* vulkan: add iq4_nl support back to FA
I was originally concerned about wasting shared memory on the LUT, but it's small
and unlikely to matter in practice.
Also support q1_0 for non-coopmat2.
Fixes#23681
* remove q1_0 FA support
* ggml-cuda: add chunked SSD matmul for Mamba-2 prefill acceleration
* cuda: added SSD CICD fixes for CUDA / HIP / MUSA / MSVC.
* ggml-cuda: review comments fixed.
* ggml-cuda: Fuse M matrix materialization into pre_matmul kernel and enabled test.
* ggml-cuda: test updates and fixes
* ggml-cuda: test updates to remove hardcoding of tensor initialise data limits.
* ggml-cuda: ssd minor review comment fixed.
* ggml-cuda: ssd minor CICD fixed.
* CUDA SSD: Fixes correctness by promoting s0_stride_seq to int64_t, improves memory coalescing in ssm_ssd_prepare_dt_kernel, and boosts efficiency by merging B_weighted and C_scaled; also addresses prior review comments.
* cuda: fix sdata read-write race in prepare_dt fallback scan loop
* spec: add DSpark speculative decoding
DSpark (DeepSpec, 2026) on top of the merged DFlash drafter. It reuses the
DFlash encoder/decoder graph, target feature extraction and KV-cache injection,
and the verify/accept path unchanged; the draft model is a new "dspark" arch
adding a low-rank Markov head (markov_w1/w2) and an optional (unused here)
confidence head. No new public APIs.
The proposal is the only change: the block is anchor-first (position 0 already
predicts the first draft) and the decoder graph applies a semi-autoregressive,
previous-token conditioned logit bias in-graph, chained per block position:
logits'(i) = logits(i) + markov_w2 . markov_w1[prev(i)]
prev(0) = the block's anchor token, prev(i>0) = argmax(logits'(i-1))
vectorized across all blocks in the batch; the anchors are fed through a
dedicated graph input (token 0 of every block). Greedy stays lossless
(verify unchanged, same as DFlash).
- new arch "dspark" (llama_model_dspark : llama_model_dflash, reuses the graph,
loads the markov/confidence tensors; shares the target's embed/lm_head).
- Qwen3DSparkModel converter.
- new spec type "draft-dspark" (common_speculative_impl_draft_dspark :
common_speculative_impl_draft_dflash, overrides draft() only: submits whole
anchor-first blocks and greedily reads back the biased logits).
* spec: read draft block size in the dflash impl
* docs: add DSpark section to speculative.md
* spec: keep dspark block size read in the dspark impl
* dspark : add TODOs for incomplete parts
- confidence head is loaded but not used yet
- confidence-scheduled prefix pruning is not implemented
- the in-graph Markov chain is greedy-only
- only Qwen3 backbones are supported for now (also noted in docs)
* spec: fold DSpark into the DFlash arch
Address review: drop LLM_ARCH_DSPARK and the dspark.block_size /
markov_rank GGUF keys. A DSpark draft now converts to a DFlash GGUF;
the Markov head tensors are detected by presence (like eagle3 d2t),
block_size is read from the existing dflash.block_size key, and the
block anchors are taken as a strided view of the decoder's token
input instead of a separate graph input.
* spec: add confidence-based draft pruning for DSpark
The DSpark confidence head predicts per-position acceptance of the
drafted block. --spec-draft-conf-min truncates the block at the first
position below the threshold (default 0 = disabled).
* fold the dspark impl into dflash, selected by spec type
* address review comments
* dspark: clean up and improve naming
* update readme
* remove trailing whitespace
* dflash: draft full n_max blocks, defer dp.n_max to the central truncation
The DSpark markov head views the draft batch as a uniform [n_seqs x block]
grid, but the per-seq dp.n_max clamp could produce blocks of different
sizes, silently corrupting the strided views and the resulting logits.
Drop the clamp and always draft the full n_max block for every sequence:
dp.n_max is already enforced by the central truncation in
common_speculative_draft(), the same way eagle3 handles it.
Co-authored-by: Zaire404 <3147879462@qq.com>
* dflash: assert the markov head block-uniformity invariant, require the conf head
With the draft batch always submitting equal-size n_max blocks, a
non-divisible token count can only mean the batch was split across
ubatches or a caller broke the layout - fail loudly instead of silently
dropping the markov bias. The block_drafts > block_size early return
stays: worst-case graph reserve passes legitimately build with
n_seq_tokens > block_size.
Also make conf_proj required when the markov head is present: the
confidence head is part of the DSpark checkpoint format, and a missing
head would otherwise leave --spec-draft-conf-min silently reading stale
embeddings instead of confidences.
Co-authored-by: Zaire404 <3147879462@qq.com>
* dspark: fold conf_min into p_min
p_min and conf_min express the same thing - the minimum predicted
survival probability for a drafted position - differing only in how the
estimate is obtained: token probability for regular drafters, the
trained confidence head for DSpark. The DSpark readback never used
p_min, so reuse it for the confidence threshold and drop the separate
--spec-draft-conf-min flag. Both defaulted to 0 (disabled), so behavior
is unchanged.
Co-authored-by: Zaire404 <3147879462@qq.com>
* dflash: note the confidence broadcast workaround
Requested in review: the ggml_repeat only adapts the [1, n_tok]
confidences to the n_embd-wide embd_nextn transport so that
llama_get_embeddings_nextn can be reused - not a placeholder.
Co-authored-by: Zaire404 <3147879462@qq.com>
* cont : clarify
[no ci]
---------
Co-authored-by: Ruixiang Wang <wangruixiang07@outlook.com>
Co-authored-by: Zaire404 <3147879462@qq.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* sycl: fix use-after-return of the SDPA scale in the oneDNN flash-attention path
The scale was uploaded with an async memcpy sourced from a stack local. On the
in-order queue that copy is ordered behind the K/V staging kernels; once n_kv is
large enough (>= ~26k observed on Arc Pro B70) the staging outlives the host
stack frame and the copy reads recycled memory, feeding the SDPA a garbage scale.
Output then collapses to a single repeated token and the KV cache is poisoned
for the rest of the session.
Short contexts win the race by accident, and test-backend-ops caps
FLASH_ATTN_EXT at kv=1024, which is why CI never caught it. The previous
device_count > 1 wait_and_throw() gate (and reverting it, PR #25741) fixes the
symptom only by keeping the frame alive across the copy at the cost of a host
sync on every FA call.
Fix: cache one device scalar per (device, value) -- the scale is constant per
model -- and upload it synchronously once. The single-device fast path (no
per-call host sync) is then safe: every device-side hazard already serializes
on the in-order queue. The multi-GPU conservative wait is kept unchanged.
Also:
- GGML_SYCL_FA_ONEDNN_MAX_KV env (0 = unlimited): optional n_kv ceiling that
routes very long sequences to the native FA kernel.
- test-backend-ops: FLASH_ATTN_EXT F16 cases up to kv=65536 (Qwen3.6-27B
geometry hsk=hsv=256 GQA 6, and hsk=128 GQA 4), closing the kv=1024 blind
spot. Note the race itself needs a live multi-op pipeline to reproduce;
single-op runs pass even on broken builds.
Verified on Arc Pro B70 (bmg_g31), Qwen3.6-27B Q4_K, -c 131072: output
byte-identical at temp 0 to the native FA path through 32k-deep prefill, with
prefill depth-flat at 820-840 t/s (vs 340-350 native at 32k depth).
Assisted-by: Claude Fable 5
* sycl: handle GGML_SYCL_FA_ONEDNN_MAX_KV like the other runtime env vars and document it
Review feedback on #25880:
- read the variable once at backend init into g_ggml_sycl_fa_onednn_max_kv via
ggml_sycl_get_env, and print it in the startup env listing (-lv 4 shows it)
- document GGML_SYCL_FA_ONEDNN and GGML_SYCL_FA_ONEDNN_MAX_KV in the SYCL.md
runtime table
Also trim the added FLASH_ATTN_EXT cases to kv={4096,16384}: the 32768/65536
shapes exceed the legacy NMSE threshold on both the oneDNN and native kernels
(long-sequence fp16 accumulation drift, present before this PR) and would fail
CI for an unrelated reason.
Assisted-by: Claude Fable 5
* sycl: clarify GGML_SYCL_FA_ONEDNN_MAX_KV default is disabled
Assisted-by: Claude Fable 5
* sycl: state default behavior of GGML_SYCL_FA_ONEDNN_MAX_KV explicitly
Assisted-by: Claude Fable 5
* Update ggml/src/ggml-sycl/fattn-onednn.cpp
Co-authored-by: Neo Zhang <zhang.jianyu@outlook.com>
* sycl: write the SDPA scale from a kernel instead of caching it
The per-(device, value) scale cache was a function-local static
unordered_map with no synchronization, so concurrent backend instances
could access and rehash it at the same time.
Write the scalar with a single_task instead. The value is captured into
the command, so no host memory has to outlive the call -- which is what
the use-after-return fix needed in the first place. That removes the
shared container, the leaked device allocation and the string key, and
it also closes the remaining async-memcpy-from-a-stack-local on the
first flash-attention call.
Ordering does not rely on timing: the queue is created with
sycl::property::queue::in_order and the dnnl stream wraps that same
queue, so the write completes before the SDPA reads the scalar. The
multi-GPU wait_and_throw() branch is unchanged.
Also drop the <cstdlib> include, which is unused.
Assisted-by: Claude Opus 5
---------
Co-authored-by: Neo Zhang <zhang.jianyu@outlook.com>
* common: fix explicit -md precedence over draft sidecar resolution
Follow-up of #25955, an explicit --model-draft file given with -hfd
was silently overridden by the sidecar resolution of the draft repo,
and its path was never resolved to a local file.
An explicit draft file selection now disables the sidecar resolution,
so the manual CLI configuration wins over the automatic one.
* common: apply the -hfd tag to the sidecar resolution
The sidecar selection was anchored on the primary of the draft plan,
so a tag without a matching full model aborted the whole plan, and
the sidecar quant silently followed the default model pick.
The tag now anchors the sidecar directly: exact tag match first, then
closest quant to the tag, and a requested sidecar resolves even when
no full model matches the tag. A wired draft sidecar also counts as
an explicit draft, so the main plan no longer downloads a second one.
* common: promote speculative load logs from trace to info
Show the loaded draft model and the MTP draft context at the default
verbosity, for consistency with the mmproj and primary logs.
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server + ui: refactor resumable stream routes to query string conv_id
The conversation id can embed a model name containing slashes
(ggml-org/...) in router mode, which the decoded path splits before the
:conv_id param is captured, so stop and resume never matched the
session. Move the id to the conv_id query string on the public routes
and on the internal router -> child hop, where slashes survive
encoding. Handlers are unchanged since query and path params land in
the same map. Add a regression test with a slashed model name.
* server: move stream route docs to server-stream.h
Address review: ngxson wants the main server.cpp registration code kept
clean and simple, with route-level explanations living in the header.
Move the query string rationale and the lookup ownership note next to
the handler declarations in server-stream.h, and shorten the wiring
comment to a pointer.
* server: cancel a pending request when its stream is stopped during model load
The conversation was registered in the conv map only after the blocking
autoload wait, so a stop issued while the model loaded found nothing to
cancel and the request went on to generate an orphan once the load
ended. Register the conversation before the wait and give the entry a
ticket: a stop erases the entry, and the parked request checks its
ticket after the wait and aborts with 400 instead of starting. A newer
request on the same conversation replaces the entry, so only the
stopped request is cancelled. Add a regression test that stops during
the load window.
* server + ui: resume a stream after a page reload during model load
A pending request died with the client socket when the page was
reloaded while its model was loading, so no session ever existed and
the conversation had nothing to recover. A session request that waited
for a load now detaches from the client socket and reaches the child
regardless, the session buffer receives the generation, and the resume
route answers 503 while the owner is loading so the client retries
instead of dropping its state. The WebUI persists the pending stream at
send time, quietly polls on 503, and attaches once the session exists.
Add a regression test that drops the client during the load window.
* ui: show the model load progress again after a page refresh
The resume wait was invisible, so a conversation refreshed while its
model was loading showed nothing until the first byte. On a 503 from
the resume probe, mark the conversation as loading again so the
assistant row persisted at send time renders the processing info, and
target the model frozen in the persisted stream state for the
progress, since the row has no model yet and the dropdown may not be
restored.
* fix CI
* fix CI bis
* Add preliminary MiniMax-M3 support
Text-only port that re-uses existing components: MiniMax-M2 style GQA with
per-head QK-norm and partial rotary, DeepSeek-V3 style leading-dense and
routed/shared experts, and swigluoai activation. Sparse attention is not
yet supported (dense fallback); vision tower and MTP heads are dropped.
* MiniMax-M3 vision tower (mmproj + clip graph)
* Delete m3_vision_ref.py
* Update clip.cpp
* MSA
* Update constants.py
* Update minimax.py
* Cache creation. Working withotu flash attention
* Added flash attention for sparse layers
* Decomposed slow cpu OP into GPU + CPU ops. Massive speedup over long ctx
* Rewrote indexer op to be cuda native. Modified flash attention to match per group block picking
* Implement sparse attention calc out of stock ops.
* Fix a cache allocation and cont issue
* Fixed -fa auto crash, flagged debug spots
* Delete vocab.json
* Delete model.safetensors.index.json
* Delete generation_config.json
* Delete Minimax directory
* Handled multi stream case to fall back on Dense Attention
* Development scaffolding cleanup. No functional change to the decode or
4-way paths. Full debug harness remains at <8136a9c68ed7a5eb009aa67bba3fda8062f4648f> for reproducing the
selection-parity validation.
* Remove redundant comment from minimax-m3.cpp
* Changed 3 Gelu Ops for vision into Gelu_erf ops
* Assert that n_kv is multiple of 128
* Rename MSA index tensors to indexer convention
Note: All GGUFs generated before this change will need to be regenerated.
* Fix incorrect Assert
* Review driven changes (#3)
* Remove comment from conversion minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove whitespaces from constants.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Tighten comment in minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* inherit MiniMax-M3 from MiniMax-M2
* drop dead text_config fallbacks
* Add indexer writer methods
* Reuse LLM_FFN_SWIGLU_OAI_MOE
* Remove duplicate indexer setters, add only block_size/local_blocks, follow value naming convention
* Fix conversion error /gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update conversion/minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update conversion/minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove whitespace in src/llama-kv-cache.cpp
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove Whitespace in Update src/llama-model.h
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove whitespace in src/llama-hparams.h
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update minimax_m3.cpp
Rewrite code comment based on feedback and to better reflect the actual architecture, and reuse existing build_vit
* Rename minimax_m3.cpp to minimax-m3.cpp
* Update CMakeLists.txt
* Remove debug code from clip.cpp
* Update clip.cpp
* Update comments in tools/mtmd/models/minimax-m3.cpp
* Permute Q/K at conversion, drop precomputed sin/cos
* Log cache size on launch, block ctx shift, support prompt caching
Log indexer cache size on launch
Disallow ctx shift
Support prompt caching
* Update minimax-m3.cpp
* Optimize implementation, add multi stream support.
Fully rewrote minimax-m3.cpp for speed and buffer size gains:
Unified the 4-way + decode, 1 FA call per layer instead of 4, with the groups mapped onto ne[3]
Custom CPU op now emits block-level mask, expanded on GPU, which causes CPU to GPU transfer to shrinks at prefill
Decode: ~25 nodes/layer vs ~50, no per-group concats/conts
Unified selection semantics, so both regimes rank bs + local bias (position-anchored local force), which means prefill/decode can no longer disagree on selection
can_reuse on the MSA bias input. Graph reuse at decode restored (was rebuilding the full graph every token)
In-place mask adds, shrinking compute buffer ~6.8 to ~4.2 GiB at ub2048/62k
Multi-stream: MSA now runs with -np N when kv_unified=false. Decode stays batched across streams (still 1 FA call), prefill loops per stream. dense fallback only for --kv-unified + multi-seq
Measured effect on expert offload bound setup: decode 6.2(4WAY)–7.15(MSA_decode) -> 7.7~7.8 t/s, flat from 5k to 60k+. prefill around 10% faster. buffer about 20% smaller, multi-user support.
* set default cache type to F32
* Fix potential DSA double indexer cache allocation bug, only allocate in-cache k_idx for archs that opt in
* remove F16 downcasts in MSA attention, force F32 indexer score accum
* Add Minimax eos to llama vocab
* Guard edge case where idx cache can become stale after a tail trim
* Update llama-kv-cache.h
* Update llama-kv-cache.cpp
* Update llama-kv-cache.cpp
* Update llama-kv-cache.h
* Change resize Pad to none, resize alg to Bicubic Pillow
* Review driven changes
* Update llama-kv-cache.cpp
* rm unrotated pos_t
* fused rope w + pad
* rename merge --> merger for consistency
* add review skill for mtmd
* graph should use hparams n_merge
* fix lint
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
The in-conversation system-message edit textarea had a fixed min-height and no auto-resize, so long messages were crammed to 2 lines. Reused existing autoResizeTextarea helper on input and when the editor opens, and added max-height to cap growth.
* ui: detect the conversation import format from file contents
iOS resolves every accept entry to a UTI and has none for ".jsonl", so the
picker greyed out exported conversations. Drop the accept filter and pick the
parser from the file contents: ZIP magic bytes, then a first "session" record
for JSONL, otherwise the legacy JSON format.
Also remove the unused importConversations() picker and an orphan doc comment,
and cover each format with unit tests.
* ui: report what a conversation import actually wrote
The import summary echoed the selection back, so re-importing conversations
already in the database claimed success while nothing was written and only a
console warning said otherwise.
Return the imported and skipped conversations from the database layer, list the
written ones in the summary, and count the rest in a toast.
* ui: name the literals of the JSONL conversation format
Introduce SessionRecordType and SESSION_HARNESS, and reuse the existing
NEWLINE constant, so the record format lives in one place.
This also covers the writer side, which predates the import path under
review and carried the same literals: an enum stated by the reader alone
lets the two sides drift.
Values are unchanged, so an export stays byte identical.
* add common/subproc.h|cpp
* add compile flag LLAMA_SUBPROCESS
* disabled by default on android and ios
* test-jinja: use common subproc
* mtmd: disable video if subproc is not set
* disable subproc on wasm
* make is_created atomic
* migrate server-mcp
* Add preliminary MiniMax-M3 support
Text-only port that re-uses existing components: MiniMax-M2 style GQA with
per-head QK-norm and partial rotary, DeepSeek-V3 style leading-dense and
routed/shared experts, and swigluoai activation. Sparse attention is not
yet supported (dense fallback); vision tower and MTP heads are dropped.
* MiniMax-M3 vision tower (mmproj + clip graph)
* Delete m3_vision_ref.py
* Update clip.cpp
* MSA
* Update constants.py
* Update minimax.py
* Cache creation. Working withotu flash attention
* Added flash attention for sparse layers
* Decomposed slow cpu OP into GPU + CPU ops. Massive speedup over long ctx
* Rewrote indexer op to be cuda native. Modified flash attention to match per group block picking
* Implement sparse attention calc out of stock ops.
* Fix a cache allocation and cont issue
* Fixed -fa auto crash, flagged debug spots
* Delete vocab.json
* Delete model.safetensors.index.json
* Delete generation_config.json
* Delete Minimax directory
* Handled multi stream case to fall back on Dense Attention
* Development scaffolding cleanup. No functional change to the decode or
4-way paths. Full debug harness remains at <8136a9c68ed7a5eb009aa67bba3fda8062f4648f> for reproducing the
selection-parity validation.
* Remove redundant comment from minimax-m3.cpp
* Changed 3 Gelu Ops for vision into Gelu_erf ops
* Assert that n_kv is multiple of 128
* Rename MSA index tensors to indexer convention
Note: All GGUFs generated before this change will need to be regenerated.
* Fix incorrect Assert
* Review driven changes (#3)
* Remove comment from conversion minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove whitespaces from constants.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Tighten comment in minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* inherit MiniMax-M3 from MiniMax-M2
* drop dead text_config fallbacks
* Add indexer writer methods
* Reuse LLM_FFN_SWIGLU_OAI_MOE
* Remove duplicate indexer setters, add only block_size/local_blocks, follow value naming convention
* Fix conversion error /gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update conversion/minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Update conversion/minimax.py
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove whitespace in src/llama-kv-cache.cpp
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove Whitespace in Update src/llama-model.h
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* Remove whitespace in src/llama-hparams.h
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
* remove multimodal code upon maintainer request. Will be made as a separate PR
* Whitespace clean in tensor_mapping.py
* Log cache size on launch, block ctx shift, support prompt caching
Log indexer cache size on launch
Disallow ctx shift
Support prompt caching
* Update minimax-m3.cpp
* Optimize implementation, add multi stream support.
Fully rewrote minimax-m3.cpp for speed and buffer size gains:
Unified the 4-way + decode, 1 FA call per layer instead of 4, with the groups mapped onto ne[3]
Custom CPU op now emits block-level mask, expanded on GPU, which causes CPU to GPU transfer to shrinks at prefill
Decode: ~25 nodes/layer vs ~50, no per-group concats/conts
Unified selection semantics, so both regimes rank bs + local bias (position-anchored local force), which means prefill/decode can no longer disagree on selection
can_reuse on the MSA bias input. Graph reuse at decode restored (was rebuilding the full graph every token)
In-place mask adds, shrinking compute buffer ~6.8 to ~4.2 GiB at ub2048/62k
Multi-stream: MSA now runs with -np N when kv_unified=false. Decode stays batched across streams (still 1 FA call), prefill loops per stream. dense fallback only for --kv-unified + multi-seq
Measured effect on expert offload bound setup: decode 6.2(4WAY)–7.15(MSA_decode) -> 7.7~7.8 t/s, flat from 5k to 60k+. prefill around 10% faster. buffer about 20% smaller, multi-user support.
* set default cache type to F32
* Fix potential DSA double indexer cache allocation bug, only allocate in-cache k_idx for archs that opt in
* remove F16 downcasts in MSA attention, force F32 indexer score accum
* Add Minimax eos to llama vocab
* Guard edge case where idx cache can become stale after a tail trim
* Update llama-kv-cache.h
* Update llama-kv-cache.cpp
* Update llama-kv-cache.cpp
* Update llama-kv-cache.h
* Update llama-kv-cache.cpp
* Review driven changes
* style fix
* indexer hparams are required
* fix tests
* fix lint
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: Sigbjørn Skjæret <1629204+CISC@users.noreply.github.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
The context gauge card starts monitoring like the dial does, because
its own processing state instance only follows the live stream while
its monitoring flag is set. It also gets back the text-sm and ring
classes the removed hover card wrapper used to inject, which restores
its layout. Routing to a conversation now lands at the bottom
instantly and keeps the pin one frame at a time until the page height
settles, since content-visibility size realizations and syntax
highlight passes grow the page without DOM mutations.
* Fix emscripten compilation with openmp
* Separate wasm job to its own workflow
* Add flags necessary for newer emsdk
* Just disable openmp
* Update triggers
* move server_pipe to common
* init impl
* vendor: update subprocess.h
* add server_mcp_stdio
* stderr drain
* server_mcp_transport
* server_mcp_stdio is now framing-only, no json
* internal/mcp-stdio: integration + tests + fixes (#26075)
* server-mcp: harden transport and wire up the tool integration
Builds on the transport/manager architecture (server_mcp_transport + server_pipe)
with the hardening and integration the draft did not yet have.
Hardening:
* Reader and stderr pumps are polled (running-aware) instead of blocking on a read
that only ends at EOF. subprocess_terminate() SIGKILLs only the direct child, so a
grandchild the MCP server spawned that inherited the pipe would otherwise keep the
write end open and hang teardown (both warmup shutdown at startup and process
shutdown). The writer is likewise non-blocking + polled.
* Windows: resolve the command through PATHEXT so "npx" (npm ships npx.cmd, never
npx.exe) spawns, matching POSIX's PATH search; and enumerate the parent environment
as UTF-8 (GetEnvironmentStringsW) instead of the active code page.
* server_pipe gains an opt-in max_size (default unbounded, so the router's streaming
use is unchanged); the MCP reply queue uses it so a server that streams unsolicited
notifications between requests cannot grow it without bound.
Integration:
* --mcp-servers-config / --mcp-servers-json flags; enabling MCP restricts default CORS
to localhost, same as --tools.
* MCP tools are exposed through /tools (and chat-completions) as <server>_<tool>,
skipping names that collide with a built-in or another MCP tool.
* Manager lifecycle wired into llama_server(): warmup at start, shutdown() from the
signal handler before the HTTP server drains, blocking teardown in clean_up().
* SIGPIPE ignored so a child dying mid-write yields EPIPE rather than killing us.
Assisted-By: Claude Opus 4.8 <noreply@anthropic.com>
* server-mcp: add MCP test suite with grandchild deadlock regression test
21 tests over the /tools endpoint: tool discovery/invocation, timeouts, crash
recovery and respawn cooldown, warmup partial failure, malformed and batched
notification+response output, tool-definition shape, and prompt shutdown during a
slow call.
The last test spawns an MCP server that leaves a grandchild inheriting its
stdout/stderr and asserts the server both starts and stops promptly. Verified it
fails (5s SIGKILL fallback on a deadlocked reader-join) when the pump is made to
ignore the running flag, and passes with the polled reader.
Assisted-By: Claude Opus 4.8 <noreply@anthropic.com>
* clean up
* clean up 2
* even stricter life cycle
* nits
* nits 2
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* fix some edge cases
* fix last_error data race
* fix response schema + docs
* server: fix MCP zombie leak and timeout-induced transport teardown
join_pumps() never reaped the child, leaking one zombie per spawn:
call subprocess_join() before subprocess_destroy().
A per-call timeout permanently closed from_server and got a healthy
transport evicted: add close_on_stop to server_pipe::read() and pass
false from send_rpc(), where should_stop is a per-request deadline
and a late reply is already skipped on id mismatch.
Also drop the unreachable disconnect cancellation in
server_mcp_tool::invoke(): support_stream is false, st is always null.
(cherry picked from commit e6de1ec043174fd0570b1e60d47f06c7c19d620d)
Assisted-by: Claude Opus 4.8
* server: make MCP test fixtures JSON-RPC 2.0 compliant
Add the missing notification guard to mcp_malformed_server.py and
mcp_burst_server.py (the latter treated id 0 as a notification and
replied to unknown ones; its notification table is now unused).
Return -32602 instead of -32601 for unknown tools: tools/call is a
valid method, the tool name is the invalid parameter.
Also fix the test module docstring: tools are named <server>_<tool>.
(cherry picked from commit 74a08e8c311dabf3b49d06cc6d754b0097ae7a38)
Assisted-by: Claude Opus 4.8
---------
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
Co-authored-by: Pascal <admin@serveurperso.com>
The INI parser creates an implicit default section for top-level metadata.
After reserved keys such as `version` are skipped, that section can have no
model options but was still added and exposed in router mode.
Skip only the empty implicit default while preserving real default presets,
named presets, and the global `[*]` settings.
Signed-off-by: JS van Dijk <267467744+hogeheer499-commits@users.noreply.github.com>
Co-authored-by: JS van Dijk <267467744+hogeheer499-commits@users.noreply.github.com>
These two parameters were overlooked when task parameters were being JSONized
within `generation_settings` and have been added. A regression test has been
added to prevent the problem from recurring and it passes.
Fixes#25803
* common : extract trie/ac to a separate file
* common : support multiple token sequences in the reasoning budget sampler
* common/trie : return matched word index
* common/trie : rename "word" to "pattern"
* common/reasoning-budget : expose matched end sequence
* common/sampling : replay end sequence when reasoning budget is done
* cont : update to use multiple end sequences
* cont : clean up
* performance harness - the empirical root
Assisted-by: Claude Opus 4.8
* 210.36ms -> 2.67ms per streamed token
Assisted-by: Claude Opus 4.8
* 11.58ms -> 0.62ms per streamed token
Assisted-by: Claude Opus 4.8
* 22.02ms -> 3.33ms per streamed token
Assisted-by: Claude Opus 4.8
* 3.07ms -> 1.36ms per streamed token at 40 messages
Assisted-by: Claude Opus 4.8
---------
Co-authored-by: Zach Winter <dmtommy@icloud.com>
* ui: remove viewport fade in and smooth autoscroll bottom snap
fadeInView mounted every message and markdown block at opacity 0 and
relied on an IntersectionObserver to reveal it. When the observer never
fires (blocks mounted offscreen during long agentic loops) the content
stays invisible forever while still present in the DOM. Remove the
action, its orphaned isElementInViewport util and all call sites:
blocks now render visible immediately.
AutoScrollController.scrollToBottom defaulted to behavior smooth and is
invoked every 100 ms while streaming. Each tick restarts an easing
animation toward a moving scrollHeight, producing a random elastic bump
of a few pixels when the user reaches the bottom and autoscroll
reengages. Default to instant scrolling; the user facing scroll down
button keeps its smooth behavior.
* ui: skip rendering of offscreen chat messages via content-visibility
Apply content-visibility auto with contain-intrinsic-size to chat
messages so the browser skips layout and paint for messages outside
the viewport. The DOM stays complete: component state, find-in-page,
text selection, and the mutation based autoscroll are unaffected, and
browsers without support simply ignore the properties.
* ui: remove conversation switch fade
Switching conversations faded the message list out and in over 500 ms
plus a 300 ms route delay, deferring the message refresh behind two
requestAnimationFrame calls. Remove the fade, its navigation hooks and
dead state, and refresh messages directly so switching is only bound
by actual render time.
* ui: describe present behavior in comments and drop unused parameter
* ui: anchor the context gauge popup to the form with plain CSS
The stats card was portaled to body and repositioned in script on
every ancestor scroll event, trailing the page by one frame while
streaming. Render it as an absolutely positioned sibling of the input
box inside the already relative form, so nothing runs during scroll.
The card sits just above the dial, centered on it and overlapping the
textarea, from a single measurement of the dial center and top taken
when it opens; the dial and the card share the same positioning frame,
so the values stay exact while the card is open. Mouse pointers open
on hover with a grace delay to reach the card, touch pointers toggle
on tap, any press outside the card and the dial closes it, and Enter
and Space toggle from the keyboard. The card lives outside the input
box because its overflow-hidden and backdrop-filter would clip any
positioned descendant.
* ui: extract context gauge popup constants and relocate its state store
Move the placement values and the close grace delay to
lib/constants/context-gauge-popup.ts, matching the auto-scroll
constants layout, and move the popup state module from the component
folder to lib/stores where runes modules live in this codebase.
* ui: declare the context gauge popup card ref as $state
* Start building graph - reuse deepseek32
* Enable kv cache and rotation for glm_dsa architecture
Just follow Deepseek 3.2 for now.
* Reuse prev_top_k for "shared" indexer layers
* GLM 5.2 uses LLAMA_ROPE_TYPE_NORM for the indexer.
This is transformers' `apply_rotary_pos_emb_interleave`
* Default indexer types to GLM pattern
Previous converted GGUFs like https://huggingface.co/unsloth/GLM-5.2-GGUF write indexer weights to _all_ layers, even if they are only required for "full" types. This PR relies on a new key "%s.attention.indexer.types"; if absent, it will use the default GLM 5.2 schedule as defined in https://huggingface.co/zai-org/GLM-5.2/blob/main/config.json#L26.
Note that conversion is not saving this key yet.
* Save indexer types to gguf, restore on load
* Use ggml_lightning_indexer when cparams.fused_lid
Co-authored-by: fairydreaming <166155368+fairydreaming@users.noreply.github.com>
* GLM 5 and 5.1 use full indexers
Co-authored-by: fairydreaming <166155368+fairydreaming@users.noreply.github.com>
* Fix indentation
* Ensure array is zero-filled
* Prefer explicit std::fill
* Assert prev_top_k exists for shared indexer
---------
Co-authored-by: fairydreaming <166155368+fairydreaming@users.noreply.github.com>
* ui: fix MCP server display name conflicts in tools lists
Tool groups were keyed by display label so two servers reporting
the same name broke the keyed each blocks and only one was visible.
Key rendering, expand state and toggles by the stable server id
instead, and suffix duplicate labels with a counter in config order.
* ui: customizable MCP server display name with autofill
Add a display name field to the MCP server form, add and edit alike.
The custom name takes precedence over the server-reported one, so two
servers reporting the same name can be told apart; clearing the field
returns to the automatic label. In the add dialog a debounced preview
handshake prefills the field with the server-reported name: a manual
edit freezes the autofill, stale responses are discarded, failures
stay silent, and an unedited prefill is not persisted so the label
keeps following the server.
* ui: fix recursive fetch passthrough in the client test setup
The original fetch was captured inside beforeEach, where it is the
previous test's spy since vi.spyOn returns the existing one, so the
default passthrough recursed on itself for any URL outside the
mocked set. Capture the real fetch once at module load.
