The child writes its state commands on stdout while the logger writes
on stderr, and both share a single pipe. The logger emits the trailing
color reset after the newline of a debug, warn or error entry, so that
escape sequence has no newline of its own and the router reads it glued
in front of the next command. The line prefix check then fails and the
command is forwarded as a log line instead of being handled, which
leaves a finished download stuck in the downloading state.
Writing the command with a leading newline closes the pending line so
it always starts at a line boundary.
* server: refactor subproc handling
* fix Windows build
* download: keep concurrent downloads of one blob apart
Every process writes the same path + .downloadInProgress, so a second
download of the same blob finds that file, takes it for its own partial
transfer and asks for the bytes after it, which produces a corrupt
result. The in-progress file now carries the pid of the process writing
it.
std::rename also replaces an existing destination on POSIX but fails on
Windows, so a download whose blob appeared in the meantime is dropped
after every retry and an etag rewrite silently keeps the old value.
std::filesystem::rename has the POSIX behaviour everywhere, and the
error now carries the reason reported by the system.
* Revert "download: keep concurrent downloads of one blob apart"
This reverts commit 917b83f149.
* tests: serialize the router tests that download the same model
Parallel workers share one cache, so the two tests fetch the same blob
into the same in-progress file and race to rename it. They now take a
file lock around the download, like the session fixture does for the
preset models.
* Revert "tests: serialize the router tests that download the same model"
This reverts commit c368a4a98c.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
The expected success table holds when the four requests enter the shared
pool together. On a loaded runner they are admitted tens of milliseconds
apart, the slot lifetimes overlap differently and the pool overflows
while a short request is still resident. The decode failure aborts every
slot, so a request the table marks as successful comes back with the
context error instead of its generation.
Such a request now passes on that error too, while any other status, a
different error or a truncated generation still fails the test.
* scripts : add initial profiling script (wip)
* src : add precompile headers (PCH) for models.h
* common : add common.h as PCH
* ggml : add PCH for ggml-impl.h
* mtmd : use PCH for models.h
* scripts : add script to build with Server/Tools/Tests
* server : add PCH for common.h
* docs: add profiling progress notes (wip)
* ggml : add exclude for GCC + SVE on ARM
Refs: https://github.com/ggml-org/llama.cpp/actions/runs/33393906061/job/99493756214?pr=28091
* ggml : attempt to fix use of std::hardware_destructive_inference_size
Refs: https://github.com/ggml-org/llama.cpp/actions/runs/33396221677/job/99501265689?pr=28091
* squash! ggml : attempt to fix use of std::hardware_destructive_inference_size
Add a version check for GCC 12 to conditionally apply the `-Winterference-size`
pragma.
* editorconfig : exclude profiling reports dir
This directory will not be included in the merge later and this commit
can be ignore at that point. Just fixing to keep CI happy.
* ggml : skip PCH for gcc on non-x86 architectures
* tests : add PCH for peg-parser/tests.h
There are 7 peg-parser tests that can share one PCH instead of then each
parsing the full tests.h.
* common : add PCH for chat.h
* docs : update linux build profiling full results
Just updating after a number of PCH additions. These are not exact
figures and will vary a bit from run to run, but they give a general idea
of the performance impact of PCH.
* cmake : introduce unity build for models
This commit introduces a unity build for the models to improve
compilation time.
The improvements were roughly the following:
```console
+------------------------+-----+------------+------------+------------+
| Build | TUs | Frontend | Backend | Total |
+------------------------+-----+------------+------------+------------+
| Full, master | 396 | 811.0 s | 692.2 s | 1,503.2 s |
| Full, with PCH | 405 | 380.0 s | 664.7 s | 1,044.7 s |
| Full, with PCH + UB | 264 | 357.7 s | 635.7 s | 993.4 s |
+------------------------+-----+------------+------------+------------+
TU = Translation Unit.
Full = includes Server, Tools, and Tests.
PCH = precompiled headers.
UB = unity build for models.
```
* docs : update linux profiling table with unitiy build results
* docs : update mac profiling results to include unity build [no ci]
* docs: remove profiling reports
* scripts : merge build profile scripts into one script
I was lazy before and just copied the first script to enable Tests,
Server, and Tools. This now merges them into a single script.
* Revert "editorconfig : exclude profiling reports dir" [no ci]
This reverts commit 2922a12118.
* src : rename ggml_view_2d_slice to gemma3n_view_2d_slice
This is to be consistent with the rename in gemma4.cpp which was
required to avoid a name clash.
* cmake : add build profile script for windows [no ci]
This commit adds a port of the scripts/build-profile.sh script to
windows powershell.
This was developed on Windows on ARM but should work on X64 as well but
needs to be tested there as well.
* server: fix speculation after an image
Pass the actual position to the drafter after an image, instead of the
token count. Affects every drafter, not just DFlash.
* rename draft n_past to pos0
n_past is used to denote number of tokens and this parameter is meant to be a position
The spacing eviction in create_checkpoint() keeps the oldest checkpoint and
erases every later one within checkpoint_min_step of it. For prompts shorter
than checkpoint_min_step this drops the checkpoint at n_tokens - 4 that the
next request resumes from, so hybrid/recurrent models re-prefill from the
previous checkpoint instead. Apply the spacing rule only once the list is at
n_ctx_checkpoints, and replace an existing checkpoint at the same n_tokens
instead of appending a duplicate.
* server: fix LRU hang on multiple requests same model
* server: keep a queued model out of the victim pool until its waiters leave
A waiter that gave up while its model was still loading left the
model idle with no request behind it, and nothing recounted the free
slots, so a second request queued behind it stayed queued forever.
tick() was only driven by requests: join, claim and the end of a
proxied request.
Keep the queue entry alive after a successful claim so the model
coming up is never picked as a victim before its waiters use it, and
recount the slots on every status change and whenever a waiter
abandons the queue. The model is then evicted as soon as it comes up
with nobody left to serve.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
Remove the build-time C++ helper and external gzip dependency,
simplifying cross-compilation. Keep the generated C++ in templates for
readability and preserve fully embedded UI assets.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* server : use pytest-xdist for server tests
This commit adds pytest-xdist to the server tests. This is pytest
plugin that distributes test execution across multiple CPU cores.
Assisted-by: pi:llama.cpp/qwen3.8-27B
Refs: https://github.com/ggml-org/llama.cpp/pull/26734#issuecomment-5220707042
* remove server_base_port and BASE_PORT
* use worksteal and pytest builting tmp_path
* server : accept data: URLs for input_video and input_audio
input_video and input_audio passed accept_base64_uri=false to
handle_media(), so data: URLs got treated as raw base64 strings and
failed later with a confusing media probe error (#27724).
pass true for these two content types the same way image_url already
does, and allow video/audio mime types in the data: url check instead
of image only. data URL validation now throws std::invalid_argument so
malformed input comes back as 400 instead of 500, matching the other
input validation in this file.
* server : simplify handle_media and drop unused accept_base64_uri flag
* server : update comment and add unit test for invalid data URI MIME
* common, server : enable preserve_reasoning kwarg by default, log its effective state
If the preserve_reasoning chat template kwarg is not specified explicitly
via --reasoning-preserve / --no-reasoning-preserve, it is enabled by
default after argument processing. The server logs the effective state of
the kwarg, warns that it is enabled by default when the template supports
it, and only warns "has no effect" when it was enabled explicitly on a
template that does not support it. Setting the kwarg via
--chat-template-kwargs is deprecated.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : update comment
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
---------
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
Rename the --tensor-read-lazy CLI argument to --lazy-mode, to match the
internal lazy_mode parameter, and add a -lzm shorthand. Sync the READMEs.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* Add ctx-per-slot argument for unifid KV cache
* Swap out ctx fractions for ctx pool slots
* Formatting cleanup
* Remove ctx-pool-slots, make ctx-per-slot an int
* refactor it
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* Add benchmark-only synthetic speculative acceptance to llama-server and llama-cli
* Address review comments
* Address review comments
* Add some comments in the code
* server: fix tool calls getting silently stripped with --prefill-assistant
Last assistant carries tool_calls + --prefill-assistant is on → request
flips into continuation mode, add_generation_prompt forced off, tail
rebuilt from reasoning_content + content only. Tool calls just vanish.
- Auto-continuation now skips trailing assistant msgs that have tool calls
- continue_final_message on those throws a clear error instead of
silently corrupting the prompt
- Regression tests included, red before / green after
Fixes#27588
Developed with AI assistance, disclosed per the contribution policy.
* server : address review: fail on prefill-assistant + trailing tool_calls
Move validation into oaicompat_chat_params_parse (next to the existing
two-or-more-assistant check) and remove it from common_chat_templates_apply,
which has no precedent for validation. Drop the regression tests.
Per review: --prefill-assistant with a trailing assistant message
containing tool calls is not supported and should fail loudly.
* fit: also take into account n_streams
* server: make the draft context follow the target context
With a non-unified KV cache the target context now holds n_ctx_train
tokens per sequence, while the draft context was still created with
n_ctx = 0 and fell back to n_ctx_train / n_streams per sequence. A slot
filled beyond that point makes the draft batch fail to decode, and the
server answers 500 on the request.
The draft context now takes its size from the target context, so both
hold the same number of tokens per sequence. Contexts that share their
cells with the target no longer need the kv_size override.
The memory reserved for the draft model before fitting is measured at
the largest context the target can take, since the draft context grows
with the target and a fixed byte margin cannot express that.
* fit: take an optional second model into account
Illustrates the alternative discussed on the draft context fix. The
memory of a draft or MTP context is currently handed to the fit as a
fixed byte margin, which cannot express a memory that grows with the
context the fit is still deciding on.
common_fit_params now takes an optional second model that shares the
devices of the main one. Its context follows the main context and its
memory is measured again whenever that context changes, so the reduce
path stays exact instead of conservative. A model that cannot be
measured on its own, such as a shared cell MTP context, is skipped with
a warning and the main model is fitted alone.
This drops the reservation block in the server, which no longer has to
probe the trained context size of the target to guess an upper bound.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
* feat: add --mmproj-device arg & backwards compatible MTMD_BACKEND_DEVICE env var
* feat: load mmproj device backend immediately, add -mmdev shortflag
* fix: its a pointer now get the name
* clean up
* gen docs
* nits
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* doc: document MCP stdio servers and CORS defaults in the server README
The MCP arguments were listed but nothing explained what an MCP server
is or how to declare one. Cover the stdio transport, the config keys,
the tool naming, and add a POSIX shell echo server as a minimal
example.
Also document the CORS behavior: the default reflected origin, the
switch to localhost once tools are enabled, and the recommended setting
per deployment.
* doc: drop the inline MCP shell example from the server README
The example parsed JSON-RPC by hand and sat in a page people copy paste
from, into servers spawned with the privileges of llama-server. Point to
the specification instead.
Link the pull request that introduced the feature, and keep a short
mcp.json snippet so the table of configuration keys has a declaration to
refer to.
* ui: move get_datetime tool to frontend
* clarify docs
* server: drop the now unused ctime include
strftime() and gmtime_r() were the only users, both went away with the
get_datetime tool. Also make the renderer's catch inert: the browser
executor always emits JSON, so a non-JSON result is no longer a date to
display.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
Replace the deprecated --mmap, --no-mmap, --mlock, and --direct-io flags with
the unified --load-mode argument across scripts, examples, and documentation.
Internal warning message and env var docs updated accordingly.
Signed-off-by: Fathi Boudra <fathi.boudra@linaro.org>
* chat: add reasoning_effort to common_chat_templates_inputs
Store OpenAI Chat Completions reasoning_effort and make it
available to jinja templates (with model specific translations
where required).
Assisted-by: llama.cpp:Muse-Glimmer-30B
* server : fixup reading reasoning effort from body
server_chat_convert_responses_to_chatcmpl already handles conversion of
Responses API reasoning.effort to reasoning_effort
* chat : expose reasoning effort
Assisted-by: Claude Opus 5
* chat : add reasoning_effort to generation_params
Assisted-by: Claude Opus 5
* chat : move reasoning_effort next to enable_thinking
Assisted-by: Claude Opus 5
* cont : mirror preserve_reasoning
* cont : pass context through analyze function
---------
Co-authored-by: Alde Rojas <hello@alde.dev>
index.html was served with `max-age=31536000, immutable` like the hashed assets, but its name is stable while its contents change every build, so a cached copy pins the UI to an old build. It now revalidates via its existing ETag, which keeps the 304 for unchanged builds.
* server : save serialized image chunks at the end of the llama state
* server : support multimodal slot state save/restore with packed payload
* server : refine image slot state serialization
* server : support media slot state and centralize media validation
* server : remove unnecessary comment
* server : remove defensive media checks and move the chunk type check to validate()
* server: add read_image tool (#25875)
Adds a server-tool that allows vision models to analyze server-side images.
This tool is reading a single file for now:
The image data is base64 encoded and passed to the UI, which
decodes it, fills the <img> tag and removes the data URI before
passing the tool result back to the model.
* cleanup read_image tool: move magic strings to constants
* Add dedicated constants file: tools/ui/src/lib/constants/read-image.ts
with PREFIX_IMAGE, PREFIX_SIZE, PREFIX_MIME constants
* Use ATTACHMENT_SAVED_REGEX from agentic.ts in ChatMessageToolCallBlockReadImage.svelte
* Use NEWLINE constant from code.ts instead of hardcoded '\n'
* Use PREFIX_SIZE in regex pattern for size parsing
* Add SERVER_TOOL_READ_IMAGE_PREFIX_* constants in C++ server-tools.cpp
to match the TypeScript PREFIX_* constants for consistency
* server: rename read_image tool to read_media for images and audio
* Rename server_tool_read_image to server_tool_read_media in C++
* Rename enum BuiltInTool.READ_IMAGE to READ_MEDIA
* Rename UI constants, parser, and Svelte component files
* Update display label from 'Read image' to 'Read media'
* ui: consolidate audio data URI handling into shared utility
* Extract getAudioInputFormat to a shared utility (was duplicated inline)
* Store raw base64 in base64Data on the message object
* Use base64Data to construct data URIs for audio rendering
* Update agentic store to build INPUT_AUDIO parts from base64Data
* server: read_media: restrict audio to wav/mp3 and minor fixes
* Server get_mime_from_extension now only advertises audio/wav and
audio/mpeg (the only formats the model's input_audio API accepts)
* Case-insensitive extension matching (fixes .MP3, .Wav, etc.)
* Unknown extensions return an error instead of a multi-MB data URI
that inflates model context with garbage
* Updated tool description to document supported formats
* Frontend AUDIO_MIME_TO_EXTENSION trimmed to match server
* fix a missing import in tools/ui/src/lib/stores/agentic.svelte.ts
* server: read_media: add to --tools help text and README tool list
* ui: fix indentation in ChatMessageToolCallBlockDefault.svelte
* server: read_media tool: fix a cast to use the correct type
* server: read_media: multiple fixes
* server-tools.cpp import cctype, remove UTF-8 char, check mime before reading file
* ui: add MimeTypePrefix.AUDIO and use it in agentic.svelte.ts
* server: make read_media inherit from read_file and add uses_cwd
* ui: fix formating issues
* rm from server
* move it to frontend-only tool
* correct partial commit
* rm unused
* ui: address review from allozaur
Replace the magic strings, regexes and number in the read_media parser
and service with named constants. Path splitting reuses
FILE_PATH_SEPARATOR_REGEX, the size header regex moves to
READ_MEDIA_SIZE_REGEX derived from PREFIX_SIZE, and
FILE_EXTENSION_SEPARATOR lands next to it in constants/code.ts.
---------
Co-authored-by: ckrafft <ckrafft@epyc>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Pascal <admin@serveurperso.com>
* llama: add new default load-mode auto which picks mmap unless a non-Metal iGPU is used
* Update ggml/src/ggml-hexagon/ggml-hexagon.cpp
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* set mmap_support to false on OpenCL backend
* fix order of load modes
* use -1 for auto
* resolve load mode auto earlier to correctly pick gpu host or cpu memory
* add load mode auto to llama-bench
* bump virtgpu api version, regenerate docs
---------
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
