Add gfx1151 (AMD Strix Halo / Ryzen AI MAX) to the default AMDGPU_TARGETS
list in the llama-cpp backend Makefile. ROCm 7.2.1 ships with gfx1151
Tensile libraries, so this architecture should be included in default builds.
Also expose AMDGPU_TARGETS as an ARG/ENV in Dockerfile.llama-cpp so that
users building for non-default GPU architectures can override the target
list via --build-arg AMDGPU_TARGETS=<arch>. Previously, passing
-DAMDGPU_TARGETS=<arch> through CMAKE_ARGS was silently overridden by
the Makefile's own append of the default target list.
Fixes#9374
Signed-off-by: Keith Mattix <keithmattix2@gmail.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
The shared grpc-server CMakeLists hardcoded `llama-common`, the post-rename
target name in upstream llama.cpp. The turboquant fork branched before that
rename and still exposes the helpers library as `common`, so the name
silently degraded to a plain `-llama-common` link flag, the PUBLIC include
directory was never propagated, and tools/server/server-task.h failed to
find common.h during turboquant-<flavor> builds.
Upstream llama.cpp (PR #21962) switched the server-side mtmd media
marker to a random per-server string and removed the legacy
"<__media__>" backward-compat replacement in mtmd_tokenizer. The
Go layer still emitted the hardcoded "<__media__>", so on the
non-tokenizer-template path the prompt arrived with a marker mtmd
did not recognize and tokenization failed with "number of bitmaps
(1) does not match number of markers (0)".
Report the active media marker via ModelMetadataResponse.media_marker
and substitute the sentinel "<__media__>" with it right before the
gRPC call, after the backend has been loaded and probed. Also skip
the Go-side multimodal templating entirely when UseTokenizerTemplate
is true — llama.cpp's oaicompat_chat_params_parse already injects its
own marker and StringContent is unused in that path. Backends that do
not expose the field keep the legacy "<__media__>" behavior.
Upstream llama.cpp (45cac7ca) renamed the CMake library target
`common` to `llama-common`. Linking the old name caused
`target_include_directories(... PUBLIC .)` from the common/ dir
to not propagate, so `#include "common.h"` failed when building
grpc-server.
chore: ⬆️ Update TheTom/llama-cpp-turboquant to `45f8a066ed5f5bb38c695cec532f6cef9f4efa9d`
Drop 0002-ggml-rpc-bump-op-count-to-97.patch; the fork now has
GGML_OP_COUNT == 97 and RPC_PROTO_PATCH_VERSION 2 upstream.
Fetch all tags in backend/cpp/llama-cpp/Makefile so tag-only commits
(the new turboquant pin is reachable only through the tag
feature-turboquant-kv-cache-b8821-45f8a06) can be checked out.
When TASK_RESPONSE_TYPE_OAI_CHAT is used, the first streaming token
produces a JSON array with two elements: a role-init chunk and the
actual content chunk. The grpc-server loop called attach_chat_deltas
for both elements with the same raw_result pointer, stamping the first
token's ChatDelta.Content on both replies. The Go side accumulated both,
emitting the first content token twice to SSE clients.
Fix: in the array iteration loops in PredictStream, detect role-init
elements (delta has "role" key) and skip attach_chat_deltas for them.
Only content/reasoning elements get chat deltas attached.
Reasoning models are unaffected because their first token goes into
reasoning_content, not content.
* fix(chat): do not retry if we had chatdeltas or tooldeltas from backend
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: use oai compat for llama.cpp
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: apply to non-streaming path too
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* map also other fields
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
The C++ PEG parser needs a few tokens to identify the reasoning format
(e.g. "<|channel>thought\n" for Gemma 4). During this warm-up, the gRPC
layer was sending raw partial tag tokens to Go, which leaked into the
reasoning field.
- Clear reply.message in gRPC when autoparser is active but has no diffs
yet, matching llama.cpp server behavior of only emitting classified output
- Prefer C++ autoparser chat deltas for reasoning/content in all streaming
paths, falling back to Go-side extraction for backends without autoparser
(e.g. vLLM)
- Override non-streaming no-tools result with chat delta content when available
- Guard PrependThinkingTokenIfNeeded against partial tag prefixes during
streaming accumulation
- Reorder default thinking tokens so <|channel>thought is checked before
<|think|> (Gemma 4 templates contain both)
* feat: add distributed mode (experimental)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix data races, mutexes, transactions
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix events and tool stream in agent chat
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* use ginkgo
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(cron): compute correctly time boundaries avoiding re-triggering
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* enhancements, refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not flood of healthy checks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not list obvious backends as text backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* tests fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop redundant healthcheck
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* enhancements, refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: wire min_p
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: inferencing defaults
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(refactor): re-use iterative parser
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: generate automatically inference defaults from unsloth
Instead of trying to re-invent the wheel and maintain here the inference
defaults, prefer to consume unsloth ones, and contribute there as
necessary.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: apply defaults also to models installed via gallery
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: be consistent and apply fallback to all endpoint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
