* ⬆️ Update antirez/ds4
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* fix(ds4): link engram support in GPU builds
The bumped ds4 engine moved DeepSeek v4.1 engram helpers into a new object. Build and link that object for CUDA and Metal while retaining the upstream CPU object set.
Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
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* ⬆️ Update antirez/ds4
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* fix(ds4): link upstream image helpers
The ds4 bump adds vision calls to the engine object. Link the new image preprocessing object into every backend target.
Assisted-by: Codex:gpt-5
---------
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* fix(ds4): build CUDA kernels for the target architecture
The ds4 backend compiled its CUDA objects with no -arch. Upstream's Makefile
leaves CUDA_ARCH empty and its `cuda` target refuses to build without one,
offering `cuda-spark` (sm_121) and `cuda-generic` (native) instead. We invoke
its object targets directly, which bypasses that guard, so nvcc fell back to
its default architecture and the kernels ran as JIT'd PTX on the real GPU.
On GB10 (sm_121) that silently corrupted inference: any prompt over roughly 128
tokens produced text unrelated to the input and never closed its thinking
block, so content came back empty and the chat showed only reasoning; longer
prompts failed with "cuda decode failed". It also cost close to two orders of
magnitude of prefill throughput. Measured on one box, same model, same prompt,
same GPU, upstream ds4 at the pinned commit, differing only in the nvcc flags:
make -B ds4 (archless, as we build it) garbage output 4.21 t/s
make cuda-spark (compute_121a/sm_121a) correct output 325.70 t/s
Select an architecture list from CUDA_MAJOR_VERSION, which the backend matrix
already declares for both ds4 cublas entries but Dockerfile.ds4 never forwarded.
Upstream's CUDA_ARCH takes a single value, so it cannot express the fat binary
these images need; NVCC_ARCH_FLAGS is overridden instead, since a command-line
assignment wins over its `:=`. The lists are copied from vllm-cpp rather than
invented so the two CUDA images cover the same GPUs, with l4t/arm64 covering
Orin, Thor and GB10. An empty CUDA_MAJOR_VERSION keeps upstream's `native`
behaviour for local developer builds, and no CI runner has a GPU to enumerate.
DS4_CUDA_HAVE_MXF4 is deliberately left unset: upstream defines it only for
single-arch sm_120/sm_121 builds and guards it with a plain #ifdef rather than
__CUDA_ARCH__, so it cannot be combined with older archs. It gates an optional
MXFP4 indexer fast path whose #ifndef branch returns 0 and falls back cleanly,
so omitting it costs speed on GB10, not correctness.
Assisted-by: Claude Code:claude-opus-5
Signed-off-by: Claudio Maradonna <git@codeshifter.xyz>
* test(ds4): cover the multi-batch prefill regression
The architecture fix has no automated guard: every existing e2e spec uses a
short prompt, and the miscompiled backend answered short prompts correctly.
The corruption only appears once a prompt spans more than one prefill batch,
so the whole suite passed against a backend that produced garbage in normal
use.
Add an opt-in "long_prefill" capability to the backend e2e suite that sends a
prompt well past one batch with a known needle and asserts the answer still
reflects it, and document in the ds4 guide why the build must never omit an
nvcc architecture, how to check which flags a configuration resolves to
without compiling, and how to run the new spec.
Assisted-by: Claude Code:claude-opus-5
Signed-off-by: Claudio Maradonna <git@codeshifter.xyz>
---------
Signed-off-by: Claudio Maradonna <git@codeshifter.xyz>
Propagate gRPC cancellation into DS4 prompt synchronization and poll it at decode boundaries.
Stop on failed stream writes and skip parser finalization and KV persistence for abandoned partial requests.
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Claudio Maradonna <git@codeshifter.xyz>
Clamp requested generation to the usable context after prompt sync while preserving the legacy 256-token fallback for omitted limits.
Constrain each speculative MTP cycle to the remaining request budget so accepted tokens cannot advance beyond the visible output limit.
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Claudio Maradonna <git@codeshifter.xyz>
DS4 appends the opening thinking marker to tokenizer-templated prompts, so generated text begins directly with reasoning bytes. Starting DsmlParser in TEXT therefore puts the reasoning and closing marker in visible content.
Start the parser in THINK for structured chat requests with thinking enabled in both Predict and PredictStream. Keep the default TEXT state for raw prompts and reasoning-off requests, and add incremental regression coverage.
Assisted-by: Codex:gpt-5
Signed-off-by: Claudio Maradonna <git@codeshifter.xyz>
* ⬆️ Update antirez/ds4
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* fix(ds4): link upstream CUDA MMQ objects
The updated ds4 CUDA object now calls into the vendored MMQ implementation. Build and link those objects into both the gRPC server and distributed worker.
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refactor(backends): extract shared package-system-libs.sh from package.sh
The arch-detect-and-copy-system-libs block (Darwin rpath / x86_64 / aarch64
loader + libc/libstdc++/libgcc_s/libm/libgomp/libdl/librt/libpthread) was
inlined verbatim in 31 backend package.sh scripts. Extract it into a single
sourced scripts/build/package-system-libs.sh, the CPU-side counterpart to
scripts/build/package-gpu-libs.sh and its sourcing contract.
Consolidating the copies fixes three drift classes that had crept in:
- libgcc_s.so.1 and libstdc++.so.6 were listed twice in 9 backends
(acestep-cpp, crispasr, moss-tts-cpp, omnivoice-cpp, piper,
qwen3-tts-cpp, silero-vad, stablediffusion-ggml, whisper); the shared
script copies each once.
- libgomp.so.1 was omitted from opus. OpenMP consumers dlopen it rather
than link it, so the missing copy only failed at runtime; the shared
script always includes it.
- the Darwin @loader_path/lib rpath was applied only in piper and
silero-vad; both now pass their packaged binary to the shared script,
preserving that behavior. Every other backend passes an empty binary
path so no rpath is added, preserving its current behavior.
Each backend's pre/post packaging steps (binary copy, run.sh, ldd closure
walks, ggml variant bundling, espeak/OpenBLAS extras, the ds4 validate step)
are preserved verbatim; only the inline if/elif/else arch block is replaced
by a single source line.
Signed-off-by: supermario_leo <leo.stack@outlook.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* ⬆️ Update antirez/ds4
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* fix(ds4): link new tensor parallel objects
The updated ds4 revision split tensor-parallel transport and layer placement into separate translation units. Build and link those objects on CPU, CUDA, and Metal builds.
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---------
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fix(distributed): reject wrong-model requests at the backend (#10952)
In distributed mode the controller caches a NodeModel row naming a backend's
host:port. A worker can recycle a stopped backend's gRPC port for a different
model's backend, and probeHealth verifies liveness rather than identity, so the
probe succeeds against whatever now occupies the port and the request is
dispatched to the wrong backend. The caller gets a silent wrong-model answer.
Nothing in the request could catch this: PredictOptions had no model field, so
model identity crossed the wire only in ModelOptions.Model at LoadModel time,
and the cached-hit path issues no LoadModel. Every backend's "model not loaded"
guard checks a nil handle, which a process holding a different model passes, so
the stale row was never dropped either.
Add PredictOptions.ModelIdentity and enforce it at the point of use:
- The controller populates it in gRPCPredictOpts from ModelConfig.Model, the
same expression ModelOptions feeds to model.WithModel and therefore the
same value the backend received as ModelOptions.Model. Both are read from
one config value in one function, so they are equal by construction and the
comparison cannot false-reject.
- Backends compare it against what they loaded and return NOT_FOUND with a
fixed sentinel. Enforced in pkg/grpc/server.go (27 Go backends), an
interceptor in backend/python/common (all 36 Python backends, no
per-backend change), and the llama-cpp / ik-llama-cpp / ds4 C++ servers.
That is every backend with real exposure: kokoros answers all four RPCs
with unimplemented and privacy-filter implements none of them.
- The router's reconcile drops the stale replica row on a mismatch, so the
next request reloads somewhere correct.
Empty means "skip the check" on both sides: a controller that predates the
field sends nothing, a backend loaded by such a controller has nothing to
compare, and the C++ server synthesizes PredictOptions internally for ASR. That
keeps upgrades working in both directions.
Scoped to the four PredictOptions RPCs. TTSRequest.model and
SoundGenerationRequest.model are deliberately NOT validated: FileStagingClient
already rewrites them to worker-local absolute paths, so in distributed mode
they already differ from the load-time value and comparing them would reject
valid requests.
IsModelMismatch requires both the NOT_FOUND code and the sentinel, unlike the
neighbouring helpers which accept either. insightface's Embedding returns
NOT_FOUND "no face detected" on a PredictOptions RPC, and a code-only check
would drop a healthy replica row on every faceless image.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
feat(ds4): wire SSD streaming + quality engine options, add 128GB DeepSeek gallery models
The ds4 backend zero-initialized ds4_engine_options and exposed none of the
engine's tunable knobs, so SSD streaming (run a model larger than RAM by
streaming routed MoE experts from the GGUF on SSD) and the quality/perf knobs
were unreachable from LocalAI model YAMLs.
Map ModelOptions.Options onto ds4_engine_options through a declarative table
(kEngineOptSpecs + apply_engine_option) instead of per-field branches: the
struct is fixed C with no reflection, so the field set is enumerated once and a
future knob is a one-line table row. Two fields use ds4's own typed parsers
(GiB budgets, cache-experts count-or-NGB). Bare flags (e.g. "ssd_streaming")
mean true; path-type options (mtp_path, expert_profile_path,
directional_steering_file) resolve relative to the model directory so a gallery
entry can reference a companion file by bare filename. mtp_draft/mtp_margin are
now validated rather than parsed with throwing std::stoi/std::stof.
Add gallery entries for the 128 GB class:
- deepseek-v4-flash-q2-q4 (~91 GB, mixed q2/q4, fits RAM, higher quality)
- deepseek-v4-flash-q4-ssd (~153 GB full 4-bit, runs on 128 GB via SSD streaming)
- deepseek-v4-flash-q2-mtp (~81 GB + MTP speculative draft weights)
- deepseek-v4-pro-q2-ssd (~433 GB Pro, experimental SSD streaming)
SSD streaming is Metal (Darwin) only; the options are inert on CUDA/CPU.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update antirez/ds4
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(ds4): add Homebrew include/lib prefix for Darwin grpc-proto build
The darwin/metal ds4 backend job runs for the first time on this bump
(it was skipped on prior ds4 PRs) and fails compiling backend.pb.cc with
'google/protobuf/runtime_version.h' file not found.
hw_grpc_proto links neither protobuf::libprotobuf nor gRPC::grpc++, so
the generated proto sources rely on default system include paths. That
works on Linux (/usr/include) but not on macOS, where Homebrew installs
under /opt/homebrew. Add the Homebrew prefix to include/link dirs on
Darwin, mirroring the llama-cpp backend that already builds on Darwin CI.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* fix(ds4): install nlohmann-json on Darwin CI for ds4 backend
After the protobuf include-path fix the ds4 darwin build advances to
compiling dsml_renderer.cpp, which includes <nlohmann/json.hpp> and
#errors when absent. On Linux the header comes from apt nlohmann-json3-dev
in the build image; the macOS runner had no equivalent. Add the
header-only nlohmann-json formula to the shared Darwin backend brew
install/link list and Homebrew cache, alongside the existing deps.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* fix(ds4): build proper OCI image tar for Darwin backend
The darwin packaging referenced scripts/build/oci-pack.sh, which was
never added to the tree, so it fell back to a plain 'tar' that omits
manifest.json. 'local-ai backends install' then rejects the tarball
with 'file manifest.json not found in tar'.
Use './local-ai util create-oci-image' (already built by the 'build'
prerequisite of the backends/ds4-darwin target), mirroring
llama-cpp-darwin.sh, to emit a real OCI image the installer accepts.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
---------
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* ⬆️ Update antirez/ds4
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* fix(ds4): link ds4_ssd.o into the backend build
Upstream antirez/ds4 splits the SSD expert-cache into its own ds4_ssd.c
translation unit, whose symbols (ds4_ssd_memory_lock_acquire/release,
ds4_ssd_cache_experts_for_byte_budget, ds4_ssd_auto_cache_plan) are
referenced by ds4.c/ds4_cpu.o. The dependency-bump automation regenerated
this branch from clean master and dropped the prior linkage fix, so the
cpu-ds4 / cublas-ds4 backend builds fail again with undefined references.
Re-apply the ds4_ssd.o linkage GPU-agnostically (mirroring ds4_distributed.o)
in both the backend Makefile (DS4_OBJ_TARGET + the engine-object build rule
for every GPU mode) and CMakeLists.txt (list(APPEND DS4_OBJS ds4_ssd.o)).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
---------
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Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ds4): add standalone ds4-worker distributed worker binary
Add worker_main.c, a minimal standalone worker that owns a slice of the
model's transformer layers and serves activations over ds4's own TCP
transport via ds4_dist_run(). It links the same engine objects the
backend already builds (including ds4_distributed.o) and has NO
gRPC/protobuf dependency, so it builds even on hosts lacking protobuf/grpc
dev headers. Launched by `local-ai worker ds4-distributed`.
Wire the ds4-worker CMake target (mirrors grpc-server's object/GPU/native
handling) and have the Makefile copy + clean the binary alongside
grpc-server. Ignore the built ds4-worker artifact.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* feat(ds4): package ds4-worker alongside grpc-server
Copy the standalone ds4-worker binary into the backend package (Linux
package.sh) and the Darwin OCI tar (ds4-darwin.sh: both the explicit copy
and the otool dylib-bundling loop) so distributed workers ship with the
backend.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* fix(ds4): tighten ds4-worker integer arg validation to match upstream
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* feat(ds4): wire grpc-server as distributed coordinator
Add distributed COORDINATOR support to the ds4 backend's gRPC server.
Distributed inference is an engine backend: when LoadModel receives
'ds4_role:coordinator', the process populates ds4_engine_options.distributed
(role, layer slice, listen host/port) before ds4_engine_open, then the normal
ds4_session_* generation path runs transparently once the worker route covers
all layers.
- New LoadModel options: ds4_role, ds4_layers (START:END or START:output),
ds4_listen (host:port), ds4_route_timeout.
- parse_layers_spec() maps the layer spec onto ds4_distributed_layers.
- wait_route_ready() blocks generation until
ds4_session_distributed_route_ready() reports full coverage (or timeout),
gating both Predict and PredictStream; returns UNAVAILABLE on timeout/error.
- No ds4_role => g_distributed stays false and wait_route_ready is a no-op,
so single-node behavior is unchanged.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* fix(ds4): don't block Status during route wait; validate coordinator opts
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* feat(cli): add ds4-distributed worker exec helper
Add the ds4WorkerArgs helper plus findDS4Backend/DS4Distributed.Run that
resolve the ds4 backend via the gallery and exec the packaged ds4-worker
binary. Unlike worker_llamacpp.go, ds4 bundles its own dynamic loader
(lib/ld.so) for glibc compatibility, so when present we exec ds4-worker
through that loader with LD_LIBRARY_PATH=<backend>/lib, mirroring
backend/cpp/ds4/run.sh; otherwise we exec it directly.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* feat(cli): register the ds4-distributed worker subcommand
Wire DS4Distributed into the Worker kong command tree so
`local-ai worker ds4-distributed` is available.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* docs(ds4): document layer-split distributed inference
Add a ds4 section to the distributed-mode feature docs (coordinator
model YAML, manual worker command, layer-range semantics, the
'GGUF on every machine' requirement, coordinator-listens dial
direction vs llama.cpp) and a terse Distributed mode section to the
ds4 backend agent guide.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* test(ds4): opt-in hardware-gated distributed e2e spec
Add a self-contained, opt-in Ginkgo spec to the backend e2e suite that
spins a ds4 coordinator (via the packaged run.sh, loaded with
ds4_role/ds4_layers/ds4_listen options) plus a ds4-worker process for
the upper layers, then uses Eventually to assert a short successful
Predict once the layer route forms, before tearing the worker down.
Gated by BACKEND_TEST_DS4_DISTRIBUTED=1 (plus the existing
BACKEND_BINARY + BACKEND_TEST_MODEL_FILE and optional layer/listen/accel
knobs); compiles and skips cleanly with no env, hardware, or model.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* test(ds4): pass coordinator ctx to worker; lowercase error string
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* docs(ds4): note distributed transport is plaintext/unauthenticated
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* style(ds4): replace em dashes in distributed docs/agent/test per repo convention
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* fix(ds4): link ds4-worker with the C++ driver for CUDA/Metal builds
The ds4-worker target is built from worker_main.c (C), so CMake linked it
with the C driver. The nvcc-built ds4_cuda.o (and Obj-C++ ds4_metal.o)
reference the C++ runtime, so the CUDA/Metal builds failed with undefined
libstdc++ symbols (std::__throw_length_error). The CPU build passed because
ds4_cpu.o is pure C. Force LINKER_LANGUAGE CXX so libstdc++ is linked.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update antirez/ds4
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(ds4): link new ds4_distributed.o into grpc-server build
Upstream ds4 e16ead1e split distributed inference into a new translation
unit (ds4_distributed.c/.h). ds4.c and ds4_cpu.o now reference its
ds4_dist_* symbols, so the grpc-server link fails with undefined
references unless that object is built and linked.
Add ds4_distributed.o to both the upstream object build (Makefile) and
the grpc-server link set (CMakeLists.txt) for every GPU mode. It is a
single GPU-agnostic object, so it is built/linked unconditionally.
Verified: the six undefined ds4_dist_session_* references in ds4_cpu.o
are all defined by the newly built ds4_distributed.o (nm cross-check).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
---------
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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ci(bump-deps): register ds4 + move version pin into the Makefile
The initial ds4 PR (#9758) put the upstream commit pin in
backend/cpp/ds4/prepare.sh as a shell variable. The auto-bump bot at
.github/bump_deps.sh greps for ^$VAR?= in a Makefile, so DS4_VERSION
was invisible to it - other backends (llama-cpp, ik-llama-cpp,
turboquant, voxtral, etc.) all pin in their Makefile.
This change:
- Moves DS4_VERSION?= and DS4_REPO?= to the top of
backend/cpp/ds4/Makefile.
- Inlines the git init/fetch/checkout recipe into the 'ds4:' target
(matches llama-cpp's 'llama.cpp:' target pattern). Directory acts
as the target so make only re-clones when missing.
- Deletes the now-redundant prepare.sh.
- Adds antirez/ds4 + DS4_VERSION + main + backend/cpp/ds4/Makefile to
the .github/workflows/bump_deps.yaml matrix so the daily bot opens
PRs against this pin.
- Updates .agents/ds4-backend.md to point at the Makefile.
Verified:
$ grep -m1 '^DS4_VERSION?=' backend/cpp/ds4/Makefile
DS4_VERSION?=ae302c2fa18cc6d9aefc021d0f27ae03c9ad2fc0
$ make -C backend/cpp/ds4 ds4 # clones into ds4/ at the pin
$ make -C backend/cpp/ds4 ds4 # no-op on second invocation
make: 'ds4' is up to date.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci: route backend/cpp/ds4/ changes through changed-backends.js
scripts/changed-backends.js:inferBackendPath has an explicit branch per
cpp dockerfile suffix (ik-llama-cpp, turboquant, llama-cpp). Without a
matching branch the function returns null, the backend never lands in
the path map, and PR change-detection cannot map "backend/cpp/ds4/X
changed" -> "rebuild ds4 image".
This is why PR #9761 produced zero ds4 jobs even though it directly
edits backend/cpp/ds4/Makefile.
Adds the missing branch (Dockerfile.ds4 -> backend/cpp/ds4/), placed
before the llama-cpp branch (since both share the .cpp ancestry but
ds4 is more specific - same ordering rule documented in
.agents/adding-backends.md).
Verified with a local Node simulation of the script against this PR's
diff: the path map now contains 'ds4 -> backend/cpp/ds4/' and a
'backend/cpp/ds4/Makefile' change correctly triggers the ds4 backend
in the rebuild set.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(adding-backends): harden the two gotchas that bit ds4
Both omissions are silent at the time you ADD a backend - the failure
mode only appears later (the bump bot stays silent forever, or the path
filter shows up on the next PR that touches your backend with zero CI
jobs and looks broken for unrelated reasons). Expanding the
`scripts/changed-backends.js` paragraph from a one-liner to a fully
worked example, and adding a new sibling paragraph for the
`bump_deps.yaml` + Makefile-pin contract.
Both call out the specific mistakes from the ds4 timeline (#9758
→ #9761) so future contributors can pattern-match on the cause.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
