* 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>
* server: support Vertex AI compatible API
* a bit safer
* support other AIP_* env var
* various fixes
* if AIP_MODE is unset, do nothing
* fix test case
* fix windows build
Previously, unknown tool names passed via --tools were silently ignored.
Now the server validates each tool name at startup and exits with an
error if an unrecognized tool is specified, listing the available tools.
Assisted-by: llama.cpp:local pi
This PR changes the logging that occurs at startup of llama-server.
Currently, it is redundant (including CPU information twice) and it is
missing the build + commit info.
The build info is now only for debug, so we avoid the duplicate
with `--version`.
The UTF-8 setup at the beginning is needed to avoid logging
garbage on Windows.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Set C locale for consistent float formatting across all binaries.
* Add C locale setting to all tools binaries
Add std::setlocale(LC_NUMERIC, "C") to all 16 binaries in the tools/
directory to ensure consistent floating-point formatting.
* Apply suggestion from @JohannesGaessler
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* 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
* 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 <>
* server: prevent data race from HTTP threads
* fix params
* fix default_generation_settings
* nits: make handle_completions_impl looks less strange
* stricter const
* fix GGML_ASSERT(idx < states.size())
* move index to be managed by server_response_reader
* http: make sure req & res lifecycle are tied together
* fix compile
* fix index handling buggy
* fix data race for lora endpoint
* nits: fix shadow variable
* nits: revert redundant changes
* nits: correct naming for json_webui_settings
* 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
* server/webui: add server-side WebUI config support
Add CLI arguments --webui-config (inline JSON) and --webui-config-file
(file path) to configure WebUI default settings from server side.
Backend changes:
- Parse JSON once in server_context::load_model() for performance
- Cache parsed config in webui_settings member (zero overhead on /props)
- Add proper error handling in router mode with try/catch
- Expose webui_settings in /props endpoint for both router and child modes
Frontend changes:
- Add 14 configurable WebUI settings via parameter sync
- Add tests for webui settings extraction
- Fix subpath support with base path in API calls
Addresses feedback from @ngxson and @ggerganov
* server: address review feedback from ngxson
* server: regenerate README with llama-gen-docs
* server: fix crash when batch > ubatch with embeddings (#12836)
Fixes#12836 where the server crashes with GGML_ASSERT failure when
running with embeddings enabled and n_batch > n_ubatch.
Root cause: Embeddings use non-causal attention which requires all
tokens to be processed within a single ubatch. When n_batch > n_ubatch,
the server attempts to split processing, causing assertion failure.
Solution:
- Add parameter validation in main() after common_params_parse()
- When embeddings enabled and n_batch > n_ubatch:
* Log warnings explaining the issue
* Automatically set n_batch = n_ubatch
* Prevent server crash
This follows the approach suggested by @ggerganov in issue #12836.
Note: This supersedes stalled PR #12940 which attempted a runtime fix
in the old examples/server/server.cpp location. This implementation
validates at startup in tools/server/server.cpp (current location).
Testing:
- Build: Compiles successfully
- Validation triggers: Warns when -b > -ub with --embedding
- Auto-correction works: Adjusts n_batch = n_ubatch
- No false positives: Valid params don't trigger warnings
- Verified on macOS M3 Pro with embedding model
* Update tools/server/server.cpp
---------
Co-authored-by: ytian218 <ytian218@bloomberg.net>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* git mv
* add server-context.h
* add server-context.h
* clean up headers
* cont : cleanup
* also expose server_response_reader (to be used by CLI)
* fix windows build
* decouple server_routes and server_http
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server : add Anthropic Messages API support
* remove -@pytest.mark.slow from tool calling/jinja tests
* server : remove unused code and slow/skip on test_anthropic_vision_base64_with_multimodal_model in test_anthropic_api.py
* server : removed redundant n field logic in anthropic_params_from_json
* server : use single error object instead of error_array in streaming response handler for /v1/chat/completions and use unordered_set instead of set in to_json_anthropic_stream()
* server : refactor Anthropic API to use OAI conversion
* make sure basic test always go first
* clean up
* clean up api key check, add test
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server: split HTTP into its own interface
* move server-http and httplib to its own file
* add the remaining endpoints
* fix exception/error handling
* renaming
* missing header
* fix missing windows header
* fix error responses from http layer
* fix slot save/restore handler
* fix case where only one stream chunk is returned
* add NOMINMAX
* do not call sink.write on empty data
* use safe_json_to_str for SSE
* clean up
* add some comments
* improve usage of next()
* bring back the "server is listening on" message
* more generic handler
* add req.headers
* move the chat template print to init()
* add req.path
* cont : minor
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* fix: correct time_ms calculation in send_partial_response
The time_ms field was incorrectly calculated. The division was happening
before the subtraction leading to incorrect values.
Before: (ggml_time_us() - slot.t_start_process_prompt / 1000) After:
(ggml_time_us() - slot.t_start_process_prompt) / 1000
* docs : document time_ms field in prompt_progress
Xuan-Son Nguyen