With LLAMA_SLEEP_EVICT_KV the KV cache device buffers are freed when a model
goes cold. update_slots() touches the KV before the decode-time vram_ensure_warm
(e.g. SWA models create a checkpoint that reads the KV via ggml_backend_tensor_get),
so the KV must already be resident by then. Move the restore to the sleep-wake
handler (handle_sleeping_state(false)), which runs before update_slots, fixing a
GGML_ASSERT(buffer) crash on iSWA models (gemma) when KV eviction is enabled.
Assisted-by: Claude
Before uploading a model's weights, acquire the shared VRAM token (ring the
doorbell so any resident model releases first). Previously load uploaded weights
to VRAM before the arbiter was active, so loading a large model while another
(e.g. the warm 4B task model) held VRAM could exceed the budget and OOM.
- add vram_arena_open() (idempotent flock/doorbell setup) and
vram_acquire_for_load(), called from load_model() before
common_init_from_params().
- a coordinated load now stays warm holding the token and serves its first
request without a re-warm (drop the init-time go_cold cold-start).
Assisted-by: Claude
The request handler only calls wait_until_no_sleep() (which wakes a server out
of its sleeping state) when sleep_idle_seconds >= 0. But the VRAM arbiter's
cross-process doorbell can put a server to sleep even when idle-sleep is
disabled, so without this a doorbell-slept server would never wake and requests
to it would hang until timeout.
Do not bypass the wake path when LLAMA_SLEEP_VRAM_ONLY is set, so the arbiter no
longer depends on --sleep-idle-seconds being configured.
Assisted-by: Claude
Extend on-demand device residency to the KV cache so that when a model's KV
plus another model would not fit in VRAM, the KV can also be evicted to a host
shadow (D2H on release, H2D on restore) instead of only the weights.
- llama_memory_i: add release_device_buffers()/restore_device_buffers()
(default no-op). Implemented in llama_kv_cache (D2H shadow of the live
ctxs_bufs, freed and reallocated like the weights); llama_memory_hybrid and
llama_kv_cache_iswa delegate to their child caches.
- llama_context::release_device(evict_kv): also evict the memory's device
buffers when requested; restore_device() rebuilds them. Public API
llama_context_release_device gains an evict_kv flag.
- server: LLAMA_SLEEP_EVICT_KV=1 enables it. Off by default (weights-only),
since the KV shadow adds a D2H/H2D copy of the live cache each cycle.
Validated on RX 580 (Vulkan), 4B @ 32k ctx: weights-only cold VRAM 1750 MB
(KV stays); weights+KV cold VRAM 726 MB (KV freed, ~1 GB reclaimed). KV
survives the round-trip: prompt cache reused after the cycle (prompt_n 4 vs
42), correct output.
Assisted-by: Claude
Add release/restore of a model's GPU weight buffers (keeping a host shadow
and the KV cache) so several always-loaded llama-server processes can
time-share a single GPU without reloading or losing the prompt cache.
- llama-model: release_device_weights()/restore_device_weights() capture a
compact host shadow (stable iteration order, view-skipping) and free then
realloc the device weight buffers; weights_resident() query.
- llama-context: release_device()/restore_device() wrappers; decode() auto-
restores; public C API llama_context_release_device/restore_device.
- server: LLAMA_SLEEP_VRAM_ONLY makes idle-sleep release only the VRAM weights
(not a full unload/reload). A cross-process flock token in LLAMA_VRAM_ARENA
enforces "resident iff holds token"; an inotify doorbell forces the holder
to release on contention. The warden thread only touches the task queue, so
releases run on the loop thread and never race a decode.
Validated on RX 580 (Vulkan): two models share 8GB, never both resident,
correct output under contention, KV cache preserved (no re-prefill).
Assisted-by: Claude
* feat(ui): add symbolic math support to JS sandbox via nerdamer
Preload nerdamer (with decimal.js) in the sandboxed worker,
exposing the `nerdamer` global for symbolic computation:
simplify, expand, factor, diff, integrate, solve, laplace,
ilt, limit, partfrac, gcd/lcm, roots, coefficients, and more.
Mirrors the math.js integration pattern from the
feature/sandbox-symbolic-math branch, but uses nerdamer
for a lighter, more focused symbolic math engine.
* Update sandbox-harness.ts
* docs(ui): update sandbox tool description with detailed nerdamer usage guide
* Clarify nerdamer usage in sandbox tool description
Updated the description of the sandbox tool to clarify usage of nerdamer.
* ui: build nerdamer sandbox prelude from vendored source
Replace the vendored all.min.js with the readable nerdamer-prime
source and its two bundled deps (big-integer, decimal.js), licenses
included. A vite plugin bundles and minifies them at build time with
the upstream esbuild flags, exposed as virtual:nerdamer and imported
lazily on first sandbox use. The vendors package.json pins commonjs
so the project level type: module does not break esbuild format
detection. The harness gains a CSP removing network egress from the
worker, and browser tests cover the prelude, exact arithmetic, the
fetch block and the timeout.
Upstream snapshot: together-science/nerdamer-prime@1936145
* feat(ui): make symbolic math (nerdamer) a user-toggleable setting
- Add SYMBOLIC_MATH_ENABLED setting key and registry entry (checkbox, default false)
- Convert SANDBOX_TOOL_DEFINITION to buildSandboxToolDefinition(includeSymbolicMath)
so the tool description includes/excludes nerdamer API docs dynamically
- Cache sandbox harness per variant ('nerdamer' / 'plain') for instant toggle
- Deprecate SANDBOX_TOOL_DEFINITION constant alias for backward compatibility
- Update tools store to pass symbolic math config into tool definition
* docs(ui): tell LLM to list nerdamer functions first, do not guess
* test(ui): enable symbolic math in sandbox tests via settingsStore config
* style(ui): fix formatting for tools.svelte.ts
---------
Co-authored-by: Pascal <admin@serveurperso.com>
The Qwen3-VL learned position embedding is interpolated to the runtime patch
grid with the default bilinear+antialias (align_corners=False) sampling, while
the transformers reference uses align_corners=True (torch.linspace(0, side-1, T)).
The mismatch scales grounding coordinates about the image center, growing with
image size and per-axis for non-square images (see #16880).
* server: return 400 instead of 500 on validation error with X-Conversation-Id
set_req() attaches the spipe as soon as the header is present, before the request
body is parsed. When params validation throws, set_next() never runs and next_orig
stays empty, so on_complete() called it and crashed with std::bad_function_call,
turning the prepared 400 JSON into a generic 500.
on_complete() now treats an empty next_orig as "streaming never started" and evicts
the session installed by set_req(), so a failed request leaves nothing behind for
discovery or replay. This also covers valid requests that carry the header but do
not stream, which previously left an empty finalized session in the map until the
GC TTL.
* ui: do not send the backend_sampling placeholder
On a fresh profile the syncable settings hold the empty string placeholder meaning
"let the server decide". Every neighbor field goes through the hasValue() guard
that filters it, except backend_sampling, which sent the placeholder verbatim and
made every default settings completion fail validation.
Guard the field with hasValue() like its neighbors. hasValue(false) is true, so an
explicit false still reaches the server and the intent of #18781 (send both true
and false) is preserved. Only the placeholder is filtered.
* 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.
* 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
* feat: Add shimmer text animation for processing state indicators
* feat: Redesign CollapsibleContentBlock component with improved UX
* feat: Add conditional setting display support with dependsOn field
* feat: Add showAgenticTurnStats setting for per-turn statistics
* feat: Update ChatMessageAgenticContent with improved UI and new features
* feat: Enhance file read tool UI/UX
* feat: Refine styling of collapsible content and code preview blocks
* feat: add terminal variant to CollapsibleContentBlock
* feat: add built-in tools UI registry
* feat: extract ChatMessageReasoningBlock and ChatMessageToolCallBlock
* refactor: simplify ChatMessageAgenticContent to use extracted blocks
* fix: correct markdown content block margin spacing
* fix: reorganize SettingsChatFields layout and reset button positioning
* fix: use direct map access in agentic store session methods
* refactor: remove reasoning preview/throttle system from CollapsibleContentBlock
* feat: add auto-scroll to reasoning block and remove showThoughtInProgress
* feat: add ChatMessageToolCallDateTime component and support for new tool types
* feat: improve auto-scroll reliability in reasoning block with RAF coalescing and MutationObserver
* feat: show MCP server favicon for tools without a built-in icon
* feat: add search-results parsing utilities and tests
* feat: add ChatMessageToolCallSearchResults component
* feat: integrate search results rendering into ChatMessageAgenticContent
* feat: display tool call input alongside output in ChatMessageToolCallBlock
* style: use muted foreground color in reasoning block content
* chore: Format
* feat: Refine reasoning block layout and make pending thoughts display configurable
* feat: Stream tool call code blocks with auto-scroll and handle partial JSON
* feat: add streaming permission gate infrastructure
* feat: wire permission gate into the agentic loop
* fix: bail out on abort and skip already-approved tool calls
* fix: clear partial tool calls on abort and savePartialResponse
* test: cover partial tool call cleanup end-to-end
* refactor: Remove streaming permission gate logic
* fix: Correct autoscroll and streaming gates for tool calls and reasoning blocks
* refactor: Chat Message Assistant componentization
* fix: Show health metadata for disabled MCP servers and promote connections on enable
* fix: Inherit global enabled state for missing MCP per-chat overrides
* refactor: Cleanup
* refactor: Split ChatMessageToolCallBlock into dedicated components
* feat: Add live streaming and auto-scroll for tool execution output
* feat: Add line numbers and change markers to file edit diffs
* chore: Formatting
* feat: Add type definitions and utilities for recommended MCP servers
* feat: Add recommended MCP servers configuration and storage key
* feat: Add McpServerCardCompact component for recommended servers
* feat: Add recommended servers section to Add New Server dialog
* feat: Update McpServerForm to support authorization requirements
* feat: Add select-none classes for text selection prevention
* feat: Add recommended MCP server icon assets
* refactor: Store dismissed MCP recommendations as a boolean flag
* feat: Render tool results as JSON or Markdown based on detected content type
* feat: UI improvement
* feat: Render search block early and update heading to show execution state
* fix: Prevent non-web-search tools from triggering the search UI block
* refactor: Cleanup
* refactor: Extract hardcoded icon size classes into shared constants
* refactor: Extract hardcoded tool result separator into a shared constant
* refactor: Tool Calls UI/logic
* refactor: Cleanup
* refactor: Cleanup
* refactor: Cleanup
read_file with append_loc emits "{n}\u2192 {line}". The space after the
arrow is meant as a separator, but it is indistinguishable from real
indentation. Models strip "{n}\u2192" yet keep the space, so the old_text
passed to edit_file carries a phantom leading space and never matches
(normalize_for_fuzzy_match trims trailing whitespace only, never leading).
Drop the separator space so the arrow abuts content: stripping "{n}\u2192"
now yields the exact line with its real indentation preserved, and the
failure mode cannot occur by construction. Update the description example
to match the new format.
In MODEL mode, modelPropsCache is never populated: fetchModelProps
call sites are gated on router-only state (isRouterMode checks,
routerModels always empty), so supportsThinking always reads an
empty chat template once a model is auto-selected.
Read serverStore.props.chat_template directly in non-router mode,
since the global /props already describes the single loaded model.
* server : clear checkpoints upon prompt clear
* server : move the prompt state data to the server_prompt_cache
Assisted-by: pi:llama.cpp/Qwen3.6-27B
* server : handle batched slot being cleared
* ui: fix MCP panel regressions after settings rework
Restore the llama-server proxy switch in the Add New Server dialog.
The dialog never passed useProxy/onUseProxyChange to McpServerForm,
which only renders the proxy switch when the handler is provided.
The flag is now wired, persisted on addServer, and reset on close.
Bound the MCP connection handshake with the configured timeout.
handshakeTimeoutMs was set in the server config but never consumed.
The SDK timeout only covers the initialize request, not
transport.start(), which can hang forever on an unreachable host.
The whole handshake now races against the timeout and closes the
transport on expiry so the underlying fetch or socket is aborted.
Keep disabled MCP servers visible in management and chat-add UIs.
Collapsing mcpDefaultServerOverrides into mcpServers[i].enabled turned
the visibleMcpServers enabled filter into a visibility trap: toggling
a server off outside a conversation hid it from every surface with no
way to re-enable it. The filter is dropped, tools derived from health
checks still skip disabled servers, and the settings page and server
card render the real card instead of a skeleton for disabled servers
that never receive a startup health check.
* ui: clarify MCP server list semantics and add regression test
Remove the visibleMcpServers getter, a filterless alias of getServers
whose name invites the next refactor to put a filter back. Call sites
read getServers directly, the duplicate list in the chat submenu is
merged, and the misleading local variable in the sheet is renamed.
A parser unit test pins the invariant: enabled is an on/off state,
never a visibility filter, so disabled servers stay listed and
toggleable.
* ui: apply the MCP request timeout setting live to all servers
The per-server requestTimeoutSeconds field was never editable in any
UI and froze the global setting at server creation time, so changing
the timeout in Settings was a no-op for existing servers. The field
is removed from the data model and parsers, the timeout is read live
from the global setting wherever a request config is built, and the
misleading "Can be overridden per server" help text is dropped. A
parser unit test guards against reintroducing the stored field.
* ui: move the MCP request timeout into the Agentic settings section
The MCP section held a single setting. The timeout is a global tool
execution parameter like the other Agentic entries, so it moves there
and the section is removed. Same settings key, no migration needed.
* ui: remove the dead tool preview lines setting
The agenticMaxToolPreviewLines setting was read into AgenticConfig
and consumed by nothing: the agentic loop only uses enabled and
maxTurns. Its help text described a previous architecture where only
truncated previews and the final response survived the loop; tool
results and intermediate turns now persist as full DB messages, so
the setting had no effect at any value. Stale keys in localStorage
or a server ui-config are ignored.
* ui: resolve absent MCP per-chat overrides to the server enabled flag
New conversations started with every MCP server off: the settings
rework stopped seeding a per-conversation override list, assuming
the enabled check would fall back to mcpServers[i].enabled, but it
fell back to false, and the send path passed the raw stored list
with no fallback at all. The per-conversation list is now sparse by
contract, holding only explicit toggles, and every access point
resolves a missing entry to the server's own enabled flag: the
toggle display, the resolved list handed to the agentic flow, and
the enabled check itself.
Migrate the tokenize tool to common_params_parse, replacing its
hand-rolled argv parsing, Windows UTF-8 handling and file reading
with the shared common helpers.
Expose the model-sourcing flags (-m, -mu, -dr, -hf, -hff, --offline,
HF_TOKEN) to LLAMA_EXAMPLE_TOKENIZE, and register --ids, --stdin,
--no-bos, --no-parse-special and --show-count as common args.
parse_special defaults to true for TOKENIZE to preserve the old
behavior. Errors now go through LOG_ERR instead of fprintf(stderr).
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
The mobile "+" sheet was missing the reasoning effort section present
in the desktop dropdown, so thinking could not be toggled on touch.
Extract the shared derivation and selection logic into useReasoningMenu
and consume it from both the desktop submenu and the mobile sheet,
keeping a single source of truth and preserving each surface idiom.
* fix: drop MCP recommendations auto-popup and silent preloads
* feat: Add consent-driven MCP recommendations inside Add New Server dialog
* refactor: Drop mcpDefaultServerOverrides for mcpServers[i].enabled
* feat: Center the empty state on the MCP settings page
* fix: keep existing MCP cards intact when adding a new server
* fix: keep MCP cards stable when a new server is added
* refactor: keep MCP server list in config insertion order
* feat: shrink the recommended-MCP cards to two tools each and fit them in one row
* feat: make recommended MCP cards click-to-fill and tighten copy
* feat: highlight the selected MCP recommendation and stop auto-focus on dialog open
* feat: derive MCP recommendation selection from the form URL
* fix: make recommendation MCP cards fully non-focusable
* fix: redirect focus from first card to the URL input on consent
* chore: Formatting
* refactor: Remove Recommended MCP Servers completely
* fix: Preserve legacy mcpDefaultServerOverrides key after merge migration for downgrade compatibility
* server: honour per-request reasoning_budget_tokens in chat completions
The reasoning-budget block in oaicompat_chat_params_parse read only the
server-level default (opt.reasoning_budget, typically -1) and the
Anthropic-style alias thinking_budget_tokens, but never the canonical
reasoning_budget_tokens field from the request body. Because the key
was then written into llama_params before the generic body-copy loop
ran, the copy loop found the key already present and silently skipped
the caller-supplied value. Any per-request override (e.g. 0 to
suppress thinking entirely) was therefore discarded.
Fix: read reasoning_budget_tokens from the request body first, so the
value that reaches the sampling layer is the one the caller intended.
Add a unit test in test-chat.cpp that exercises this path via
oaicompat_chat_params_parse with a Qwen3 template (which the autoparser
detects as a thinking-capable model) and asserts the returned
llama_params carries reasoning_budget_tokens == 0.
* server: honour per-request reasoning_budget_message in chat completions
The reasoning-budget block in oaicompat_chat_params_parse wrote
reasoning_budget_message into llama_params straight from the server-level
default (opt.reasoning_budget_message) and never read the canonical
reasoning_budget_message field from the request body. Because the key
was written before the generic body-copy loop ran, that loop found the
key already present and silently skipped the caller-supplied value. Any
per-request override of the message injected before the end tag when the
budget is exhausted was therefore discarded, even though server-task.cpp
already reads reasoning_budget_message from that data.
This mirrors the reasoning_budget_tokens bug fixed in the previous commit.
Fix: read reasoning_budget_message from the request body first, falling
back to the server default, so the value that reaches the sampling layer
is the one the caller intended.
While here, collapse the adjacent reasoning_budget_tokens override to a
single json_value() call; json_value already falls back to the default on
a missing/null/wrong-type key, so the explicit body.contains() guard was
redundant. No behavioral change.
Add a unit test in test-chat.cpp that exercises this path via
oaicompat_chat_params_parse with a Qwen3 template (which the autoparser
detects as a thinking-capable model) and asserts the returned
llama_params carries the per-request reasoning_budget_message rather than
the server default.
* cleanup
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
If mmproj is explicitly disabled via the model preset or command-line
parameters then the model won't be able to handle image/audio inputs and
this shouldn't be declared as supported input modality on the /v1/models
endpoint.
* mtmd: fix silent prompt truncation on embedded NUL
mtmd_input_text carried the prompt as a bare const char* with no
length, so a NUL byte in message content cut the prompt at the
tokenizer boundary and dropped every later message plus the assistant
marker, with no log. Add an explicit text_len and thread it through,
matching llama_tokenize and the text only path.
* cleanup
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server : fix image blocks in tool_result being dropped during Anthropic→OpenAI conversion
server_chat_convert_anthropic_to_oai() silently discarded image blocks
inside Anthropic tool_result content. This broke multimodal tool outputs
(e.g. a tool that returns an image) because the model never received the
image.
When tool_result contains image blocks, convert them to OpenAI
multimodal content parts (text + image_url array). Plain-text results
remain simple strings for backwards compatibility.
* server : add test for image blocks in Anthropic tool_result conversion
* server: accept null sampling params
Extend the schema validation to treat a null value as absent, so
clients can send null on nullable params (temperature, top_p, ...)
to request the server default. This matches the OpenAI spec and the
json_value convention used elsewhere.
Add has_field() to skip null in the field eval guards.
* has_field -> has_value
* mtmd: deepseek-ocr v1 multi-tile dynamic resolution + unified image-preprocessors for both versions (ds-ocr v1 and v2)
* remove hacky API
* fuse row into a long image
* almost working
* adapt to new preprocessor api
* rm debugging printf
* improve
* mtmd: dsocr-tiles fixes (#25481)
* ds-ocr img-preproc fuse_row tile-drop fix for multi rows and columns images
* mtmd drop the duplicate redundant img_end
* deepseekocr graph simplify CLS broadcast cleanup
* test-deepseek-ocr: relax v1 single-view tolerance; drop trailing prompt space; make DRY opt-in and n_predict model-specific (#25486)
---------
Co-authored-by: Saba Fallah <10401143+sfallah@users.noreply.github.com>
Co-authored-by: Saba Fallah <sabafallah@gmail.com>
* llama-cli: fix crash on wrong server base url by catching exceptions and graceful exit
* review: leaner catch group: json error and standard exception
downloadConversation serialized activeMessages, the root -> currNode
path, so exporting a conversation with edited or regenerated messages
dropped every alternate version and kept only the selected one.
Fetch the whole message tree via getConversationMessages so the export
carries all message versions, matching the multi-conversation export
path which already did this. Keep the active conversation as the header
source to preserve an up-to-date currNode.
Forks are separate conversations, each with its own convId, and are
exported on their own.
A model whose chat template parses at init but fails parser generation
at apply time (e.g. uses {% call %}) throws std::invalid_argument from
common_chat_templates_support_enable_thinking(), which ran outside the
try/catch guarding common_chat_templates_init(). The throw was uncaught
and llama-cli aborted (SIGABRT) instead of failing to load. Moved the
probe inside that try/catch so an apply-time error fails load the same
way an init parse error does.
Signed-off-by: Jesse LaRose <jesse@taey.ai>
Lumpiasty
