* server: fix query params lost when proxying requests in multi-model router mode
* server: re-encode query params using httplib::encode_query_component in proxy
* llama : remove write/read of output ids/logits/embeddings
This commit removes the write/read of output ids, logits and
embeddings from the llama context state.
Refs: https://github.com/ggml-org/llama.cpp/pull/18862#issuecomment-3756330941
* completion : add replying of session state
This commit updates the session handing in the completion tool to handle
the that logits are no longer stored in the session file. Instead, we
need to replay the last token to get the logits for sampling.
* common : add common_prompt_batch_decode function
This commit adds a new function which is responsible for decoding prompt
and optionally handle the saving for session data.
* update save-state.cpp to use llama_state_load_file
This commit updates the save-load-state example to utilize the new
llama_state_load_file function for loading the model state from a file.
And it also replays the last token after loading since this state is now
stored before the last token is processed.
* examples : set n_seq_max = 2 for ctx3
This commit updates the save-load-state example to set the n_seq_max
parameter to 2 when initializing the ctx3 context.
The motivation for this change is that using 1 as n_parallel/n_seq_max
the context only supports one sequence, but the test laster tries to
use a second sequence which results in the following error:
```console
main : loaded state with 4 tokens
main : seq 0 copied, 225760 bytes
main : kv cache cleared
find_slot: seq_id=1 >= n_seq_max=1 Try using a bigger --parallel value
state_read_meta: failed to find available cells in kv cache
```
This seems to only happen for recurrent/hybrid models.
* mtmd : chat : Fix extra \n between text and media marker
Thanks to @tugot17 for detecting and reporting the issue.
For vision models (e.g. LFM2.5-VL-1.6B and Qwen/Qwen3-VL-4B-Instruct) `llama-mtmd-cli` produces identical output to HF implementation.
However `llama-server` doesn't. I traced it down to extra newline
inserted after `<__media__>`.
This happens in `to_json_oaicompat`, that treats media markers as text
and joins all parts with `\n` separator.
PR introduces new type `media_marker` and uses it for media markers.
Extra logic is added to prevent insertion of newlines before and after
media markers.
With this change number of input tokens is identical to HF
implementation and as a result the output is also identical.
I explored other ways to address the issue
* remove completely `\n` between text parts in `to_json_oaicompat`
* merge text messages in server-common.cpp before sending them to `to_json_oaicompat`
Please propose alternative ways of fixing this issue.
* Refactor to use explicite per type ifs
* Update common/chat.cpp
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
* Update common_chat_templates_apply_legacy
---------
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
* save generated text for the /slots endpoint
* update debug_generated_text only when LLAMA_SERVER_SLOTS_DEBUG > 0
* Apply suggestions from code review
---------
Co-authored-by: Matteo <matteo@matteo>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
This option was introduced as a workaround because cpp-httplib could not
build on visionOS. Since it has been fixed and now compiles on all platforms,
we can remove it and simplify many things.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* feat: Enable adding System Prompt per-chat
* fix: Save draft message in Chat Form when adding System Prompt from new chat view
* fix: Proper system message deletion logic
* chore: Formatting
* chore: update webui build output
* Move dequant_model to after the text_config merge
Add new kimi-k2.5 keys to mtmd convert
Update V_MMPROJ tensor mapping for new mm_projector.proj keys
Update V_M_IMP_NORM for new mm_projector.pre_norm key
* Fix a couple of oversights
* Add image support for Kimi-K2.5
* Revert changes to KimiVLForConditionalGeneration
* Fix an assert crash
* Fix permute swapping w / h on accident
* Kimi-K2.5: Use merged QKV for vision
* Kimi-K2.5: pre-convert vision QK to use build_rope_2d
* Kimi-K2.5: support non-interleaved rope for vision
* Kimi-K2.5: fix min / max pixel
* Kimi-K2.5: remove v/o permutes, unnecessary
* Kimi-K2.5: update permute name to match
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Kimi-K2.5: replace build_rope_2d ggml_cont with ggml_view_3d pointers
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* support qwen3.5 series
* remove deepstack for now, and some code clean
* code clean
* add FULL_ATTENTION_INTERVAL metadata
* code clean
* reorder v heads for linear attention to avoid expensive interleaved repeat
* completion : simplify batch (embd) processing
This commit simplifies the processing of embd by removing the for loop
that currently exists which uses params.n_batch as its increment. This
commit also removes the clamping of n_eval as the size of embd is always
at most the size of params.n_batch.
The motivation is to clarify the code as it is currently a little
confusing when looking at this for loop in isolation and thinking that
it can process multiple batches.
* add an assert to verify n_eval is not greater than n_batch
Experimenting with AI, my environment gets messy fast and it's not
always easy to know what model my software is trying to load. This helps
with troubleshooting.
before:
Error: {
code = 400,
message = "model not found",
type = "invalid_request_error"
}
After:
Error: {
code = 400,
message = "model 'toto' not found",
type = "invalid_request_error"
}
* add option --tensor-type-file to llama-quantize, but it raises an error.
* add error message when file not found
* quantize: update help menu, fix CI
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
---------
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Aaron Teo <aaron.teo1@ibm.com>
Pascal
Radoslav Gerganov
Aleksander Grygier
Daniel Bevenius
Sigbjørn Skjæret
Kilian Krampf
Aldehir Rojas
crsawyer
ddh0
megemini
Saba Fallah
Tarek Dakhran
matteo
Xuan-Son Nguyen
Adrien Gallouët
AesSedai
Anav Prasad
iMil
RichardScottOZ
Georgi Gerganov
JJJYmmm
손희준
Sascha Rogmann
ddh0
Matthieu Coudron
Christian Kastner
EugeoSynthesisThirtyTwo
tc-mb