* 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.
* support "reasoning_effort": "none" in OAI API
* handle reasoning.effort: "none" in OAI responses API
* clarify non-"none" values of reasoning_effort have no effect
* use json_value instead of body.at
* hex-l2: use dirty ranges for flushing
* hex-l2: simplify range based flush logic
* hex-l2: optimize dirty range scans
* hex-hvx: support for reduce_max_i32
* hex-mm: optimize fused MUL_MAT+ADD to use vtcm for bias when it fits
* hex-mmid: optimize mmid row-mapping generation
* hex-mmid: optimize mmid row-mapping generation
* hex-mmid: optimize mmid row-mapping generation (round2)
* hmx-mm: optimize output proc by tiling (col-chunking)
* hex-fa: start the next q dmas a bit earlier
* hex-fa: prefetch Q even earlier
* hvx-fa: optimize softmax to keep things in hvx registers
* hex-fa: hoist const register init in softmax loop
* hmx-fa: kick off next-qkv DMAs before o-proc
* hmx-fa: hoist various checks out of the inner loop
* hmx-fa: adjust the cost model to better balance softmax work across hvx threads
* hmx-fa: overlap diag rescale build with last HMX task
* hmx-fa: optimize idx update in output proc
* hmx-fa: unroll the softmax loops for improved perf
* hmx-fa: overlap qk-dot with softmax, double-buffer p and s tiles
* hex-trace: double the default number of trace entries
* hex-trace: add trace events for opbatch and buffer mgmt
* hex-trace: overhaul tracing to simplify runtime event handling and support opbatch stats
* hex-trace: replace ascii timeline diagram with pipeline bubbles detector
* hex-trace: handle missing start/stop events
* hex-dma: always log stop/start trace events even for dummy dmas
* hex-scripts: fix flake warnings
* ui: add Default reasoning option that defers to the server
The webui always injected enable_thinking, overriding the chat template
default and the --reasoning flag, breaking models that reason
unconditionally (e.g. Gemma 4 E4B) on a fresh client.
Default sends nothing so the server decides, Off and effort levels
force the value as before. All choices are remembered.
Also remove the boolean thinking API from the conversations store and
drop ChatFormReasoningEffortSubmenu.svelte (dead code).
* ui: close the whole menu tree on reasoning level selection
The reasoning levels were raw buttons inside the SubContent, so
selecting one only closed the submenu via manual state while the root
dropdown stayed open. DropdownMenu.Item closes the full tree on select
like the sibling entries and brings native keyboard navigation.
* ui: prevent the add menu tooltip from flashing when the dropdown closes
* Squash history before conflict-resolution during rebase on master
WIP commit
Add 32-byte loads, restore per-block amax
Use nvfp4x4 intrinsic when available
Fuse per-channel amax and quantization kernels
Do pointer arithmetic only once on x
Remove unnecessary ternary in the load
We assert on host side that ne00 is 64-aligned
Add back scale-search, but optimize it with intrinsics
Code cleanup
Make scale in MMQ-epilogue NVFP4-specific/restrictive for now
Remove unneeded include, add comment
Fix trailing whitespace
Guard __builtin_align__(32) struct to NVIDIA
Seems like HIP doesn't have this available, see https://github.com/ggml-org/llama.cpp/actions/runs/29438651734/job/87431623001
* compiler massaging to avoid unnecessary LDCs
* kvalues_mxfp4 -> kvalues_nvfp4 in quantize_mmq_nvfp4
* Always pass in src1_scale.ptr
* Extract ggml_cuda_is_aligned helper
