submit_generation_button() only performed normal generation when
voice_typing_mode==0. If a session saved voice_typing_mode>0 and is then
reopened without a Whisper model loaded, the option is greyed out and
cannot be reset, so onclick fell through and did nothing while the button
was still visually a submit button - Generate More (and Submit) stopped
working.
Guard the branch with is_using_kcpp_with_whisper(), matching the pattern
already used everywhere else voice_typing_mode is checked (init, submit
button rendering, ready_to_record). When Whisper is unavailable the button
now behaves as a normal generation button regardless of the stale saved
setting. Behaviour is unchanged when Whisper is loaded.
Fixes#2353
* feat: WIP
* feat: Replace conversation rename flow with unified AlertDialog component
* feat: Add radio group component and consolidate title generation settings
* refactor: Remove JS Sandbox global toggle and migrate legacy user state
* chore: Formatting
* refactor: Cleanup
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* refactor: Cleanup
* refactor: Marquee selection hook
* feat: UI improvements
* refactor: Bulk db operations
* fix: optimize bulk conversation deletion to handle ancestor chains
* refactor: remove pairedKey mechanism from settings system
* fix: remove redundant onclick handler from dialog cancel button
* chore: pin @lucide/svelte to exact version
* feat: Run JavaScript tool disabled by default
* fix: correct active conversation deletion tracking in bulk delete
* feat: improve shift-key multi-selection support in sidebar via keyboard
* refactor: Retrieve JS Tool enabling via Developer Settings
* nits: sync, dialog wording, cycle guard, and lockfile follow-ups
- Restore titleGenerationUseLLM registry entry so it syncs across devices again
- Mention fork cascade in the bulk delete confirmation dialog
- Clear newParent on cycle guard break so children never point at a deleted conversation
- Align @lucide/svelte in package-lock.json with the exact pin in package.json
---------
Co-authored-by: Pascal <admin@serveurperso.com>
Edge paragraph margins are now zeroed at the source in
markdown-content.css, but the user bubble and the system message still
carried the -my-4 compensation for them. The uncompensated negative
margins shrank the wrapper 2rem below its content, collapsing
single-line user bubbles into a scrollable sliver and skewing the
system message expand threshold.
* ui: fix Show tool call in progress toggle ignored
The showToolCallInProgress setting was disconnected from the render
path during the agentic content rework: getDefaultExpanded() returns
a hardcoded false for tool call sections and an unconditional effect
auto-expands the currently executing tool call regardless of the
setting.
Drive default expansion of all tool call section types from the
setting and remove the now redundant auto-expand effect. Manual
toggling still takes precedence over the default in both directions.
* ui: rename Show tool call in progress to Always show tool call content
The previous name suggested symmetry with Show thought in progress,
which only applies while inference is running, but tool call content
stays expanded after completion. Rename the label, the settings key
and the syncable server key to alwaysShowToolCallContent. The synced
parameter never worked under its previous name so no migration is
needed.
The agentic gate counted MCP servers, builtin and custom tools but not
frontend tools, so with the JS sandbox as the only tool source the
agentic flow was skipped, no tools field reached the server and the
chat template rendered without the tool system prompt.
The sandbox is fully client-side: frontendTools derives from the
Developer settings toggle alone, counting it in the gate restores that
single source of truth.
Treat the presence of sdtiledvae separately from its truthiness so the documented zero value survives a launcher config reload. Fixes#2065.
Co-authored-by: LK-Customs <lolikun@sunpraise-mc.com>
DeepSeek-V4's ffn_gate_tid2eid tensor is an i32 token-id -> expert-id
index table, not weights. It was never added to the name-based
exclusion list alongside ffn_gate_inp.weight, so llama-quantize tries
to quantize it and fails since i32 cannot convert to a float type.
Fixesggml-org/llama.cpp#25754
Signed-off-by: Yash Raj Pandey <yashpn62@gmail.com>
* fix(api): don't iterate a string banned_tokens character by character (#2333)
banned_tokens/banned_strings are consumed as a list of substrings. When a
caller supplies a bare string instead, `banned_tokens[:ban_token_max]`
slices it and `for tok in banned_tokens` walks it one character at a time,
so every letter in the value becomes its own banned substring. Banning
common letters like "e" makes generation collapse into garbage, with no
error to point at the cause.
Coerce a string value into a single-element list, matching how the OpenAI
`stop` parameter is already normalized in transform_genparams.
* fix(api): parse a JSON-array string in banned_tokens instead of inerting it
Per review: coercing the string form to a single-element list left the
reported gendefaults case a seemingly-effective no-op. Parse a JSON array
supplied as a string so the reported config bans "exclude" as intended,
and keep the bare-string form ("exclude") working as a single substring ban.
---------
Co-authored-by: Anai-Guo <antai12232931@anaiguo.com>
The two websearch status messages in koboldcpp.py print with no leading
newline, so they run onto the end of the preceding generation-stats line
(which has no trailing newline), e.g.:
...Total:26.31sReturning cached websearch...
Give both the cached-result print and the new-search print a leading
newline so each starts on its own line, matching the approach already
taken elsewhere (adding the missing newline at the offending print
rather than changing the stats line). Fixes#2337.
Co-authored-by: Anai-Guo <antai12232931@anaiguo.com>
* common: auto-download dflash- and eagle3- HF sidecars
Mirror the existing mtp- sidecar logic to support auto-discovery and
download of DFlash (dflash-) and Eagle3 (eagle3-) speculative decoding
sidecars from Hugging Face repos.
Changes:
- Add --dflash and --eagle3 CLI flags to trigger sidecar download
- Add find_best_dflash() and find_best_eagle3() using find_best_sibling
- Exclude dflash- and eagle3- filenames from primary model selection
- Filter dflash- and eagle3- from cached model listings
- Wire download tasks that set speculative.draft.mparams as fallback
Assisted-by: pi:llama.cpp/Qwen3.6-27B
* docs : regen
* vulkan: Support Q2_0
The backend perf tests for mat-vec-mul weren't very good at first (worse than
q2_k), doubling the rows per workgroup made a big difference.
* reorder
* resolve merge conflict, adjust err threshold for f16->q2_0 set_rows
* opencl: load quant as uint in mv_q4_k_f32_flat
helps older compilers (e.g., E031.41, boosts 2x),
no impact on newer compilers (e.g., E031.45 or newer)
* opencl: load quant as uint in mv_q5_K_f32_flat
helps older compilers (e.g., E031.41)
* opencl: format
---------
Co-authored-by: Li He <lih@qti.qualcomm.com>
* hex-mm: fix artificial limit in the solver that restricted number of act-prep threads
* hex-mm: fix warning
* hex-prof: do not apply --top to the timeline report
* hmx-mm: add suport for tiled act-processing to better distribute hvx work
* hex-l2: add tracing for l2flush events
* workqueue: redo the legacy workpool api to match hmx-queue and dma-queue
* hmx-mm: fix f32 activation buffer alignmnet for nhvx=5,6,7
* hex-work: minor cleanup for work-queue apis
* hex-work: further cleanup of the work-queue api
* hex-l2: optimize l2flushes at the opbatch level
* hex-work: remove unused mask
* hex-work: no need to drop hvx ctx in the work-queue
* hex-work: add explicit wakeup/suspend and make threads spin
* hex-bufs: mark any non-weight tensor as compute
* hex-dma: dma-queue support for alias queues and cached dma
* hex-l2: track tensor aliases and delay or skip flushes as much as possible
* hex-l2: simplify tensor alias handling
* hex-l2: handle overlapping views as a circular list of aliases
* hex-tens: add flags helper
* hex-l2: add helper for marking tensors clearn/dirty
* hex-l2: mark binary and rope outputs as l2-clean and keep the rest as is for now
* hex-l2: proper support for handling all tensor overlap scenarios
* hex-trace: instrument matmul init code and cleanup trace checks
* hex-thread: introduce dedicated main thread with explicit stack and priority
* hex-l2: track dirty state as bitmap and introduce threaded flush
* hex-trace: remove redundant checks for ctx != null
* hex-l2: allocate entire context as one buffer and l2fetch it after big flushes
* hex-l2: disable tensor clearing in binary and rope for now seems to cause issues with fusion
* hmx-mm: update act proc to use fastdivs and fix DMA overflow
* hmx-mm: make MUL_MAT_ID kernels robust to multi-chunk cases (start_row>0)
* hex-queue: remove obsolete queue interfaces and flush hmx-queue at the end of the op-batch
* hex-queue: dont use early wakeup for small op-batches
* hex-tensors: properly cap max_tensors in op-batches and dirty_map
* hex-l2: make sure threaded l2flush does proper rounding
* hex-l2: factor out htp_tensor_flush for reuse (if needed)
* hex-l2: optimize tensor flushes by coalescing flush-all
* hex-l2: optimize multi-threaded flush
* hex-drv: futureproof version checks
* hexagon: fix errors and warnings on windows
* hex-main: update main thread to only use dspqueue_read, dspqueue_peek is not available on some platforms
* hex-main: add fallback mode for dspqueue with callbacks
* hex-main: introduce fallback mode for using dspqueue callbacks for full op processing
* hex-main: remove early wakeup, not helping and seems to cause some errors with certain batch sizes
* hex-l2: make sure to use invalidate version of flushall
* hex-l2: dont try to trace early l2flush at the start of op-batch
* hex-main: remove offset_ctx that must be zero anyway
* hex-hmx: fix hmx_queue_depth to use idx_write - idx_read
* hex-hmx: use atomic_load for idx_read/write
* hex-main: add static assert to make sure n_threads are aligned
The current integration treats SME as a single capability (CPU_FEATURE_SME)
with no distinction between SME(v1) and SME2. The kernels dispatched under
CPU_FEATURE_SME use SME2-specific instructions, making dispatch incorrect
on SME(v1)-only hardware.
We introduce build-time and runtime distinction between SME and SME2, and
wire SME(v1) and SME2 kernels based on actual hardware support.
Microsoft BitNet Hugging Face configs use BitNetForCausalLM while the
converter only registered BitnetForCausalLM, causing conversion to fail
with "Model BitNetForCausalLM is not supported".
Register both spellings in TEXT_MODEL_MAP and the Bitnet model class.
Fixesggml-org/llama.cpp#25629
Concedo
Tai An
Todor Boinovski
Aleksander Grygier
Aman Gupta
Pascal
askmyteapot
Hongqiang Wang
DilanRG
henk717
Ruixiang Wang
Yash Raj Pandey
lhez
Georgi Gerganov
fairydreaming
Aaron Teo
Jeff Bolz
Todd Malsbary
Gezahegne
akleine
Max Krasnyansky
Rajendra Matcha
Ruben Ortlam
Khashayar Ghafouri
Johannes Gäßler
Alessandro de Oliveira Faria (A.K.A.CABELO)
Chipmunk