* server: real-time reasoning interruption via control endpoint
Builds on the manual reasoning budget trigger from #23949. Adds a
CONTROL task that mirrors the CANCEL path on the live slot and calls
common_sampler_reasoning_budget_force to end thinking mid-generation.
POST /v1/chat/completions/control with { id_slot, action }, opt-in
reasoning_control arms the budget sampler on demand. Router and single
model. Minimal WebUI button as a skeleton for further UI work.
* ui: track reasoning phase via explicit streaming state
Add isReasoning to the chat store, mirroring the isLoading pattern:
per conversation map, private setter, public accessor and reactive
export. Set from the stream callbacks, true on reasoning chunks, false
on the first content chunk, reset on stream end and resynced on
conversation switch. The skip button now keys off isReasoning so it
shows only during the thinking phase, not the whole generation.
* ui: extract control endpoint and action into constants
Move the chat completion routes, the slots route and the reasoning
control action out of chat.service into api-endpoints and a dedicated
control-actions module. No behavior change, drops the magic strings so
the control protocol has a single source of truth.
* server: target reasoning control by completion id
Address @ngxson review on the control endpoint.
Switch from id_slot to the chat completion id to avoid a TOCTOU: the
slot can be reassigned between the lookup and the control request, so
matching the live completion (oaicompat_cmpl_id) is safe and a finished
one simply matches nothing. Rename the action to reasoning_end, guard
it on the reasoning_control flag of the target slot, and reduce the
response to {success} with an optional message.
* ui: target reasoning control by completion id
Keep the streamed completion id on the message and post it back to the
control endpoint instead of probing /slots. Drops the slot discovery
and the TOCTOU that came with it. Action renamed to reasoning_end,
response read as {success}.
* server: address review from @ngxson
Move the control fields into task_params and drop the redundant
comments on the control path.
* server: document the reasoning control endpoint
* Update tools/ui/src/lib/types/database.d.ts
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* ui: rename cmplId to completionId
Per @allozaur review, clearer name for the streamed completion id.
* ui: wire completion id capture through the agentic flow
The webui streams through the agentic flow, which relayed onModel but
not onCompletionId, so the completion id never reached the message and
the control request was never sent. Relay it through the flow and its
callbacks type, declare id on the chunk type, and log an explicit error
when the button fires without a usable id.
* ui: target reasoning control model from the message
The model is a property of the completion, so read it from the streaming
message like the id, not from the model dropdown which is unrelated UI
state. Makes the request self-consistent by construction instead of just
unlikely to drift.
---------
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* common : add common_chat_split_by_role
* cont : fix spans to reach end of message
* server: fix checkpoints creation
- extract message_spans from chat templates
- find the prompt token position before the latest user message
- split prompt batching at that position
- create a context checkpoint before the latest user input
- avoid periodic mid-prompt checkpoints when that position is known
- handle multimodal prompts when mapping text/template positions to server prompt tokens
- add --checkpoint-min-step to control minimum spacing between checkpoints
* cont : clean-up
* Support autoparser detection for message barriers
* server: fix message span delimiter and update docs
---------
Co-authored-by: Alde Rojas <hello@alde.dev>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Piotr Wilkin <piotr.wilkin@syndatis.com>
- HunyuanOCR shares the same HF arch and vision layout as HunyuanVL butwas split into a separate path that skipped the +0.1 bilinear sampler used by the HF reference.
- Collapse OCR into the HUNYUANVL projector + HUNYUAN_VL text arch
* spec: support MTP
* fix batch size
* rename files
* cont : simplify (#7)
* MTP: clean-up (#9)
* MTP: clean-up
* review: use llama_context_type instead of llama_graph_type
* review: remove llama_model_has_mtp
* review: fix convert issues
* convert: fix pycheck
* review: formatting
* use `mtp-` for identifying mtp models
* convert: fix mtp conversion
* mtp -> draft-mtp
* remove unused llama_arch
* add need_embd in speculative
* llama: allow partial seq_rm for GDN models for speculative decoding
Currently speculative checkpoint needs to restart from a checkpoint
after some draft tokens are not accepted, this leads to some wastage in
running the target again. This PR adds the ability to rollback upto
`draft_max` by storing the GDN intermediates.
* fix pending state
* vulkan: add GDN partial rollback
* meta: extend check to axis 1
* metal: add GDN partial rollback
Extend the gated delta net kernel to store intermediate states for
partial rollback support on the Metal backend.
- Add K (snapshot slot count) as a function constant
- Read input state from slot 0 of the 3D state tensor
- Write intermediate states to different slots during token loop
- For K=1, maintain backward-compatible single-slot behavior
Ref: https://github.com/ggml-org/llama.cpp/commit/8c05923630110223669f069af2000e9cf10c02bc
Assisted-by: llama.cpp:local pi
* delta_net_base: use ggml_pad instead of new_tensor
* review: add need_rs_seq
* review: rename part_bounded to n_rs
* review: deslop comments
* review: rename, add asserts
* server : adjust checkpoint logic (#11)
* server : adjust checkpoint logic
* cont : rm asserts
* server-context: fix early exit
* spec : fix compatibility with n-gram and add TODOs (#13)
* metal : cleanup
* llama : fix faulty bitwise check in recurrent memory
* server : disable RS-based MTP in combination with other spec types
* spec : add TODOs
* cont : fix comment
* cont : update comment
* common : fix logic for ngram + mtp compat
* llama-memory: enable checkpointing with partial rollback
* cont: add test-case for loading into a dirty ctx
* llama-memory-recurrent: clear rs_idx in clear
* download: fix mtp path
* llama-arch: fix enorm op
* docs: update docs
* conversion: fix type annotations
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* spec : refactor
* spec : drop support for incompatible vocabs
* spec : update common_speculative_init()
* cont : pass seq_id
* cont : dedup ctx_seq_rm_type
* server : sketch the ctx_dft decode loop
* server : draft prompt cache and checkpoints
* server : improve ctx names
* server, spec : transition to unified spec context
* cont : sync main and drft contexts
* cont : async drft eval when possible
* cont : handle non-ckpt models
* cont : pass correct n_past for drafting
* cont : process images throught the draft context
* spec : handle draft running out of context
* server : fix mtmd draft processing
* server : fix URL for draft model
* server : add comment
* server : clean-up + dry
* speculative-simple : update
* spec : fix n_past type
* server : fix slot ctx_drft ptr
* tools : update readme
* naming : improve consistency
* spec : refactor for multi-sequence speculative context
* cont : prepare params
* cont : prepare params
* spec : support parallel drafts
* server : support parallel drafting
* llama : reuse device buffers when possible
* server, spec : clean-up
* cont : clean-up
* cont : minor
* spec : reset `drafting` flag at the end
* spec : introduce `common_speculative_process()`
* spec : allow for multiple spec types (chain of speculators)
* replace old type field of type common_speculative_type in the
common_params_speculative struct with a vector to allow multiple
types to be specified
* introduce common_get_enabled_speculative_impls(const std::vector<enum common_speculative_type>)
to figure out which implementations the user has enabled
* introduce common_speculative_type_from_names(const std::vector<std::string> & names)
to parse the already user provided spec types
* all speculators run sequentially, best one wins (we verify its drafted tokens)
* maximize expected accepted tokens for current round by calculating the
product between the probability of accepting current token (n_acc_tokens / n_gen_drafts)
and the draft's length
---------
Co-authored-by: Petros Sideris <petros.sideris@nokia.com>
* docs : update speculative decoding parameters after refactor (#22397)
Update docs/speculative.md to reflect the new parameter naming scheme
introduced in PR #22397:
- Replace --draft-max/--draft-min with --spec-draft-n-max/--spec-draft-n-min
- Replace --spec-ngram-size-n/m with per-implementation variants
- Add documentation for all new --spec-ngram-*- parameters
- Update all example commands
Assisted-by: llama.cpp:local pi
* pi : add rule to use gh CLI for GitHub resources
Assisted-by: llama.cpp:local pi
* docs : run llama-gen-docs
* arg : fix typo
* server: respect the verbose_prompt parameter
* Revert "server: respect the verbose_prompt parameter"
This reverts commit 8ed885cf37.
* Remove --verbose-prompt parameter from llama-server
* Using set_examples instead of set_excludes
* misc : prefer ggml-org models in docs and examples
Prefer referring to known-good quantizations under ggml-org rather than
3rd-party uploaders.
* remove accidentally committed file
* server : support multiple model aliases via comma-separated --alias
* server : update --alias description and regenerate docs
* server : multiple model aliases and tags
- address review feedback from ngxson
- --alias accepts comma-separated values (std::set, no duplicates)
- --tags for informational metadata (not used for routing)
- aliases resolve transparently in router via get_meta/has_model
- /v1/models exposes aliases and tags fields
* regenerate docs
* nits
* server : use first alias as model_name for backward compat
address review feedback from ngxson
* server : add single-model test for aliases and tags
* common : use two decimal places for float arg help messages
This commit updates the help messages for various command-line arguments
in arg.cpp to display floating-point default values with two decimal
places instead of one.
The motivation for this changes is that currently only having one decimal
place means that values generated using --help or llama-gen-docs will not
display the correct values.
For example, currently the value of top-p in tools/server/README.md is
`0.9`, but the default value is actually '0.95'. And running
llama-gen-docs does not update this value as it uses the output from the
help message, which shows only one decimal place, so the values look
like they are unchanged.
* docs : run llama-gen-docs to update docs
* from previous PR
* Make instruction(system) as first message
* Convert [input_message] (text/image/file)
* Rename convert_responses_to_chatcmpl(body) -> response_body
* Initial tool call support
* Erase instructions field from chatcmpl body
* Feed reasoning texts to chat template
* Use std::vector instead of opaque json array
* Make output_item.added events consistent
* Move `server_task_result_cmpl_partial::update` from header to source
* Match ID of output_item.added and .done events
* Add function_call only if there is no "fc_" prefix
* Add function call output at non-streaming API
* Test if ID is persistent
* Add doc
* Fix style - use trailing comma
* Rewrite state management
* catch up with upstream/master
* Fix style - "type" is the first item of SSE data
* Explicitly check "instructions" from response_body
* Make lambdas static
* Check if reasoning content exists
* Add `oai_resp_id` to task_result_state(also initialized at ctor), server_task_result_cmpl_partial, and server_task_result_cmpl_final
* Reject `input_file` since it is not supported by chatcmpl
* Add "fc_" prefix to non-straming function call id as coderabbit pointed out
---------
Co-authored-by: openingnow <>
* initial commit for branch
* simplify constants
* add params to `struct common_params_sampling`, add reference to PR
* explicitly clamp `min_target` and `max_target` to `[0.0, 1.0]`
* add args, rename `queue_size` -> `window_size`
* improved comments
* minor
* remove old unused code from algorithm
* minor
* add power law case to `common_sampler_init`, add sampler name mappings
* clarify behaviour when `window_size = 0`
* add missing enums
* remove `target_range` param, make `target == 1` no-op, cleanup code
* oops, straggler
* add missing parameters in `server-task.cpp`
* copy from author
ref:
https://gist.github.com/MrJackSpade/9be99c7efbba7b95a41377e123b7b069
* remove old debug log, style nit
* fix compiler warning, add commented-out logging per token
* re-write + change parameters + simplify
* oops forgot args.cpp
* fix leftover `window_size`
* add missing values to `common_params_sampling::print()`
* with logging
* does this fix it?
* no, but does this?
* update default decay
* optimize
* fix bad merge
my git skills are lacking
* silence `missing initializer for member`
* update default decay to 0.9
* fix logging
* format (double)
* add power law to the new `samplers` vector
* log sampler init values
* improve logging messages in llama_sampler_power_law
* remove extraneous logging
* simplify target computation
last commit with debug logging!
* remove debug logging, explicitly clamp params at init
* add `use_power_law` flag + logic, minor cleanup
* update `power-law` -> `adaptive-p`
* fix cold start EMA
- `ctx->weighted_sum` is now initialized and reset to `target / (1.0f -
clamped_decay)`
- `ctx->total_weight` is now initialized and reset to `1.0f / (1.0f -
clamped_decay)`
this fixes a "cold start" problem with the moving average
* update `SHARPNESS` constant to `10.0f`
* minor style fixes
no functional changes
* minor style fixes cont.
* update `llama_sampler_adaptive_p_i` for backend sampling (ref: #17004)
* separate into `apply` + `accept` functions
* `pending_token_idx`: switch from `llama_token` to `int32`
functionally identical (`llama.h` has `typedef int32_t llama_token;`),
but its more correct now
* don't transform logits <= -1e9f
* fix masking in backend top-p, min-p
* address review comments
* typo in comments `RND` -> `RNG`
* add docs
* add recommended values in completion docs
* address PR feedback
* remove trailing whitespace (for CI `editorconfig`)
* add to adaptive-p to `common_sampler_types_from_chars`
* implement sleeping at queue level
* implement server-context suspend
* add test
* add docs
* optimization: add fast path
* make sure to free llama_init
* nits
* fix use-after-free
* allow /models to be accessed during sleeping, fix use-after-free
* don't allow accessing /models during sleep, it is not thread-safe
* fix data race on accessing props and model_meta
* small clean up
* trailing whitespace
* rm outdated comments
* arg: fix order to use short form before long form
* arg: update doc
* arg: update test-arg-parser
* arg: address review feedback from ngxson
simplified to check first.length() <= last.length() only
fixed: --sampler-seq, --rerank, --draft ordering
note: middle positions in 3+ arg sets are not verified
* arg: update doc
* presets: refactor, allow cascade presets from different sources
* update docs
* fix neg arg handling
* fix empty mmproj
* also filter out server-controlled args before to_ini()
* skip loading custom_models if not specified
* fix unset_reserved_args
* fix crash on windows
Xuan-Son Nguyen