_index_++;
+            buf_.erase(0, close_gt + 1);
+            ParserEvent e;
+            e.type = ParserEvent::TOOL_START;
+            e.tool_name = current_tool_name_;
+            e.tool_id   = RandomToolId();
+            e.index     = tool_index_;
+            out.push_back(std::move(e));
+            args_emitted_open_brace_ = false;
+            args_param_count_ = 0;
+            state_ = State::INVOKE;
+            return true;
+        }
+        return false;
+    }
+    case State::INVOKE: {
+        if (consume_literal(buf_, kInvokeClose)) {
+            FinishCurrentToolCall(out);
+            state_ = State::TOOL_CALLS;
+            return true;
+        }
+        // <｜DSML｜parameter name="K" string="true|false">
+        if (buf_.compare(0, std::strlen(kParamOpenPfx), kParamOpenPfx) == 0) {
+            size_t close_q = buf_.find('"', std::strlen(kParamOpenPfx));
+            if (close_q == std::string::npos) return false;
+            size_t string_attr = buf_.find("string=\"", close_q);
+            if (string_attr == std::string::npos) return false;
+            size_t string_q = buf_.find('"', string_attr + 8);
+            if (string_q == std::string::npos) return false;
+            size_t close_gt = buf_.find('>', string_q);
+            if (close_gt == std::string::npos) return false;
+            param_name_ = buf_.substr(std::strlen(kParamOpenPfx),
+                                      close_q - std::strlen(kParamOpenPfx));
+            std::string string_val = buf_.substr(string_attr + 8,
+                                                 string_q - (string_attr + 8));
+            param_is_string_ = (string_val == "true");
+            param_value_.clear();
+            buf_.erase(0, close_gt + 1);
+            // Emit args JSON opener / separator.
+            std::string opener;
+            if (!args_emitted_open_brace_) { opener = "{"; args_emitted_open_brace_ = true; }
+            else                            { opener = ","; }
+            opener += "\"" + json_escape(param_name_) + "\":";
+            if (param_is_string_) opener += "\"";
+            EmitArgsChunk(opener, out);
+            args_param_count_++;
+            state_ = State::PARAM_VALUE;
+            return true;
+        }
+        return false;
+    }
+    case State::PARAM_VALUE: {
+        if (consume_literal(buf_, kParamClose)) {
+            if (param_is_string_) EmitArgsChunk("\"", out);
+            state_ = State::INVOKE;
+            return true;
+        }
+        return false;
+    }
+    }
+    return false;
+}
+
+void DsmlParser::DrainPlain(std::vector<ParserEvent> &out) {
+    // Drain everything up to the next '<' that *might* start a marker.
+    // Anything before the next '<' is safe to emit; the '<...' tail stays buffered.
+    while (!buf_.empty()) {
+        size_t lt = next_tag(buf_, 0);
+        if (lt == std::string::npos) {
+            // No tag at all - emit (or accumulate) the whole buffer.
+            ParserEvent e;
+            if (state_ == State::PARAM_VALUE) {
+                std::string esc = param_is_string_ ? json_escape(buf_) : buf_;
+                EmitArgsChunk(esc, out);
+            } else if (state_ == State::THINK) {
+                e.type = ParserEvent::REASONING;
+                e.text = buf_;
+                out.push_back(std::move(e));
+            } else if (state_ == State::TEXT) {
+                e.type = ParserEvent::CONTENT;
+                e.text = buf_;
+                out.push_back(std::move(e));
+            }
+            // Inside INVOKE / TOOL_CALLS with no marker, raw bytes are
+            // structural whitespace - discard.
+            buf_.clear();
+            return;
+        }
+        if (lt > 0) {
+            std::string chunk = buf_.substr(0, lt);
+            buf_.erase(0, lt);
+            ParserEvent e;
+            if (state_ == State::PARAM_VALUE) {
+                std::string esc = param_is_string_ ? json_escape(chunk) : chunk;
+                EmitArgsChunk(esc, out);
+            } else if (state_ == State::THINK) {
+                e.type = ParserEvent::REASONING;
+                e.text = chunk;
+                out.push_back(std::move(e));
+            } else if (state_ == State::TEXT) {
+                e.type = ParserEvent::CONTENT;
+                e.text = chunk;
+                out.push_back(std::move(e));
+            }
+        }
+        // buf_[0] == '<' - try consuming a marker. If we consumed one, loop again.
+        if (!TryConsumeMarker(out)) {
+            // Could be a partial marker - wait for more bytes.
+            if (looks_like_prefix(buf_)) return;
+            // Otherwise this '<' is a literal - emit one char and continue.
+            std::string one(1, buf_[0]);
+            buf_.erase(0, 1);
+            ParserEvent e;
+            if (state_ == State::PARAM_VALUE) {
+                std::string esc = param_is_string_ ? json_escape(one) : one;
+                EmitArgsChunk(esc, out);
+            } else if (state_ == State::THINK) {
+                e.type = ParserEvent::REASONING;
+                e.text = one;
+                out.push_back(std::move(e));
+            } else if (state_ == State::TEXT) {
+                e.type = ParserEvent::CONTENT;
+                e.text = one;
+                out.push_back(std::move(e));
+            }
+        }
+    }
+}
+
+void DsmlParser::Feed(const std::string &chunk, std::vector<ParserEvent> &out) {
+    buf_ += chunk;
+    DrainPlain(out);
+}
+
+void DsmlParser::Flush(std::vector<ParserEvent> &out) {
+    // At flush time we no longer wait for marker completion - drain everything
+    // (the trailing bytes won't grow). Mirror DrainPlain's state-aware
+    // classification: PARAM_VALUE bytes become TOOL_ARGS, THINK bytes become
+    // REASONING, TEXT bytes become CONTENT, and INVOKE/TOOL_CALLS bytes are
+    // structural whitespace (discarded).
+    auto emit_plain = [&](const std::string &chunk) {
+        if (chunk.empty()) return;
+        if (state_ == State::PARAM_VALUE) {
+            std::string esc = param_is_string_ ? json_escape(chunk) : chunk;
+            EmitArgsChunk(esc, out);
+            return;
+        }
+        if (state_ == State::THINK) {
+            ParserEvent e;
+            e.type = ParserEvent::REASONING;
+            e.text = chunk;
+            out.push_back(std::move(e));
+            return;
+        }
+        if (state_ == State::TEXT) {
+            ParserEvent e;
+            e.type = ParserEvent::CONTENT;
+            e.text = chunk;
+            out.push_back(std::move(e));
+            return;
+        }
+        // INVOKE / TOOL_CALLS: structural whitespace, discard.
+    };
+    while (!buf_.empty()) {
+        size_t lt = next_tag(buf_, 0);
+        if (lt == std::string::npos) {
+            emit_plain(buf_);
+            buf_.clear();
+            return;
+        }
+        if (lt > 0) {
+            std::string chunk = buf_.substr(0, lt);
+            buf_.erase(0, lt);
+            emit_plain(chunk);
+        }
+        if (!TryConsumeMarker(out)) {
+            // Definitely a literal '<' now (no chance of more bytes arriving).
+            std::string one(1, buf_[0]);
+            buf_.erase(0, 1);
+            emit_plain(one);
+        }
+    }
+    // If we ended mid-tool-call (model truncated), close it cleanly.
+    if (state_ == State::INVOKE || state_ == State::PARAM_VALUE) {
+        if (state_ == State::PARAM_VALUE && param_is_string_) EmitArgsChunk("\"", out);
+        FinishCurrentToolCall(out);
+        state_ = State::TEXT;
+    }
+}
+
+std::string RandomToolId() {
+    static thread_local std::mt19937_64 rng{
+        static_cast<uint64_t>(std::chrono::system_clock::now().time_since_epoch().count())};
+    const char *alphabet =
+        "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
+    std::string out = "call_";
+    for (int i = 0; i < 16; ++i) {
+        out += alphabet[rng() % 62];
+    }
+    return out;
+}
+
+} // namespace ds4cpp

backend/cpp/ds4/dsml_parser.h

@@ -0,0 +1,77 @@
+#pragma once
+#include <functional>
+#include <string>
+#include <vector>
+
+namespace ds4cpp {
+
+struct ParserEvent {
+    enum Type { CONTENT, REASONING, TOOL_START, TOOL_ARGS, TOOL_END };
+    Type type;
+    std::string text;        // CONTENT, REASONING, TOOL_ARGS
+    std::string tool_name;   // TOOL_START
+    std::string tool_id;     // TOOL_START (caller-assigned)
+    int index = 0;           // TOOL_START / TOOL_ARGS / TOOL_END
+};
+
+// Streaming parser. Stateless across instances; one per Predict call.
+class DsmlParser {
+public:
+    DsmlParser();
+
+    // Feed a chunk of raw model-emitted text. Appends classified events to
+    // `out`. May buffer the tail of `chunk` internally if it looks like a
+    // marker prefix.
+    void Feed(const std::string &chunk, std::vector<ParserEvent> &out);
+
+    // Flush any remaining buffered text as CONTENT (called at generation end).
+    void Flush(std::vector<ParserEvent> &out);
+
+    // True when the parser is inside a DSML structural position - that is,
+    // tags/markers between tool-call boundaries where the model is expected
+    // to emit protocol bytes verbatim. Mirrors ds4_server.c's "force
+    // temperature=0 unless dsml_decode_state_uses_payload_sampling" rule:
+    //
+    //   TEXT / THINK                  -> false (user sampling applies)
+    //   PARAM_VALUE                   -> false (payload uses user sampling)
+    //   TOOL_CALLS / INVOKE           -> true  (structural; force greedy)
+    //
+    // Callers should use this BEFORE the next sample() call to pick the
+    // effective temperature; the parser's state reflects what's already
+    // been consumed, so it predicts the next token's classification.
+    bool IsInDsmlStructural() const;
+
+private:
+    enum class State { TEXT, THINK, TOOL_CALLS, INVOKE, PARAM_VALUE };
+    State state_ = State::TEXT;
+    std::string buf_;
+    std::string current_tool_name_;
+    int tool_index_ = -1;
+    // While parsing a parameter value:
+    std::string param_name_;
+    bool param_is_string_ = true;
+    std::string param_value_;
+    // Incrementally-built arguments JSON for the active tool call.
+    std::string args_json_so_far_;
+    bool args_emitted_open_brace_ = false;
+    int args_param_count_ = 0;
+
+    // Try to consume one structural marker starting at buf_[0]. Returns true
+    // and advances state if a complete marker was consumed; false if the
+    // buffer is ambiguous (could be a marker prefix).
+    bool TryConsumeMarker(std::vector<ParserEvent> &out);
+
+    // Drain plain text from buf_ as far as we're sure it's not a marker prefix.
+    // Emits CONTENT or REASONING depending on current state.
+    void DrainPlain(std::vector<ParserEvent> &out);
+
+    // Emit the next chunk of arguments JSON to the consumer.
+    void EmitArgsChunk(const std::string &chunk, std::vector<ParserEvent> &out);
+    void FinishCurrentToolCall(std::vector<ParserEvent> &out);
+};
+
+// Generate a random tool call ID (e.g. "call_AbCdEf"). Used by the gRPC layer
+// when assigning IDs to streamed tool calls.
+std::string RandomToolId();
+
+} // namespace ds4cpp

backend/cpp/ds4/dsml_renderer.cpp

@@ -0,0 +1,140 @@
+#include "dsml_renderer.h"
+
+// We accept either nlohmann::json (if available) or fall back to a tiny
+// hand-rolled parser. The LocalAI tree already has nlohmann/json bundled
+// in vendor paths; we use the apt-installed nlohmann-json3-dev (installed
+// in Task 11 step 1) when present, otherwise the bundled copy.
+#if __has_include(<nlohmann/json.hpp>)
+#include <nlohmann/json.hpp>
+using json = nlohmann::json;
+#else
+#error "nlohmann/json.hpp not found; install nlohmann-json3-dev"
+#endif
+
+#include <sstream>
+
+namespace ds4cpp {
+
+namespace {
+
+void render_param(std::ostringstream &os, const std::string &name,
+                  const json &value) {
+    bool is_string = value.is_string();
+    os << "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter name=\"" << name
+       << "\" string=\"" << (is_string ? "true" : "false") << "\">";
+    if (is_string) {
+        os << value.get<std::string>();
+    } else {
+        os << value.dump();
+    }
+    os << "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter>\n";
+}
+
+} // namespace
+
+std::string RenderAssistantToolCalls(const std::string &tool_calls_json) {
+    if (tool_calls_json.empty()) return "";
+    json arr;
+    try {
+        arr = json::parse(tool_calls_json);
+    } catch (const std::exception &) {
+        return "";
+    }
+    if (!arr.is_array() || arr.empty()) return "";
+
+    std::ostringstream os;
+    os << "\n\n<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>\n";
+    for (const auto &call : arr) {
+        // OpenAI shape: { id, type, function: { name, arguments (JSON string) } }
+        // Anthropic shape comes through normalized by LocalAI.
+        std::string name;
+        std::string args_str;
+        if (call.contains("function")) {
+            const auto &fn = call["function"];
+            if (fn.contains("name") && fn["name"].is_string())
+                name = fn["name"].get<std::string>();
+            if (fn.contains("arguments") && fn["arguments"].is_string())
+                args_str = fn["arguments"].get<std::string>();
+        }
+        os << "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke name=\"" << name << "\">\n";
+        if (!args_str.empty()) {
+            json args;
+            try {
+                args = json::parse(args_str);
+            } catch (...) {
+                args = json{};
+            }
+            if (args.is_object()) {
+                for (auto it = args.begin(); it != args.end(); ++it) {
+                    render_param(os, it.key(), it.value());
+                }
+            }
+        }
+        os << "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke>\n";
+    }
+    os << "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>";
+    return os.str();
+}
+
+std::string RenderToolResult(const std::string &tool_call_id, const std::string &content) {
+    std::ostringstream os;
+    // ds4_server.c wraps tool results in a "tool_result" DSML tag carrying
+    // the tool_call_id. Match that shape.
+    os << "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_result id=\"" << tool_call_id << "\">"
+       << content
+       << "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_result>";
+    return os.str();
+}
+
+std::string RenderToolsManifest(const std::string &tools_json) {
+    if (tools_json.empty()) return "";
+    json arr;
+    try {
+        arr = json::parse(tools_json);
+    } catch (const std::exception &) {
+        return "";
+    }
+    if (!arr.is_array() || arr.empty()) return "";
+
+    // Extract each OpenAI tool's `function` object, dump as compact JSON, one
+    // per line. Mirrors openai_function_schema_from_tool() in ds4_server.c.
+    std::ostringstream schemas;
+    for (const auto &tool : arr) {
+        if (tool.contains("function") && tool["function"].is_object()) {
+            schemas << tool["function"].dump() << "\n";
+        } else if (tool.is_object()) {
+            // Anthropic / direct-schema form: pass through.
+            schemas << tool.dump() << "\n";
+        }
+    }
+    if (schemas.tellp() == std::streampos(0)) return "";
+
+    // Verbatim text from ds4_server.c append_tools_prompt_text. Do NOT
+    // paraphrase - the model was trained on these exact bytes.
+    std::ostringstream os;
+    os << "## Tools\n\n"
+          "You have access to a set of tools to help answer the user question. "
+          "You can invoke tools by writing a \"<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>\" block like the following:\n\n"
+          "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>\n"
+          "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke name=\"$TOOL_NAME\">\n"
+          "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter name=\"$PARAMETER_NAME\" string=\"true|false\">$PARAMETER_VALUE</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter>\n"
+          "...\n"
+          "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke>\n"
+          "<\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke name=\"$TOOL_NAME2\">\n"
+          "...\n"
+          "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "invoke>\n"
+          "</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "tool_calls>\n\n"
+          "String parameters should be specified as raw text and set `string=\"true\"`. "
+          "Preserve characters such as `>`, `&`, and `&&` exactly; never replace normal string characters with XML or HTML entity escapes. "
+          "Only if a string value itself contains the exact closing parameter tag `</\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter>`, write that tag as `&lt;/\xef\xbd\x9c" "DSML\xef\xbd\x9c" "parameter>` inside the value. "
+          "For all other types (numbers, booleans, arrays, objects), pass the value in JSON format and set `string=\"false\"`.\n\n"
+          "If thinking_mode is enabled (triggered by <think>), you MUST output your complete reasoning inside <think>...</think> BEFORE any tool calls or final response.\n\n"
+          "Otherwise, output directly after </think> with tool calls or final response.\n\n"
+          "### Available Tool Schemas\n\n"
+       << schemas.str()
+       << "\nYou MUST strictly follow the above defined tool name and parameter schemas to invoke tool calls. "
+          "Use the exact parameter names from the schemas.";
+    return os.str();
+}
+
+} // namespace ds4cpp

backend/cpp/ds4/dsml_renderer.h

@@ -0,0 +1,27 @@
+#pragma once
+#include <string>
+
+namespace ds4cpp {
+
+// Render an assistant message's tool_calls JSON array into the DSML block
+// that ds4 expects in its prompt. `tool_calls_json` is the value of
+// proto.Message.tool_calls (OpenAI shape: array of {id, type, function:{name, arguments}}).
+// Returns the DSML text to append after the assistant's content.
+std::string RenderAssistantToolCalls(const std::string &tool_calls_json);
+
+// Render a role="tool" message into the DSML "tool result" block. ds4's
+// prompt template expects tool results inside a specific tag; we wrap the
+// `content` with that tag and include the `tool_call_id` so the model can
+// correlate.
+std::string RenderToolResult(const std::string &tool_call_id, const std::string &content);
+
+// Render the "## Tools" manifest that ds4 expects in the SYSTEM prompt when
+// tools are available. Without this preamble the model has no idea tools
+// exist and will not emit DSML tool calls. Mirrors append_tools_prompt_text()
+// in ds4_server.c (~line 1646): a fixed preamble + "### Available Tool
+// Schemas" section + one JSON schema per line (extracted from each OpenAI
+// tool's .function object) + a fixed closing instruction. Returns empty
+// when tools_json is empty / unparseable.
+std::string RenderToolsManifest(const std::string &tools_json);
+
+} // namespace ds4cpp

backend/cpp/ds4/grpc-server.cpp

@@ -0,0 +1,696 @@
+// ds4 LocalAI gRPC backend.
+//
+// Wraps antirez/ds4's `ds4_engine_*` / `ds4_session_*` public API
+// (see ds4/ds4.h) over LocalAI's backend.proto. Tool calls, thinking
+// mode, and disk KV cache are wired in follow-up commits; this commit
+// is just the bind/listen/Health/Free skeleton.
+
+#include "backend.pb.h"
+#include "backend.grpc.pb.h"
+
+#include "dsml_parser.h"   // populated in Task 12
+#include "dsml_renderer.h" // populated in Task 16
+#include "kv_cache.h"      // populated in Task 17
+
+extern "C" {
+#include "ds4.h"
+}
+
+#include <grpcpp/grpcpp.h>
+#include <grpcpp/server.h>
+#include <grpcpp/server_builder.h>
+#include <grpcpp/ext/proto_server_reflection_plugin.h>
+
+#include <atomic>
+#include <chrono>
+#include <csignal>
+#include <cstring>
+#include <iostream>
+#include <memory>
+#include <mutex>
+#include <string>
+#include <thread>
+#include <vector>
+
+using grpc::Server;
+using grpc::ServerBuilder;
+using grpc::ServerContext;
+using grpc::ServerWriter;
+// NOTE: do NOT alias `grpc::Status` as `Status` - the Status RPC method below
+// would shadow the type, breaking the other RPC method declarations that use
+// it as a return type. Use GStatus instead.
+using GStatus = ::grpc::Status;
+using grpc::StatusCode;
+
+namespace {
+
+// Global state - ds4 is single-engine-per-process by design.
+std::mutex g_engine_mu;
+ds4_engine *g_engine = nullptr;
+ds4_session *g_session = nullptr;
+int g_ctx_size = 32768;
+std::string g_kv_cache_dir; // empty disables disk cache
+
+std::atomic<Server *> g_server{nullptr};
+
+// Parse a "key:value" option string. Returns empty when no colon.
+static std::pair<std::string, std::string> split_option(const std::string &opt) {
+    auto colon = opt.find(':');
+    if (colon == std::string::npos) return {opt, ""};
+    return {opt.substr(0, colon), opt.substr(colon + 1)};
+}
+
+static void append_token_text(ds4_engine *engine, int token, std::string &out) {
+    size_t len = 0;
+    const char *text = ds4_token_text(engine, token, &len);
+    if (text && len > 0) out.append(text, len);
+}
+
+struct CollectCtx {
+    ds4_engine *engine;
+    std::string raw_buf;  // exact raw bytes for Reply.message
+    ds4cpp::DsmlParser parser;
+    backend::Reply *reply;
+    int tokens;
+
+    // Per-tool aggregation: accumulate ChatDelta tool_calls so we emit one
+    // delta with all calls, mirroring how vllm's non-streaming path returns.
+    struct Pending {
+        std::string id;
+        std::string name;
+        std::string args;
+    };
+    std::vector<Pending> pending;
+
+    std::string content_buf;
+    std::string reasoning_buf;
+};
+
+static void apply_events(CollectCtx *c, const std::vector<ds4cpp::ParserEvent> &events) {
+    for (const auto &e : events) {
+        switch (e.type) {
+        case ds4cpp::ParserEvent::CONTENT:
+            c->content_buf += e.text;
+            break;
+        case ds4cpp::ParserEvent::REASONING:
+            c->reasoning_buf += e.text;
+            break;
+        case ds4cpp::ParserEvent::TOOL_START:
+            if ((int)c->pending.size() <= e.index)
+                c->pending.resize(e.index + 1);
+            c->pending[e.index].id = e.tool_id;
+            c->pending[e.index].name = e.tool_name;
+            break;
+        case ds4cpp::ParserEvent::TOOL_ARGS:
+            if ((int)c->pending.size() > e.index)
+                c->pending[e.index].args += e.text;
+            break;
+        case ds4cpp::ParserEvent::TOOL_END:
+            // No-op for non-streaming: the final delta is emitted at the end.
+            break;
+        }
+    }
+}
+
+static void collect_emit(void *ud, int token) {
+    auto *c = static_cast<CollectCtx *>(ud);
+    if (token == ds4_token_eos(c->engine)) return;
+    size_t len = 0;
+    const char *text = ds4_token_text(c->engine, token, &len);
+    if (!text || len == 0) return;
+    std::string chunk(text, len);
+    c->raw_buf += chunk;
+    std::vector<ds4cpp::ParserEvent> events;
+    c->parser.Feed(chunk, events);
+    apply_events(c, events);
+    c->tokens++;
+}
+static void collect_done(void *) {}
+
+struct StreamCtx {
+    ds4_engine *engine;
+    ServerWriter<backend::Reply> *writer;
+    ds4cpp::DsmlParser parser;
+    int tokens;
+    bool aborted;
+    // Track which tool indices we've seen TOOL_START for, so subsequent
+    // ARGS deltas can elide the redundant id/name fields.
+    std::vector<bool> tool_started;
+};
+
+static void stream_emit(void *ud, int token) {
+    auto *s = static_cast<StreamCtx *>(ud);
+    if (s->aborted) return;
+    if (token == ds4_token_eos(s->engine)) return;
+    size_t len = 0;
+    const char *text = ds4_token_text(s->engine, token, &len);
+    if (!text || len == 0) return;
+    std::string chunk(text, len);
+    std::vector<ds4cpp::ParserEvent> events;
+    s->parser.Feed(chunk, events);
+    if (events.empty()) { s->tokens++; return; }
+
+    backend::Reply reply;
+    auto *delta = reply.add_chat_deltas();
+    bool any_field = false;
+    for (const auto &e : events) {
+        switch (e.type) {
+        case ds4cpp::ParserEvent::CONTENT:
+            delta->set_content(delta->content() + e.text);
+            any_field = true;
+            break;
+        case ds4cpp::ParserEvent::REASONING:
+            delta->set_reasoning_content(delta->reasoning_content() + e.text);
+            any_field = true;
+            break;
+        case ds4cpp::ParserEvent::TOOL_START: {
+            if ((int)s->tool_started.size() <= e.index)
+                s->tool_started.resize(e.index + 1, false);
+            s->tool_started[e.index] = true;
+            auto *tc = delta->add_tool_calls();
+            tc->set_index(e.index);
+            tc->set_id(e.tool_id);
+            tc->set_name(e.tool_name);
+            any_field = true;
+            break;
+        }
+        case ds4cpp::ParserEvent::TOOL_ARGS: {
+            auto *tc = delta->add_tool_calls();
+            tc->set_index(e.index);
+            tc->set_arguments(e.text);
+            any_field = true;
+            break;
+        }
+        case ds4cpp::ParserEvent::TOOL_END:
+            // No marker delta needed - the Go side closes the tool call on
+            // the final aggregator pass.
+            break;
+        }
+    }
+    reply.set_message(chunk);
+    reply.set_tokens(1);
+    if (any_field) {
+        if (!s->writer->Write(reply)) s->aborted = true;
+    }
+    s->tokens++;
+}
+static void stream_done(void *) {}
+
+// Per-thread RNG seed for ds4_session_sample. Initialized lazily from
+// system_clock; ds4 owns the random walk after that.
+static uint64_t *get_rng() {
+    static thread_local uint64_t seed = 0;
+    if (seed == 0) {
+        seed = static_cast<uint64_t>(
+            std::chrono::system_clock::now().time_since_epoch().count());
+        if (seed == 0) seed = 1;
+    }
+    return &seed;
+}
+
+struct SampleParams {
+    float temperature;
+    int top_k;
+    float top_p;
+    float min_p;
+};
+
+// Compute the effective sampling parameters for the next token, mirroring
+// ds4_server.c:7102-7115:
+//   - thinking mode enabled -> override (T=1, top_k=0, top_p=1, min_p=0)
+//   - inside DSML structural position (tool-call markers) -> force T=0
+//   - otherwise -> the request's user-supplied sampling settings
+// The parser argument carries state from tokens emitted so far; its
+// IsInDsmlStructural() predicts the next token's classification.
+static SampleParams compute_sample_params(const backend::PredictOptions *request,
+                                          const ds4cpp::DsmlParser &parser,
+                                          bool think_enabled);
+
+static ds4_think_mode parse_think_mode(const backend::PredictOptions *request) {
+    // Per the vllm backend convention, "enable_thinking" gates thinking on/off,
+    // and "reasoning_effort" picks the strength when on.
+    const auto &md = request->metadata();
+    auto et = md.find("enable_thinking");
+    bool enabled = true; // default ON per ds4-server
+    if (et != md.end()) enabled = (et->second == "true" || et->second == "1");
+    if (!enabled) return DS4_THINK_NONE;
+    auto re = md.find("reasoning_effort");
+    if (re != md.end() && (re->second == "max" || re->second == "xhigh"))
+        return DS4_THINK_MAX;
+    return DS4_THINK_HIGH;
+}
+
+static SampleParams compute_sample_params(const backend::PredictOptions *request,
+                                          const ds4cpp::DsmlParser &parser,
+                                          bool think_enabled) {
+    SampleParams p = {
+        request->temperature(),
+        request->topk(),
+        request->topp(),
+        request->minp(),
+    };
+    if (think_enabled) {
+        // Match ds4-server: thinking mode wants creativity in the reasoning
+        // pass and the trailing content, so the entire generation overrides
+        // sampling unless DSML structural bytes take over below.
+        p.temperature = 1.0f;
+        p.top_k = 0;
+        p.top_p = 1.0f;
+        p.min_p = 0.0f;
+    }
+    if (parser.IsInDsmlStructural()) {
+        // Tool-call structural bytes (tags, markers, headers) must parse
+        // cleanly. Force greedy regardless of user/thinking settings.
+        p.temperature = 0.0f;
+    }
+    return p;
+}
+
+// Build the rendered text for cache keying. We feed the same text the model
+// will see; that lets the cache survive small client-side reformatting of
+// chat history (the cache is keyed on bytes, not tokens).
+static std::string render_prompt_text(const backend::PredictOptions *request) {
+    // Two-mode: either the raw prompt or the chat-template path. We mirror
+    // build_prompt's branching but accumulate text (not tokens) so we can
+    // SHA1 it for the cache key. ds4_session caches a tokens-indexed
+    // checkpoint, but the disk format keys on bytes per ds4-server's design.
+    if (!request->usetokenizertemplate() || request->messages_size() == 0) {
+        return request->prompt();
+    }
+    std::string out;
+    const std::string sys_role = "system";
+    for (const auto &m : request->messages()) {
+        if (m.role() == sys_role) { out += "[sys] " + m.content() + "\n"; break; }
+    }
+    for (const auto &m : request->messages()) {
+        if (m.role() == sys_role) continue;
+        out += "[" + m.role() + "] " + m.content() + "\n";
+    }
+    return out;
+}
+
+ds4cpp::KvCache g_kv_cache;
+
+// Try to recover prefill state for `rendered`. Returns the matched prefix length.
+static size_t maybe_load_cache(const std::string &rendered) {
+    if (!g_kv_cache.enabled() || !g_session) return 0;
+    return g_kv_cache.LoadLongestPrefix(g_session, rendered, g_ctx_size);
+}
+
+static void maybe_save_cache(const std::string &rendered) {
+    if (g_kv_cache.enabled() && g_session) {
+        g_kv_cache.Save(g_session, rendered, g_ctx_size);
+    }
+}
+
+static void build_prompt(ds4_engine *engine, const backend::PredictOptions *request,
+                         ds4_tokens *out) {
+    if (!request->usetokenizertemplate() || request->messages_size() == 0) {
+        ds4_tokenize_text(engine, request->prompt().c_str(), out);
+        return;
+    }
+    // Chat-template path: render via ds4's helpers.
+    ds4_chat_begin(engine, out);
+
+    ds4_think_mode think = parse_think_mode(request);
+
+    // ds4_encode_chat_prompt is convenient when there is exactly one
+    // system+user pair, but for arbitrary turn lists we use the granular
+    // append helpers. Pull the first system message (if any), then append
+    // every other message in order.
+    const std::string sys_role = "system";
+    std::string system_text;
+    for (const auto &m : request->messages()) {
+        if (m.role() == sys_role) { system_text = m.content(); break; }
+    }
+    // Inject the tools manifest into the system prompt when tools are present.
+    // ds4 was trained to emit DSML tool calls ONLY when this preamble is in
+    // the system message - without it, the model has no idea tools exist and
+    // the e2e tool-call test will fail. The renderer lives in dsml_renderer
+    // and is a verbatim port of ds4_server.c's append_tools_prompt_text.
+    std::string tools_manifest;
+    if (!request->tools().empty()) {
+        tools_manifest = ds4cpp::RenderToolsManifest(request->tools());
+    }
+    if (!system_text.empty() || !tools_manifest.empty()) {
+        std::string combined = system_text;
+        if (!tools_manifest.empty()) {
+            if (!combined.empty()) combined += "\n\n";
+            combined += tools_manifest;
+        }
+        ds4_chat_append_message(engine, out, "system", combined.c_str());
+    }
+    for (const auto &m : request->messages()) {
+        if (m.role() == sys_role) continue;
+        if (m.role() == "assistant" && !m.tool_calls().empty()) {
+            std::string combined = m.content();
+            combined += ds4cpp::RenderAssistantToolCalls(m.tool_calls());
+            ds4_chat_append_message(engine, out, "assistant", combined.c_str());
+        } else if (m.role() == "tool") {
+            std::string body = ds4cpp::RenderToolResult(m.tool_call_id(), m.content());
+            ds4_chat_append_message(engine, out, "user", body.c_str());
+        } else {
+            ds4_chat_append_message(engine, out, m.role().c_str(), m.content().c_str());
+        }
+    }
+    ds4_chat_append_assistant_prefix(engine, out, think);
+}
+
+class DS4Backend final : public backend::Backend::Service {
+public:
+    GStatus Health(ServerContext *, const backend::HealthMessage *,
+                  backend::Reply *reply) override {
+        reply->set_message(std::string("OK"));
+        return GStatus::OK;
+    }
+
+    GStatus Free(ServerContext *, const backend::HealthMessage *,
+                backend::Result *result) override {
+        std::lock_guard<std::mutex> lock(g_engine_mu);
+        if (g_session) { ds4_session_free(g_session); g_session = nullptr; }
+        if (g_engine)  { ds4_engine_close(g_engine);  g_engine  = nullptr; }
+        result->set_success(true);
+        return GStatus::OK;
+    }
+
+    GStatus LoadModel(ServerContext *, const backend::ModelOptions *request,
+                     backend::Result *result) override {
+        std::lock_guard<std::mutex> lock(g_engine_mu);
+
+        if (g_engine) {
+            if (g_session) { ds4_session_free(g_session); g_session = nullptr; }
+            ds4_engine_close(g_engine);
+            g_engine = nullptr;
+        }
+
+        std::string model_path = request->modelfile();
+        if (model_path.empty()) model_path = request->model();
+        if (model_path.empty()) {
+            result->set_success(false);
+            result->set_message("ds4: ModelOptions.Model or .ModelFile must be set");
+            return GStatus::OK;
+        }
+
+        std::string mtp_path;
+        int mtp_draft = 0;
+        float mtp_margin = 3.0f;
+        for (const auto &opt : request->options()) {
+            auto [k, v] = split_option(opt);
+            if (k == "mtp_path") mtp_path = v;
+            else if (k == "mtp_draft") mtp_draft = std::stoi(v);
+            else if (k == "mtp_margin") mtp_margin = std::stof(v);
+            else if (k == "kv_cache_dir") g_kv_cache_dir = v;
+        }
+
+        g_kv_cache.SetDir(g_kv_cache_dir);
+
+        ds4_engine_options opt = {};
+        opt.model_path = model_path.c_str();
+        opt.mtp_path = mtp_path.empty() ? nullptr : mtp_path.c_str();
+        opt.n_threads = request->threads() > 0 ? request->threads() : 0;
+        opt.mtp_draft_tokens = mtp_draft;
+        opt.mtp_margin = mtp_margin;
+        opt.directional_steering_file = nullptr;
+        opt.warm_weights = false;
+        opt.quality = false;
+
+#if defined(DS4_NO_GPU)
+        opt.backend = DS4_BACKEND_CPU;
+#elif defined(__APPLE__)
+        opt.backend = DS4_BACKEND_METAL;
+#else
+        opt.backend = DS4_BACKEND_CUDA;
+#endif
+
+        int rc = ds4_engine_open(&g_engine, &opt);
+        if (rc != 0 || !g_engine) {
+            result->set_success(false);
+            result->set_message("ds4_engine_open failed (rc=" + std::to_string(rc) + ")");
+            return GStatus::OK;
+        }
+
+        g_ctx_size = request->contextsize() > 0 ? request->contextsize() : 32768;
+        rc = ds4_session_create(&g_session, g_engine, g_ctx_size);
+        if (rc != 0 || !g_session) {
+            ds4_engine_close(g_engine);
+            g_engine = nullptr;
+            result->set_success(false);
+            result->set_message("ds4_session_create failed (rc=" + std::to_string(rc) + ")");
+            return GStatus::OK;
+        }
+
+        result->set_success(true);
+        result->set_message("loaded " + model_path);
+        return GStatus::OK;
+    }
+
+    GStatus TokenizeString(ServerContext *, const backend::PredictOptions *request,
+                          backend::TokenizationResponse *response) override {
+        std::lock_guard<std::mutex> lock(g_engine_mu);
+        if (!g_engine) return GStatus(StatusCode::FAILED_PRECONDITION, "ds4: model not loaded");
+        ds4_tokens out = {};
+        ds4_tokenize_text(g_engine, request->prompt().c_str(), &out);
+        for (int i = 0; i < out.len; ++i) response->add_tokens(out.v[i]);
+        response->set_length(out.len);
+        ds4_tokens_free(&out);
+        return GStatus::OK;
+    }
+
+    GStatus Predict(ServerContext *, const backend::PredictOptions *request,
+                   backend::Reply *reply) override {
+        std::lock_guard<std::mutex> lock(g_engine_mu);
+        if (!g_engine || !g_session) {
+            return GStatus(StatusCode::FAILED_PRECONDITION, "ds4: model not loaded");
+        }
+        ds4_tokens prompt = {};
+        build_prompt(g_engine, request, &prompt);
+        int n_predict = request->tokens() > 0 ? request->tokens() : 256;
+
+        CollectCtx collect = {g_engine, "", {}, reply, 0, {}, "", ""};
+        std::string cache_key = render_prompt_text(request);
+        size_t cache_hit = maybe_load_cache(cache_key);
+        (void)cache_hit; // future: skip prompt prefix if hit covers full prompt
+
+        // Manual generation loop on g_session. When MTP speculative weights
+        // were loaded (LoadModel option 'mtp_path:'), we use the
+        // ds4_session_eval_speculative_argmax path which may accept N>1
+        // tokens per outer iteration. Otherwise per-token argmax + eval.
+        // Either way g_session advances so the disk KV cache picks up a
+        // real checkpoint after the call (see maybe_save_cache below).
+        char err[256] = {0};
+        int rc = ds4_session_sync(g_session, &prompt, err, sizeof(err));
+        int prompt_len = prompt.len;
+        ds4_tokens_free(&prompt);
+        if (rc == 0) {
+            const int eos = ds4_token_eos(g_engine);
+            const int draft_max = ds4_engine_mtp_draft_tokens(g_engine);
+            const bool think_enabled = ds4_think_mode_enabled(parse_think_mode(request));
+            int produced = 0;
+            while (produced < n_predict) {
+                SampleParams sp = compute_sample_params(request, collect.parser, think_enabled);
+                int first;
+                if (sp.temperature <= 0.0f) {
+                    first = ds4_session_argmax(g_session);
+                } else {
+                    first = ds4_session_sample(g_session,
+                                               sp.temperature, sp.top_k,
+                                               sp.top_p, sp.min_p, get_rng());
+                }
+                if (first == eos) break;
+                // MTP only when sampling is greedy (ds4-server gate).
+                if (draft_max > 0 && sp.temperature <= 0.0f) {
+                    constexpr int kAcceptedMax = 8;
+                    int accepted[kAcceptedMax];
+                    int cap = std::min(kAcceptedMax, draft_max + 1);
+                    int n = ds4_session_eval_speculative_argmax(
+                        g_session, first, draft_max, eos,
+                        accepted, cap, err, sizeof(err));
+                    if (n < 0) { rc = -1; break; }
+                    bool stop = false;
+                    for (int j = 0; j < n; ++j) {
+                        if (accepted[j] == eos) { stop = true; break; }
+                        collect_emit(&collect, accepted[j]);
+                        if (++produced >= n_predict) { stop = true; break; }
+                    }
+                    if (stop) break;
+                } else {
+                    collect_emit(&collect, first);
+                    if (++produced >= n_predict) break;
+                    rc = ds4_session_eval(g_session, first, err, sizeof(err));
+                    if (rc != 0) break;
+                }
+            }
+            collect_done(&collect);
+        }
+        maybe_save_cache(cache_key);
+
+        // Flush any buffered parser state.
+        std::vector<ds4cpp::ParserEvent> events;
+        collect.parser.Flush(events);
+        apply_events(&collect, events);
+
+        if (rc != 0) {
+            return GStatus(StatusCode::INTERNAL,
+                          std::string("ds4 generation failed: ") + err);
+        }
+
+        // Emit one ChatDelta with content/reasoning/tool_calls.
+        auto *delta = reply->add_chat_deltas();
+        delta->set_content(collect.content_buf);
+        delta->set_reasoning_content(collect.reasoning_buf);
+        for (size_t i = 0; i < collect.pending.size(); ++i) {
+            auto *tc = delta->add_tool_calls();
+            tc->set_index(static_cast<int32_t>(i));
+            tc->set_id(collect.pending[i].id);
+            tc->set_name(collect.pending[i].name);
+            tc->set_arguments(collect.pending[i].args);
+        }
+
+        reply->set_message(collect.raw_buf);
+        reply->set_tokens(collect.tokens);
+        reply->set_prompt_tokens(prompt_len);
+        return GStatus::OK;
+    }
+
+    GStatus PredictStream(ServerContext *, const backend::PredictOptions *request,
+                         ServerWriter<backend::Reply> *writer) override {
+        std::lock_guard<std::mutex> lock(g_engine_mu);
+        if (!g_engine || !g_session) {
+            return GStatus(StatusCode::FAILED_PRECONDITION, "ds4: model not loaded");
+        }
+        ds4_tokens prompt = {};
+        build_prompt(g_engine, request, &prompt);
+        int n_predict = request->tokens() > 0 ? request->tokens() : 256;
+
+        StreamCtx s = {g_engine, writer, {}, 0, false, {}};
+        std::string cache_key = render_prompt_text(request);
+        size_t cache_hit = maybe_load_cache(cache_key);
+        (void)cache_hit;
+
+        // Manual loop on g_session - see Predict() above for the rationale.
+        // MTP speculative path used when ds4_engine_mtp_draft_tokens > 0.
+        char err[256] = {0};
+        int rc = ds4_session_sync(g_session, &prompt, err, sizeof(err));
+        ds4_tokens_free(&prompt);
+        if (rc == 0) {
+            const int eos = ds4_token_eos(g_engine);
+            const int draft_max = ds4_engine_mtp_draft_tokens(g_engine);
+            const bool think_enabled = ds4_think_mode_enabled(parse_think_mode(request));
+            int produced = 0;
+            while (produced < n_predict && !s.aborted) {
+                SampleParams sp = compute_sample_params(request, s.parser, think_enabled);
+                int first;
+                if (sp.temperature <= 0.0f) {
+                    first = ds4_session_argmax(g_session);
+                } else {
+                    first = ds4_session_sample(g_session,
+                                               sp.temperature, sp.top_k,
+                                               sp.top_p, sp.min_p, get_rng());
+                }
+                if (first == eos) break;
+                if (draft_max > 0 && sp.temperature <= 0.0f) {
+                    constexpr int kAcceptedMax = 8;
+                    int accepted[kAcceptedMax];
+                    int cap = std::min(kAcceptedMax, draft_max + 1);
+                    int n = ds4_session_eval_speculative_argmax(
+                        g_session, first, draft_max, eos,
+                        accepted, cap, err, sizeof(err));
+                    if (n < 0) { rc = -1; break; }
+                    bool stop = false;
+                    for (int j = 0; j < n; ++j) {
+                        if (accepted[j] == eos) { stop = true; break; }
+                        stream_emit(&s, accepted[j]);
+                        if (s.aborted) { stop = true; break; }
+                        if (++produced >= n_predict) { stop = true; break; }
+                    }
+                    if (stop) break;
+                } else {
+                    stream_emit(&s, first);
+                    if (s.aborted || ++produced >= n_predict) break;
+                    rc = ds4_session_eval(g_session, first, err, sizeof(err));
+                    if (rc != 0) break;
+                }
+            }
+            stream_done(&s);
+        }
+        maybe_save_cache(cache_key);
+
+        // Flush parser state.
+        std::vector<ds4cpp::ParserEvent> events;
+        s.parser.Flush(events);
+        if (!events.empty() && !s.aborted) {
+            backend::Reply reply;
+            auto *delta = reply.add_chat_deltas();
+            for (const auto &e : events) {
+                if (e.type == ds4cpp::ParserEvent::CONTENT) {
+                    delta->set_content(delta->content() + e.text);
+                } else if (e.type == ds4cpp::ParserEvent::REASONING) {
+                    delta->set_reasoning_content(delta->reasoning_content() + e.text);
+                }
+            }
+            s.writer->Write(reply);
+        }
+
+        if (rc != 0 && !s.aborted) {
+            return GStatus(StatusCode::INTERNAL,
+                          std::string("ds4 generation failed: ") + err);
+        }
+        return GStatus::OK;
+    }
+
+    GStatus Status(ServerContext *, const backend::HealthMessage *,
+                  backend::StatusResponse *response) override {
+        std::lock_guard<std::mutex> lock(g_engine_mu);
+        response->set_state(g_engine ? backend::StatusResponse::READY
+                                     : backend::StatusResponse::UNINITIALIZED);
+        return GStatus::OK;
+    }
+};
+
+void RunServer(const std::string &addr) {
+    DS4Backend service;
+    grpc::EnableDefaultHealthCheckService(true);
+    grpc::reflection::InitProtoReflectionServerBuilderPlugin();
+
+    ServerBuilder builder;
+    builder.AddListeningPort(addr, grpc::InsecureServerCredentials());
+    builder.RegisterService(&service);
+    builder.SetMaxReceiveMessageSize(64 * 1024 * 1024);
+    builder.SetMaxSendMessageSize(64 * 1024 * 1024);
+
+    std::unique_ptr<Server> server(builder.BuildAndStart());
+    if (!server) {
+        std::cerr << "ds4 grpc-server: failed to bind " << addr << "\n";
+        std::exit(1);
+    }
+    g_server = server.get();
+    std::cerr << "ds4 grpc-server listening on " << addr << "\n";
+    server->Wait();
+}
+
+void signal_handler(int) {
+    if (auto *srv = g_server.load()) {
+        srv->Shutdown(std::chrono::system_clock::now() +
+                      std::chrono::seconds(3));
+    }
+}
+
+} // namespace
+
+int main(int argc, char *argv[]) {
+    std::string addr = "127.0.0.1:50051";
+    for (int i = 1; i < argc; ++i) {
+        std::string a = argv[i];
+        const std::string addr_flag = "--addr=";
+        if (a.rfind(addr_flag, 0) == 0) addr = a.substr(addr_flag.size());
+        else if (a == "--addr" && i + 1 < argc) addr = argv[++i];
+        else if (a == "--help" || a == "-h") {
+            std::cout << "Usage: grpc-server --addr=HOST:PORT\n";
+            return 0;
+        }
+    }
+    std::signal(SIGINT, signal_handler);
+    std::signal(SIGTERM, signal_handler);
+    RunServer(addr);
+    return 0;
+}

backend/cpp/ds4/kv_cache.cpp

@@ -0,0 +1,205 @@
+#include "kv_cache.h"
+
+#include <cerrno>
+#include <cstdio>
+#include <cstring>
+#include <dirent.h>
+#include <fstream>
+#include <sys/stat.h>
+#include <vector>
+
+namespace ds4cpp {
+
+namespace {
+
+// Minimal SHA1 (public domain reference). 30 lines; used only here.
+struct Sha1 {
+    uint32_t h[5];
+    uint64_t bits;
+    uint8_t block[64];
+    size_t used;
+    Sha1() { h[0]=0x67452301; h[1]=0xEFCDAB89; h[2]=0x98BADCFE; h[3]=0x10325476; h[4]=0xC3D2E1F0; bits=0; used=0; }
+    static uint32_t rol(uint32_t x, int n){ return (x<<n)|(x>>(32-n)); }
+    void transform(const uint8_t *b) {
+        uint32_t w[80];
+        for (int i=0;i<16;i++) w[i] = (uint32_t)b[i*4]<<24 | (uint32_t)b[i*4+1]<<16 | (uint32_t)b[i*4+2]<<8 | b[i*4+3];
+        for (int i=16;i<80;i++) w[i] = rol(w[i-3]^w[i-8]^w[i-14]^w[i-16], 1);
+        uint32_t a=h[0],bb=h[1],c=h[2],d=h[3],e=h[4];
+        for (int i=0;i<80;i++) {
+            uint32_t f,k;
+            if (i<20)      { f=(bb&c)|((~bb)&d); k=0x5A827999; }
+            else if (i<40) { f=bb^c^d;            k=0x6ED9EBA1; }
+            else if (i<60) { f=(bb&c)|(bb&d)|(c&d); k=0x8F1BBCDC; }
+            else           { f=bb^c^d;            k=0xCA62C1D6; }
+            uint32_t t = rol(a,5)+f+e+k+w[i];
+            e=d; d=c; c=rol(bb,30); bb=a; a=t;
+        }
+        h[0]+=a; h[1]+=bb; h[2]+=c; h[3]+=d; h[4]+=e;
+    }
+    void update(const void *p, size_t n) {
+        const uint8_t *bp = (const uint8_t*)p;
+        bits += (uint64_t)n*8;
+        while (n) {
+            size_t take = 64-used;
+            if (take>n) take=n;
+            std::memcpy(block+used, bp, take);
+            used += take; bp += take; n -= take;
+            if (used == 64) { transform(block); used = 0; }
+        }
+    }
+    void final(uint8_t out[20]) {
+        uint8_t pad[64] = {0x80};
+        size_t padlen = (used < 56) ? (56-used) : (120-used);
+        uint64_t lb = bits;
+        uint8_t len[8];
+        for (int i=0;i<8;i++) len[7-i] = (uint8_t)(lb >> (i*8));
+        update(pad, padlen);
+        update(len, 8);
+        for (int i=0;i<5;i++) {
+            out[i*4]   = h[i]>>24;
+            out[i*4+1] = h[i]>>16;
+            out[i*4+2] = h[i]>>8;
+            out[i*4+3] = h[i];
+        }
+    }
+};
+
+std::string mkdir_p(const std::string &d) {
+    if (d.empty()) return d;
+    struct stat st{};
+    if (stat(d.c_str(), &st) == 0) return d;
+    mkdir(d.c_str(), 0755);
+    return d;
+}
+
+bool file_exists(const std::string &p) {
+    struct stat st{};
+    return stat(p.c_str(), &st) == 0;
+}
+
+} // namespace
+
+std::string Sha1Hex(const void *data, size_t len) {
+    Sha1 s;
+    s.update(data, len);
+    uint8_t out[20];
+    s.final(out);
+    char hex[41];
+    for (int i = 0; i < 20; ++i) std::snprintf(hex + i*2, 3, "%02x", out[i]);
+    hex[40] = 0;
+    return std::string(hex);
+}
+
+KvCache::KvCache() = default;
+
+void KvCache::SetDir(const std::string &dir) {
+    dir_ = dir;
+    if (!dir_.empty()) {
+        mkdir_p(dir_);
+        std::fprintf(stderr, "ds4 KvCache: enabled at %s\n", dir_.c_str());
+    } else {
+        std::fprintf(stderr, "ds4 KvCache: disabled (no dir set)\n");
+    }
+}
+
+std::string KvCache::Path(const std::string &rendered_text) const {
+    if (dir_.empty()) return "";
+    return dir_ + "/" + Sha1Hex(rendered_text.data(), rendered_text.size()) + ".kv";
+}
+
+size_t KvCache::LoadLongestPrefix(ds4_session *session,
+                                  const std::string &rendered_text,
+                                  int ctx_size) {
+    if (dir_.empty() || !session) return 0;
+    // Strategy: enumerate all .kv files in dir, read their stored prefix
+    // header, pick the longest one that is also a prefix of rendered_text.
+    DIR *d = opendir(dir_.c_str());
+    if (!d) return 0;
+    struct dirent *de;
+    size_t best_len = 0;
+    std::string best_path;
+    while ((de = readdir(d)) != nullptr) {
+        std::string name = de->d_name;
+        if (name.size() < 4 || name.substr(name.size()-3) != ".kv") continue;
+        std::string path = dir_ + "/" + name;
+        std::ifstream f(path, std::ios::binary);
+        if (!f) continue;
+        char magic[4]; f.read(magic, 4);
+        if (f.gcount() != 4 || std::memcmp(magic, "DS4G", 4) != 0) continue;
+        uint32_t version=0, file_ctx=0, prefix_len=0;
+        f.read((char*)&version, 4); f.read((char*)&file_ctx, 4); f.read((char*)&prefix_len, 4);
+        if (version != 1) continue;
+        if ((int)file_ctx != ctx_size) continue;
+        if (prefix_len > rendered_text.size()) continue;
+        std::vector<char> prefix(prefix_len);
+        f.read(prefix.data(), prefix_len);
+        if (std::memcmp(prefix.data(), rendered_text.data(), prefix_len) != 0) continue;
+        if (prefix_len > best_len) {
+            best_len = prefix_len;
+            best_path = path;
+        }
+    }
+    closedir(d);
+    if (best_len == 0) return 0;
+
+    // Load best_path's payload into session.
+    std::ifstream f(best_path, std::ios::binary);
+    char magic[4]; f.read(magic, 4);
+    uint32_t version, file_ctx, prefix_len;
+    f.read((char*)&version, 4); f.read((char*)&file_ctx, 4); f.read((char*)&prefix_len, 4);
+    f.seekg(prefix_len, std::ios::cur);
+    uint64_t payload_bytes = 0;
+    f.read((char*)&payload_bytes, 8);
+    // ds4_session_load_payload reads from a FILE*; reopen via fopen.
+    FILE *fp = std::fopen(best_path.c_str(), "rb");
+    if (!fp) return 0;
+    // Seek past header + prefix + payload_bytes field.
+    std::fseek(fp, 4 + 4 + 4 + 4 + prefix_len + 8, SEEK_SET);
+    char errbuf[256] = {0};
+    int rc = ds4_session_load_payload(session, fp, payload_bytes, errbuf, sizeof(errbuf));
+    std::fclose(fp);
+    if (rc != 0) return 0;
+    return best_len;
+}
+
+void KvCache::Save(ds4_session *session, const std::string &rendered_text, int ctx_size) {
+    if (dir_.empty()) {
+        std::fprintf(stderr, "ds4 KvCache::Save: skipped (dir empty)\n");
+        return;
+    }
+    if (!session) {
+        std::fprintf(stderr, "ds4 KvCache::Save: skipped (session null)\n");
+        return;
+    }
+    std::string path = Path(rendered_text);
+    uint64_t payload_bytes = ds4_session_payload_bytes(session);
+    std::fprintf(stderr, "ds4 KvCache::Save: path=%s payload_bytes=%llu prefix_len=%zu\n",
+                 path.c_str(), (unsigned long long)payload_bytes, rendered_text.size());
+    FILE *fp = std::fopen(path.c_str(), "wb");
+    if (!fp) {
+        std::fprintf(stderr, "ds4 KvCache::Save: fopen failed: %s\n", std::strerror(errno));
+        return;
+    }
+    char magic[4] = {'D','S','4','G'};
+    uint32_t version = 1;
+    uint32_t ctx = static_cast<uint32_t>(ctx_size);
+    uint32_t prefix_len = static_cast<uint32_t>(rendered_text.size());
+    std::fwrite(magic, 4, 1, fp);
+    std::fwrite(&version, 4, 1, fp);
+    std::fwrite(&ctx, 4, 1, fp);
+    std::fwrite(&prefix_len, 4, 1, fp);
+    std::fwrite(rendered_text.data(), prefix_len, 1, fp);
+    std::fwrite(&payload_bytes, 8, 1, fp);
+    char errbuf[256] = {0};
+    int rc = ds4_session_save_payload(session, fp, errbuf, sizeof(errbuf));
+    std::fclose(fp);
+    if (rc != 0) {
+        std::fprintf(stderr, "ds4 KvCache::Save: ds4_session_save_payload rc=%d err=%s; removing %s\n",
+                     rc, errbuf, path.c_str());
+        std::remove(path.c_str());
+    } else {
+        std::fprintf(stderr, "ds4 KvCache::Save: wrote %s ok\n", path.c_str());
+    }
+}
+
+} // namespace ds4cpp

backend/cpp/ds4/kv_cache.h

@@ -0,0 +1,44 @@
+#pragma once
+#include <string>
+extern "C" {
+#include "ds4.h"
+}
+
+namespace ds4cpp {
+
+// Disk-backed KV cache for ds4 sessions. Keyed by SHA1(rendered prompt prefix).
+// Format (our own, NOT bit-compatible with ds4-server's KVC files - interop
+// is a follow-up plan):
+//
+//   "DS4G" (4 bytes magic) + u32 version=1 + u32 ctx_size +
+//   u32 prefix_text_len + prefix_text + u64 payload_bytes + payload
+class KvCache {
+public:
+    KvCache(); // disabled (dir empty)
+
+    // Set the cache directory. Empty disables.
+    void SetDir(const std::string &dir);
+
+    // Returns the cache file path for a given rendered text prefix.
+    std::string Path(const std::string &rendered_text) const;
+
+    // Look up the longest cached prefix that is also a prefix of
+    // `rendered_text`. Loads it into `session` if found. Returns the
+    // matched prefix length in bytes (0 if no hit).
+    size_t LoadLongestPrefix(ds4_session *session,
+                             const std::string &rendered_text,
+                             int ctx_size);
+
+    // Save the current session, associated with this rendered text prefix.
+    void Save(ds4_session *session, const std::string &rendered_text, int ctx_size);
+
+    bool enabled() const { return !dir_.empty(); }
+
+private:
+    std::string dir_;
+};
+
+// Compute SHA1 of arbitrary bytes; returns 40-char hex.
+std::string Sha1Hex(const void *data, size_t len);
+
+} // namespace ds4cpp

backend/cpp/ds4/package.sh

@@ -0,0 +1,39 @@
+#!/bin/bash
+set -e
+CURDIR=$(dirname "$(realpath "$0")")
+REPO_ROOT="${CURDIR}/../../.."
+
+mkdir -p "$CURDIR/package/lib"
+cp -avf "$CURDIR/grpc-server" "$CURDIR/package/"
+cp -rfv "$CURDIR/run.sh"     "$CURDIR/package/"
+
+UNAME_S=$(uname -s)
+if [ "$UNAME_S" = "Darwin" ]; then
+    # Darwin: bundle dylibs via otool -L (handled by scripts/build/ds4-darwin.sh).
+    echo "package.sh: Darwin handled by ds4-darwin.sh"
+    exit 0
+fi
+
+if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
+    cp -arfLv /lib64/ld-linux-x86-64.so.2 "$CURDIR/package/lib/ld.so"
+    LIBDIR=/lib/x86_64-linux-gnu
+elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
+    cp -arfLv /lib/ld-linux-aarch64.so.1 "$CURDIR/package/lib/ld.so"
+    LIBDIR=/lib/aarch64-linux-gnu
+else
+    echo "package.sh: unknown architecture" >&2; exit 1
+fi
+
+for lib in libc.so.6 libgcc_s.so.1 libstdc++.so.6 libm.so.6 libgomp.so.1 \
+           libdl.so.2 librt.so.1 libpthread.so.0; do
+    cp -arfLv "$LIBDIR/$lib" "$CURDIR/package/lib/$lib"
+done
+
+GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
+if [ -f "$GPU_LIB_SCRIPT" ]; then
+    source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
+    package_gpu_libs
+fi
+
+echo "ds4 package contents:"
+ls -lah "$CURDIR/package/" "$CURDIR/package/lib/"

backend/cpp/ds4/run.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+# Entry point for the ds4 backend image / BACKEND_BINARY mode.
+set -e
+CURDIR=$(dirname "$(realpath "$0")")
+export LD_LIBRARY_PATH="$CURDIR/lib:$LD_LIBRARY_PATH"
+if [ -f "$CURDIR/lib/ld.so" ]; then
+    exec "$CURDIR/lib/ld.so" "$CURDIR/grpc-server" "$@"
+fi
+exec "$CURDIR/grpc-server" "$@"

backend/cpp/ik-llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-IK_LLAMA_VERSION?=8b56d813a9ed04fa7b7fe2588fddd845cf64eccb
+IK_LLAMA_VERSION?=c35189d83c91aad780aba62b89f2830cb2916223
 LLAMA_REPO?=https://github.com/ikawrakow/ik_llama.cpp
 
 CMAKE_ARGS?=

backend/cpp/llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-LLAMA_VERSION?=bbeb89d76c41bc250f16e4a6fefcc9b530d6e3f3
+LLAMA_VERSION?=87589042cac2c390cec8d68fb2fad64e0a2a252a
 LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
 
 CMAKE_ARGS?=

backend/cpp/llama-cpp/grpc-server.cpp

@@ -32,10 +32,13 @@
 #include <grpcpp/health_check_service_interface.h>
 #include <grpcpp/security/server_credentials.h>
 #include <regex>
+#include <algorithm>
 #include <atomic>
 #include <cstdlib>
 #include <fstream>
 #include <iterator>
+#include <list>
+#include <map>
 #include <mutex>
 #include <signal.h>
 #include <thread>
@@ -443,10 +446,24 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
     // Draft model for speculative decoding
     if (!request->draftmodel().empty()) {
         params.speculative.draft.mparams.path = request->draftmodel();
-        // Default to draft type if a draft model is set but no explicit type
+        // Default to draft type if a draft model is set but no explicit type.
+        // Upstream (post ggml-org/llama.cpp#22838) made the speculative type a
+        // vector; the turboquant fork still uses the legacy scalar. The
+        // LOCALAI_LEGACY_LLAMA_CPP_SPEC macro is injected by
+        // backend/cpp/turboquant/patch-grpc-server.sh for fork builds only.
+        // Upstream renamed COMMON_SPECULATIVE_TYPE_DRAFT -> ..._DRAFT_SIMPLE
+        // in ggml-org/llama.cpp#22964; the fork still uses the old name.
+#ifdef LOCALAI_LEGACY_LLAMA_CPP_SPEC
         if (params.speculative.type == COMMON_SPECULATIVE_TYPE_NONE) {
             params.speculative.type = COMMON_SPECULATIVE_TYPE_DRAFT;
         }
+#else
+        const bool no_spec_type = params.speculative.types.empty() ||
+            (params.speculative.types.size() == 1 && params.speculative.types[0] == COMMON_SPECULATIVE_TYPE_NONE);
+        if (no_spec_type) {
+            params.speculative.types = { COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE };
+        }
+#endif
     }
 
     //  params.model_alias ??
@@ -671,12 +688,178 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
                     // If conversion fails, keep default value (8)
                 }
             }
+
+        // --- physical batch size (upstream -ub / --ubatch-size) ---
+        // Note: line ~482 already aliases n_ubatch to n_batch as a default; this
+        // option lets users decouple the two (useful for embeddings/rerank).
+        } else if (!strcmp(optname, "n_ubatch") || !strcmp(optname, "ubatch")) {
+            if (optval != NULL) {
+                try { params.n_ubatch = std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- main-model batch threads (upstream -tb / --threads-batch) ---
+        } else if (!strcmp(optname, "threads_batch") || !strcmp(optname, "n_threads_batch")) {
+            if (optval != NULL) {
+                try {
+                    int n = std::stoi(optval_str);
+                    if (n <= 0) n = (int)std::thread::hardware_concurrency();
+                    params.cpuparams_batch.n_threads = n;
+                } catch (...) {}
+            }
+
+        // --- pooling type for embeddings (upstream --pooling) ---
+        } else if (!strcmp(optname, "pooling_type") || !strcmp(optname, "pooling")) {
+            if (optval != NULL) {
+                if      (optval_str == "none") params.pooling_type = LLAMA_POOLING_TYPE_NONE;
+                else if (optval_str == "mean") params.pooling_type = LLAMA_POOLING_TYPE_MEAN;
+                else if (optval_str == "cls")  params.pooling_type = LLAMA_POOLING_TYPE_CLS;
+                else if (optval_str == "last") params.pooling_type = LLAMA_POOLING_TYPE_LAST;
+                else if (optval_str == "rank") params.pooling_type = LLAMA_POOLING_TYPE_RANK;
+                // unknown values silently leave UNSPECIFIED (auto-detect)
+            }
+
+        // --- llama log verbosity threshold (upstream -lv / --verbosity) ---
+        } else if (!strcmp(optname, "verbosity")) {
+            if (optval != NULL) {
+                try { params.verbosity = std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- O_DIRECT model loading (upstream --direct-io) ---
+        } else if (!strcmp(optname, "direct_io") || !strcmp(optname, "use_direct_io")) {
+            if (optval_str == "true" || optval_str == "1" || optval_str == "yes" || optval_str == "on" || optval_str == "enabled") {
+                params.use_direct_io = true;
+            } else if (optval_str == "false" || optval_str == "0" || optval_str == "no" || optval_str == "off" || optval_str == "disabled") {
+                params.use_direct_io = false;
+            }
+
+        // --- embedding normalization (upstream --embd-normalize) ---
+        // -1 none, 0 max-abs, 1 taxicab, 2 L2 (default), >2 p-norm
+        } else if (!strcmp(optname, "embd_normalize") || !strcmp(optname, "embedding_normalize")) {
+            if (optval != NULL) {
+                try { params.embd_normalize = std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- reasoning parser (upstream --reasoning-format) ---
+        // Picks the parser for <think> blocks emitted by reasoning models.
+        // none / auto / deepseek / deepseek-legacy
+        } else if (!strcmp(optname, "reasoning_format")) {
+            if (optval != NULL) {
+                if      (optval_str == "none")             params.reasoning_format = COMMON_REASONING_FORMAT_NONE;
+                else if (optval_str == "auto")             params.reasoning_format = COMMON_REASONING_FORMAT_AUTO;
+                else if (optval_str == "deepseek")         params.reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK;
+                else if (optval_str == "deepseek-legacy" || optval_str == "deepseek_legacy")
+                                                            params.reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK_LEGACY;
+                // unknown values silently keep the upstream default (DEEPSEEK)
+            }
+
+        // --- reasoning budget (upstream --reasoning-budget) ---
+        // -1 unlimited, 0 disabled, >0 token budget for thinking blocks.
+        // Distinct from per-request `enable_thinking` (chat_template_kwargs).
+        } else if (!strcmp(optname, "enable_reasoning") || !strcmp(optname, "reasoning_budget")) {
+            if (optval != NULL) {
+                try { params.enable_reasoning = std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- prefill assistant turn (upstream --no-prefill-assistant) ---
+        } else if (!strcmp(optname, "prefill_assistant")) {
+            if (optval_str == "true" || optval_str == "1" || optval_str == "yes" || optval_str == "on" || optval_str == "enabled") {
+                params.prefill_assistant = true;
+            } else if (optval_str == "false" || optval_str == "0" || optval_str == "no" || optval_str == "off" || optval_str == "disabled") {
+                params.prefill_assistant = false;
+            }
+
+        // --- mmproj GPU offload (upstream --no-mmproj-offload, inverted) ---
+        } else if (!strcmp(optname, "mmproj_use_gpu") || !strcmp(optname, "mmproj_offload")) {
+            if (optval_str == "true" || optval_str == "1" || optval_str == "yes" || optval_str == "on" || optval_str == "enabled") {
+                params.mmproj_use_gpu = true;
+            } else if (optval_str == "false" || optval_str == "0" || optval_str == "no" || optval_str == "off" || optval_str == "disabled") {
+                params.mmproj_use_gpu = false;
+            }
+
+        // --- per-image vision token budget (upstream --image-min/max-tokens) ---
+        } else if (!strcmp(optname, "image_min_tokens")) {
+            if (optval != NULL) {
+                try { params.image_min_tokens = std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "image_max_tokens")) {
+            if (optval != NULL) {
+                try { params.image_max_tokens = std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- main-model tensor buffer overrides (upstream --override-tensor) ---
+        // Format: <tensor regex>=<buffer type>,<tensor regex>=<buffer type>,...
+        // Mirrors the existing `draft_override_tensor` parser below.
+        } else if (!strcmp(optname, "override_tensor") || !strcmp(optname, "tensor_buft_overrides")) {
+            ggml_backend_load_all();
+            std::map<std::string, ggml_backend_buffer_type_t> buft_list;
+            for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
+                auto * dev = ggml_backend_dev_get(i);
+                auto * buft = ggml_backend_dev_buffer_type(dev);
+                if (buft) {
+                    buft_list[ggml_backend_buft_name(buft)] = buft;
+                }
+            }
+            static std::list<std::string> override_names;
+            std::string cur;
+            auto flush = [&](const std::string & spec) {
+                auto pos = spec.find('=');
+                if (pos == std::string::npos) return;
+                const std::string name = spec.substr(0, pos);
+                const std::string type = spec.substr(pos + 1);
+                auto it = buft_list.find(type);
+                if (it == buft_list.end()) return; // unknown buffer type: ignore
+                override_names.push_back(name);
+                params.tensor_buft_overrides.push_back(
+                    {override_names.back().c_str(), it->second});
+            };
+            for (char c : optval_str) {
+                if (c == ',') { if (!cur.empty()) { flush(cur); cur.clear(); } }
+                else { cur.push_back(c); }
+            }
+            if (!cur.empty()) flush(cur);
+
         // Speculative decoding options
         } else if (!strcmp(optname, "spec_type") || !strcmp(optname, "speculative_type")) {
-            auto type = common_speculative_type_from_name(optval_str);
+#ifdef LOCALAI_LEGACY_LLAMA_CPP_SPEC
+            // Fork only knows a single scalar `type`. Take the first comma-
+            // separated value and assign it via the singular helper.
+            std::string first = optval_str;
+            const auto comma = first.find(',');
+            if (comma != std::string::npos) first = first.substr(0, comma);
+            auto type = common_speculative_type_from_name(first);
             if (type != COMMON_SPECULATIVE_TYPE_COUNT) {
                 params.speculative.type = type;
             }
+#else
+            // Upstream switched to a vector of types (comma-separated for multi-type
+            // chaining via common_speculative_types_from_names). We keep accepting a
+            // single value here, but also tolerate comma-separated lists.
+            //
+            // ggml-org/llama.cpp#22964 also renamed the registered names from
+            // underscore- to dash-separated form, and replaced the bare
+            // `draft`/`eagle3` aliases with `draft-simple`/`draft-eagle3`. We
+            // normalize each token here so existing model configs keep working.
+            auto normalize_spec_name = [](std::string s) -> std::string {
+                std::replace(s.begin(), s.end(), '_', '-');
+                if (s == "draft")  return "draft-simple";
+                if (s == "eagle3") return "draft-eagle3";
+                return s;
+            };
+            std::vector<std::string> names;
+            std::string item;
+            for (char c : optval_str) {
+                if (c == ',') {
+                    if (!item.empty()) { names.push_back(normalize_spec_name(item)); item.clear(); }
+                } else {
+                    item.push_back(c);
+                }
+            }
+            if (!item.empty()) names.push_back(normalize_spec_name(item));
+            auto parsed = common_speculative_types_from_names(names);
+            if (!parsed.empty()) {
+                params.speculative.types = parsed;
+            }
+#endif
         } else if (!strcmp(optname, "spec_n_max") || !strcmp(optname, "draft_max")) {
             if (optval != NULL) {
                 try { params.speculative.draft.n_max = std::stoi(optval_str); } catch (...) {}
@@ -710,10 +893,155 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
                 try { params.speculative.draft.n_gpu_layers = std::stoi(optval_str); } catch (...) {}
             }
         } else if (!strcmp(optname, "draft_ctx_size")) {
-            if (optval != NULL) {
-                try { params.speculative.draft.n_ctx = std::stoi(optval_str); } catch (...) {}
-            }
+            // The draft context size is no longer a separate field upstream: the draft
+            // shares the target context size. Accept the option for backward
+            // compatibility but silently ignore it.
+
+// Everything below relies on struct shape introduced in ggml-org/llama.cpp#22838
+// (parallel drafting): `ngram_mod`, `ngram_map_k`, `ngram_map_k4v`,
+// `ngram_cache`, and the `draft.{cache_type_*, cpuparams*, tensor_buft_overrides}`
+// fields. The turboquant fork branched before that, so its build defines
+// LOCALAI_LEGACY_LLAMA_CPP_SPEC via patch-grpc-server.sh and these option
+// keys become unrecognized (silently dropped, like any unknown opt) for it.
+//
+// The `#ifdef LOCALAI_LEGACY_LLAMA_CPP_SPEC` / `#else` split below sits at the
+// closing-brace position of the `draft_ctx_size` branch on purpose: in the
+// legacy build the chain ends here (the brace closes draft_ctx_size), and in
+// the modern build the chain continues with `} else if (...)` instead, so the
+// brace count stays balanced under both branches of the preprocessor.
+#ifdef LOCALAI_LEGACY_LLAMA_CPP_SPEC
         }
+#else
+        // --- ngram_mod family (upstream --spec-ngram-mod-*) ---
+        } else if (!strcmp(optname, "spec_ngram_mod_n_min")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_mod.n_min = std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "spec_ngram_mod_n_max")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_mod.n_max = std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "spec_ngram_mod_n_match")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_mod.n_match = std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- ngram_map_k family (upstream --spec-ngram-map-k-*) ---
+        } else if (!strcmp(optname, "spec_ngram_map_k_size_n")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_map_k.size_n = (uint16_t)std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "spec_ngram_map_k_size_m")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_map_k.size_m = (uint16_t)std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "spec_ngram_map_k_min_hits")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_map_k.min_hits = (uint16_t)std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- ngram_map_k4v family (upstream --spec-ngram-map-k4v-*) ---
+        } else if (!strcmp(optname, "spec_ngram_map_k4v_size_n")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_map_k4v.size_n = (uint16_t)std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "spec_ngram_map_k4v_size_m")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_map_k4v.size_m = (uint16_t)std::stoi(optval_str); } catch (...) {}
+            }
+        } else if (!strcmp(optname, "spec_ngram_map_k4v_min_hits")) {
+            if (optval != NULL) {
+                try { params.speculative.ngram_map_k4v.min_hits = (uint16_t)std::stoi(optval_str); } catch (...) {}
+            }
+
+        // --- ngram lookup caches (upstream --lookup-cache-static / -dynamic) ---
+        } else if (!strcmp(optname, "spec_lookup_cache_static") || !strcmp(optname, "lookup_cache_static")) {
+            params.speculative.ngram_cache.lookup_cache_static = optval_str;
+        } else if (!strcmp(optname, "spec_lookup_cache_dynamic") || !strcmp(optname, "lookup_cache_dynamic")) {
+            params.speculative.ngram_cache.lookup_cache_dynamic = optval_str;
+
+        // --- draft model KV cache types (upstream --spec-draft-type-k / -v) ---
+        } else if (!strcmp(optname, "draft_cache_type_k") || !strcmp(optname, "spec_draft_cache_type_k")) {
+            params.speculative.draft.cache_type_k = kv_cache_type_from_str(optval_str);
+        } else if (!strcmp(optname, "draft_cache_type_v") || !strcmp(optname, "spec_draft_cache_type_v")) {
+            params.speculative.draft.cache_type_v = kv_cache_type_from_str(optval_str);
+
+        // --- draft model thread counts (upstream --spec-draft-threads / -batch) ---
+        } else if (!strcmp(optname, "draft_threads") || !strcmp(optname, "spec_draft_threads")) {
+            if (optval != NULL) {
+                try {
+                    int n = std::stoi(optval_str);
+                    if (n <= 0) n = (int)std::thread::hardware_concurrency();
+                    params.speculative.draft.cpuparams.n_threads = n;
+                } catch (...) {}
+            }
+        } else if (!strcmp(optname, "draft_threads_batch") || !strcmp(optname, "spec_draft_threads_batch")) {
+            if (optval != NULL) {
+                try {
+                    int n = std::stoi(optval_str);
+                    if (n <= 0) n = (int)std::thread::hardware_concurrency();
+                    params.speculative.draft.cpuparams_batch.n_threads = n;
+                } catch (...) {}
+            }
+
+        // --- draft model MoE on CPU (upstream --spec-draft-cpu-moe / --spec-draft-n-cpu-moe) ---
+        } else if (!strcmp(optname, "draft_cpu_moe") || !strcmp(optname, "spec_draft_cpu_moe")) {
+            // Bool-style flag: optval may be missing, "true"/"1"/"yes" enables.
+            const bool enable = (optval == NULL) ||
+                optval_str == "true" || optval_str == "1" || optval_str == "yes" ||
+                optval_str == "on" || optval_str == "enabled";
+            if (enable) {
+                params.speculative.draft.tensor_buft_overrides.push_back(llm_ffn_exps_cpu_override());
+            }
+        } else if (!strcmp(optname, "draft_n_cpu_moe") || !strcmp(optname, "spec_draft_n_cpu_moe")) {
+            if (optval != NULL) {
+                try {
+                    int n = std::stoi(optval_str);
+                    if (n < 0) n = 0;
+                    // Keep override-name storage alive for the lifetime of the params struct
+                    // (mirrors upstream arg.cpp behavior with a function-local static).
+                    static std::list<std::string> buft_overrides_draft;
+                    for (int i = 0; i < n; ++i) {
+                        buft_overrides_draft.push_back(llm_ffn_exps_block_regex(i));
+                        params.speculative.draft.tensor_buft_overrides.push_back(
+                            {buft_overrides_draft.back().c_str(), ggml_backend_cpu_buffer_type()});
+                    }
+                } catch (...) {}
+            }
+
+        // --- draft model tensor buffer overrides (upstream --spec-draft-override-tensor) ---
+        } else if (!strcmp(optname, "draft_override_tensor") || !strcmp(optname, "spec_draft_override_tensor")) {
+            // Format: <tensor regex>=<buffer type>,<tensor regex>=<buffer type>,...
+            // We replicate upstream's parse_tensor_buffer_overrides (static in arg.cpp).
+            ggml_backend_load_all();
+            std::map<std::string, ggml_backend_buffer_type_t> buft_list;
+            for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
+                auto * dev = ggml_backend_dev_get(i);
+                auto * buft = ggml_backend_dev_buffer_type(dev);
+                if (buft) {
+                    buft_list[ggml_backend_buft_name(buft)] = buft;
+                }
+            }
+            static std::list<std::string> draft_override_names;
+            std::string cur;
+            auto flush = [&](const std::string & spec) {
+                auto pos = spec.find('=');
+                if (pos == std::string::npos) return;
+                const std::string name = spec.substr(0, pos);
+                const std::string type = spec.substr(pos + 1);
+                auto it = buft_list.find(type);
+                if (it == buft_list.end()) return; // unknown buffer type: ignore
+                draft_override_names.push_back(name);
+                params.speculative.draft.tensor_buft_overrides.push_back(
+                    {draft_override_names.back().c_str(), it->second});
+            };
+            for (char c : optval_str) {
+                if (c == ',') { if (!cur.empty()) { flush(cur); cur.clear(); } }
+                else { cur.push_back(c); }
+            }
+            if (!cur.empty()) flush(cur);
+        }
+#endif // LOCALAI_LEGACY_LLAMA_CPP_SPEC — closes the `else`/`#ifdef` opened at draft_ctx_size
     }
 
     // Set params.n_parallel from environment variable if not set via options (fallback)
@@ -2610,7 +2938,9 @@ public:
             }
         }
 
-        int embd_normalize = 2; // default to Euclidean/L2 norm
+        // Honor the load-time embd_normalize set via options:embd_normalize.
+        // -1 none, 0 max-abs, 1 taxicab, 2 L2 (default), >2 p-norm.
+        int embd_normalize = params_base.embd_normalize;
         // create and queue the task
         auto rd = ctx_server.get_response_reader();
         {
@@ -2704,7 +3034,7 @@ public:
 
             tasks.reserve(documents.size());
             for (size_t i = 0; i < documents.size(); i++) {
-                auto tmp = format_prompt_rerank(ctx_server.impl->model, ctx_server.impl->vocab, ctx_server.impl->mctx, request->query(), documents[i]);
+                auto tmp = format_prompt_rerank(ctx_server.impl->model_tgt, ctx_server.impl->vocab, ctx_server.impl->mctx, request->query(), documents[i]);
                 server_task task = server_task(SERVER_TASK_TYPE_RERANK);
                 task.id = rd.queue_tasks.get_new_id();
                 task.index = i;
@@ -2882,7 +3212,7 @@ public:
                 // Get template source and reconstruct a common_chat_template for analysis
                 std::string tmpl_src = common_chat_templates_source(ctx_server.impl->chat_params.tmpls.get());
                 if (!tmpl_src.empty()) {
-                    const auto * vocab = llama_model_get_vocab(ctx_server.impl->model);
+                    const auto * vocab = llama_model_get_vocab(ctx_server.impl->model_tgt);
                     std::string token_bos, token_eos;
                     if (vocab) {
                         auto bos_id = llama_vocab_bos(vocab);

backend/cpp/turboquant/Makefile

@@ -1,7 +1,7 @@
 
 # Pinned to the HEAD of feature/turboquant-kv-cache on https://github.com/TheTom/llama-cpp-turboquant.
 # Auto-bumped nightly by .github/workflows/bump_deps.yaml.
-TURBOQUANT_VERSION?=69d8e4be47243e83b3d0d71e932bc7aa61c644dc
+TURBOQUANT_VERSION?=5aeb2fdbe26cd4c534c6fa15de73cb5749bd0403
 LLAMA_REPO?=https://github.com/TheTom/llama-cpp-turboquant
 
 CMAKE_ARGS?=

backend/cpp/turboquant/patch-grpc-server.sh

@@ -108,4 +108,47 @@ else
     echo "==> $SRC has no post-#22397 speculative field refs, skipping spec rename patch"
 fi
 
+# 4. Revert the `ctx_server.impl->model_tgt` rename introduced by upstream
+#    ggml-org/llama.cpp#22838 (parallel drafting). The turboquant fork still
+#    exposes the field as `model` on `server_context_impl`. The two call sites
+#    are in the Rerank and ModelMetadata RPC handlers.
+if grep -q 'ctx_server\.impl->model_tgt' "$SRC"; then
+    echo "==> patching $SRC to revert ctx_server.impl->model_tgt -> ctx_server.impl->model"
+    sed -E 's/ctx_server\.impl->model_tgt/ctx_server.impl->model/g' "$SRC" > "$SRC.tmp"
+    mv "$SRC.tmp" "$SRC"
+    echo "==> model_tgt rename OK"
+else
+    echo "==> $SRC has no ctx_server.impl->model_tgt refs, skipping model_tgt rename patch"
+fi
+
+# 5. Define LOCALAI_LEGACY_LLAMA_CPP_SPEC at the top of the file so the
+#    grpc-server option parser skips the new option-handler blocks (ngram_mod,
+#    ngram_map_k, ngram_map_k4v, ngram_cache, draft.cache_type_*, draft.cpuparams*,
+#    draft.tensor_buft_overrides) introduced for the post-#22838 layout. Those
+#    blocks reference struct fields that simply do not exist in the fork.
+if grep -q '^#define LOCALAI_LEGACY_LLAMA_CPP_SPEC' "$SRC"; then
+    echo "==> $SRC already defines LOCALAI_LEGACY_LLAMA_CPP_SPEC, skipping"
+else
+    echo "==> patching $SRC to define LOCALAI_LEGACY_LLAMA_CPP_SPEC at the top"
+    # Insert the define before the very first `#include` so it precedes all the
+    # speculative-decoding code paths.
+    awk '
+        !done && /^#include/ {
+            print "#define LOCALAI_LEGACY_LLAMA_CPP_SPEC 1"
+            print "// ^ injected by backend/cpp/turboquant/patch-grpc-server.sh"
+            print ""
+            done = 1
+        }
+        { print }
+        END {
+            if (!done) {
+                print "patch-grpc-server.sh: no #include anchor found to insert LOCALAI_LEGACY_LLAMA_CPP_SPEC" > "/dev/stderr"
+                exit 1
+            }
+        }
+    ' "$SRC" > "$SRC.tmp"
+    mv "$SRC.tmp" "$SRC"
+    echo "==> LOCALAI_LEGACY_LLAMA_CPP_SPEC define OK"
+fi
+
 echo "==> all patches applied"

backend/go/sherpa-onnx/backend.go

@@ -2,6 +2,7 @@ package main
 
 import (
 	"bytes"
+	"context"
 	"encoding/binary"
 	"fmt"
 	"os"
@@ -998,7 +999,7 @@ func (s *SherpaBackend) loadOnlineASR(opts *pb.ModelOptions) error {
 // Transcription
 // =============================================================
 
-func (s *SherpaBackend) AudioTranscription(req *pb.TranscriptRequest) (pb.TranscriptResult, error) {
+func (s *SherpaBackend) AudioTranscription(_ context.Context, req *pb.TranscriptRequest) (pb.TranscriptResult, error) {
 	if s.onlineRecognizer != 0 {
 		return s.runOnlineASR(req, nil)
 	}
@@ -1056,6 +1057,7 @@ func (s *SherpaBackend) AudioTranscription(req *pb.TranscriptRequest) (pb.Transc
 // Closes `results` before returning so the server wrapper's reader
 // goroutine can exit.
 func (s *SherpaBackend) AudioTranscriptionStream(
+	_ context.Context,
 	req *pb.TranscriptRequest,
 	results chan *pb.TranscriptStreamResponse,
 ) error {

backend/go/sherpa-onnx/backend_test.go

@@ -1,6 +1,7 @@
 package main
 
 import (
+	"context"
 	"os"
 	"path/filepath"
 	"testing"
@@ -79,7 +80,7 @@ var _ = Describe("Sherpa-ONNX", func() {
 		})
 
 		It("rejects AudioTranscription", func() {
-			_, err := (&SherpaBackend{}).AudioTranscription(&pb.TranscriptRequest{
+			_, err := (&SherpaBackend{}).AudioTranscription(context.Background(), &pb.TranscriptRequest{
 				Dst: "/tmp/nonexistent.wav",
 			})
 			Expect(err).To(HaveOccurred())

backend/go/stablediffusion-ggml/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # stablediffusion.cpp (ggml)
 STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
-STABLEDIFFUSION_GGML_VERSION?=3d6064b37ef4607917f8acf2ca8c8906d5087413
+STABLEDIFFUSION_GGML_VERSION?=bd17f53b7386fb5f60e8587b75e73c4b2fed3426
 
 CMAKE_ARGS+=-DGGML_MAX_NAME=128
 

backend/go/vibevoice-cpp/govibevoicecpp.go

@@ -1,6 +1,7 @@
 package main
 
 import (
+	"context"
 	"encoding/json"
 	"fmt"
 	"io"
@@ -480,7 +481,7 @@ func (w *byteWriter) Write(p []byte) (int, error) {
 	return len(p), nil
 }
 
-func (v *VibevoiceCpp) AudioTranscription(req *pb.TranscriptRequest) (pb.TranscriptResult, error) {
+func (v *VibevoiceCpp) AudioTranscription(_ context.Context, req *pb.TranscriptRequest) (pb.TranscriptResult, error) {
 	if v.asrModel == "" {
 		return pb.TranscriptResult{}, fmt.Errorf("vibevoice-cpp: AudioTranscription requested but no ASR model was loaded")
 	}
@@ -623,9 +624,9 @@ func (v *VibevoiceCpp) Diarize(req *pb.DiarizeRequest) (pb.DiarizeResponse, erro
 // transcription, emit each segment's content as a delta, then close
 // with a final_result whose Text equals the concatenated deltas (the
 // e2e harness asserts those match).
-func (v *VibevoiceCpp) AudioTranscriptionStream(req *pb.TranscriptRequest, results chan *pb.TranscriptStreamResponse) error {
+func (v *VibevoiceCpp) AudioTranscriptionStream(ctx context.Context, req *pb.TranscriptRequest, results chan *pb.TranscriptStreamResponse) error {
 	defer close(results)
-	res, err := v.AudioTranscription(req)
+	res, err := v.AudioTranscription(ctx, req)
 	if err != nil {
 		return err
 	}

backend/go/vibevoice-cpp/vibevoicecpp_test.go

@@ -107,7 +107,7 @@ var _ = Describe("VibeVoice-cpp", func() {
 		})
 
 		It("rejects AudioTranscription without a loaded ASR model", func() {
-			_, err := (&VibevoiceCpp{}).AudioTranscription(&pb.TranscriptRequest{
+			_, err := (&VibevoiceCpp{}).AudioTranscription(context.Background(), &pb.TranscriptRequest{
 				Dst: "/tmp/some.wav",
 			})
 			Expect(err).To(HaveOccurred())
@@ -255,7 +255,7 @@ var _ = Describe("VibeVoice-cpp", func() {
 
 		It("closes the channel and errors on AudioTranscriptionStream without a loaded model", func() {
 			ch := make(chan *pb.TranscriptStreamResponse, 4)
-			err := (&VibevoiceCpp{}).AudioTranscriptionStream(&pb.TranscriptRequest{
+			err := (&VibevoiceCpp{}).AudioTranscriptionStream(context.Background(), &pb.TranscriptRequest{
 				Dst: "/tmp/some.wav",
 			}, ch)
 			Expect(err).To(HaveOccurred())

backend/go/voxtral/govoxtral.go

@@ -1,6 +1,7 @@
 package main
 
 import (
+	"context"
 	"fmt"
 	"os"
 	"strings"
@@ -27,7 +28,7 @@ func (v *Voxtral) Load(opts *pb.ModelOptions) error {
 	return nil
 }
 
-func (v *Voxtral) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
+func (v *Voxtral) AudioTranscription(_ context.Context, opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
 	dir, err := os.MkdirTemp("", "voxtral")
 	if err != nil {
 		return pb.TranscriptResult{}, err

backend/go/whisper/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
-WHISPER_CPP_VERSION?=4bf733672b2871d4153158af4f621a6dd9104f4a
+WHISPER_CPP_VERSION?=968eebe77225d25e57a3f981da7c696310f0e881
 SO_TARGET?=libgowhisper.so
 
 CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF

backend/go/whisper/cpp/gowhisper.cpp

@@ -1,12 +1,47 @@
 #include "gowhisper.h"
 #include "ggml-backend.h"
 #include "whisper.h"
+#include <atomic>
 #include <vector>
 
 static struct whisper_vad_context *vctx;
 static struct whisper_context *ctx;
 static std::vector<float> flat_segs;
 
+static std::atomic<int> g_abort{0};
+
+static std::atomic<uintptr_t> g_go_new_segment_cb{0};
+static std::atomic<uintptr_t> g_go_new_segment_user_data{0};
+
+static bool abort_cb(void * /*user_data*/) {
+    return g_abort.load(std::memory_order_relaxed) != 0;
+}
+
+static void new_segment_cb(struct whisper_context *cb_ctx,
+                           struct whisper_state * /*state*/, int n_new,
+                           void * /*user_data*/) {
+    uintptr_t go_cb = g_go_new_segment_cb.load(std::memory_order_relaxed);
+    if (go_cb == 0) {
+        return;
+    }
+    int total = whisper_full_n_segments(cb_ctx);
+    int idx_first = total - n_new;
+    if (idx_first < 0) {
+        idx_first = 0;
+    }
+    uintptr_t ud = g_go_new_segment_user_data.load(std::memory_order_relaxed);
+    reinterpret_cast<go_new_segment_cb>(go_cb)(idx_first, n_new, ud);
+}
+
+extern "C" void set_abort(int v) {
+    g_abort.store(v, std::memory_order_relaxed);
+}
+
+extern "C" void set_new_segment_callback(uintptr_t cb_ptr, uintptr_t user_data) {
+    g_go_new_segment_cb.store(cb_ptr, std::memory_order_relaxed);
+    g_go_new_segment_user_data.store(user_data, std::memory_order_relaxed);
+}
+
 static void ggml_log_cb(enum ggml_log_level level, const char *log,
                         void *data) {
   const char *level_str;
@@ -124,10 +159,28 @@ int transcribe(uint32_t threads, char *lang, bool translate, bool tdrz,
   wparams.tdrz_enable = tdrz;
   wparams.initial_prompt = prompt;
 
+  // Reset stale abort flag from any prior cancelled call, then install the
+  // ggml abort hook so a subsequent set_abort(1) from Go aborts the next
+  // compute graph step.
+  g_abort.store(0, std::memory_order_relaxed);
+  // Only install the new-segment callback when streaming is requested
+  // (Go side calls set_new_segment_callback before transcribe()). Leaving
+  // it always-on is harmless but adds a function-pointer dispatch per
+  // segment for the offline path.
+  if (g_go_new_segment_cb.load(std::memory_order_relaxed) != 0) {
+      wparams.new_segment_callback = new_segment_cb;
+      wparams.new_segment_callback_user_data = nullptr;
+  }
+  wparams.abort_callback = abort_cb;
+  wparams.abort_callback_user_data = nullptr;
+
   fprintf(stderr, "info: Enable tdrz: %d\n", tdrz);
   fprintf(stderr, "info: Initial prompt: \"%s\"\n", prompt);
 
   if (whisper_full(ctx, wparams, pcmf32, pcmf32_len)) {
+    if (g_abort.load(std::memory_order_relaxed)) {
+      return 2;   // aborted by client
+    }
     fprintf(stderr, "error: transcription failed\n");
     return 1;
   }

backend/go/whisper/cpp/gowhisper.h

@@ -15,4 +15,16 @@ int64_t get_segment_t1(int i);
 int n_tokens(int i);
 int32_t get_token_id(int i, int j);
 bool get_segment_speaker_turn_next(int i);
+void set_abort(int v);
+
+// Function pointer from Go (returned by purego.NewCallback). Invoked once
+// per new-segment event during whisper_full(). The callback runs on the
+// decode thread - if Go blocks (slow gRPC consumer), the decode blocks
+// too. That is the intended backpressure path.
+typedef void (*go_new_segment_cb)(int idx_first, int n_new, uintptr_t user_data);
+
+// Install the callback used by the next transcribe() call. Pass cb=0 to
+// clear. user_data is opaque to C; the Go side uses it to look up
+// per-call state.
+void set_new_segment_callback(uintptr_t cb_ptr, uintptr_t user_data);
 }

backend/go/whisper/gowhisper.go

@@ -1,16 +1,21 @@
 package main
 
 import (
+	"context"
 	"fmt"
 	"os"
 	"path/filepath"
 	"strings"
+	"sync"
+	"sync/atomic"
 	"unsafe"
 
 	"github.com/go-audio/wav"
 	"github.com/mudler/LocalAI/pkg/grpc/base"
 	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
 	"github.com/mudler/LocalAI/pkg/utils"
+	"google.golang.org/grpc/codes"
+	"google.golang.org/grpc/status"
 )
 
 var (
@@ -24,8 +29,84 @@ var (
 	CppNTokens                   func(i int) int
 	CppGetTokenID                func(i int, j int) int
 	CppGetSegmentSpeakerTurnNext func(i int) bool
+	CppSetAbort                  func(v int)
+	// Set by main.go via purego.RegisterLibFunc. Installs (or clears with cb=0)
+	// the C-side trampoline that whisper.cpp invokes per new segment.
+	CppSetNewSegmentCallback func(cbPtr uintptr, userData uintptr)
 )
 
+// streamCallStates maps per-AudioTranscriptionStream call IDs to the
+// state the Go callback needs to emit deltas. Only one entry is ever
+// live today (base.SingleThread), but the map shape mirrors
+// sherpa-onnx's TTS callback registry and survives a future SingleThread
+// removal without a contract change.
+var (
+	streamCallStates sync.Map // uint64 -> *streamCallState
+	streamCallSeq    atomic.Uint64
+	goNewSegmentCb   uintptr // purego.NewCallback(onNewSegment) result; set in main.go at boot
+)
+
+type streamCallState struct {
+	results chan *pb.TranscriptStreamResponse
+	diarize bool
+	// nextIdx tracks how many segments we've already emitted. The C
+	// trampoline passes idx_first = total - n_new, but we walk from
+	// nextIdx to (idx_first + n_new) defensively in case whisper.cpp ever
+	// coalesces multiple commits into a single callback invocation.
+	nextIdx int
+	// assembled mirrors the literal concat of every Delta sent on results.
+	// We reuse it as the final TranscriptResult.Text so the e2e
+	// invariant `final.Text == concat(deltas)` holds exactly. Written from
+	// the cgo decode thread inside onNewSegment and read by the streaming
+	// method after CppTranscribe returns; the cgo boundary provides the
+	// happens-before edge.
+	assembled strings.Builder
+}
+
+// onNewSegment is the Go side of the C trampoline declared in
+// gowhisper.cpp:new_segment_cb. Whisper.cpp invokes it once per
+// new-segment event during whisper_full(). Reads segment text via the
+// existing CppGetSegment* getters (safe to call against the singleton
+// ctx; whisper.cpp is the only writer and it has already published the
+// segments by the time this fires).
+//
+// Sends deltas synchronously: if the channel is full, this blocks the
+// whisper decode thread. That's the intended backpressure path -
+// dropping deltas would break the concat(deltas) == final.Text invariant
+// the e2e suite asserts.
+func onNewSegment(idxFirst int32, nNew int32, userData uintptr) {
+	v, ok := streamCallStates.Load(uint64(userData))
+	if !ok {
+		return // call already torn down (race with cancel + cb fire)
+	}
+	state := v.(*streamCallState)
+	end := int(idxFirst) + int(nNew)
+	for i := state.nextIdx; i < end; i++ {
+		txt := strings.ToValidUTF8(strings.Clone(CppGetSegmentText(i)), "<22>")
+		txt = strings.TrimSpace(txt)
+		if state.diarize && CppGetSegmentSpeakerTurnNext(i) {
+			txt += " [SPEAKER_TURN]"
+		}
+		if txt == "" {
+			state.nextIdx = i + 1
+			continue
+		}
+		// Prefix subsequent deltas with a single space so the assembled
+		// stream reads as one space-joined transcript. The first delta has
+		// no leading space, otherwise concat(deltas) would not match
+		// final.Text and the e2e invariant would break.
+		var delta string
+		if state.assembled.Len() == 0 {
+			delta = txt
+		} else {
+			delta = " " + txt
+		}
+		state.results <- &pb.TranscriptStreamResponse{Delta: delta}
+		state.assembled.WriteString(delta)
+		state.nextIdx = i + 1
+	}
+}
+
 type Whisper struct {
 	base.SingleThread
 }
@@ -92,7 +173,11 @@ func (w *Whisper) VAD(req *pb.VADRequest) (pb.VADResponse, error) {
 	}, nil
 }
 
-func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
+func (w *Whisper) AudioTranscription(ctx context.Context, opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
+	if err := ctx.Err(); err != nil {
+		return pb.TranscriptResult{}, status.Error(codes.Canceled, "transcription cancelled")
+	}
+
 	dir, err := os.MkdirTemp("", "whisper")
 	if err != nil {
 		return pb.TranscriptResult{}, err
@@ -105,14 +190,12 @@ func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptR
 		return pb.TranscriptResult{}, err
 	}
 
-	// Open samples
 	fh, err := os.Open(convertedPath)
 	if err != nil {
 		return pb.TranscriptResult{}, err
 	}
 	defer fh.Close()
 
-	// Read samples
 	d := wav.NewDecoder(fh)
 	buf, err := d.FullPCMBuffer()
 	if err != nil {
@@ -120,8 +203,6 @@ func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptR
 	}
 
 	data := buf.AsFloat32Buffer().Data
-	// whisper.cpp resamples to 16 kHz internally; this matches buf.Format.SampleRate
-	// for the converted file produced by AudioToWav above.
 	var duration float32
 	if buf.Format != nil && buf.Format.SampleRate > 0 {
 		duration = float32(len(data)) / float32(buf.Format.SampleRate)
@@ -129,7 +210,31 @@ func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptR
 	segsLen := uintptr(0xdeadbeef)
 	segsLenPtr := unsafe.Pointer(&segsLen)
 
-	if ret := CppTranscribe(opts.Threads, opts.Language, opts.Translate, opts.Diarize, data, uintptr(len(data)), segsLenPtr, opts.Prompt); ret != 0 {
+	// Watcher: flips the C-side abort flag when ctx is cancelled. The
+	// goroutine is joined synchronously (close(done) signals it to exit,
+	// wg.Wait() blocks until it has) so a late CppSetAbort(1) cannot fire
+	// after the function returns and corrupt the next transcription call.
+	done := make(chan struct{})
+	var wg sync.WaitGroup
+	wg.Add(1)
+	go func() {
+		defer wg.Done()
+		select {
+		case <-ctx.Done():
+			CppSetAbort(1)
+		case <-done:
+		}
+	}()
+	defer func() {
+		close(done)
+		wg.Wait()
+	}()
+
+	ret := CppTranscribe(opts.Threads, opts.Language, opts.Translate, opts.Diarize, data, uintptr(len(data)), segsLenPtr, opts.Prompt)
+	if ret == 2 {
+		return pb.TranscriptResult{}, status.Error(codes.Canceled, "transcription cancelled")
+	}
+	if ret != 0 {
 		return pb.TranscriptResult{}, fmt.Errorf("Failed Transcribe")
 	}
 
@@ -171,3 +276,120 @@ func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptR
 		Duration: duration,
 	}, nil
 }
+
+// AudioTranscriptionStream runs whisper_full() and emits deltas via
+// whisper.cpp's new_segment_callback as segments are decoded, then a
+// final TranscriptResult. The offline AudioTranscription is unchanged;
+// both paths share whisper's single-instance ctx and the SingleThread
+// concurrency model.
+func (w *Whisper) AudioTranscriptionStream(ctx context.Context, opts *pb.TranscriptRequest, results chan *pb.TranscriptStreamResponse) error {
+	defer close(results)
+
+	if err := ctx.Err(); err != nil {
+		return status.Error(codes.Canceled, "transcription cancelled")
+	}
+
+	dir, err := os.MkdirTemp("", "whisper")
+	if err != nil {
+		return err
+	}
+	defer func() { _ = os.RemoveAll(dir) }()
+
+	convertedPath := filepath.Join(dir, "converted.wav")
+	if err := utils.AudioToWav(opts.Dst, convertedPath); err != nil {
+		return err
+	}
+
+	fh, err := os.Open(convertedPath)
+	if err != nil {
+		return err
+	}
+	defer func() { _ = fh.Close() }()
+
+	d := wav.NewDecoder(fh)
+	buf, err := d.FullPCMBuffer()
+	if err != nil {
+		return err
+	}
+	data := buf.AsFloat32Buffer().Data
+	var duration float32
+	if buf.Format != nil && buf.Format.SampleRate > 0 {
+		duration = float32(len(data)) / float32(buf.Format.SampleRate)
+	}
+
+	// Register per-call state and install the C-side callback. defer
+	// teardown so even a panic clears the C pointer (otherwise a stale
+	// callback fires on the next AudioTranscription call).
+	callID := streamCallSeq.Add(1)
+	state := &streamCallState{
+		results: results,
+		diarize: opts.Diarize,
+	}
+	streamCallStates.Store(callID, state)
+	CppSetNewSegmentCallback(goNewSegmentCb, uintptr(callID))
+	defer func() {
+		CppSetNewSegmentCallback(0, 0)
+		streamCallStates.Delete(callID)
+	}()
+
+	// Same abort-watcher pattern as AudioTranscription. Joined synchronously
+	// so a late CppSetAbort(1) cannot fire after this function returns.
+	done := make(chan struct{})
+	var wg sync.WaitGroup
+	wg.Add(1)
+	go func() {
+		defer wg.Done()
+		select {
+		case <-ctx.Done():
+			CppSetAbort(1)
+		case <-done:
+		}
+	}()
+	defer func() {
+		close(done)
+		wg.Wait()
+	}()
+
+	segsLen := uintptr(0xdeadbeef)
+	segsLenPtr := unsafe.Pointer(&segsLen)
+	ret := CppTranscribe(opts.Threads, opts.Language, opts.Translate, opts.Diarize, data, uintptr(len(data)), segsLenPtr, opts.Prompt)
+	if ret == 2 {
+		return status.Error(codes.Canceled, "transcription cancelled")
+	}
+	if ret != 0 {
+		return fmt.Errorf("Failed Transcribe")
+	}
+
+	// Build the final TranscriptResult. Segments[] mirrors the offline
+	// path so the SSE done event carries the same per-segment shape.
+	// final.Text reuses the assembled stream so concat(deltas) == final.Text
+	// holds exactly, matching the e2e contract.
+	segments := []*pb.TranscriptSegment{}
+	for i := range int(segsLen) {
+		s := CppGetSegmentStart(i) * 10000000
+		t := CppGetSegmentEnd(i) * 10000000
+		txt := strings.ToValidUTF8(strings.Clone(CppGetSegmentText(i)), "<22>")
+		tokens := make([]int32, CppNTokens(i))
+		if opts.Diarize && CppGetSegmentSpeakerTurnNext(i) {
+			txt += " [SPEAKER_TURN]"
+		}
+		for j := range tokens {
+			tokens[j] = int32(CppGetTokenID(i, j))
+		}
+		segments = append(segments, &pb.TranscriptSegment{
+			Id:    int32(i),
+			Text:  txt,
+			Start: s, End: t,
+			Tokens: tokens,
+		})
+	}
+
+	final := &pb.TranscriptResult{
+		Segments: segments,
+		Text:     state.assembled.String(),
+		Language: opts.Language,
+		Duration: duration,
+	}
+	results <- &pb.TranscriptStreamResponse{FinalResult: final}
+	return nil
+}

backend/go/whisper/gowhisper_test.go

@@ -0,0 +1,174 @@
+package main
+
+import (
+	"context"
+	"os"
+	"strings"
+	"sync"
+	"testing"
+	"time"
+
+	"github.com/ebitengine/purego"
+	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+	"google.golang.org/grpc/codes"
+	"google.golang.org/grpc/status"
+)
+
+func TestWhisper(t *testing.T) {
+	RegisterFailHandler(Fail)
+	RunSpecs(t, "Whisper Backend Suite")
+}
+
+var (
+	libLoadOnce sync.Once
+	libLoadErr  error
+)
+
+// ensureLibLoaded mirrors main.go's bootstrap so a Go test can drive the
+// bridge without spinning up the gRPC server. Skips the current spec when the
+// shared library isn't present (e.g. running before `make backends/whisper`).
+func ensureLibLoaded() {
+	libLoadOnce.Do(func() {
+		libName := os.Getenv("WHISPER_LIBRARY")
+		if libName == "" {
+			libName = "./libgowhisper-fallback.so"
+		}
+		if _, err := os.Stat(libName); err != nil {
+			libLoadErr = err
+			return
+		}
+		gosd, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
+		if err != nil {
+			libLoadErr = err
+			return
+		}
+		purego.RegisterLibFunc(&CppLoadModel, gosd, "load_model")
+		purego.RegisterLibFunc(&CppTranscribe, gosd, "transcribe")
+		purego.RegisterLibFunc(&CppGetSegmentText, gosd, "get_segment_text")
+		purego.RegisterLibFunc(&CppGetSegmentStart, gosd, "get_segment_t0")
+		purego.RegisterLibFunc(&CppGetSegmentEnd, gosd, "get_segment_t1")
+		purego.RegisterLibFunc(&CppNTokens, gosd, "n_tokens")
+		purego.RegisterLibFunc(&CppGetTokenID, gosd, "get_token_id")
+		purego.RegisterLibFunc(&CppGetSegmentSpeakerTurnNext, gosd, "get_segment_speaker_turn_next")
+		purego.RegisterLibFunc(&CppSetAbort, gosd, "set_abort")
+		purego.RegisterLibFunc(&CppSetNewSegmentCallback, gosd, "set_new_segment_callback")
+	})
+	if libLoadErr != nil {
+		Skip("whisper library not loadable: " + libLoadErr.Error())
+	}
+}
+
+// fixturesOrSkip returns the model + audio paths or skips the spec if either
+// env var is unset. The test never runs in default CI — it requires a real
+// whisper model and a long audio file (~3 minutes) on disk.
+func fixturesOrSkip() (string, string) {
+	modelPath := os.Getenv("WHISPER_MODEL_PATH")
+	audioPath := os.Getenv("WHISPER_AUDIO_PATH")
+	if modelPath == "" || audioPath == "" {
+		Skip("set WHISPER_MODEL_PATH and WHISPER_AUDIO_PATH to run this spec")
+	}
+	return modelPath, audioPath
+}
+
+var _ = Describe("Whisper", func() {
+	Context("AudioTranscription cancellation", func() {
+		It("returns codes.Canceled and resets the abort flag for the next call", func() {
+			modelPath, audioPath := fixturesOrSkip()
+			ensureLibLoaded()
+
+			w := &Whisper{}
+			Expect(w.Load(&pb.ModelOptions{ModelFile: modelPath})).To(Succeed())
+
+			ctx, cancel := context.WithCancel(context.Background())
+			go func() {
+				time.Sleep(100 * time.Millisecond)
+				cancel()
+			}()
+
+			start := time.Now()
+			_, err := w.AudioTranscription(ctx, &pb.TranscriptRequest{
+				Dst:      audioPath,
+				Threads:  4,
+				Language: "en",
+			})
+			elapsed := time.Since(start)
+
+			Expect(err).To(HaveOccurred(), "transcription completed in %s without cancel — try a longer audio file", elapsed)
+			st, ok := status.FromError(err)
+			Expect(ok).To(BeTrue(), "expected gRPC status error, got %v", err)
+			Expect(st.Code()).To(Equal(codes.Canceled), "expected codes.Canceled, got %v", err)
+			Expect(elapsed).To(BeNumerically("<", 5*time.Second), "cancellation took %s, expected <5s", elapsed)
+
+			// Subsequent transcription must succeed — proves g_abort reset.
+			res, err := w.AudioTranscription(context.Background(), &pb.TranscriptRequest{
+				Dst:      audioPath,
+				Threads:  4,
+				Language: "en",
+			})
+			Expect(err).ToNot(HaveOccurred(), "post-cancel transcription failed")
+			Expect(res.Text).ToNot(BeEmpty(), "post-cancel transcription returned empty text")
+		})
+	})
+
+	Context("AudioTranscriptionStream", func() {
+		It("emits multiple deltas progressively for a multi-segment clip", func() {
+			modelPath, audioPath := fixturesOrSkip()
+			ensureLibLoaded()
+
+			// The streaming method dispatches through the package-level
+			// goNewSegmentCb. main.go normally builds it; in this test
+			// process main() is never called, so build it here lazily.
+			// purego.NewCallback returns a stable pointer; calling it once
+			// per process is correct.
+			if goNewSegmentCb == 0 {
+				goNewSegmentCb = purego.NewCallback(onNewSegment)
+			}
+
+			w := &Whisper{}
+			Expect(w.Load(&pb.ModelOptions{ModelFile: modelPath})).To(Succeed())
+
+			results := make(chan *pb.TranscriptStreamResponse, 64)
+			done := make(chan error, 1)
+			go func() {
+				done <- w.AudioTranscriptionStream(context.Background(), &pb.TranscriptRequest{
+					Dst:      audioPath,
+					Threads:  4,
+					Language: "en",
+					Stream:   true,
+				}, results)
+			}()
+
+			var deltas []string
+			var assembled strings.Builder
+			var finalText string
+			var finalSegmentCount int
+			for chunk := range results {
+				if d := chunk.GetDelta(); d != "" {
+					deltas = append(deltas, d)
+					assembled.WriteString(d)
+				}
+				if final := chunk.GetFinalResult(); final != nil {
+					finalText = final.GetText()
+					finalSegmentCount = len(final.GetSegments())
+				}
+			}
+			Expect(<-done).ToNot(HaveOccurred())
+
+			// The whisper-specific bar: real streaming via new_segment_callback
+			// fires once per decoded segment, so a multi-segment clip MUST
+			// produce >=2 delta events. A faked-streaming impl (run
+			// whisper_full to completion, then walk the segment list) would
+			// also pass len(deltas) >= 1, which is why the generic e2e spec
+			// is not strict enough.
+			Expect(len(deltas)).To(BeNumerically(">=", 2),
+				"expected multiple deltas from a multi-segment clip, got %d (assembled=%q)",
+				len(deltas), assembled.String())
+			Expect(finalSegmentCount).To(BeNumerically(">=", 2),
+				"expected final to carry multiple segments")
+			Expect(assembled.String()).To(Equal(finalText),
+				"concat(deltas) must equal final.Text")
+		})
+	})
+})

backend/go/whisper/main.go

@@ -41,12 +41,19 @@ func main() {
 		{&CppNTokens, "n_tokens"},
 		{&CppGetTokenID, "get_token_id"},
 		{&CppGetSegmentSpeakerTurnNext, "get_segment_speaker_turn_next"},
+		{&CppSetAbort, "set_abort"},
+		{&CppSetNewSegmentCallback, "set_new_segment_callback"},
 	}
 
 	for _, lf := range libFuncs {
 		purego.RegisterLibFunc(lf.FuncPtr, gosd, lf.Name)
 	}
 
+	// Build a stable C-callable function pointer from the Go callback. The
+	// pointer lives for the lifetime of the process; per-call dispatch is
+	// keyed by user_data through streamCallStates.
+	goNewSegmentCb = purego.NewCallback(onNewSegment)
+
 	flag.Parse()
 
 	if err := grpc.StartServer(*addr, &Whisper{}); err != nil {

backend/index.yaml

@@ -72,6 +72,29 @@
     nvidia-cuda-12: "cuda12-turboquant"
     nvidia-l4t-cuda-12: "nvidia-l4t-arm64-turboquant"
     nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-turboquant"
+- &ds4
+  name: "ds4"
+  alias: "ds4"
+  license: mit
+  description: |
+    antirez/ds4 - DeepSeek V4 Flash inference engine. Single-model,
+    optimized for Metal (Darwin) and CUDA (Linux). Requires the GGUFs
+    published at huggingface.co/antirez/deepseek-v4-gguf.
+  urls:
+    - https://github.com/antirez/ds4
+  tags:
+    - text-to-text
+    - LLM
+    - CPU
+    - CUDA
+    - Metal
+  capabilities:
+    default: "cpu-ds4"
+    nvidia: "cuda13-ds4"
+    nvidia-cuda-13: "cuda13-ds4"
+    nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-ds4"
+    metal: "metal-ds4"
+    metal-darwin-arm64: "metal-ds4"
 - &whispercpp
   name: "whisper"
   alias: "whisper"
@@ -287,6 +310,7 @@
     amd: "rocm-sglang"
     intel: "intel-sglang"
     nvidia-cuda-12: "cuda12-sglang"
+    nvidia-cuda-13: "cuda13-sglang"
     nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-sglang"
     cpu: "cpu-sglang"
 - &vllm-omni
@@ -823,6 +847,35 @@
     nvidia-l4t-cuda-12: "nvidia-l4t-vibevoice"
     nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vibevoice"
   icon: https://avatars.githubusercontent.com/u/6154722?s=200&v=4
+- &liquid-audio
+  urls:
+    - https://github.com/Liquid4All/liquid-audio
+    - https://huggingface.co/LiquidAI/LFM2.5-Audio-1.5B
+  description: |
+    LiquidAI LFM2 / LFM2.5 Audio Python backend. End-to-end speech-to-speech, ASR,
+    TTS (4 baked voices), and text chat from a single 1.5B model. Wraps the
+    upstream `liquid-audio` package; supports fine-tuning via LocalAI's
+    /v1/fine-tuning/jobs endpoint.
+  tags:
+    - speech-to-speech
+    - any-to-any
+    - text-to-speech
+    - speech-to-text
+    - TTS
+    - ASR
+    - realtime
+  license: LFM-Open-License-v1.0
+  name: "liquid-audio"
+  alias: "liquid-audio"
+  capabilities:
+    nvidia: "cuda12-liquid-audio"
+    intel: "intel-liquid-audio"
+    amd: "rocm-liquid-audio"
+    default: "cpu-liquid-audio"
+    nvidia-cuda-13: "cuda13-liquid-audio"
+    nvidia-cuda-12: "cuda12-liquid-audio"
+    nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-liquid-audio"
+  icon: https://cdn-avatars.huggingface.co/v1/production/uploads/61b8e2ba285851687028d395/7_6D7rWrLxp2hb6OHSV1p.png
 - &qwen-tts
   urls:
     - https://github.com/QwenLM/Qwen3-TTS
@@ -1126,6 +1179,15 @@
     nvidia-cuda-12: "cuda12-turboquant-development"
     nvidia-l4t-cuda-12: "nvidia-l4t-arm64-turboquant-development"
     nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-turboquant-development"
+- !!merge <<: *ds4
+  name: "ds4-development"
+  capabilities:
+    default: "cpu-ds4-development"
+    nvidia: "cuda13-ds4-development"
+    nvidia-cuda-13: "cuda13-ds4-development"
+    nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-ds4-development"
+    metal: "metal-ds4-development"
+    metal-darwin-arm64: "metal-ds4-development"
 - !!merge <<: *stablediffusionggml
   name: "stablediffusion-ggml-development"
   capabilities:
@@ -1672,6 +1734,47 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-turboquant"
   mirrors:
     - localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-turboquant
+## ds4
+- !!merge <<: *ds4
+  name: "cpu-ds4"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-ds4"
+  mirrors:
+    - localai/localai-backends:latest-cpu-ds4
+- !!merge <<: *ds4
+  name: "cpu-ds4-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-cpu-ds4"
+  mirrors:
+    - localai/localai-backends:master-cpu-ds4
+- !!merge <<: *ds4
+  name: "cuda13-ds4"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-ds4"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-13-ds4
+- !!merge <<: *ds4
+  name: "cuda13-ds4-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-ds4"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-13-ds4
+- !!merge <<: *ds4
+  name: "cuda13-nvidia-l4t-arm64-ds4"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-ds4"
+  mirrors:
+    - localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-ds4
+- !!merge <<: *ds4
+  name: "cuda13-nvidia-l4t-arm64-ds4-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-ds4"
+  mirrors:
+    - localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-ds4
+- !!merge <<: *ds4
+  name: "metal-ds4"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-ds4"
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-ds4
+- !!merge <<: *ds4
+  name: "metal-ds4-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-ds4"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-ds4
 ## whisper
 - !!merge <<: *whispercpp
   name: "whisper-development"
@@ -1965,6 +2068,7 @@
     amd: "rocm-sglang-development"
     intel: "intel-sglang-development"
     nvidia-cuda-12: "cuda12-sglang-development"
+    nvidia-cuda-13: "cuda13-sglang-development"
     nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-sglang-development"
     cpu: "cpu-sglang-development"
 - !!merge <<: *sglang
@@ -1972,6 +2076,11 @@
   uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-sglang"
   mirrors:
     - localai/localai-backends:latest-gpu-nvidia-cuda-12-sglang
+- !!merge <<: *sglang
+  name: "cuda13-sglang"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-sglang"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-13-sglang
 - !!merge <<: *sglang
   name: "cuda13-nvidia-l4t-arm64-sglang"
   uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-sglang"
@@ -1997,6 +2106,11 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-sglang"
   mirrors:
     - localai/localai-backends:master-gpu-nvidia-cuda-12-sglang
+- !!merge <<: *sglang
+  name: "cuda13-sglang-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-sglang"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-13-sglang
 - !!merge <<: *sglang
   name: "cuda13-nvidia-l4t-arm64-sglang-development"
   uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-sglang"
@@ -3352,6 +3466,77 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-vibevoice"
   mirrors:
     - localai/localai-backends:master-metal-darwin-arm64-vibevoice
+## liquid-audio
+- !!merge <<: *liquid-audio
+  name: "liquid-audio-development"
+  capabilities:
+    nvidia: "cuda12-liquid-audio-development"
+    intel: "intel-liquid-audio-development"
+    amd: "rocm-liquid-audio-development"
+    default: "cpu-liquid-audio-development"
+    nvidia-cuda-13: "cuda13-liquid-audio-development"
+    nvidia-cuda-12: "cuda12-liquid-audio-development"
+    nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-liquid-audio-development"
+- !!merge <<: *liquid-audio
+  name: "cpu-liquid-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-liquid-audio"
+  mirrors:
+    - localai/localai-backends:latest-cpu-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cpu-liquid-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-cpu-liquid-audio"
+  mirrors:
+    - localai/localai-backends:master-cpu-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cuda12-liquid-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-liquid-audio"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-12-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cuda12-liquid-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-liquid-audio"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-12-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cuda13-liquid-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-liquid-audio"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-13-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cuda13-liquid-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-liquid-audio"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-13-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "intel-liquid-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-liquid-audio"
+  mirrors:
+    - localai/localai-backends:latest-gpu-intel-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "intel-liquid-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-liquid-audio"
+  mirrors:
+    - localai/localai-backends:master-gpu-intel-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "rocm-liquid-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-liquid-audio"
+  mirrors:
+    - localai/localai-backends:latest-gpu-rocm-hipblas-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "rocm-liquid-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-liquid-audio"
+  mirrors:
+    - localai/localai-backends:master-gpu-rocm-hipblas-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cuda13-nvidia-l4t-arm64-liquid-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-liquid-audio"
+  mirrors:
+    - localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-liquid-audio
+- !!merge <<: *liquid-audio
+  name: "cuda13-nvidia-l4t-arm64-liquid-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-liquid-audio"
+  mirrors:
+    - localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-liquid-audio
 ## qwen-tts
 - !!merge <<: *qwen-tts
   name: "qwen-tts-development"

backend/python/chatterbox/install.sh

@@ -23,3 +23,15 @@ fi
 
 
 installRequirements
+
+# chatterbox-tts upstream pulls `russian-text-stresser` (unpinned git URL) which
+# transitively pins spacy==3.6.* and other ancient packages. That cascade forces
+# pip to backtrack through Jinja2/MarkupSafe/omegaconf/ruamel.yaml into Python-2-era
+# sdists that no longer build. We install chatterbox-tts itself with --no-deps and
+# list its real runtime deps in requirements-*.txt instead.
+echo "Installing chatterbox-tts with --no-deps"
+if [ "x${USE_PIP}" == "xtrue" ]; then
+    pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps "chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster"
+else
+    uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps "chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster"
+fi

backend/python/chatterbox/requirements-cpu.txt

@@ -4,6 +4,16 @@ torch
 torchaudio
 numpy>=1.24.0,<1.26.0
 transformers
-# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
-#chatterbox-tts==0.1.4
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0

backend/python/chatterbox/requirements-cublas12.txt

@@ -2,6 +2,17 @@ torch
 torchaudio
 transformers
 numpy>=1.24.0,<1.26.0
-# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0
 accelerate

backend/python/chatterbox/requirements-cublas13.txt

@@ -3,6 +3,17 @@ torch
 torchaudio
 transformers
 numpy>=1.24.0,<1.26.0
-# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0
 accelerate

backend/python/chatterbox/requirements-hipblas.txt

@@ -3,6 +3,17 @@ torch==2.10.0+rocm7.0
 torchaudio==2.10.0+rocm7.0
 transformers
 numpy>=1.24.0,<1.26.0
-# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0
 accelerate

backend/python/chatterbox/requirements-intel.txt

@@ -3,8 +3,19 @@ torch
 torchaudio
 transformers
 numpy>=1.24.0,<1.26.0
-# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0
 accelerate
 oneccl_bind_pt==2.3.100+xpu
 optimum[openvino]

backend/python/chatterbox/requirements-l4t12.txt

@@ -3,5 +3,17 @@ torch
 torchaudio
 transformers
 numpy>=1.24.0,<1.26.0
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0
 accelerate

backend/python/chatterbox/requirements-l4t13.txt

@@ -3,5 +3,17 @@ torch
 torchaudio
 transformers
 numpy>=1.24.0,<1.26.0
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0
 accelerate

backend/python/chatterbox/requirements-mps.txt

@@ -3,5 +3,16 @@ torchaudio
 accelerate
 numpy>=1.24.0,<1.26.0
 transformers
-# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
-chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+# chatterbox-tts itself is installed with --no-deps in install.sh.
+# These are its real runtime deps, mirroring upstream's pyproject.toml
+# minus russian-text-stresser (whose ancient pins break the resolver).
+omegaconf==2.3.0
+resampy==0.4.3
+librosa
+s3tokenizer
+diffusers
+resemble-perth==1.0.1
+conformer
+safetensors
+spacy-pkuseg
+pykakasi==2.3.0

backend/python/coqui/requirements-cpu.txt

@@ -1,6 +1,6 @@
 --extra-index-url https://download.pytorch.org/whl/cpu
 transformers==4.48.3
 accelerate
-torch==2.4.1
+torch==2.12.0+xpu
 torchaudio==2.4.1
 coqui-tts

backend/python/coqui/requirements-cublas12.txt

@@ -1,4 +1,4 @@
-torch==2.4.1
+torch==2.12.0+xpu
 torchaudio==2.4.1
 transformers==4.48.3
 accelerate

backend/python/coqui/requirements-hipblas.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/rocm7.0
-torch==2.10.0+rocm7.0
+torch==2.12.0+xpu
 torchaudio==2.10.0+rocm7.0
 transformers==4.48.3
 accelerate

backend/python/coqui/requirements-intel.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://download.pytorch.org/whl/xpu
-torch==2.8.0+xpu
+torch==2.12.0+xpu
 torchaudio==2.8.0+xpu
 optimum[openvino]
 setuptools

backend/python/coqui/requirements-mps.txt

@@ -1,4 +1,4 @@
-torch==2.7.1
+torch==2.12.0+xpu
 transformers==4.48.3
 accelerate
 coqui-tts

backend/python/faster-whisper/Makefile

@@ -10,4 +10,5 @@ protogen-clean:
 
 .PHONY: clean
 clean: protogen-clean
-	rm -rf venv __pycache__
+	rm -rf venv __pycache__
+# trigger per-arch+merge rebuild for faster-whisper pilot

backend/python/liquid-audio/Makefile

@@ -0,0 +1,23 @@
+.PHONY: liquid-audio
+liquid-audio:
+	bash install.sh
+
+.PHONY: run
+run: liquid-audio
+	@echo "Running liquid-audio..."
+	bash run.sh
+	@echo "liquid-audio run."
+
+.PHONY: test
+test: liquid-audio
+	@echo "Testing liquid-audio..."
+	bash test.sh
+	@echo "liquid-audio tested."
+
+.PHONY: protogen-clean
+protogen-clean:
+	$(RM) backend_pb2_grpc.py backend_pb2.py
+
+.PHONY: clean
+clean: protogen-clean
+	rm -rf venv __pycache__

backend/python/liquid-audio/backend.py

@@ -0,0 +1,871 @@
+#!/usr/bin/env python3
+"""
+Liquid Audio backend for LocalAI.
+
+Wraps LiquidAI's `liquid-audio` Python package (https://github.com/Liquid4All/liquid-audio).
+The same model serves four roles, selected by the `mode` option at load time:
+chat, asr, tts, s2s. Fine-tuning is exposed via StartFineTune.
+"""
+from concurrent import futures
+import argparse
+import json
+import os
+import queue
+import signal
+import sys
+import threading
+import time
+import traceback
+import uuid
+
+import grpc
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'common'))
+from grpc_auth import get_auth_interceptors  # noqa: E402
+from python_utils import parse_options  # noqa: E402
+
+import backend_pb2  # noqa: E402
+import backend_pb2_grpc  # noqa: E402
+
+_ONE_DAY_IN_SECONDS = 60 * 60 * 24
+MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
+
+# Voice id → system-prompt suffix. The model only ships these four voices.
+VOICE_PROMPTS = {
+    "us_male":   "Perform TTS. Use the US male voice.",
+    "us_female": "Perform TTS. Use the US female voice.",
+    "uk_male":   "Perform TTS. Use the UK male voice.",
+    "uk_female": "Perform TTS. Use the UK female voice.",
+}
+DEFAULT_VOICE = "us_female"
+
+# Special-token IDs that LFM2-Audio emits to delimit modality boundaries.
+# Sourced from liquid_audio/model/lfm2_audio.py (see generate_sequential/_sample_*).
+TEXT_END_TOKEN = 130        # <|text_end|>
+AUDIO_START_TOKEN = 128     # <|audio_start|>
+IM_END_TOKEN = 7            # <|im_end|>
+AUDIO_EOS_CODE = 2048       # signals end-of-audio in any codebook position
+
+_PATCHED_LOCAL_PATHS = False
+
+
+def _patch_liquid_audio_local_paths():
+    """Make liquid_audio.utils.get_model_dir() tolerate local directories.
+
+    Upstream always passes its argument to huggingface_hub.snapshot_download,
+    which only accepts `owner/repo` ids. LocalAI's gallery hands us absolute
+    paths under <ModelPath>/<owner>/<repo>, so we intercept snapshot_download
+    in the liquid_audio.utils namespace and return the directory as-is when
+    it already exists on disk. Idempotent.
+    """
+    global _PATCHED_LOCAL_PATHS
+    if _PATCHED_LOCAL_PATHS:
+        return
+    import liquid_audio.utils as _la_utils
+    _orig_snapshot_download = _la_utils.snapshot_download
+
+    def _local_first_snapshot_download(repo_id, revision=None, **kwargs):
+        if isinstance(repo_id, (str, os.PathLike)) and os.path.isdir(str(repo_id)):
+            return str(repo_id)
+        return _orig_snapshot_download(repo_id, revision=revision, **kwargs)
+
+    _la_utils.snapshot_download = _local_first_snapshot_download
+    _PATCHED_LOCAL_PATHS = True
+
+
+def _select_device():
+    import torch
+    if torch.cuda.is_available():
+        return "cuda"
+    if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+        return "mps"
+    return "cpu"
+
+
+class ActiveJob:
+    """Tracks an in-flight fine-tune so FineTuneProgress can stream from its queue."""
+
+    def __init__(self, job_id):
+        self.job_id = job_id
+        self.progress_queue = queue.Queue()
+        self.thread = None
+        self.stopped = False
+        self.completed = False
+        self.error = None
+
+
+class BackendServicer(backend_pb2_grpc.BackendServicer):
+    def __init__(self):
+        self.processor = None
+        self.model = None
+        self.device = "cpu"
+        self.dtype = None
+        self.options = {}
+        self.model_id = None
+        self.active_job = None
+
+    @property
+    def mode(self):
+        return str(self.options.get("mode", "chat")).lower()
+
+    @property
+    def voice(self):
+        v = str(self.options.get("voice", DEFAULT_VOICE)).lower()
+        return v if v in VOICE_PROMPTS else DEFAULT_VOICE
+
+
+    def Free(self, request, context):
+        # Called by LocalAI when unloading the model. Drop GPU tensors so the
+        # next load starts from a clean state instead of bumping into OOM.
+        try:
+            for attr in ("model", "processor", "tokenizer"):
+                if hasattr(self, attr):
+                    try:
+                        delattr(self, attr)
+                    except Exception:
+                        pass
+            import gc
+            gc.collect()
+            try:
+                import torch
+                if torch.cuda.is_available():
+                    torch.cuda.empty_cache()
+            except Exception:
+                pass
+            return backend_pb2.Result(success=True, message="OK")
+        except Exception as exc:
+            print(f"Free failed: {exc}", file=sys.stderr)
+            return backend_pb2.Result(success=False, message=str(exc))
+
+
+    def Health(self, request, context):
+        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
+
+
+    def LoadModel(self, request, context):
+        try:
+            import torch
+
+            self.options = parse_options(request.Options)
+            if self.options.get("voice") and self.options["voice"] not in VOICE_PROMPTS:
+                print(f"Warning: unknown voice '{self.options['voice']}'; defaulting to '{DEFAULT_VOICE}'",
+                      file=sys.stderr)
+
+            requested_device = self.options.get("device")
+            self.device = requested_device or _select_device()
+            if self.device == "cuda" and not torch.cuda.is_available():
+                return backend_pb2.Result(success=False, message="CUDA requested but not available")
+            if self.device == "mps" and not (hasattr(torch.backends, "mps") and
+                                             torch.backends.mps.is_available()):
+                print("MPS not available; falling back to CPU", file=sys.stderr)
+                self.device = "cpu"
+
+            dtype_name = str(self.options.get("dtype", "bfloat16")).lower()
+            self.dtype = {
+                "bfloat16": torch.bfloat16,
+                "bf16":     torch.bfloat16,
+                "float16":  torch.float16,
+                "fp16":     torch.float16,
+                "half":     torch.float16,
+                "float32":  torch.float32,
+                "fp32":     torch.float32,
+            }.get(dtype_name, torch.bfloat16)
+
+            # request.Model holds the raw `parameters.model` value (an HF
+            # repo id like "LiquidAI/LFM2.5-Audio-1.5B"); request.ModelFile
+            # is LocalAI's ModelPath-prefixed local copy that exists only
+            # when the gallery supplied a `files:` list. Mirror the
+            # transformers/vibevoice convention: prefer the repo id and
+            # only switch to the local path if it's been staged on disk.
+            model_id = request.Model
+            if not model_id:
+                model_id = request.ModelFile
+            if not model_id:
+                return backend_pb2.Result(success=False, message="No model identifier provided")
+            if request.ModelFile and os.path.isdir(request.ModelFile):
+                model_id = request.ModelFile
+            self.model_id = model_id
+
+            # Pure fine-tune jobs don't need an in-memory inference model — the
+            # Trainer instantiates its own copy at StartFineTune time.
+            if self.mode == "finetune":
+                print(f"Loaded liquid-audio backend in fine-tune mode (model id: {model_id})",
+                      file=sys.stderr)
+                return backend_pb2.Result(success=True, message="OK")
+
+            from liquid_audio import LFM2AudioModel, LFM2AudioProcessor
+
+            # liquid_audio's from_pretrained unconditionally routes through
+            # huggingface_hub.snapshot_download, which rejects local paths
+            # (HFValidationError on `/models/LiquidAI/LFM2.5-Audio-1.5B`).
+            # When LocalAI's gallery has already staged the weights on disk,
+            # short-circuit the download to return the local directory.
+            _patch_liquid_audio_local_paths()
+
+            print(f"Loading liquid-audio model '{model_id}' on {self.device} ({self.dtype})",
+                  file=sys.stderr)
+            self.processor = LFM2AudioProcessor.from_pretrained(model_id, device=self.device).eval()
+            self.model = LFM2AudioModel.from_pretrained(
+                model_id, device=self.device, dtype=self.dtype
+            ).eval()
+
+            print(f"Liquid-audio mode={self.mode}, voice={self.voice}", file=sys.stderr)
+            return backend_pb2.Result(success=True, message="OK")
+
+        except Exception as exc:
+            print(f"LoadModel failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            return backend_pb2.Result(success=False, message=str(exc))
+
+
+    def Predict(self, request, context):
+        try:
+            text = "".join(self._generate_text_stream(request))
+            return backend_pb2.Reply(message=text.encode("utf-8"))
+        except Exception as exc:
+            print(f"Predict failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            context.set_code(grpc.StatusCode.INTERNAL)
+            context.set_details(str(exc))
+            return backend_pb2.Reply()
+
+    def PredictStream(self, request, context):
+        try:
+            for delta in self._generate_text_stream(request):
+                yield backend_pb2.Reply(message=delta.encode("utf-8"))
+        except Exception as exc:
+            print(f"PredictStream failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            context.set_code(grpc.StatusCode.INTERNAL)
+            context.set_details(str(exc))
+
+
+    def VAD(self, request, context):
+        # Stub voice-activity detector: RMS-energy threshold over 30ms frames at
+        # 16 kHz. Good enough for the realtime endpoint's handleVAD loop, which
+        # only inspects segment presence + last segment end. The proper signal
+        # would come from the model's audio encoder, but that ride-along is a
+        # PR-D scope item — until then this keeps the legacy pipeline path
+        # working without forcing the operator to install a separate VAD model.
+        import numpy as np
+        try:
+            audio = np.asarray(request.audio, dtype=np.float32)
+            if audio.size == 0:
+                return backend_pb2.VADResponse(segments=[])
+
+            sample_rate = 16000
+            frame_size = sample_rate * 30 // 1000  # 30ms → 480 samples
+            threshold = float(self.options.get("vad_rms_threshold", 0.01))
+            min_speech_frames = int(self.options.get("vad_min_speech_frames", 2))  # ≥60ms
+            # handleVAD ticks every 300 ms and only inspects segment presence
+            # + last segment end relative to silence_threshold (~500 ms). Cap
+            # the analysed window to the tail of the buffer so we don't redo
+            # the entire growing utterance every tick.
+            window_s = float(self.options.get("vad_window_s", 5.0))
+            window_samples = int(window_s * sample_rate)
+            time_offset_s = 0.0
+            if audio.size > window_samples:
+                time_offset_s = (audio.size - window_samples) / sample_rate
+                audio = audio[-window_samples:]
+
+            n_frames = audio.size // frame_size
+            if n_frames == 0:
+                return backend_pb2.VADResponse(segments=[])
+            frames = audio[: n_frames * frame_size].reshape(n_frames, frame_size)
+            rms = np.sqrt(np.mean(frames ** 2, axis=1))
+            speech = rms > threshold
+
+            def _emit(start_idx, end_idx, out):
+                if end_idx - start_idx >= min_speech_frames:
+                    out.append(backend_pb2.VADSegment(
+                        start=time_offset_s + start_idx * frame_size / sample_rate,
+                        end=time_offset_s + end_idx * frame_size / sample_rate,
+                    ))
+
+            segments = []
+            start_idx = None
+            for i, is_speech in enumerate(speech):
+                if is_speech and start_idx is None:
+                    start_idx = i
+                elif not is_speech and start_idx is not None:
+                    _emit(start_idx, i, segments)
+                    start_idx = None
+            if start_idx is not None:
+                _emit(start_idx, n_frames, segments)
+            return backend_pb2.VADResponse(segments=segments)
+        except Exception as exc:
+            print(f"VAD failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            context.set_code(grpc.StatusCode.INTERNAL)
+            context.set_details(str(exc))
+            return backend_pb2.VADResponse(segments=[])
+
+
+    def TTS(self, request, context):
+        try:
+            if self.model is None or self.processor is None:
+                return backend_pb2.Result(success=False, message="Model not loaded")
+
+            import torch
+            import torchaudio
+            from liquid_audio import ChatState
+
+            voice = request.voice.lower() if request.voice else self.voice
+            voice = voice.removeprefix("lfm2:").removeprefix("lfm:")
+            if voice not in VOICE_PROMPTS:
+                voice = self.voice
+            system_prompt = VOICE_PROMPTS[voice]
+
+            chat = ChatState(self.processor)
+            chat.new_turn("system")
+            chat.add_text(system_prompt)
+            chat.end_turn()
+            chat.new_turn("user")
+            chat.add_text(request.text or "")
+            chat.end_turn()
+            chat.new_turn("assistant")
+
+            audio_top_k = int(self.options.get("audio_top_k", 64))
+            audio_temp = float(self.options.get("audio_temperature", 0.8))
+            max_new = int(self.options.get("max_new_tokens", 2048))
+
+            audio_out = []
+            for tok in self.model.generate_sequential(
+                **chat,
+                max_new_tokens=max_new,
+                audio_temperature=audio_temp,
+                audio_top_k=audio_top_k,
+            ):
+                if tok.numel() > 1:
+                    audio_out.append(tok)
+
+            if len(audio_out) <= 1:
+                return backend_pb2.Result(success=False, message="No audio frames generated")
+
+            # Drop the trailing end-of-audio frame, matching the package's examples.
+            audio_codes = torch.stack(audio_out[:-1], 1).unsqueeze(0)
+            waveform = self.processor.decode(audio_codes)
+
+            out_path = request.dst
+            if not out_path:
+                return backend_pb2.Result(success=False, message="dst path is required")
+            os.makedirs(os.path.dirname(out_path) or ".", exist_ok=True)
+            # soundfile in preference to torchaudio.save — the latter routes
+            # through torchcodec, whose native libs need NVIDIA NPP that we
+            # don't bundle in the cuda13 image.
+            import soundfile as _sf
+            _sf.write(out_path, waveform.cpu().numpy().squeeze(0).T, 24_000)
+
+            return backend_pb2.Result(success=True)
+        except Exception as exc:
+            print(f"TTS failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            return backend_pb2.Result(success=False, message=str(exc))
+
+
+    def AudioToAudioStream(self, request_iterator, context):
+        """Bidirectional any-to-any speech-to-speech stream.
+
+        See `backend.proto` AudioToAudioStream for the wire protocol. Audio
+        is decoded once per turn here; chunked detokenization for sub-second
+        TTFB is left to a future iteration once the LFM2AudioDetokenizer
+        gains a streaming entry point.
+        """
+        try:
+            yield from self._audio_to_audio_stream(request_iterator, context)
+        except Exception as exc:
+            print(f"AudioToAudioStream failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            yield backend_pb2.AudioToAudioResponse(
+                event="error",
+                meta=json.dumps({"message": str(exc)}).encode("utf-8"),
+            )
+
+    def _audio_to_audio_stream(self, request_iterator, context):
+        if self.model is None or self.processor is None:
+            raise RuntimeError("Model not loaded")
+
+        import torch
+        import torchaudio
+        from liquid_audio import ChatState
+
+        cfg = None
+        chat = None
+        input_sample_rate = 16000
+        output_sample_rate = 24000
+        sequence = 0
+
+        def _new_event(event, **kwargs):
+            nonlocal sequence
+            sequence += 1
+            kwargs.setdefault("sequence", sequence)
+            return backend_pb2.AudioToAudioResponse(event=event, **kwargs)
+
+        def _ensure_chat():
+            """Build a fresh ChatState seeded with the system prompt."""
+            nonlocal chat
+            chat = ChatState(self.processor)
+            system_prompt = (cfg.system_prompt if cfg and cfg.system_prompt
+                             else "Respond with interleaved text and audio.")
+            chat.new_turn("system")
+            chat.add_text(system_prompt)
+            chat.end_turn()
+
+        # Buffers for the in-flight user turn
+        pcm_buffer = bytearray()
+
+        def _consume_user_turn():
+            nonlocal pcm_buffer
+            if not pcm_buffer:
+                return
+            # Avoid the bytes(pcm_buffer) copy and let the float widen happen
+            # in-place: numpy view → torch view → in-place divide.
+            import numpy as np
+            arr = np.frombuffer(memoryview(pcm_buffer), dtype=np.int16)
+            wav = torch.from_numpy(arr).to(torch.float32).div_(32768.0).unsqueeze(0)
+            chat.new_turn("user")
+            chat.add_audio(wav, input_sample_rate)
+            chat.end_turn()
+            pcm_buffer = bytearray()
+
+        def _run_generation():
+            """Run generate_interleaved; yield response events as we go."""
+            chat.new_turn("assistant")
+            audio_top_k = int(self.options.get("audio_top_k", 4))
+            audio_temp = float(self.options.get("audio_temperature", 1.0))
+            text_top_k = int(self.options.get("text_top_k", 0)) or None
+            text_temp = float(self.options.get("text_temperature", 0)) or None
+            max_new = int(self.options.get("max_new_tokens", 512))
+
+            audio_tokens = []
+            for tok in self.model.generate_interleaved(
+                **chat,
+                max_new_tokens=max_new,
+                text_temperature=text_temp,
+                text_top_k=text_top_k,
+                audio_temperature=audio_temp,
+                audio_top_k=audio_top_k,
+            ):
+                if tok.numel() == 1:
+                    if tok.item() == IM_END_TOKEN:
+                        break
+                    text = self.processor.text.decode(tok)
+                    if not text:
+                        continue
+                    yield _new_event(
+                        "response.audio_transcript.delta",
+                        meta=json.dumps({"delta": text}).encode("utf-8"),
+                    )
+                else:
+                    audio_tokens.append(tok)
+
+            # Detokenize the accumulated audio at end-of-turn — the
+            # LFM2AudioDetokenizer is non-streaming today.
+            if len(audio_tokens) > 1:
+                audio_codes = torch.stack(audio_tokens[:-1], 1).unsqueeze(0)
+                waveform = self.processor.decode(audio_codes)
+                # Convert to s16le PCM bytes at output_sample_rate
+                if output_sample_rate != 24000:
+                    waveform = torchaudio.functional.resample(
+                        waveform.cpu(), 24000, output_sample_rate
+                    )
+                pcm = (waveform.cpu().squeeze(0).clamp(-1, 1) * 32767.0).to(
+                    torch.int16
+                ).numpy().tobytes()
+                yield _new_event(
+                    "response.audio.delta",
+                    pcm=pcm,
+                    sample_rate=output_sample_rate,
+                )
+
+            yield _new_event("response.done", meta=b"{}")
+
+        for req in request_iterator:
+            if not context.is_active():
+                return
+            payload = req.WhichOneof("payload")
+            if payload == "config":
+                cfg = req.config
+                if cfg.input_sample_rate > 0:
+                    input_sample_rate = cfg.input_sample_rate
+                if cfg.output_sample_rate > 0:
+                    output_sample_rate = cfg.output_sample_rate
+                # The first config implicitly resets state.
+                _ensure_chat()
+                pcm_buffer = bytearray()
+            elif payload == "frame":
+                if chat is None:
+                    _ensure_chat()
+                if req.frame.pcm:
+                    pcm_buffer.extend(req.frame.pcm)
+                if req.frame.end_of_input:
+                    _consume_user_turn()
+                    yield from _run_generation()
+            elif payload == "control":
+                event = req.control.event
+                if event == "input_audio_buffer.commit":
+                    _consume_user_turn()
+                    yield from _run_generation()
+                elif event == "response.cancel":
+                    # Synchronous generation here means cancel can only
+                    # take effect between turns; we ack so the client unblocks.
+                    yield _new_event("response.done", meta=b'{"cancelled":true}')
+                elif event == "session.update":
+                    # Free-form session re-config; treat as a soft reset.
+                    _ensure_chat()
+                    pcm_buffer = bytearray()
+                # Unknown events are ignored — forward-compatible.
+
+
+    def AudioTranscription(self, request, context):
+        try:
+            if self.model is None or self.processor is None:
+                return backend_pb2.TranscriptResult(segments=[], text="")
+
+            import torchaudio
+            from liquid_audio import ChatState
+
+            audio_path = request.dst
+            if not audio_path:
+                return backend_pb2.TranscriptResult(segments=[], text="")
+
+            chat = ChatState(self.processor)
+            chat.new_turn("system")
+            chat.add_text("Perform ASR.")
+            chat.end_turn()
+            chat.new_turn("user")
+            # soundfile in preference to torchaudio.load — the latter routes
+            # through torchcodec which needs NVIDIA NPP libs we don't bundle.
+            import soundfile as _sf
+            import torch
+            audio_np, sr = _sf.read(audio_path, dtype="float32", always_2d=True)
+            wav = torch.from_numpy(audio_np.T)  # (channels, samples)
+            if wav.shape[0] > 1:
+                # Down-mix to mono — the processor expects a single channel
+                wav = wav.mean(dim=0, keepdim=True)
+            chat.add_audio(wav, sr)
+            chat.end_turn()
+            chat.new_turn("assistant")
+
+            max_new = int(self.options.get("max_new_tokens", 1024))
+
+            pieces = []
+            for tok in self.model.generate_sequential(**chat, max_new_tokens=max_new):
+                if tok.numel() == 1:
+                    if tok.item() == IM_END_TOKEN:
+                        break
+                    pieces.append(self.processor.text.decode(tok))
+
+            text = "".join(pieces).strip()
+            duration_ms = int((wav.shape[1] / sr) * 1000)
+            segment = backend_pb2.TranscriptSegment(
+                id=0, start=0, end=duration_ms, text=text, tokens=[],
+            )
+            return backend_pb2.TranscriptResult(segments=[segment], text=text)
+        except Exception as exc:
+            print(f"AudioTranscription failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            return backend_pb2.TranscriptResult(segments=[], text="")
+
+
+    def StartFineTune(self, request, context):
+        if self.active_job is not None and not self.active_job.completed:
+            return backend_pb2.FineTuneJobResult(
+                job_id="", success=False,
+                message="A fine-tuning job is already running",
+            )
+
+        job_id = request.job_id or str(uuid.uuid4())
+        job = ActiveJob(job_id)
+        self.active_job = job
+
+        thread = threading.Thread(target=self._run_training, args=(request, job), daemon=True)
+        job.thread = thread
+        thread.start()
+
+        return backend_pb2.FineTuneJobResult(
+            job_id=job_id, success=True, message="Training started",
+        )
+
+    def FineTuneProgress(self, request, context):
+        if self.active_job is None or self.active_job.job_id != request.job_id:
+            context.set_code(grpc.StatusCode.NOT_FOUND)
+            context.set_details(f"Job {request.job_id} not found")
+            return
+
+        job = self.active_job
+        while True:
+            try:
+                update = job.progress_queue.get(timeout=1.0)
+            except queue.Empty:
+                if job.completed or job.stopped:
+                    break
+                if not context.is_active():
+                    break
+                continue
+            if update is None:
+                break
+            yield update
+            if update.status in ("completed", "failed", "stopped"):
+                break
+
+    def StopFineTune(self, request, context):
+        # We can't kill the Accelerate training loop mid-step cleanly from here;
+        # LocalAI's job manager kills the backend process on stop. The flag below
+        # at least lets the progress stream terminate quickly.
+        if self.active_job is not None and self.active_job.job_id == request.job_id:
+            self.active_job.stopped = True
+            self.active_job.progress_queue.put(None)
+        return backend_pb2.Result(success=True, message="OK")
+
+    def _run_training(self, request, job):
+        try:
+            self._do_train(request, job)
+            job.completed = True
+            job.progress_queue.put(backend_pb2.FineTuneProgressUpdate(
+                job_id=job.job_id, status="completed", message="Training completed",
+                progress_percent=100.0,
+            ))
+        except Exception as exc:
+            job.error = str(exc)
+            job.completed = True
+            print(f"Training failed: {exc}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            job.progress_queue.put(backend_pb2.FineTuneProgressUpdate(
+                job_id=job.job_id, status="failed", message=str(exc),
+            ))
+        finally:
+            job.progress_queue.put(None)
+
+    def _do_train(self, request, job):
+        from liquid_audio import LFM2AudioModel  # noqa: F401  (sanity import)
+        from liquid_audio.data.dataloader import LFM2DataLoader
+        from liquid_audio.trainer import Trainer
+
+        model_id = request.model or self.model_id or "LiquidAI/LFM2.5-Audio-1.5B"
+
+        dataset_path = request.dataset_source
+        if not dataset_path:
+            raise ValueError("dataset_source is required (path to a preprocessed dataset)")
+
+        extras = dict(request.extra_options) if request.extra_options else {}
+        val_path = extras.get("val_dataset")
+
+        # Map FineTuneRequest hyperparameters to liquid_audio.Trainer constructor args
+        lr = request.learning_rate or 3e-5
+        max_steps = request.max_steps or 1000
+        warmup_steps = request.warmup_steps or min(100, max_steps // 10)
+        batch_size = request.batch_size or 16
+        save_interval = request.save_steps or max(1, max_steps // 4)
+
+        output_dir = request.output_dir or os.path.join(
+            os.environ.get("LIQUID_AUDIO_OUTPUT_DIR", "/tmp"),
+            f"liquid-audio-{job.job_id}",
+        )
+        os.makedirs(output_dir, exist_ok=True)
+
+        job.progress_queue.put(backend_pb2.FineTuneProgressUpdate(
+            job_id=job.job_id, status="loading_dataset",
+            message=f"Loading preprocessed dataset from {dataset_path}",
+        ))
+        train_data = LFM2DataLoader(dataset_path)
+        val_data = LFM2DataLoader(val_path) if val_path else None
+
+        job.progress_queue.put(backend_pb2.FineTuneProgressUpdate(
+            job_id=job.job_id, status="loading_model",
+            message=f"Loading base model {model_id}",
+        ))
+
+        # The Liquid Trainer logs via self.accelerator.print; we subclass it to
+        # also push progress events onto the queue every logging_interval steps.
+        progress_q = job.progress_queue
+
+        class QueuedTrainer(Trainer):
+            def log(self_, model_output):
+                if self_.step > 0 and self_.step % self_.logging_interval == 0:
+                    try:
+                        loss = self_.accelerator.reduce(
+                            model_output.loss.detach(), reduction="mean"
+                        ).item()
+                    except Exception:
+                        loss = float("nan")
+                    lr_now = self_.optimizer.param_groups[0]["lr"]
+                    pct = (self_.step / self_.max_steps * 100.0) if self_.max_steps else 0.0
+                    progress_q.put(backend_pb2.FineTuneProgressUpdate(
+                        job_id=job.job_id,
+                        current_step=int(self_.step),
+                        total_steps=int(self_.max_steps),
+                        current_epoch=float(self_.epoch),
+                        loss=float(loss),
+                        learning_rate=float(lr_now),
+                        progress_percent=float(pct),
+                        status="training",
+                    ))
+                # Honour stop requests: raising here terminates the loop cleanly
+                if job.stopped:
+                    raise KeyboardInterrupt("stop requested")
+                return super().log(model_output)
+
+            def validate(self_):
+                progress_q.put(backend_pb2.FineTuneProgressUpdate(
+                    job_id=job.job_id, current_step=int(self_.step),
+                    total_steps=int(self_.max_steps), status="training",
+                    message=f"Running validation at step {self_.step}",
+                ))
+                return super().validate()
+
+        trainer = QueuedTrainer(
+            model_id=model_id,
+            train_data=train_data,
+            val_data=val_data,
+            lr=lr,
+            max_steps=max_steps,
+            warmup_steps=warmup_steps,
+            batch_size=batch_size,
+            save_interval=save_interval,
+            output_dir=output_dir,
+            weight_decay=request.weight_decay or 0.1,
+        )
+
+        job.progress_queue.put(backend_pb2.FineTuneProgressUpdate(
+            job_id=job.job_id, status="training", message="Training started",
+            total_steps=int(max_steps),
+        ))
+        trainer.train()
+
+        job.progress_queue.put(backend_pb2.FineTuneProgressUpdate(
+            job_id=job.job_id, status="saving",
+            message=f"Saved final model to {output_dir}",
+            checkpoint_path=os.path.join(output_dir, "final"),
+        ))
+
+
+    def _build_chat_state(self, messages, user_prompt, tools_prelude=None):
+        """Build a ChatState from a list of (role, content) tuples plus an optional final user turn.
+
+        tools_prelude, when non-empty, is prepended as an extra system turn carrying
+        the LFM2 tool-list block — mirrors gallery/lfm.yaml's `function:` template
+        so the model sees the same prompt shape whether served via llama-cpp or here.
+        """
+        from liquid_audio import ChatState
+        chat = ChatState(self.processor)
+        if tools_prelude:
+            chat.new_turn("system")
+            chat.add_text(tools_prelude)
+            chat.end_turn()
+        for role, content in messages:
+            chat.new_turn(role)
+            chat.add_text(content)
+            chat.end_turn()
+        if user_prompt:
+            chat.new_turn("user")
+            chat.add_text(user_prompt)
+            chat.end_turn()
+        chat.new_turn("assistant")
+        return chat
+
+    def _collect_messages(self, request):
+        """Translate PredictOptions.Messages into (role, content) tuples."""
+        out = []
+        for m in request.Messages:
+            role = (m.role or "user").lower()
+            if role not in ("system", "user", "assistant"):
+                role = "user"
+            out.append((role, m.content or ""))
+        return out
+
+    def _render_tools_prelude(self, request):
+        """Build the LFM2 `<|tool_list_start|>…<|tool_list_end|>` system prelude
+        from request.Tools (OpenAI Chat-Completions tool JSON). Returns "" when
+        no tools are attached. Output mirrors gallery/lfm.yaml's `function:`
+        template so the model sees the same prompt whether routed via llama-cpp
+        or this backend."""
+        tools_raw = getattr(request, "Tools", "") or ""
+        if not tools_raw:
+            return ""
+        try:
+            tools = json.loads(tools_raw)
+        except json.JSONDecodeError:
+            print(f"liquid-audio: ignoring malformed Tools JSON: {tools_raw[:200]!r}",
+                  file=sys.stderr)
+            return ""
+        if not isinstance(tools, list) or not tools:
+            return ""
+        # The LFM2 chat template uses single-quoted Python-dict-ish syntax in
+        # examples, but the tokenizer treats this whole block as opaque text;
+        # JSON works fine and is what other backends emit.
+        return (
+            "You are a function calling AI model. You are provided with functions to "
+            "execute. You may call one or more functions to assist with the user query. "
+            "Don't make assumptions about what values to plug into functions.\n"
+            "List of tools: <|tool_list_start|>"
+            + json.dumps(tools, separators=(",", ":"))
+            + "<|tool_list_end|>"
+        )
+
+    def _generate_text_stream(self, request):
+        """Yield text-only deltas from generate_sequential. Caller joins for unary Predict."""
+        if self.model is None or self.processor is None:
+            raise RuntimeError("Model not loaded")
+        messages = self._collect_messages(request)
+        user_prompt = request.Prompt or None
+        tools_prelude = self._render_tools_prelude(request)
+        # If the request already carries Messages, Prompt is the templated form
+        # of the same content — don't append a duplicate user turn.
+        chat = self._build_chat_state(
+            messages,
+            user_prompt if not messages else None,
+            tools_prelude=tools_prelude,
+        )
+
+        max_new = request.Tokens if request.Tokens > 0 else int(self.options.get("max_new_tokens", 512))
+        temperature = request.Temperature if request.Temperature > 0 else None
+        top_k = request.TopK if request.TopK > 0 else None
+
+        for tok in self.model.generate_sequential(
+            **chat,
+            max_new_tokens=max_new,
+            text_temperature=temperature,
+            text_top_k=top_k,
+        ):
+            if tok.numel() == 1:
+                if tok.item() == IM_END_TOKEN:
+                    break
+                yield self.processor.text.decode(tok)
+
+
+def serve(address):
+    server = grpc.server(
+        futures.ThreadPoolExecutor(max_workers=MAX_WORKERS),
+        options=[
+            ('grpc.max_message_length', 50 * 1024 * 1024),
+            ('grpc.max_send_message_length', 50 * 1024 * 1024),
+            ('grpc.max_receive_message_length', 50 * 1024 * 1024),
+        ],
+        interceptors=get_auth_interceptors(),
+    )
+    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
+    server.add_insecure_port(address)
+    server.start()
+    print(f"Liquid-audio backend listening on {address}", file=sys.stderr, flush=True)
+
+    def stop(_signum, _frame):
+        server.stop(0)
+        sys.exit(0)
+
+    signal.signal(signal.SIGTERM, stop)
+    signal.signal(signal.SIGINT, stop)
+
+    try:
+        while True:
+            time.sleep(_ONE_DAY_IN_SECONDS)
+    except KeyboardInterrupt:
+        server.stop(0)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Liquid Audio gRPC backend")
+    parser.add_argument("--addr", default="localhost:50051", help="gRPC server address")
+    args = parser.parse_args()
+    serve(args.addr)

backend/python/liquid-audio/install.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+set -e
+
+# liquid-audio requires Python ≥ 3.12 (per its pyproject.toml); the default
+# portable Python in libbackend.sh is 3.10. Override before sourcing.
+export PYTHON_VERSION="${PYTHON_VERSION:-3.12}"
+export PYTHON_PATCH="${PYTHON_PATCH:-11}"
+
+backend_dir=$(dirname $0)
+if [ -d $backend_dir/common ]; then
+    source $backend_dir/common/libbackend.sh
+else
+    source $backend_dir/../common/libbackend.sh
+fi
+
+# liquid-audio's torch wheels are large; allow upgrades to satisfy transitive pins
+EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
+installRequirements

backend/python/liquid-audio/protogen.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+set -e
+
+backend_dir=$(dirname $0)
+if [ -d $backend_dir/common ]; then
+    source $backend_dir/common/libbackend.sh
+else
+    source $backend_dir/../common/libbackend.sh
+fi
+
+runProtogen

backend/python/liquid-audio/requirements-cpu.txt

@@ -0,0 +1,13 @@
+--extra-index-url https://download.pytorch.org/whl/cpu
+torch>=2.8.0
+torchaudio>=2.8.0
+torchcodec>=0.9.1
+transformers>=4.55.4
+accelerate>=1.10.1
+datasets>=4.8.4
+einops>=0.8.1
+librosa>=0.11.0
+soundfile>=0.12.1
+sentencepiece>=0.2.1
+huggingface-hub>=1.3.0
+liquid-audio>=1.2.0

backend/python/liquid-audio/requirements-cublas12.txt

@@ -0,0 +1,13 @@
+--extra-index-url https://download.pytorch.org/whl/cu121
+torch>=2.8.0
+torchaudio>=2.8.0
+torchcodec>=0.9.1
+transformers>=4.55.4
+accelerate>=1.10.1
+datasets>=4.8.4
+einops>=0.8.1
+librosa>=0.11.0
+soundfile>=0.12.1
+sentencepiece>=0.2.1
+huggingface-hub>=1.3.0
+liquid-audio>=1.2.0

backend/python/liquid-audio/requirements-cublas13.txt

@@ -0,0 +1,13 @@
+--extra-index-url https://download.pytorch.org/whl/cu130
+torch>=2.8.0
+torchaudio>=2.8.0
+torchcodec>=0.9.1
+transformers>=4.55.4
+accelerate>=1.10.1
+datasets>=4.8.4
+einops>=0.8.1
+librosa>=0.11.0
+soundfile>=0.12.1
+sentencepiece>=0.2.1
+huggingface-hub>=1.3.0
+liquid-audio>=1.2.0

backend/python/liquid-audio/requirements-hipblas.txt

@@ -0,0 +1,13 @@
+--extra-index-url https://download.pytorch.org/whl/rocm7.0
+torch>=2.8.0
+torchaudio>=2.8.0
+torchcodec>=0.9.1
+transformers>=4.55.4
+accelerate>=1.10.1
+datasets>=4.8.4
+einops>=0.8.1
+librosa>=0.11.0
+soundfile>=0.12.1
+sentencepiece>=0.2.1
+huggingface-hub>=1.3.0
+liquid-audio>=1.2.0

backend/python/liquid-audio/requirements-l4t13.txt

@@ -0,0 +1,13 @@
+--extra-index-url https://pypi.jetson-ai-lab.io/jp7/cu130
+torch>=2.8.0
+torchaudio>=2.8.0
+torchcodec>=0.9.1
+transformers>=4.55.4
+accelerate>=1.10.1
+datasets>=4.8.4
+einops>=0.8.1
+librosa>=0.11.0
+soundfile>=0.12.1
+sentencepiece>=0.2.1
+huggingface-hub>=1.3.0
+liquid-audio>=1.2.0

backend/python/liquid-audio/requirements-mps.txt

@@ -0,0 +1,12 @@
+torch>=2.8.0
+torchaudio>=2.8.0
+torchcodec>=0.9.1
+transformers>=4.55.4
+accelerate>=1.10.1
+datasets>=4.8.4
+einops>=0.8.1
+librosa>=0.11.0
+soundfile>=0.12.1
+sentencepiece>=0.2.1
+huggingface-hub>=1.3.0
+liquid-audio>=1.2.0