* model : add LiquidAI/d1-2B and LiquidAI/d1-omni-2B
Assisted-by: Claude Opus 5.5
* convert : keep the speech task templates out of the d1 GGUFs
Assisted-by: Claude Opus 5.5
* small refactoring: no_batching
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server: expose the reasoning effort levels of the chat template
The capability probe renders a user turn for each candidate level
(minimal, low, medium, high, xhigh, max) and for an unknown level. A
level is honored when it renders without raising and differently from
the unknown level, which shows the template fallback. Levels sharing a
render are aliases and the highest one is kept.
The caps serialize to JSON, and chat_template_caps in /props reports
the list as reasoning_effort_levels, from lowest to highest.
* jinja: keep the caps free of the json dependency
The caps keep reporting their flags as a map, and the effort levels
stay a plain member. common_chat_templates_get_caps() builds the JSON
the server reports from both, so jinja depends on json only for the
probe inputs.
* model : add LiquidAI/LFM3-Audio-2B and LiquidAI/LFM3-Omni-2B
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* convert : read the LFM3-Audio config.json as released
A transformers that knows lfm3_audio rewrites the config into another layout (no lfm/encoder keys).
Assisted-by: Claude Opus 5.5
* mtmd : disable flash attention for the LFM3-Audio depthformer
Assisted-by: Claude Opus 5.5
* tts : add a voice option for LFM3-Audio and LFM3-Omni
The model card offers a female and a male voice; --tts-voice for llama-tts, "voice" for the server /tts.
Assisted-by: Claude Opus 5.5
* clean up template handling
* convert : detect LFM3-Audio and LFM3-Omni by model_type
Assisted-by: Claude Opus 5.5
* move banned tokens --> logits bias --> mtmd_helper
* leave mtmd-cli unchanged
* no more template_asr_system
* left over
* llama : keep the LFM3-Audio encoder convs and codec unquantized
Assisted-by: Claude Opus 5.5
* common, mtmd : shorten comments
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* common : support deferred tools and tool_reference content parts
Assisted-by: Claude Opus 5.5
* common : credit the deferred tools co-author
Co-authored-by: Aldehir Rojas <765227+aldehir@users.noreply.github.com>
Assisted-by: Claude Opus 5.5
* tests : fix the type check of the deferred tools test
Assisted-by: Claude Opus 5.5
* server: add --models-memory-max parameter to allow dynamically unloading models when they exceed a memory size threshold
estimate with to-be-loaded model size included
use no_alloc to get memory requirements for model load
only set model memory_mb if not previously calculated
use memory margin instead of total size limit, apply to each device separately
add server memory debug logging
move llama_context_device_memory function to llama-ext.h
fix model count exceeded check
improve memory_per_device map naming
improve variable naming, fix style
also strip models memory margin from child processes
cont : clean-up
replace device memory map with buft memory map. Use llama_get_memory_breakdown
extract duplicated check into helper function
move model memory estimation to subprocess
precompute name->buft map, map GPU host types to CPU buft
cleanup unused variable
remove duplicated init calls
* adapt to upstream changes
* wip
* common_memory_reports internface
* SERVER_ROLE_MEASURE
* server-models-sched
* fix build
* server : fix memory accounting of measure children and claim spin
A measure child runs no_alloc, so the free memory it reports does not
include its estimate: subtracting self there erased the memory held by
other processes, down to zero with --fit on, and the next load could
overshoot the margin. Subtract self only for instance reports.
A queued load only checked --models-max before claiming, so when the
memory margin blocked it behind a busy model, load() threw and the
waiter retried in a tight loop. Refuse the claim while the limits are
exceeded and no idle model can be unloaded, so the waiter sleeps on
the condition variable until one goes idle.
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Pascal <admin@serveurperso.com>
* model : add MiniCPM-OCR-Jev support
The model is a Qwen3.5-VL trunk with a value head read at the last token: it
scores an OCR text against an image rendered from it, it does not generate.
Add the openbmb-minicpm-ocr-jev decision type, served by POST /v1/systemone.
The class scores are the pooled output of the sequence, read with last pooling,
so the conversion turns score.weight into cls.output and sets
embedding_length_out. The checkpoint has no LM head, so text generation is
rejected instead of using the output weights duplicated from the token
embeddings.
The task is fixed, so its prompt is entirely in the systemone template, the
same way h2o-lightning keeps its default there. The processor of the checkpoint
allows up to 16384 merged tokens per image, more than the Qwen-VL default of
mtmd, so the mmproj keeps the image budget of the preprocessor config. The
checkpoint declares MiniCPMOCRForSequenceClassification in its config.json, as
other models do.
Signed-off-by: tc-mb <tianchi_cai@icloud.com>
* fix code
Signed-off-by: tc-mb <tianchi_cai@icloud.com>
* use gguf meta classifier_output_labels
* remove redudant code changes
---------
Signed-off-by: tc-mb <tianchi_cai@icloud.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* common, grammar: add recursive depth limit, make it a requirement
* catch more recursive functions
* common : tidy up peg parser changes
* grammar : reject candidates in a loop, without a depth limit
The depth limit in llama_grammar_reject_candidates_for_stack counted
the code points of a vocab token, so any token of 256 chars or more
was always rejected under a grammar, such as the 512-space token of
GLM-4.7-Flash or the long space tokens of Laguna-S-2.1.
The rejection now walks the code points with its own stack of levels
instead of recursing: there is no limit and no stack risk, whatever
the length of a token from the GGUF, and the masks match master.
* grammar : track rejected candidates as indices into the input
At a given code point a candidate only differs from its input by the
position of its code point pointer, so the levels now carry indices
into the input candidates instead of copies. The first level needs no
special case and the rejects map back to the input directly.
Grammar sampling gets faster than master on GLM-4.7, Laguna, Qwen3.6
and gemma-4 with the json, list and spaces grammars, same masks.
* nit : shorten the comment of llama_grammar_reject_step
* common : add depth_guard for schema walks
* grammar : move GRAMMAR_RECURSIVE_LIMIT into the .cpp
* common : reduce recursion limit for peg parser
* improve
---------
Co-authored-by: Alde Rojas <hello@alde.dev>
Co-authored-by: Pascal <admin@serveurperso.com>
* chat : reject JSON nested more than 128 levels before walking it
The schema builder, the jinja engine and the decision code walk request
JSON with recursion. A request nested deep enough overflows the stack of
the HTTP thread and llama-server dies (SIGBUS on macOS, SIGSEGV on Linux):
for a tool schema from a few hundred levels on macOS and about 10000 on
Linux.
Check the depth first and answer 400 past 128 levels: the chat inputs in
common_chat_templates_apply (tools, tool-call arguments,
chat_template_kwargs, json_schema), the json_schema of /completion, and the
whole /v1/systemone body. A gemma4 tool result that is too deep stays text.
* fix the root, not the call side
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* model : add DeepSeek-V4.1-Flash (deepseek41)
* deepseek41 : remove MXFP8, convert the Engram table to BF16
* deepseek41 : compute the compressed-KV read layers once in the cache
* deepseek41 : use get_cells() for the shared-history check, drop llama_kv_cache::seq_pos_tok_le
* deepseek41 : gather the Engram rows in-graph like qwen4exp, drop the host gather
* deepseek41 : keep the Engram hash constants in hparams.ple_*, one module per Engram layer
* deepseek41 : drop the LLAMA_DSV41_KV_MIRROR toggle
* deepseek41 : keep il last in build_hc_mixes
* deepseek41 : sort the top-k rows before the sparse gather
* tests : add deepseek41 to the Metal fusion baseline
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* mtmd: add audio out stream api
* add /tts endpoint
* add docs
* wire up mtmd_helper_model_can_chat
* upload speaker_ref via form-data
* expose seed to api
* fix header for pcm
* wip
* fix penalty_last_n
* fix server_output_limits
* fix pocket-tts stream
* wip
* add server_schema for tts
* add server routing
* server: coerce seed and stream from multipart form fields
Form fields arrive as strings, so -F seed=42 and -F stream=true were
rejected by the schema. seed joins the integer fields, parsed as a long
long so a full uint32 seed fits, and stream is read as a boolean when
it comes as a string.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
* model : add H2O-Lightning-4B decision model
Adds the h2o-lightning decision type for h2oai/h2o-lightning-4b
(Qwen3.5-4B with a merged decision LoRA).
None of the existing types match this model. It answers with " A"
rather than "A", uses up to 255 labels, and was trained on Python
json.dumps text, so floats like 12.0 must render as 12.0.
The converter writes the decision metadata and the systemone template
from the model's serve_config.json and refuses a config that doesn't
match. Tests skip unless the tiny test model is available locally.
Assisted-by: Claude Opus 5.5
* rm redundant code
* put labels to gguf
---------
Co-authored-by: Jonathan C. McKinney <jon.mckinney@h2o.ai>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* spec : save the dynamic ngram cache file
* save the cache at the common_speculative_impl_ngram_cache destruction
* remove save_static/save_dynamic flags as well as the relevant TODO
* if the dynamic cache file does not exist, start with an empty cache
that is written on exit. if it exists but cannot be read, abort
instead of overwriting it.
* spec : fix draft_one not updating the ngram cache history correctly
* common_ngram_cache_update received only the new tokens with none of
the tokens before them causing ngrams ending at the new token to not
being formed, leading the context cache to only ever hold the prompt
* fix: pass the full history to common_ngram_cache_update with nnew set
to the number of new tokens the way llama-lookup does and also reset
cache_size to 0 on each new request
---------
Co-authored-by: Petros Sideris <petros.sideris@nokia.com>
* init
* wip
* wire it up
* make it clear that it's experimental
* add props.connect_code
* nits
* fix windows build
* server: do not advertise a connect code without the tunnel
--connect-code on its own had no effect other than being served in
/props, so the Web UI showed a remote access code that no tunnel was
serving. Clear it when --connect is off, and say so once at startup.
The teardown comment claimed that terminate() closes the child stdout.
It does not: the log thread leaves fgets() only once every writer of
that pipe is gone, so a descendant of llama-connect would block the
join forever. Describe the real contract instead.
Also restore the --reasoning-preserve default in the generated docs.
* Update tools/connect/CMakeLists.txt
Co-authored-by: Adrien Gallouët <angt@huggingface.co>
* server: dial llama-connect on the bound port and a reachable host
Pass ctx_http.port so --port 0 and the GCP override work, pick the
dial host from --host (wildcards map to loopback, IPv6 is bracketed)
and refuse --connect when only unix sockets are bound.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
Co-authored-by: Adrien Gallouët <angt@huggingface.co>
* common : resolve <quant>-<sidecar> download tags and list cached sidecars
A Q4_0-mtp style tag now resolves the sidecar file when no model file matches it, so a solo draft or mmproj download actually pulls the file. Cached sidecar files list as their own entries so the state survives a restart, and removing such a tag deletes only the sidecar.
Assisted-by: pi:zai-org/GLM-5.3
* ui : optional sanitized raw HTML in markdown
Add an allowHtml prop to MarkdownContent: raw HTML found in the markdown is
rendered after DOMPurify sanitization instead of being escaped as literal
text. Default stays escaped.
Assisted-by: pi:GLM-5.3-Flash
* ui : add the discover models components
The Discover surface: the curated-catalog list with its search and
skeletons, the details pane with its readme, metadata, Hub stats and
download options, and the standalone download progress bar that replaces
the plain one. The quant download button sizes its select with a new xs
trigger, so the select gains that size and the muted box look. The store
stays incomplete when a repo fails, so the next mount retries it.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : put the discover view in the models manager
The manager dialog gains its second view: the Discover Models call to
action fades the table out, slides the title with its compass mark, and
fades the discover surface in; the arrow button returns to the table.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
# Conflicts:
# tools/ui/src/lib/components/ui/button/button.svelte
* ui : add the Enable Discover Models setting
The flag gates browsing and downloading HuggingFace GGUF models, so it is
declared on the discover layer; the repo-tree lookup in the manager layer
above reads it from here.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : resume model downloads from the pause point
A stopped download keeps its partial file instead of deleting it, so
re-posting the tag resumes from disk. The first progress record now
carries the resume offset, the paused snapshot survives into the
resumed entry, and a pause settles as soon as it is requested.
Assisted-by: pi
* ui : lead the discover list with downloads
The discover sidebar lists running downloads above the suggested models,
and steps aside while a query is active. A paused download stays in the
manager table, where it is resumed or dropped.
Assisted-by: pi
* ui : make resuming a paused download work
Re-posting the tag of a paused download hit the router's "already
exists" check, because a paused download parks its entry as DOWNLOADED
until the next reload: a download entry that is not running is now
replaced and resumed. The UI keeps the paused row when the request still
fails, instead of dropping it and looking finished.
Assisted-by: pi
* ui : remember unfinished model downloads
A partial file is named after its content hash, so nothing on disk says
which model it belongs to once the router restarts. The router now keeps
the tags of the downloads it started, clears a tag when the download
finishes or is deleted, and lists what is left as still downloading
without starting anything. The UI adopts those tags as paused on every
list fetch, so a refresh or a fresh open shows an incomplete download and
can resume it from the files already on disk.
Assisted-by: pi
* ui : show a paused download's state on its chip
A paused quant chip reads as paused at rest, the way a running one shows
its spinner, and offers the resume action on hover. The selector's
download row gets a View in Discover action beside its cancel.
Assisted-by: pi
* ui : collapse the download options by default
The copyable download command starts collapsed so the option rows
lead; expanding it stays one click away.
Assisted-by: pi
* ui : keep decision models out of the hub lists
Decision models answer with calibrated probabilities instead of text,
so llama-ui cannot run them: the hub data layer drops them from the
catalog and every search, keyed by the decision-model tag or a
text-classification pipeline.
Assisted-by: pi
* ui : read download tags as quant and sidecar
A `<repo>:<quant>-<sidecar>` tag now parses into its quant and sidecar
instead of one opaque quant token, and ModelsService.draftSidecarsByRepo
collects the router listing's sidecar-only entries per repo, replacing
the inline copy in the models store.
Assisted-by: pi
* ui : cluster draft downloads under their main model
Tracked downloads group by repo: the main weights lead and the draft
sidecars ride inside their item as compact sub-lines, on the selector,
the discover list and the manager table. The main model's controls
pause, resume and cancel the whole cluster, and the manager's download
rows select into the configuration pane.
Assisted-by: pi
* ui : act on tracked downloads from the table rows
The table passes its clusters' draft sub-lines to the model rows. A
row's actions cascade pause and resume, an in-flight row offers Cancel
download while a paused one keeps Delete from disk, and the confirm
dialog's copy follows the state.
Assisted-by: pi
* ui : give downloads a configuration pane of their own
Selecting a tracked download opens the pane in a download mode: live
progress with pause, resume and cancel, and See in Discover, instead of
metadata and load actions that a model without files cannot offer.
Assisted-by: pi
* ui : make the discover details self-fetching and responsive
ModelsDiscoverDetailsContainer owns the details, tree and readme
fetches so hosts outside the discover view can render the pane, and the
details layout adapts to narrow panes with container queries instead of
viewport breakpoints.
Assisted-by: pi
* ui : download a matching draft with the main model
A main quant download now pulls the quant-matched draft of the most
preferred kind the repo ships (DFlash before MTP), fire-and-forget, so
speculative decoding is ready when the main lands. Manual draft chips
stay available; the options row also collapses to one column in narrow
panes.
Assisted-by: pi
* ui : keep discover off by default and couple it with the hub setting
Discover Models starts unchecked. Enabling it turns the Hugging Face
Hub setting on and disabling it turns it back off, so the checkbox
never lies; with discover off the hub setting stays available on its
own for the display data. Stored and reset state are corrected the same
way on load.
Assisted-by: pi
* ui : open the manage models dialog on the manager view
The dialog now opens on the manager instead of returning to the last
view, discover entries still land on the discover view while the
setting allows it, and the discover surfaces follow the setting's
state.
Assisted-by: pi
* ui : give the discover search room for its focus ring
The sticky search bar insets from the panel edges so the focus ring
stays inside the scroll container, and rows scroll behind an opaque bar
instead of through it.
Assisted-by: pi
* common: settle sidecar names on the listing and drop unfinished partials
An infix or trailing sidecar token is ambiguous: draft heads use it
(Model-MTP-BF16.gguf), so do full models with embedded heads
(Model-Q8D-MTP.gguf). Such a name is a sidecar only next to token-free
main weights of the same family, while mmproj or imatrix anywhere in the
name, or a leading token, decides alone (mmproj_f16.gguf).
A quant tag always carries its bit count, so a sidecar named after no
quant (mtp-Model-it.gguf) gets the bare tag: the listing, the plan and
remove all use it. An imatrix tag resolves into a plan slot of its own,
downloaded but never wired into the params.
remove resolves the tag the way a download does and deletes the partial
files of every planned blob, so cancelling a running download or
dropping one left unfinished by an earlier run leaves nothing on disk.
The router passes its token and releases its lock around the call, and
records the unfinished downloads with an atomic write.
llama download succeeds on a sidecar-only plan and prints its paths.
* ui : move dialog views and draft states into enums and constants
The models dialog's views become the ModelsDialogView enum, the draft
subline's states join ModelRowDownloadState, the view fade and the
copy-feedback reset move to ui constants, and the dialog's compass
marks come from DISCOVER_ICON.
Assisted-by: pi
* ui : drop the unused discover surface
The dead openDiscoverModels twin, the commented-out command divider,
the details pane's unused onClose and its header's close button, and a
redundant type cast leave; the command's copy feedback joins the shared
reset constant.
Assisted-by: pi
* ui : trim the download option comments and highlight the chat template
The comment verbosity the options panel and its chips carried shrinks
to the non-obvious why, and the chat template dialog renders through
SyntaxHighlightedCode as jinja instead of a plain pre block.
Assisted-by: pi
* common: only a .gguf file is a sidecar, and mmproj/imatrix as whole words
A non-GGUF file named like a sidecar (quantization-mmproj-Q8_0.json) is
picked as the mmproj, and a sidecar word inside a longer word of a model
name (Phi-2-OmniMatrix.i1-Q4_K_M.gguf) drops the model.
* ui: dedupe draft sidecar badges per quant
The draft sidecar badges deduped by kind and repo without the quant, so
with a draft cached at two quants only one badge survived, and a delete
of the other main quant found no badge to remove its sidecar with.
Also restores the getDownloadEntries doc lost when the clusters method
landed above it.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: adopt the incomplete download status and drop the paused-ids registry
The store inferred an unfinished download from a downloading entry it
held no local state for, which misread a download running in another
tab as paused and offered a resume the server rejects. The listing
carries the "incomplete" status now, so the adoption keys off it
directly.
The paused ids no longer need to survive in localStorage: the server
remembers them across restarts, and the progress snapshot was stale
after a reload anyway. The stale localStorage key is removed.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: quant-match the pause and cancel cascades
Pause, resume and cancel cascaded to every draft sidecar of the repo
while delete only took the quant-matched ones, so canceling a Q4_0
download also killed a Q8_0 draft that belongs to another quant's
main. Every cascade acts on the quant-matched drafts now, matching
what a delete takes with it.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: collapse the duplicated draft subline markup
The downloaded and in-flight branches repeated the identical connector,
label and badge markup; one block with a conditional tail keeps the two
states in sync.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: scrub positioned styles out of sanitized model card html
The style attribute stays allowed for the KaTeX output, which let a
third party card draw a fixed overlay over the app. The sanitize hook
drops position:fixed and position:absolute values and leaves the KaTeX
layout styles alone.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: run the discover mount fetch once and reuse the shared repoOf helper
fetch() toggles its loading flag synchronously inside the mount effect,
which re-ran the fetch on every toggle and retried failed catalog repos
endlessly; the effect now untracks the call. The local repoOf copy and
the duplicate services import give way to the shared helpers.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: narrow the spec-type map to the draft sidecars
SPEC_TYPE carried empty entries for the aux sidecars it is never
indexed with; the map and the command component now type the badge as
a draft sidecar through a draftBadgeOf helper instead of a cast.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: name the decision-model tags and markdown cache keys
The decision-model hub tag and pipeline tag move into the huggingface
constants next to the other pipeline tags, and the markdown transform
cache prefixes get names instead of bare one-letter tokens.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: read the discover setting through one truthiness check
Three places read the setting with !== false and one with Boolean();
all four read it the same way now.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* ui: compare the models dialog view against its enum
The template compared the view state against the 'manage' literal in
three spots while the script used the enum.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* nit: Remove `+` before draft sidecar badge
* server: list unfinished downloads as incomplete
A download that never finished was reported as "downloading", the same
status a live download carries, so a client could not tell a running
download from a dead one. The tags remembered in unfinished-downloads
now list under a dedicated "incomplete" status, without an instance.
Assisted-by: pi (zai-org/GLM-5.3-Flash)
* server: download a model with its sidecars as -hf does
Resolution goes back to master. POST /models takes the sidecar kinds to
pull with the model (mmproj by default) and the download child gets them
as -hf flags, so the server picks the files. /models lists real models
only, each with the sidecars it has on disk, and incomplete downloads
keep their sidecars across restarts. A stopped download keeps its
partial files for the next attempt, and DELETE purges them through the
same plan the download follows.
* ui: download sidecars as parameters of their model
The download options keep their chips, but a chip no longer posts a
sidecar tag: the store maps it to its model and the sidecar kinds to
pull, the quant chip takes its companion draft in the same download,
and draft badges come from the sidecars each cached model lists.
The server adds the sidecars a cached model lacks when it is posted
again, and DELETE removes a single sidecar of a cached model.
* ui : mirror the server's sidecar lookup in draft badges
The server resolves a sidecar by the case-sensitive `<kind>-` token in the same
directory as the weights. The UI matched the token loosely, so a badge could
offer a draft the server never pulls.
Assisted-by: DeepSeek-V4.1-Flash
* ui : post the model's sidecar kinds with its download
The store keeps one download per model: the chip's kinds ride along with the
model's own sidecars, and a download row no longer expands into one row per
sidecar. Draft badges carry no quant of their own yet, so a sidecar of a cached
model is never labelled with the model's quant.
Assisted-by: DeepSeek-V4.1-Flash
* ui : join a quant's draft into its download chip
One chip per quant, its draft badged inside it and its size covering both
files. The draft is the file the server would pick: the same directory, the
exact quant, else the closest bit depth, so a 4-bit model can pair with a
16-bit head.
Assisted-by: DeepSeek-V4.1-Flash
* ui : drop the draft download rows from the manager and selector
A download is one row per model again: the drafts ride with it, and the rows
read the sidecars on disk off the listing instead of pairing sidecar entries
with their model. Pause, resume and cancel act on the model's own download.
Assisted-by: DeepSeek-V4.1-Flash
* ui : keep the discover download list one row per model
The list leads with one row per downloading model, its sidecars as sub-lines.
A row badges only the draft kinds the server can resolve, so a badge never
outlives the file its lookup would pick.
Assisted-by: DeepSeek-V4.1-Flash
* ui : keep the discover chips readable in dark mode
The metadata chips, the chat template button and the View on Hugging Face link
carried a faint border and no surface over the dialog background, so they were
near invisible. They take the tertiary button surface now, and their icons size
with size-* so the variant's base rule leaves them alone.
Assisted-by: DeepSeek-V4.1-Flash
* ui : carry the draft through the download options
One chip per main quant, its draft badged on it and the chip's downloaded state
covering both files. The drafts sit behind an opt-in checkbox with an inline
type pick, and each row opens its own command: it pins the row's quant and only
names the draft type, so -hfd is gone.
Assisted-by: DeepSeek-V4.1-Flash
* ui : line the details skeleton up with the loaded pane
Same root padding and container context as the loaded view, so the container
queries resolve alike. The download options card pads its blocks instead of
itself, the readme gets its card, and a description line stands in for the
catalog paragraph.
Assisted-by: DeepSeek-V4.1-Flash
* common : drop the partials of a removed sidecar
Removing a sidecar alone left the .downloadInProgress files of the sidecars a
download had planned in blobs/. The removal purges them through the same plan
the download follows, and the test covers a finished draft beside an unfinished
one, whose partial goes while the model keeps its files.
Assisted-by: DeepSeek-V4.1-Flash
* server : name why a download is refused
A model that is already downloading, or that is running, answered "already
exists". It now says which: "is already downloading", or "is running, unload it
first", both before the resumable check. The router test covers the two.
Assisted-by: DeepSeek-V4.1-Flash
* ui : post a download once per click
Two quick clicks on the same chip posted twice, and the second answer was
"already exists". The store tracks the model as pending, returns early while it
is pending or in flight, and reads it as in flight before the server answers, so
the chip shows the download at once. The new client test pins the flows: one
POST per double click, the chip reading downloaded once the list reports the
model, a resume keeping its sidecars, a cancel dropping the whole download, and
a reload restoring the paused state.
Assisted-by: DeepSeek-V4.1-Flash
* ui : keep a plain download row the height of the others
The sub-lines wrapper of a download row was rendered even with nothing in it, so
its padding made the row taller than a plain one and the overlaid progress bar
sat in that empty strip. It renders only with sub-lines now, in the selector and
in the discover list, and the selector row takes the phone padding its
neighbours have.
Assisted-by: DeepSeek-V4.1-Flash
* ui : badge a repo's draft once
The args of a loaded model and the listing of a cached one report the same draft
in different words, one with the file's quant and one with the kind alone, so
the merge kept both and a repo row showed the same kind twice. The badges merge
per kind now, the args one winning as it knows the quant, and the test pins both
sources of a real repo.
Assisted-by: DeepSeek-V4.1-Flash
* server : report the sidecars of a preset or a download on its way
A model the preset also names is registered as a preset, so its drafts were
never reported and no row could badge them. A download on its way reported none
either, though the record of the kinds it pulls is right there: those win over
the plan now, the plan resolves through the preset's hf-repo, and a models dir
stays out of it.
Assisted-by: DeepSeek-V4.1-Flash
* ui : badge a download's drafts and open its model from the row
A draft still coming down badges the model id now, the way a landed one does,
while an on-disk draft keeps its checked sub-line. The row itself opens the
model, the status slot beside it pauses or resumes, and the manager resolves a
focus on a download row so its panel opens.
Assisted-by: DeepSeek-V4.1-Flash
* common : report a removed sidecar that only had a partial
Removing a sidecar alone dropped the result of the partial purge, so a sidecar
that only ever landed as a .downloadInProgress blob answered false and the UI
had no reason to refetch. The purge result is folded into the return now, and
the test covers a partial-only removal.
Assisted-by: DeepSeek-V4.1-Flash
* ui : ignore a pause while the download POST is still on its way
The chip reads as downloading before the server answers, so a quick second click
unloaded a model that had not started and left the store neither in flight nor
paused. A pause returns early while the POST is pending, before it touches the
feed or the paused marker. The client test holds the POST open and pins it.
Assisted-by: DeepSeek-V4.1-Flash
* ui : offer a missing draft as its own chip
A model already on disk without its draft had no way to add it: the quant chip
carried the draft, so it read as a download of both. The quant chip keeps to its
own state now, its joined draft shows only while it rides along or is on disk,
and a downloaded quant missing its draft gets a chip of its own - badge, size,
download - that posts the model with that kind, so the server keeps the files
already there and pulls the draft.
Assisted-by: DeepSeek-V4.1-Flash
* server : list a paused sidecar download by the files on disk
A model on disk whose sidecar download stops keeps its unfinished record,
and the listing reported the kinds that record plans as if they were on
disk: the UI checked a draft that never landed and offered no way to add it.
The planned kinds now stand in only while the download runs.
* chore: Clean up comments
* server : list sidecars only for a model that resolves from a HF repo
A preset on a local file has no HF repo, yet the listing resolved its name
as one: the plan threw on the invalid repo format and GET /models failed
for every model. The sidecars now come from the repo a preset names or a
cached model is listed under, and a local file lists without them.
* common : fix download cancel regression
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* common : preserve model partials when removing sidecars
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* server : one sidecar table and an unfinished downloads class
Address review from @ggerganov.
The sidecar kinds live in one table in common/download, mapping each name to
its download option and plan file; the server validates, builds its options
and lists cached sidecars through it instead of its own lists.
The unfinished downloads move into server_unfinished_downloads, a record with
its own mutex and a struct per entry, and server_models exposes them through
unfinished_downloads_get and unfinished_downloads_remove.
* common: one sidecar table, and removals that keep shared files
The resolution, the cached listing and the removal follow a single
table of sidecar kinds, so a kind is declared once with its file
keyword, whether it is a draft, its option and its plan file. The
server reads the same table for the kinds it accepts, the default
sidecars and the child flags.
Removing a tag keeps the files another cached tag still loads, such as
an mmproj named after the removed quant. A sidecar removed on its own
goes for every tag that resolves it.
An unfinished download records the exact paths of its partials when
it starts. A removal deletes those without asking the hub, and keeps a
partial another recorded download also writes. The record is taken
once the child is spawned, and the files go under the models lock, so
a download of the same tag cannot start while they are removed.
* server: drop stale partials and refuse a tag that resolves nothing
Recording a download again deletes the partials of the earlier record
that the new plan no longer writes, such as those of an older hub
revision or of a sidecar the new request leaves out.
A posted tag that resolves no file of the repo is refused before the
download starts. Removing a model follows a single path, whether the
reload erased its entry during the wait or not.
* server: fix the CI race between the router download tests
The pytest workers run in parallel on one shared cache, so a download
test could find the file another test had just fetched and see no
progress, or start from the unfinished downloads record another test
wrote. Each download test now runs on an empty cache of its own.
* server: refuse a DELETE of an unknown name and decide downloads in load()
A DELETE of a name that is neither a model nor a recorded download
went to common_download_remove, and without a tag it wiped the whole
repo cache, including the files of a loaded quant or of a download on
its way. Such a name is now not found, as it was before.
A POST that downloads over an existing entry checked its state outside
the lock, so a load of the same model in between got its instance
killed. The checks now run in load(), under the lock, right before the
spawn. The fake load time of the tests applies to model loads only,
since a download worker loads none.
* server: add incomplete_sidecars to the /models API
A sidecar added to a cached model and then paused kept its record, but
the listing showed only the complete model, so a fresh UI lost the
pause. The model entry now carries incomplete_sidecars, the kinds its
unfinished download has not written yet; a POST with the kind resumes
one and a DELETE with it drops its partial.
* common : drop a kept partial when a resume gets 416
Now that partials survive between attempts, an old or complete
partial makes every retry fail with the same 416.
Delete it so the next attempt can start over from zero.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* common: drop a kept partial when a resume gets 200
A server that ignores the range answers 200 to a resume, and the kept
partial then fails every attempt the same way a 416 does. Drop it as
well, so the next attempt starts over without a range.
* server: refuse a download that shares a partial with one on its way
Two downloads of quants that share a file, the mmproj or an mtp picked
by the closest bits, appended to the same partial and renamed a file
with interleaved bytes. A download whose plan writes a partial that a
running download also writes is now refused until that one is done.
* common : check the saved etag before resuming a partial download
Before resuming, compare the etag saved with the partial to the one
the server now serves. If it is missing or different, start over,
so a resumed download never mixes bytes from two versions of the file.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
---------
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
Co-authored-by: Pascal <admin@serveurperso.com>
Co-authored-by: Adrien Gallouët <angt@huggingface.co>
* feat(convert): Add decision.chat to support decision models that can also chat
Branch: GraniteSwitchDecision
AI-usage: full (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(convert): Add conversion for Granite Switch as decision model
The template follows from the usage sample:
https://huggingface.co/ibm-granite/granite-switch-4.1-8b#guardian-and-decision-side-by-side
Branch: GraniteSwitchDecision
AI-usage: draft (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(common): Add support for chat+decision models in common
Branch: GraniteSwitchDecision
AI-usage: full (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(common): Add granite switch decision model enum
Branch: GraniteSwitchDecision
AI-usage: full (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(server): Plumb through decision_chat bool to support decision+chat models
Branch: GraniteSwitchDecision
AI-usage: full (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(server): Add Granite Switch decision support
Branch: GraniteSwitchDecision
AI-usage: draft (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* docs: Update server README for granite switch decisions / chat+decisions
Branch: GraniteSwitchDecision
AI-usage: draft (Claude + Sonnet 5.5)
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* Revert "feat(convert): Add decision.chat to support decision models that can also chat"
This reverts commit 952ef56764.
* Revert "feat(common): Add support for chat+decision models in common"
This reverts commit 93ed782e3a.
* Revert "feat(server): Plumb through decision_chat bool to support decision+chat models"
This reverts commit 97e9af60dd.
* fix: If Granite Switch supports decisions, it always supports text too
Branch: GraniteSwitchDecision
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* docs: Remove reference to decision.chat in server README
Branch: GraniteSwitchDecision
AI-usage: none
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* common: honor HTTP_PROXY/HTTPS_PROXY env vars in http client
common_http_client() was ignoring standard proxy env vars, causing
downloads via -hf and similar flags to fail silently in environments
behind an HTTP proxy (corporate networks, air-gapped infra, etc.).
Checks HTTPS_PROXY/https_proxy for https:// URLs and HTTP_PROXY/http_proxy
for http:// URLs, in that order. If a proxy URL is set and parseable,
passes it to httplib's set_proxy() and set_proxy_basic_auth() as
appropriate. Malformed proxy URLs are silently ignored so existing
callers aren't affected.
Fixes#21694
* common: drop misleading comment about generic proxy fallback
The comment referenced a 'generic one' that doesn't exist in the code — both
HTTP_PROXY and HTTPS_PROXY are scheme-specific. Reviewer noted the mismatch.
Addresses review feedback from @ServeurpersoCom.
* common : warn when the proxy URL from the environment is malformed
* common : honor NO_PROXY when selecting the http proxy
* ci : retrigger checks (test-thread-safety flake)
* common : bypass the proxy for loopback destinations
llama cli talks to its spawned server on 127.0.0.1 through common_http_client, so with HTTP_PROXY set and no NO_PROXY the health polling went to the corporate proxy, which rejects loopback targets, and the wait loop never exits ("Loading model..." hangs forever).
A remote proxy can never reach the client machine's own loopback, so these destinations are now always contacted directly, before NO_PROXY is consulted: localhost, *.localhost, 127.0.0.0/8, ::1 and 0.0.0.0. Similar to Go's net/http. Proxy handling for downloads and remote --server-base endpoints is unchanged.
Signed-off-by: texasich <101962694+texasich@users.noreply.github.com>
* docs: move proxy tip from README to server docs
per review: the top level README stays lean; the proxy howto now lives with the server docs under Usage
Signed-off-by: texasich <101962694+texasich@users.noreply.github.com>
---------
Signed-off-by: texasich <101962694+texasich@users.noreply.github.com>
Co-authored-by: texasich <texasich@users.noreply.github.com>
Co-authored-by: texasich <texasich@gmail.com>
Co-authored-by: marecabo <23156476+marecabo@users.noreply.github.com>
* model: add Muse Spark Open (text, vision and audio)
Muse Spark Open is a latent space MoE: the residual stream stays at 8192
while the 256 experts live in 4096, with a projection down and up around
them, top-8 sigmoid routing with a correction bias. Attention interleaves
three sliding layers at a 2048 window with rope for one global layer
without rope, with a sigmoid output gate and a weightless QK-norm.
Residuals are norm preserving, their gate is folded at conversion time.
Vision reuses the Muse Glimmer tower. Audio is a causal convolutional
pyramid with no attention and no spectrogram, four stages folding 16, 6,
5 and 4 samples into the channel dim, one embedding per 80 ms of 24 kHz.
The quantizer keeps the latent projections and the attention gate at
Q8_0, a little over 1% of the weights, since the whole residual stream
passes through them and the low-bit types turned the output into a
repeating loop. The model saver writes the post norm epsilon, and the
arch is registered in test-llama-archs.
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Muse Spark: drop the redundant forward expand
* Muse Spark: drop the redundant forward expand and tighten the comments
* Update src/llama-quant.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* Update src/llama-graph.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* Update conversion/muse_spark.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* Update conversion/muse_spark.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* Update conversion/muse_spark.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* Update conversion/muse_spark.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
tojson wrote nan, inf and -inf for these floats, as values and as dict
keys; json.dumps writes NaN, Infinity and -Infinity. The string and safe
filters of a float keep nan and inf, as Python's str() does, so they no
longer use the tojson function. float_to_json is renamed float_repr, as
it now gives str(); float_json gives the json.dumps text.
Also say in a comment why a last digit 9 is not bumped at a power of 2.
* server: save only restorable slot states to the prompt cache
The idle-slot save loop stores every idle slot whenever a task starts,
while only completion tasks restore from the prompt cache. Rerank,
embedding, decision and infill states fill the cache up to its limit
without ever being read back, and slots already cached are offered
again at every task start.
Each slot now tracks with cache_pending whether its state is restorable
and missing from the cache: a completion release or an explicit slot
restore sets it, prompt_save consumes it, prompt_clear resets it. Both
save paths share this rule, and the LRU path restores only for
completion tasks.
* server: test that decision slots skip the prompt cache
Decision tasks never mark their slot as cacheable, so starting new
tasks must not save their idle slots to the RAM prompt cache, with or
without a unified KV cache.
* server: restore any reusing task from the prompt cache
Embedding and rerank tasks never reuse their state, so their slots are
cleared on release like child slots and the cache only holds states
that a later task can restore. Infill and decision tasks now restore
from the cache too, which replaces the cache_pending flag.
Decision models disable the prompt cache unless --cache-ram is given,
since their states seldom repeat.
* spec : add lilicorr support
* convert : use convention for hparam assignment
* add todo for hparam use in llama-batch.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* typo fix
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* common : add --spec-draft-n-ubatch
Allow configuring the physical batch size of the draft context. The
drafters feed it at most the drafted tokens per sequence and chunk larger
batches by its own n_ubatch, so it does not need the ubatch of the target.
A smaller value shrinks the draft compute buffer and leaves more VRAM for
the target KV cache (the draft is fitted together with the target).
The default 0 keeps the current behavior of following --n-ubatch.
Assisted-by: pi:llama.cpp/Qwen3.8-Flash-Next
* cont : remove comment
[no ci]
tojson printed floats through a C++ stream (6 significant digits, no
".0"), so 48.858844 became 48.8588 and 1.0 became 1 in tool definitions,
tool-call arguments and other template output. Write the shortest digits
that read back as the same value, as json.dumps does. The string and safe
filters of a float use the same code.
* tests : consolidate the context state tests into test-llama-context
test-save-load-state, test-recurrent-state-rollback and
test-state-restore-fragmented check the same object from three places:
the KV cache and the recurrent state of a llama_context, saved, loaded,
copied, rolled back. Each had its own main, its own loop over the
models, its own copy of the token and the comparison helpers, and a run
of all three loaded the same models several times.
They are one binary now, and the case is the unit of the test:
tests/llama-context/test-case.h the interface a case implements
tests/llama-context/cases-kv.cpp the cases of the KV cache
tests/llama-context/cases-rs.cpp the cases of the recurrent state
tests/llama-context/test-util.cpp tokens, generation, comparison
tests/llama-context/test-runner.cpp the models of a case, on threads
tests/llama-context/test-log.cpp the log file of a model
A run is a table: a row per model, a column per case, a cell holds the
verdict of that pair. The models load on several threads (-j, --threads,
min(cores, 4) by default), the table is printed when it is complete and
the log of a model that failed is printed after it, in the order of the
rows. A case returns a verdict and the reason for it, and the runner is
the only one who reports - the test does not use tests/testing.h, a run
over 130 models is a matrix of verdicts and not a tree of subtests.
Staging no longer travels through the environment: llama_model_set_attn_rot
replaces the LLAMA_ATTN_ROT_DISABLE variable, which a model loaded in one
thread used to change for the models the other threads were loading, and
llama_memory_get_buffers is added for the cases that copy the buffers of
a memory. common_log_set_stdo keeps the console quiet while the table is
being built.
ggml_aligned_malloc allocates with posix_memalign when the thread
sanitizer is on. On macOS it allocates with the Mach VM, which the
sanitizer does not intercept, so it never sees a page range change hands
and reports the first write into recycled memory as a race - 30 of them
in this test, and every one of them false.
Assisted-by: pi:llama.cpp/Qwen3.8-Flash-Next
* cont : run single-threaded by default
* cont : try to build the tests on all platforms
* cont : trim down some body fat
* cont : fix
* cont : fix the fix
* examples : fix draft sampling and rejection handling
This commit fixes two issues in the speculative example which are
described in detail in the linked issue.
Resolves: https://github.com/ggml-org/llama.cpp/issues/29975
* examples : add kv-unified requirement for parallel > 1
Add an optional ggml_backend_sched_realloc_callback that user code registers with
ggml_backend_sched_set_realloc_callback to be notified when the buffers reserved for a
graph are not sufficient and have to be reserved again. The callback reports whether the
backend assignments and the graph size changed since the previous scheduling.
llama_context registers the callback when creating the scheduler (wrapped into the new
llama_context::sched_new helper) and treats the reallocations that follow a change of the
backend assignments as expected, counting the rest by graph size - unchanged or changed
from the previously scheduled graph. Both counters are reported on one line in the perf
stats.
Assisted-by: pi:llama.cpp/Qwen3.8-Flash-Next
* common : read a GGUF's trained context from its metadata
common_get_gguf_n_ctx_train opens only the file's metadata (no_alloc,
like common_get_decision_type) and reads <arch>.context_length, so a
caller can learn the trained context without loading the model. It
accepts both u32 and u64 values and returns 0 when the file is missing,
unreadable, invalid, or reports no context length.
Assisted-by: pi:zai-org/GLM-5.3-Flash
* server : report the trained context in the models listing
update_caps already resolves the model file offline to read its
modalities, so it now reads the trained context from the same GGUF
metadata, and GET /models reports it as context_length when it is
known. A router listing then carries the context without any Hub
request, which lets the UI sort and filter by it offline.
Assisted-by: pi:zai-org/GLM-5.3-Flash
* ui : take the trained context from the models listing
The router now reports context_length per model, so the option mapping
fills contextLength from it and the manager reads it before the Hub
record. The Context column, the context sort and the context filter
then work with the Hugging Face Hub API turned off. A browser suite
guards the sort and the search, the Hub-cache driven context filter and
the re-sort when details arrive after the sort was clicked.
Assisted-by: pi:zai-org/GLM-5.3-Flash
* ui : mark favorite models with a heart
A favorited model shows a rose heart in the selector even before its
row is hovered, and the crossed heart takes its place on hover, so
unfavoriting stays one hover away. The manager table marks its
favorited rows with the same heart after the badges and capabilities.
Assisted-by: pi:zai-org/GLM-5.3-Flash
* fix: UI text nit
* fix: UI nits
* fix: Favorite models grouping in models table
* feat: Remove sorting from Status column in Models Table
* server: read the GGUF metadata once per model
Read the decision type and the trained context in a single GGUF open,
accept only a UINT32 context length like the model loader, and reset
n_ctx_train with the other caps so a failed refresh drops it.
* fix: Post-review fixes
---------
Co-authored-by: Pascal <admin@serveurperso.com>
* server : preserve context checkpoints across slot save/restore
Append the checkpoints after the packed server_tokens payload added in #26640
and count them in n_written / n_read, so a restored slot can still roll back to
a checkpoint instead of re-processing the whole prompt.
* server : drop draft checkpoint data that does not match the draft context
Restoring a slot saved with a different draft KV cache type aborted in
load_dft(). Test-load one draft checkpoint on restore and drop the draft
data if it does not fit, instead of crashing. Adds a regression test.
Co-authored-by: Igor Okulist <okigan@gmail.com>
* server : harden the checkpoint appendix of slot save files
Bound each blob size by the bytes left in the file before allocating, open the
file with UTF-8 paths on Windows like the llama state payload, fall back to full
prompt re-processing when a checkpoint restored from a slot file fails to load,
and replace the 1024 count cap by keeping the last n_ctx_checkpoints while reading.
* server : report an incomplete checkpoint appendix as a failed slot save
Return an error to the client when the appendix cannot be written, like a
failed payload write, and make the oversized-blob test declare a size that
cannot be allocated, so an unbounded allocation fails the test.
* server : reject an empty target state in the checkpoint appendix
A saved checkpoint always holds a target state, an empty blob would roll back
without restoring anything. Also log with the slot id, and load the draft test
model from the HF cache instead of a second download.
* common : return bool from checkpoint load_tgt / load_dft
A checkpoint restored from a slot file falls back to full prompt re-processing
when it fails to load, a checkpoint created in memory still aborts.
---------
Co-authored-by: Igor Okulist <okigan@gmail.com>
* model : add LiquidAI/d1-omni-600M decision model
Assisted-by: Claude Opus 5.5
* mtmd : keep conformer GLU sigmoid on CUDA
Assisted-by: Claude Opus 5.5
* server : take d1omni audio through images and input_audio, scope memory-less lfm2 to non-causal
Assisted-by: Claude Opus 5.5
* common : rename decision type d1omni to lfm2-d1-omni, server : make images an alias of files
Assisted-by: Claude Opus 5.5
* bugfix: infinite recursion caused by a tool named 'call'(#29967)
* chat : use index for schema and argument rules
* tests : remove tests
* tests : add expect_rules to peg test parser
---------
Co-authored-by: Alde Rojas <hello@alde.dev>
