A provider is a server entry with a base url, an optional key, a protocol
and the paths its API lives at; the local llama.cpp server is the built-in
one. Backends persist in settings and the active one is restored on load.
Requests resolve against the active backend, model ids become
backend-qualified, and every backend's model list is fetched and cached in
the background. The manager's helpers learn to read a model's drafts,
context and the provider that serves it.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
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
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
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
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
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
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
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
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
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
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 : add the drawer, sheet and grouped list primitives
Add the drawer and sheet overlay components, the toggle and toggle
group, the shared searchable input, the collapsible sections and the
grouped list, and the near viewport helper they position with.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : add the shared model components and data layer
Add the model row pieces shared by the selector and the manager, the
models store with its download status feed, the huggingface and
migration services, and the model utils, enums and constants they
read through.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : rework the models selector around its providers
Group the selector components under their own folder, rework the list
around the provider grouping, add the mobile trigger and the download
item, and derive the selection state in one hook.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : add the models manager
Add the manager table with its repo, quant and status rows, the
filters and the toolbar, the row actions in a drawer, the downloads
section, the manage models dialog and the stories and tests.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : rework the chat form actions and the mobile experience
Move the add actions into a drawer and a sheet, float the model
actions in a bar on a phone, open the context panel in a drawer, and
derive the attachment, reasoning and tools menus in hooks.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : move the mcp servers to the sidebar rail and tidy the dialogs
Move the mcp servers dialog to the sidebar rail with its menu
entries, even out the dialogs on a phone, and group the mcp and
settings stores behind their own modules.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : polish the shell
The secondary button gets its own look back and the chat add button its
own light surface. Pressable elements get a pointer cursor again, the
font rendering smooths on the app shell, and the agent skills stay out
of prettier's way.
The root layout props probe rework that came with this polish reads the
providers api url and stays with the providers change instead.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : wrap the model id classes
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* ui : load the model the new chat CTA picks
Start a new chat selected the model but left it unloaded, so the chat
opened against a server with nothing in memory. Both CTAs share a load
helper now.
Assisted-by: pi:llama.cpp/DeepSeek-V4.1-Flash
* refactor: Post-review fixes
* hexagon: fix IM2COL patch-embed DMA ring overflow
The exact-tiling (stride == kernel, no pad/dilation) IM2COL DMA kernel
issues IC*KH DDR->VTCM descriptors per output row without checking the
return value of dma_queue_push(), and then pops IC*KH times. The per-thread
DMA ring holds 256 entries and a push into a full ring returns false
and drops the transfer, so for IC*KH > 255 the remaining rows of the
VTCM staging buffer were never written and stale data (often NaN/inf)
leaked into the output.
Solution is to retire the oldest descriptor when the ring is full, just as the blocked
kernel in the same file already does, and wait with dma_queue_flush().
For testing, added exact-tiling test cases with IC*KH > 256 (2D 1x1, 2D 2x2 patch
embed and 1D, F16 and F32 dst), which fail on HTP without this fix.
* Apply suggestion from @max-krasnyansky
---------
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* CUDA: radix top-k for large row counts
Replaces CUB's per-row DeviceTopKKernel with a grid-over-rows radix select,
gated on GGML_CUDA_TOPK_RADIX_MIN_ROWS. On qwen4exp at 34,816 tokens this cuts
top-k from 1,671,253 launches / 5,761.8 ms to 2,329 / 941.8 ms.
* CUDA: select the TOP_K implementation by shape
Replace the nrows/ncols special case with the decision boundary from #28547
(as implemented in #29278): bitonic for short rows, radix select for several
long rows, and DeviceTopK or CUB argsort for a single long row. The
thresholds stay overridable at build time.
Two refinements on top of that boundary:
- bitonic stays in use for rows up to a padded 1024 while the rows fit in one
wave of blocks (nrows <= number of SMs); radix select pays a fixed cost of
about a dozen launches that only amortizes over more rows
- with DeviceTopK available, it handles up to two rows
Radix select now processes rows in chunks so its scratch memory stays bounded,
and the bitonic path keeps its chunking. HIP and MUSA keep their previous
thresholds.
Add perf cases around the bitonic/radix crossover to test-backend-ops.
* CUDA: make top-k comments less verbose
* CUDA: remove the TOP_K width limit from supports_op
* CUDA: use DeviceTopK for single-row TOP_K if available
* CUDA: avoid ncols overflow in the TOP_K bitonic check
* CUDA: share the row chunking helper between argsort and top-k
* CUDA: do the TOP_K radix blocks_per_row math in int64_t
* CUDA: rename GGML_CUDA_TOP_K_NROWS_THRESHOLD_DEVICETOPK to GGML_CUDA_TOP_K_NROWS_THRESHOLD
* CUDA: share one sort helper between the bitonic and CUB TOP_K paths
* CUDA: update the TOP_K TODO, threshold and chunking comments
* tests: add TOP_K cases that span several row chunks
* CUDA: use int64_t col in the TOP_K radix loops, fix threshold comment
* CUDA: limit TOP_K and ARGSORT support to ne[0] <= INT_MAX
---------
Co-authored-by: praneshgo <227579474+praneshgo@users.noreply.github.com>
Co-authored-by: Pranesh Gonegandla <pgonegandla@nvidia.com>
* CUDA: fix CCCL version guard breaking on major version rollover
The guard compared the major and minor components independently:
CCCL_MAJOR_VERSION >= 3 && CCCL_MINOR_VERSION >= 1
Minor resets to 0 whenever a new major series is cut, so on CCCL 4.x
this evaluates as 4 >= 3 && 0 >= 1, i.e. false. STRIDED_ITERATOR_AVAILABLE
stops being defined and argsort silently falls back to the
init_offsets path. Nothing warns and the build still succeeds, so the
regression is a quiet performance loss rather than a compile error.
CCCL already exposes the version as a single packed integer in
MMMmmmpp form, which is what its own version header uses:
CCCL_VERSION = MAJOR * 1000000 + MINOR * 1000 + PATCH
so 3.4.3 is 3004003 and ">= 3.1" is a plain ">= 3001000". One
comparison, with no component arithmetic left to get wrong.
Checked against a hand-written "version >= 3.1" reference over 2.9.9,
3.0.0, 3.1.0, 3.1.99, 3.2.0, 3.4.3, 3.9.9, 3.99.99, 4.0.0, 4.2.7 and
5.0.0: no divergences. The old guard disagreed at 4.0.0 and 5.0.0.
Verified on RTX 4070 (sm_89), CUDA 13.4, CCCL 3.4.3:
- cmake --build build --config Release: exit 0
- test-backend-ops test -o ARGSORT -b CUDA0: 98/98 passed, CUDA0 OK
Note that a passing regression test does not on its own prove the guard
is still taken, since the fallback path passes too. Preprocessing the
real translation unit confirms the strided-iterator branch is the one
compiled in: counting_iterator is present, init_offsets is not.
Signed-off-by: Heitor <heitorgm@outlook.com>
* Update ggml/src/ggml-cuda/argsort.cu
* Apply suggestion from @ORippler
---------
Signed-off-by: Heitor <heitorgm@outlook.com>
Co-authored-by: Oliver Simons <osimons@nvidia.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>
The bucket search in topk_nary_search.comp started from the range
[0, 0xFF800000), which ends just below the ordered-uint mapping of +inf,
so +inf and NaN were never counted. A workgroup block with fewer than k
countable values left the ballot empty and the shader read uninitialized
shared state (hang/device lost on NVIDIA, wrong indices on AMD), and a few
+inf in a block were selected without being counted, dropping real top
values.
Map NaN to -inf on input, start from [0, 0xFFFFFFFF) so every value is
counted, and clamp the top bucket's end (2^32) instead of wrapping to 0.
The k = 1 path compared float bits as signed integers, which orders
negative values backwards; compare floats instead.
Add test_top_k_inf to test-backend-ops: negative values, fewer than k
+inf and many -inf, for k = 1, 10, 40.
Assisted-by: Claude Opus 5.5
* cuda : support arbitrary striding for unary ops on f16, f32, and bf16
* Remove added newline
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* sycl: fuse the delta-net alpha gate (add + unary + mul)
* tests: cover the fused add + unary + mul chain
* sycl: give the fused alpha gate a flat path and pin the node skip
* model : support classifier_activation for rerankers
Assisted-by: Claude Opus 5.5
* model : map classifier gelu to gelu_erf and accept tanh
Assisted-by: Claude Opus 5.5
* model : default act_cls to tanh, ModernBERT falls back to gelu_erf
Assisted-by: Claude Opus 5.5
* ggml-cuda: assign two GDN state columns per warp
* ggml-cuda: use 4 GDN state columns per warp at S_v=128
* ggml-cuda: default cols_per_warp=4
* ggml-cuda: address GDN review nits
* hex-bufs: add support for alloc_buffer_n
* hex-bufs: add support for splitting large tensors into separate buffers
* hex-bufs: update GGML_HEXAGON_MBUF to accept three values dyn,static,total
* hex-bufs: bump dyn. default to 512MB since 128MB causes perf regressions with big MOEs
* hex-run: add --no-embd-offload option to simplify command lines on devices that need it
* Update scripts/snapdragon/run.py
Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>
---------
Co-authored-by: Jhen-Jie Hong <iainst0409@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>
* model : add LiquidAI/d1-3b decision model
mtmd : read LFM2 image resize algo from GGUF
Assisted-by: Claude Opus 5.5
* common : rename decision type d1 to lfm2-d1
Assisted-by: Claude Opus 5.5
Aleksander Grygier
Xuan-Son Nguyen
Pascal
ynankani
Mark TodorovichandMax Krasnyansky
Nicolas Mowen
bri-prism
Hrishith Thadicherla
Johannes Gäßler
Prabhsimran Singh
hey-gmandOliver Simons
Simon Sudarushkin
Aman Gupta
Leebr Data ConsultingandIgor Okulist
gianni-cor
Jeff Bolz
Adrien Gallouët
Muhammad SaadandJohannes Gäßler
Bertay Eren
Eden
Titaniumtown
cwriterandcwriter
bosh
SXX
Sam Malayek
kurquhar
Tarek Dakhran
Nicolas Budyn
Frost-54andAlde Rojas