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>
* cli: move to HTTP-based implementation
* wip
* working
* remote server ok
* cli support router mode
Co-authored-by: Piotr Wilkin <ilintar@gmail.com>
* case: router with only one model
* Apply suggestions from code review
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
* remove outdated comment
* use destructor instead
* add ftype
* cli-view --> cli-ui
* pimpl
* no more json in header
* nits fixes
* also show model aliases
---------
Co-authored-by: Piotr Wilkin <ilintar@gmail.com>
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
* server : improve message span logic
* cont : cast size_t to int32_t in comparisons
* server : create checkpoints before every user msg
* chat : remove \n in gemma4 delimiters
* chat : merge msg delimiter structs into one
* cont : reword comment
* cont : initialize tokens in delimiter
* cont : add server_tokens::get_raw_tokens() for mtmd
* cont : move message finding to server_tokens and skip mtmd tokens
* cont : update cohere2moe parser
* cont : increase min-step to 8192 and always produce a chkpt for last user message
* server: log prompts to directory
Add `--log-prompts-dir` to write each prompt to a separate text file in
the specified directory.
* Apply suggestion from @ngxson
---------
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
* common : fix state save in common_prompt_batch_decode
This commit addresses a bug in common_prompt_batch_decode that affects
the session state store/restore in completion.cpp and
save-load-state.cpp.
The motivation for this is that currently the code is saving n-1 tokens
in both the session_tokens and in the KV cache. Then when loading the
session tokens, and if the prompt matches, it would replay the last
saved token (n-1) into the next position, effectively replaying the
same token in the wrong position.
The fix is to store all n tokens in session_tokens, while the memory
state only reflects n-1 processed tokens as the saving happens before
the last token is decoded in common_prompt_batch_decode.
I ran both completion.cpp and save-load-state.cpp with a transformer, a
recurrent, and a hybrid model.
Resolves: https://github.com/ggml-org/llama.cpp/issues/23400
Co-authored-by: fairydreaming <166155368+fairydreaming@users.noreply.github.com>
* 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>
* llama: save more VRAM by reserving n_outputs == n_seqs when possible
* add n_outputs_per_seq
* move n_outputs_max to server-context
* change ubatch to batch everywhere
* 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>
* Move to backend sampling for MTP draft path
Run top_k(10) on the draft backend. D2H transfers happen only for the top 10 logits
Make backend sampling more robust and fallback to CPU on failure cases, such as with "-sm tensor" or when a backend doesn't support TOP_K.
* Allow sampler chains to be partially offloaded to backend
* Add --spec-draft-backend-sampling argument. Enabled by default.
* save-load-state : refactor into separate phase functions
- Split monolithic main() into 4 self-contained phase functions, each
managing its own context/sampler/batch lifecycle
- Each function tokenizes internally using its local ctx instance
- main() is now a clean orchestrator: init -> run phases -> assert results
- Proper resource cleanup on every exit path (return {} on error)
Assisted-by: llama.cpp:local pi
* save-load-state : use params.out_file instead of separate state_file
- Remove state_file parameter from all phase functions
- Each function accesses params.out_file directly
- Initialize params.out_file in main alongside params.prompt
Assisted-by: llama.cpp:local pi
* save-load-state : use smart pointers for ctx and smpl
- Replace raw llama_context* with llama_context_ptr
- Replace raw llama_sampler* with llama_sampler_ptr
- Remove all manual llama_free() and llama_sampler_free() calls
- Keep llama_batch as raw (managed manually with llama_batch_free)
Assisted-by: llama.cpp:local pi
* save-load-state : add local llama_batch_ptr RAII wrapper
- Add llama_batch_ptr struct holding llama_batch by value
- Calls llama_batch_free() in destructor
- Eliminates all manual llama_batch_free() calls
Assisted-by: llama.cpp:local pi
* save-load-state : replace printf/fprintf with logging macros
- Add log.h include
- Replace fprintf(stderr, ...) errors with LOG_ERR
- Replace fprintf(stderr, ...) info with LOG_TRC
- Replace printf output with LOG
Assisted-by: llama.cpp:local pi
* save-load-state : refactor tests to check results inline
Each follow-up phase now accepts an expected result and performs
the comparison internally instead of collecting results in main().
Assisted-by: llama.cpp:local pi
* save-load-state : improve test output readability
Add phase labels, remove redundant run prefixes, and show
PASS after each test.
Assisted-by: llama.cpp:local pi
* pi : add rule about git signing
* save-load-state : simplify llama_batch_ptr
Change get() to return a reference and remove operator*().
Use batch.get() throughout for consistency.
Assisted-by: llama.cpp:local pi
* save-load-state : extract generate_tokens helper
Factor out the repeated token generation loop into a shared
helper function used by all phases.
Assisted-by: llama.cpp:local pi
* save-load-state : update comments to use test terminology
Replace "Phase" with "Test" and list each test's steps
as bullet points.
Assisted-by: llama.cpp:local pi
* save-load-state : rename test functions
Rename to test_baseline, test_state_load, test_seq_cp_host,
test_seq_cp_device. Update comments and logs accordingly.
Assisted-by: llama.cpp:local pi
* pi : add rule to never git push without confirmation
Assisted-by: llama.cpp:local pi
* common : add model_only option to common_init_from_params
Add bool model_only parameter to skip context creation,
sampler init, and context-dependent setup.
Use in save-load-state to initialize only the model,
with each test creating its own context.
Assisted-by: llama.cpp:local pi
---------
Co-authored-by: ggerganov <ggerganov@users.noreply.github.com>
Concedo
Xuan-Son Nguyen
Adrien Gallouët
Aldehir Rojas
zhangrunda
Ruixiang Wang
Georgi Gerganov
jacekpoplawski
Daniel Bevenius
Pascal
Aman Gupta
Gaurav Garg