* server : add realtime conversation and transcription on /v1/realtime
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* examples : default the realtime client to the server port 9931
Assisted-by: Claude Opus 5.5
* server : sample realtime responses right after their own decode
Slots respond in turns on one context: sampling at the start of the next step read the logits of whichever slot decoded last, so concurrent sessions mixed their outputs.
Assisted-by: Claude Opus 5.5
* move more stuff to server-realtime, making it self-contained
* examples : fix the type check of the realtime client
Assisted-by: Claude Opus 5.5
* examples : use the model card prompts in the realtime client
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* 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
* model : add LiquidAI/LFM3-1.7B and LiquidAI/LFM3-VL-2B
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* tests : set the SWA rope base of the LFM3 test model
Assisted-by: Claude Opus 5.5
* llama : enable recurrent state rollback for LFM3
Assisted-by: Claude Opus 5.5
* Apply batched suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Tarek Dakhran <github@dakhran.com>
* gguf-py : align the lfm3vl mapping comments
Assisted-by: Claude Opus 5.5
* llama : fix CRLF line endings from the review suggestions
Assisted-by: Claude Opus 5.5
* tests : add the LFM3 Metal fusion baseline
Assisted-by: Claude Opus 5.5
* llama : keep the LFM3-VL depthwise conv kernels in F32 when quantizing
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
The expand button wrapping the system message card defaulted to
inline-block. WebKit takes an inline-block's baseline from its last
line even when that line is clipped by the card's max-height, so the
row grew to the height of the whole prompt and left a large empty gap
below the card. Make the button a block so the row matches the card.
Assisted-by: Claude (Opus 5.5 Medium)
* 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>
The org-less group renders without a header, so when it followed a named
org its models looked like they belonged to that org. Put it ahead of the
named org groups.
Fixes#25227
Assisted-by: Claude (Opus 5.5 Medium)
On desktop, the reasoning effort toggle now gets a muted background on
hover and while its menu is open, matches the model selector's 24px
height, uses a 13px icon and sits 5px from the selector.
Assisted-by: Claude (Opus 5.5 Medium)
* ui: add conversation compaction
Add a compaction action that asks the model to summarize the
conversation so far and stores the summary in a new compaction node
appended to the branch. Later requests slice the branch at the last
compaction node, keeping the system prefix and continuing from the
summary instead of the full history, which frees up context while the
complete history stays visible and navigable in the UI.
The slice is applied once at the request funnel, covering the plain
send, the agentic flow and the KV cache pre-encode, plus the continue
path that bypasses it. The summary request is a one-shot outside the
SSE replay machinery, streamed live into the node with a full rollback
on abort, error or empty result.
The action is exposed as a /compact slash command and a Compact button
in the context gauge popup, with an overridable summarization prompt
in the settings.
* ui: pre-fill KV cache and refresh context gauge after compaction
Once the summary is stored, pre-encode the compacted branch and stamp
the returned prompt timings on the compaction node: re-encoding the
reduced prefix is part of the compaction itself, so the server KV
cache and the context gauge reflect the summary right away.
The summary stream is registered under a prefixed identity
(compact::convId), so the visibility kick and byte-offset resume
protect it through tab switches while the reload probe never
reattaches it as a chat turn. The stamped node becomes the shared
context truth for the gauge and the processing state restore, and the
stale live state that kept the gauge full is cleared.
* chore: format
* ui: allow a dedicated model for conversation compaction
An opt-in setting reveals a model selector whose options come from the
live router model list. The chosen model writes the summary and is
loaded on demand when it is not resident, while the default path keeps
resolving to the conversation's own model.
* ui: align the compaction model field with project conventions
* ui: fix the model option helpers import path
The compaction model selector pulls filterModelOptions and
groupModelOptions from the models component folder, where they no
longer live, so the build fails to resolve the module. Point the
import at the navigation folder, which now owns them.
Missed during the rebase: the helpers moved in a commit that does
not touch any compaction file, so nothing conflicted.
* ui: import the model option helpers from models/utils
* ui: follow the moved models selector in the compaction model field
The models manager moved ModelsSelectorList under ModelsSelector and
the model option helpers to /utils, where groupModelOptions takes
the options alone. Drop the stale copy the rebase kept and read the
helpers from their new home.
* ui: drop the dedicated compaction model
A summary written by another model loses the prefix the conversation
model cached, so the whole history is prefilled again, and the model
then resumes from text it did not write. The conversation model
always writes its own summary.
* ui: keep the last steps of a compacted conversation
A compaction now folds the steps the model reads but the last ones,
a step being a user message or an assistant message with its tool
results, and stores how many it kept on the compaction node. The
model then reads the system prefix, the summary, the kept steps and
what follows.
The summary request is the request the chat sends, with its options,
tools and message shaping, cut before the preserved steps: the server
reuses the prefix it cached and only the instruction is new. The
number of preserved steps is a setting, 10 by default.
* ui: run every compaction summary through one path
Three callers needed the same thing - the automatic pre-encode pass, the
action in the context gauge, and re-running a summary from the block - and
each of them had grown its own copy of the request, the streaming and the
storing.
There is one path now: a summarization owns a node, streams into it, and
reports itself through a ledger the rest of the app reads (`isCompacting`,
which node belongs to which conversation). Re-running a summary is the same
call on an existing node, so the two entry points cannot drift apart again.
* ui: give the compaction row its own summary UI
The summary was a line of text in a tool-call-shaped collapsible, which is
how a compaction reads as a side note rather than as the thing the rest of
the conversation now stands on.
The row is its own block: a divider that names the boundary, and the summary
inside it with the model that wrote it, its statistics, and the same actions
an assistant turn has - copy, edit, fork, regenerate and delete all apply to
the summary, and it collapses to the divider once a summary is in, because
the shrunk context is the headline and the prose is the detail.
The divider is a variant of the shared collapsible block, which also needed
the toggle and the title split into snippets so a caller can lay them out
without copying the markup. The action icons no longer take a role: they
render what a message offers, and a compaction offers the same as any other
stored message.
* ui: report compaction progress on the row
The row owns the run, so the row says how it is going: the prompt progress
in the header while the context is being read, the phase once the summary
starts streaming, and the token count once it is in. Before the first
summary token there is nothing to collapse, so the header stands on its own
instead of offering an empty block.
* ui: keep the summarized turns quiet while a compaction runs
The turns being summarized used to keep their own "Processing..." indicator
and live reading stats while the summary streamed, so the conversation said
the same thing twice in two places. The row reports the run, so the turns it
replaces stay silent until it is done.
* ui: hand the compact action to the context gauge
Compacting is a decision about the context, so the action belongs with the
numbers that show the context filling up rather than inside the form: it sits
at the bottom of both the hover card and the drawer, under the breakdown it
acts on, quiet enough to stay a footnote and disabled - with the row's own
spinner - while a summary is already running.
* ui: follow the bottom, otherwise leave the view alone
The screen scrolled itself with a controller of observers, intervals,
direction heuristics and landing timers, and still managed to move the view
while the reader was reading: any mutation that grew the branch was treated
as a reason to keep following.
The page is the scroller, so it follows when the reader sits at the bottom,
and stays where it is otherwise. A resize observer plus native scroll
anchoring does the rest, and `pointerdown` buys the reader a moment of grace
to be caught mid-drag.
* ui: expand collapsible bodies with a height transition
Expanding a block snapped it open: the body was mounted the moment `open`
flipped, so a tall block moved the conversation around it in one frame.
The body now goes through the same region the models table uses. The height
interpolates and the visibility follows it, so a body is unmounted once the
collapse has finished rather than the moment it starts - a closed block
still costs nothing while tokens stream past it.
* ui: open a compaction summary at the top of the screen
Toggling a summary left the reader wherever they were, so a conversation that
had just compacted showed the divider at the bottom of the screen and read
down from there.
A toggle now scrolls the page once and lands the divider a breath under the
tabs, both ways: the summary is read from its beginning, and closing it returns
to the same boundary instead of wherever the page happens to come to rest. The
scroll waits for the body to reach its height, because before that the page is
too short to scroll the divider up there and the call would clamp.
That wait is the shared collapse duration rather than a transition event: an
engine without `interpolate-size` animates the region's grid row instead of its
height, so a listener on `height` would never fire there and the page would not
move at all.
* ui: spin the compaction icon while the summary runs
The divider reported the phase in its title while the icon still showed a
finished block, so a run in progress and a summary that had landed looked the
same in the one place the eye reads first. The icon spins while the summary is
running and folds back once it is in.
* ui: let the compaction summary speak without the reasoning trimmings
The summary is the thing the conversation now stands on, not a note beside
it, and the conversation model always writes it, so the body drops the
reasoning block's rule and indent (`flushBody` keeps them for the blocks
that borrow them) and the model selector under the summary is gone - there
is nothing left to swap.
* ui: drop the model override from the compaction path
The summary row no longer offers a model selector, so nothing hands
regenerateCompaction a model anymore. Remove the parameter from the
whole path, with the on-demand load of another model it carried: the
summary always comes from the model the request funnel resolves.
* ui: let the compaction summary think as the chat does
The summary request forced thinking off, overriding the reasoning
effort the user chose. The summary is the text the conversation
resumes from, the task where reasoning helps the most, so the request
now carries the very options of the chat.
* ui: pre-encode the compacted branch as the next turn reads it
The post-compaction pre-encode sent the branch without tools, while
the tools render ahead of the messages, so it warmed a prefix the next
turn never reads and that turn prefilled the whole compacted context
again. The pre-encode now sends the tools, message shaping and
reasoning handling of the chat, so the next turn only prefills its new
message.
* ui: pre-encode the branch the next turn actually reads
The per-turn pre-encode sent the messages of the request plus one
assistant message holding the streamed text, without tools. With
tools on, it replaced the slot the next turn extends with a prefix
nobody reads again, and after an agentic turn its history did not
match the stored calls and results. Without agentic, it never ran.
Both pre-encodes now read the stored branch up to its leaf, cut at the
last compaction, and send it with the tools, message shaping and
reasoning handling of the chat. The plain completion path triggers it
too.
* ui: refuse a compaction summary the output limit cut
The stream handler read every chunk but dropped the finish reason, so
a summary cut by max_tokens folded the conversation into half a text.
The handlers now hand the finish reason to onComplete, and a summary
that ends on length rolls the compaction back with an error.
The summary was framed through a replacement string, so $& or 32560 in
it changed the text the model read; it is framed as written now.
* ui: wait for the collapse transition in the tool call tests
The collapsible body now unmounts once its collapse animation ends rather
than as soon as the block closes, so the "folds back" assertions ran before
the body was gone. Wait out COLLAPSIBLE_TRANSITION_MS first.
Assisted-by: Claude (Opus 5.5 Medium)
---------
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* ui: open model details in a global drawer without leaving the page
The model info actions in the selector used to navigate to the models page
to open its details pane, and a phone opened a separate dialog instead. The
drawer now lives outside the models table, driven by uiStore, so the info
icon opens it over whatever page is showing.
The models dropdown and the phone picker stay open under the drawer's
backdrop, and keep focus while the drawer opens and closes, so the trigger's
tooltip no longer pops over the drawer.
Assisted-by: Claude (Opus 5.5 Medium)
* ui: let the model details drawer reopen after a drag to dismiss
Dragging the drawer down wrote vaul's own open state, which the one-way open prop then kept closed, so the info action could not open it again until a refresh. Bind open both ways through the store instead.
Assisted-by: Claude (Opus 5.5 Medium)
* ui: close the models selector from the details drawer chat actions
Assisted-by: Claude (Opus 5.5 Medium)
Extract the keyboard-shortcut delete confirmation into DialogConversationDelete
and reuse it in the sidebar and mobile search page instead of the native
window.confirm prompt.
Assisted-by: Claude (Opus 5.5 Medium)
* ui : land opened conversations at their bottom before the first paint
Pin the page to its bottom with a ResizeObserver until it stops resizing or the reader interacts, and mount the last rows eagerly so the landing frame shows real content.
Assisted by: Claude (Opus 5.5 Medium)
* ui : make conversation tabs browser-style
A plain navigation shows the chat in the current tab instead of adding one, and the new-chat tab turns into the conversation it starts. New tabs come only from explicit actions: the + button, Cmd/Ctrl-click or middle-click on a sidebar chat, and its Open in new tab menu item, which open in the background. Closing a tab moves to its neighbour among the tabs the view shows.
Assisted by: Claude (Opus 5.5 Medium)
* ui : share the tab surface and tab bar fade styles
Move the tab item surface (shape, resting and active looks) to TAB_SURFACE_* class constants and the fade under the tab bar to a global chat-top-fade class, so other elements can match the tabs.
Assisted by: Claude (Opus 5.5 Medium)
* ui : fit the chat column below the tab bar
The tab bar reported 1.25rem of its height while it takes 3.3125rem (pt-3.25 + h-10), so a short conversation still left a few pixels to scroll. Use the bar's full height and drop the extra 1rem from the column's minimum height, so it fills the viewport exactly; the centered new-chat form moves up by the same 1rem to keep its place.
Assisted by: Claude (Opus 5.5 Medium)
* ui : stop the page from bouncing past its ends
Elastic overscroll on the root scroller dragged the sticky and fixed bars (tab bar, chat form) along at the top and bottom of a chat, and they jumped back on release. Set overscroll-behavior: none on html and body.
Assisted by: Claude (Opus 5.5 Medium)
* ui : stop scrolled dialogs from bouncing past their ends
Dialogs scroll on their own (the settings panel, the search results), so the page rule did not reach them and their sticky navigation still jumped on overscroll. Turn off overscroll on dialog panels and on the scroll containers inside them. Only scroll containers: Firefox counts an overflow-hidden box such as truncated text as one, and `none` there kept the wheel from scrolling the list around it.
Assisted by: Claude (Opus 5.5 Medium)
* ui : fit a first exchange opened by the working directory row
The last answer's minimum height leaves room for the last question only, so the synthetic row that a new chat starts with (Set working directory to ...) made a short first exchange overflow by that row. When everything above the last question is synthetic, count those rows as part of it.
Assisted by: Claude (Opus 5.5 Medium)
* ui : keep following a streaming response until the reader scrolls up
Auto-scroll stopped whenever the page moved up, including moves the
reader did not make: scroll anchoring and blocks re-rendering shorter
while a response streams. Only the reader's wheel, touch, scroll keys
or scrollbar drag now count as scrolling up.
The send scroll also looked up the new user bubble by position, which
picked an older message when the answer row had not rendered yet.
Assisted by: Claude (Opus 5.5 Medium)
* ui : fade the chat form between its centered and bottom positions
The form no longer slides across the column between the new-chat center
and the bottom. It fades out drifting toward where it goes and fades
back in where it lands, quicker when opening a chat than when going back
to a new one. Its wrapper keeps the same height in both positions, so
the messages never shift while it moves.
The new-chat greeting fades in as the form settles, also on a refresh or
a first visit. Reduced motion keeps only the fades.
Assisted by: Claude (Opus 5.5 Medium)
* ui : let the expanded sidebar be resized by dragging its edge
Bring back the desktop sidebar resize handle that was dropped with the
shadcn sidebar primitive. The width is clamped between 18rem and 32rem,
persists across reloads, and resets on a double-click of the handle. The
tab bar follows the same width so a wider sidebar never covers it.
Assisted by: Claude (Opus 5.5 Medium)
* ui : rubber-band the sidebar edge past its bounds and drag it shut
Past the max width the edge resists harder the further it is pulled, and
the same happens below the min width until the pull passes 9rem, where it
snaps to the pointer and letting go hides the sidebar. A release outside
the bounds springs the width back to the nearest one.
Assisted by: Claude (Opus 5.5 Medium)
* ui : show the sidebar edge strip faintly on hover and solid while dragging
The strip is clipped to the sidebar's rounded corners through its own
overlay, so the sidebar itself is never clipped.
Assisted by: Claude (Opus 5.5 Medium)
* ui : remember whether the desktop sidebar is open across reloads
A phone opens the sidebar as an overlay, so it always starts closed there
and its toggling never overwrites the desktop preference.
Assisted by: Claude (Opus 5.5 Medium)
* ui : fade the sidebar labels and conversation list with its width
The fade follows the live width, so it tracks both the toggle's width
transition and a drag below the minimum width.
Assisted by: Claude (Opus 5.5 Medium)
* ui : persist the sidebar width on release and clamp a restored one
A drag now updates only the live width and writes it to localStorage once
when released. A width restored from localStorage is clamped to the
current bounds, so a value saved under older bounds does not stick.
Assisted-by: Claude (Opus 5.5 Medium)
* 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>
* ui : move models manager to its own route, keep Discover as a dialog
Models now lives at #/models instead of a dialog. Discover opens as a
standalone dialog over it, and leaving the page returns to the chat it
was opened from.
Assisted by: Claude (Opus 5.5 Medium)
* ui : polish the models page layout and filters
Give the models page a page header with the Discover action, calmer
column labels, tinted section and family headers, and an empty state.
Load the model list on a direct visit, slide the detail pane over the
table below xl, and draw the filter toggles as one box matching the
context select, with room for their shadow.
Assisted by: Claude (Opus 5.5 Medium)
* ui : round the models table family headers
Assisted by: Claude (Opus 5.5 Medium)
* ui : fix models page navigation and Discover gating
Record the models page's way back after every navigation, so Back,
a typed URL or a reload no longer return to a stale chat. Escape
closes the detail pane, then leaves the page. Gate every Discover
entry point on one shared check, recheck the API key on /models,
skip the duplicate router fetch on a direct load, and share the
route load between pages.
Assisted by: Claude (Opus 5.5 Medium)
* ui : show model details in a drawer
Open the models manager's detail pane in a drawer, from the right on
desktop and from the bottom on a phone, instead of an inline side
panel and a full-screen cover. Pad the pane on both sides, drop its
close button on a phone, and assert that filtered rows are gone from
the page rather than merely hidden.
Assisted by: Claude (Opus 5.5 Medium)
* ui : make whole models table rows clickable
A click anywhere on a model or quant row opens it, unless it lands on
one of the row's own controls (load toggle, actions menu). The name
button stays the keyboard path to the same action.
Assisted by: Claude (Opus 5.5 Medium)
Use the dropdown menu surface (border, radius, background, shadow,
padding) for the hover card and the context gauge popup, and fix the
hover card open/close animation to use bits-ui data-state attributes.
Assisted-by: Claude (Opus 5.5 Medium)
* mtmd : lfm2 bilinear resize matches torchvision
Lfm2VlImageProcessor and d1-omni vision.py resize uint8 images with
torchvision (antialias=True). That is Pillow's algorithm, except that the
weights are int16 with as many fractional bits as the largest weight allows,
where Pillow uses 22 bits. The Pillow port was 1-2 levels off on about 1% of
the values of the d1-omni and LFM2.5-VL crops.
RESIZE_ALGO_BILINEAR_TORCH rounds the weights of the Pillow port to that
precision and scales them back to 22 bits, which gives the output of
torchvision with the same passes, and "bilinear" maps to it for LFM2 and
d1-omni. Other models keep the Pillow algorithms.
* mtmd : lfm2 bicubic resize matches torchvision
Lfm2VlImageProcessor resizes with torchvision for the bicubic checkpoints too
(d1-3B, LFM2-VL), so "bicubic" maps to RESIZE_ALGO_BICUBIC_TORCH for LFM2: the
Pillow bicubic filter (a = -0.5, as torchvision with antialias) with the int16
weights of torchvision. The Pillow port was 1-2 levels off on about 0.25% of
the values of the d1-3B crops.
* use bitfield, add hparams setter
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Add Soprano-80M and Soprano-1.1-80M (https://huggingface.co/ekwek/Soprano-1.1-80M)
as an audio generation model: a Qwen3 backbone plus a Vocos decoder that runs
as a gen-only mmproj.
- convert: detect Soprano checkpoints and export the backbone as qwen3 and the
decoder.pth Vocos weights as the mmproj
- vocab: add the soprano pre-tokenizer (lowercase, whitespace collapse,
per-digit split, [UNK] fallback)
- mtmd: add the Vocos graph and ISTFT, allow loading a gen-only mmproj for
Soprano and include the gen-audio context in mtmd_get_memory_usage
- mtmd-helper: add the Soprano pipeline; the decoder runs over the whole
utterance, so stream mode sends the audio in one chunk after flush()
- tts: document Soprano usage
Assisted-by: Codex
Assisted-by: Claude Opus 5.5
Run npm audit fix, then bump the remaining vulnerable packages within
their current majors: storybook 10.6.2, vitest 4.1.12, vite 7.3.7,
@modelcontextprotocol/sdk 1.32.1, dompurify 3.4.17, mermaid 11.17.2,
@vite-pwa/assets-generator 1.0.4 and @tailwindcss/typography 0.5.20.
Override katex to 0.18.11 and postcss-selector-parser to 7.1.6 since
their dependents still pin vulnerable ranges, bump the sharp override
to 0.35.5, and pin @storybook/svelte so npm does not resolve the 11.0
alpha through the addon-svelte-csf peer range.
Storybook stays on 10.6.2 as 10.6.3 is newer than min-release-age.
Assisted by: Claude (Opus 5.5 Medium)
* server: realtime API: send complete after committed audio drains
* server: realtime API: complete a commit at its end row
Completion is triggered when the stream runs dry, which is a timing
proxy: audio appended while the tail drains leaks into the committed
item, a final commit before the drain merges both items, and back to
back commits collapse into one.
mtmd_audio_stream_flush() records the row count at the end of the
flushed audio (mtmd_audio_stream_get_n_rows_flushed), next to the rows
produced so far (mtmd_audio_stream_get_n_rows). The slot keeps a FIFO
of these end rows and completes each commit once every row up to it is
decoded.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
* server : support typed content input for rerank endpoint
Assisted-by: Opencode/Qwen3.8 27B
* server : address rerank multimodal review findings
- reject multimodal rerank input when the model has no rerank chat template (images were silently dropped)
- translate handle_media download/base64 failures to 400 instead of 500
- reject negative top_n with 400 instead of letting resize throw
- fix comment typos, redundant comments, indentation and trailing whitespace
- README: document that TEI input accepts the same shape as Jina; drop stray blank line
Assisted-by: opencode
* Trimmed README
---------
Co-authored-by: timothywang21 <timothywang21@users.noreply.github.com>
* feat(ui): add Show tool call in progress display setting
Add the showToolCallInProgress key and its checkbox to Settings > Display,
right next to its "always show" counterpart. Upstream dropped a setting of
this exact name in 43b5e63589, folding it into alwaysShowToolCallContent
because the old name promised expansion that outlives the call; this brings
back the narrower, in-progress-only meaning.
The entry is registry-driven, so SETTING_CONFIG_DEFAULT, the dialog field and
the ui_settings admin baseline pick it up without extra wiring. It ships
enabled, mirroring Show thought in progress, and the always-show help text is
reworded so the two toggles read as a pair rather than contradicting each
other.
Assisted by: llama-ui (ggml-org/Qwen3.8-Flash-Next:Q8_0)
* feat(ui): expand tool call blocks while they are in progress
Drive the default expansion of TOOL_CALL_STREAMING and TOOL_CALL_PENDING from
showToolCallInProgress and leave TOOL_CALL, the terminal state, to
alwaysShowToolCallContent. A finished call now folds back on its own once its
result lands, which is exactly how the reasoning block behaves when the
thought completes.
Manual toggling keeps precedence over both defaults in either direction:
isExpanded() only consults the settings while expandedStates holds no entry
for the section.
Client tests pin the truth table for the two toggles, including the automatic
fold-back and both manual overrides.
Assisted by: llama-ui (ggml-org/Qwen3.8-Flash-Next:Q8_0)
* fix(ui): keep running tool calls expanded
A call the agentic loop reports as running now outranks its section type.
exec_shell_command persists an empty result before reading any output, so a
live call is already TOOL_CALL and folded back, which hid the streaming
output the setting is meant to show.
Move the expansion default to isSectionExpandedByDefault so the running-id
rule is covered by a truth table, and test the pending -> finished transition
instead of only the finished state: a block that only ever got mounted
finished cannot prove it folds back on its own.
Assisted by: llama-ui (ggml-org/Qwen3.8-Flash-Next:Q8_0)
* feat(ui): stream the exec command from the first character
The exec parser read its args strictly, so while the model was still
typing the call the block title stayed empty and the body claimed
"Running...". Parse the args partially (the read_file / edit_file /
write_file pattern), keep a terminal cursor while the args JSON is
incomplete, and stand the conversation cwd in for the x-tool-cwd that
only arrives with the result message, so the prompt is there from the
first character. The body stays empty while the args stream, shows
"Executing command..." once the call is executing, and the wrapper
drops its padding for empty phases so the title sits flush with the
frame.
Assisted by: Delta (zai-org/GLM-5.3)
* fix(ui): stream file tool bodies even before a path arrives
write_file and edit_file refused to render until their args carried a
path, so a call that streams its body first (or a same-named tool with
other arg names) showed an empty block. Meta now carries optional
fileName/filePath, path alias reading moves to shared helpers, and the
blocks fall back to the raw args JSON when no known content key is
present.
Assisted by: Delta (zai-org/GLM-5.3)
* fix(ui): keep an empty write_file body instead of the raw args
A call carrying {"content":""} fell through to the raw-args fallback, so
a finished write of an empty file showed the args JSON. The parser now
leaves content undefined when the key is missing and the block tests
!== undefined, so an empty write renders as an empty code block with its
byte count.
Assisted by: DeepSeek-V4.1-Flash (deepseek-ai)
Two quants of one repo pulled each other's draft: the badge read every
--model-draft arg of the repo, so each row showed both drafts.
Assisted-by: DeepSeek-V4.1-Flash-1017
* model : add SenseNova U1 understanding support
Add support for the dense SenseNova U1 understanding branch, including
the U1.5-8B-MoT model.
- Add HF-to-GGUF conversion for NEOChatModel, excluding MoT generation
tensors and concatenating temporal and spatial Q/K normalization
weights.
- Register the sensenova_u1 GGUF architecture and custom spatial RoPE
metadata.
- Implement temporal/spatial Q/K normalization with 4-axis RoPE.
- Keep U1-specific text position handling in the model implementation.
- Add synthetic architecture coverage for sensenova_u1.
Only the dense understanding branch is supported; generation
branches are intentionally rejected during conversion.
* conversion : treat one-expert SenseNova U1 configs as dense
* mtmd : add SenseNova U1 vision support
Add conversion support for the SenseNova U1 vision encoder and implement
its CPU mtmd projector graph.
The graph applies patch embedding, GELU, adjacent-pair 2D RoPE, spatial
downsampling, and dense projection for dynamic-resolution image inputs.
* mtmd : fix SenseNova U1 vision token layout
* model : clean up SenseNova U1 RoPE metadata
Replace the hard-coded spatial RoPE key with shared GGUF and LLM_KV
definitions used by conversion, model loading, and architecture tests.
Clarify why SenseNova U1 retains its custom text-position input: U1 uses
[t, 0, 0, 0], while the generic M-RoPE input uses [t, t, t, 0].
* mtmd : simplify SenseNova U1 projector integration
Map the SenseNova U1 dense projection to the standard mm.0 weight and
bias tensors and reuse the shared projector fields in the loader and graph.
Read vision parameters from the checkpoint configuration and remove the
U1-specific tensor names and model fields while preserving its strided
projection, bias, and row-major token layout.
* mtmd : fix SenseNova U1 image positions and attention
* fix spacing
* mtmd : restore generic test input chunks
* mtmd : restore SenseNova U1 integration after upstream merge
* Update conversion/sensenova_u1.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* Update src/models/sensenova-u1.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* model : remove SenseNova U1 BF16 activation casts
Use standard backend precision handling for QKV, FFN, and output
projections instead of casting inputs based on the output tensor type.
Assisted-by: Codex
* Update src/models/sensenova-u1.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* server : forward llama.cpp sampling params on /v1/messages
* server : pass the request through on /v1/messages instead of copying listed keys
* NIT: Change comment from multiline to single line
* server : accept llama.cpp params under extra_params on /v1/messages
* server : remove test case for trivial functionality
* server : show extra_params in the /v1/messages README example
* 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>
* server: add realtime transcription API
* drop transcription_sessions
* proxy ws
* add docs
* server: let the API key middleware guard the websocket
httplib runs the pre-routing handler before the websocket upgrade, so
the API key middleware answers 401 at handshake like any other route.
This covers the router proxy, whose children run keyless, and accepts
the same key forms as HTTP (Bearer, raw key, X-Api-Key).
* server: keep realtime slots out of the prompt loop
A realtime slot waiting for audio is GENERATING with nothing to decode,
so it fell through the prompt loop and took slot_batched. A request on
a higher slot then failed can_batch_with on the task type and starved
for the whole session. Realtime slots have no prompt: the loop sets
them up once and always leaves them.
* server: start the realtime session once its slot is live
The audio stream was created in the prompt loop, which skips a slot
that cannot batch with the one generating, and session.created went out
before the task was posted: early appends failed and the reader quit,
leaving the socket open and the slot held until the HTTP timeout.
The slot now sets up its stream at launch and signals it with the begin
result, session.created waits for it, and a reader that stops closes
the socket so the session ends with it.
* server: name the committed item in input_audio_buffer.committed
Per the Realtime spec, item_id is the item made from the committed audio
and previous_item_id the one committed before it, null for the first.
committed now comes before the transcript that completes that item, and
both go out with the item switch under one lock, so a delta cannot land
between them.
* server: use the GA transcription session shape
The session object follows the GA Realtime schema: type transcription,
with the input format, transcription model, turn detection and noise
reduction under audio.input. The rate stays the model sample rate, which
is what the client must send for now.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
* return logprobs in spec path
* server: add regression test for logprobs with speculative decoding
Asserts accepted draft tokens report the target model's logprobs,
comparing a draft-enabled run against a no-draft baseline (#24271).
Fails on master (top_logprobs empty, logprob 0.0), passes with the
fix from #27196.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01KARBWpPcijcBXzJEvttuwk
---------
Co-authored-by: Jeonghyun Lee <sig.jhl@gmail.com>
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* mtmd : lfm2 tiles stretch the image to the grid
Lfm2VlImageProcessor.crop_image_to_patches resizes the image straight to
(512 * rows, 512 * cols) before it cuts the tiles. llama.cpp kept the aspect
ratio and added black bars for LFM2 (only d1-omni stretched), so the tiles of
d1-3B and every LFM2-VL / LFM2.5-VL model differed from transformers unless
the image had the aspect ratio of the grid. With PAD_NONE the tiles are the
same as in transformers.
* mtmd : lfm2 layout with Python rounding in double precision
Lfm2VlImageProcessor.smart_resize rounds with Python's round (half to even)
and computes beta and the tile grid aspect ratio in double. llama.cpp used
std::round and float, so 31926 of the 16.7M sizes in [1,4096]^2 got another
thumbnail size or grid than transformers (and d1-omni vision.py), e.g.
400x600 -> 416x608 instead of 384x608 and 720x1600 -> 2x5 tiles instead of
2x4. The lfm2 smart resize and grid choice now follow the Python code and
match it on every size of that range.
* fix
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* 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>
* Router wasn't propagating the client disconnects fully to the child, the response wait could cause a delayed cancellation
* tests: satisfy router disconnect type check
* server : remove timing-sensitive router cancellation test
Assisted-by: Codex
