* extract & return thoughts in reasoning_content field (unless --reasoning-format) for DeepSeek R1 & Command R7B
* tool-calls: add deepseek r1 template (models/templates/llama-cpp-deepseek-r1.jinja) + hackommodate broken official template
* tool-calls: accommodate variety of wrong tool call opening tags both R1 Qwen 32B and 7B distills like to spit out
* server/oai: ensure content is null when there are tool calls, and reasoning_content appears before content for readability
* tool-calls: add DeepSeek R1 Qwen distills to server/README.md & server tests
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
The C API in llama.h claims users can implement `llama_sampler_i` to
create custom `llama_sampler`. The sampler chain takes ownership and
calls `llama_sampler_free` on them. However, `llama_sampler_free` is
hard-coded to use `delete`. This is undefined behavior if the object
wasn't also allocated via `new` from libllama's C++ runtime. Callers
in C and C-compatible languages do not use C++'s `new` operator. C++
callers may not be sharing the same heap as libllama.
* common : add default embeddings presets
This commit adds default embeddings presets for the following models:
- bge-small-en-v1.5
- e5-small-v2
- gte-small
These can be used with llama-embedding and llama-server.
For example, with llama-embedding:
```console
./build/bin/llama-embedding --embd-gte-small-default -p "Hello, how are you?"
```
And with llama-server:
```console
./build/bin/llama-server --embd-gte-small-default
```
And the embeddings endpoint can then be called with a POST request:
```console
curl --request POST \
--url http://localhost:8080/embeddings \
--header "Content-Type: application/json" \
--data '{"input": "Hello, how are you?"}'
```
I'm not sure if these are the most common embedding models but hopefully
this can be a good starting point for discussion and further
improvements.
Refs: https://github.com/ggerganov/llama.cpp/issues/10932
List devices in the same order as they appear when evaluating the model
and splitting tensors across devices, i.e. RPC devices come first in the
list.
ref #11435
* initial porting of previous LLG patch
* update for new APIs
* build: integrate llguidance as an external project
* use '%llguidance' as marker to enable llg lark syntax
* add some docs
* clarify docs
* code style fixes
* remove llguidance.h from .gitignore
* fix tests when llg is enabled
* pass vocab not model to llama_sampler_init_llg()
* copy test-grammar-integration.cpp to test-llguidance.cpp
* clang fmt
* fix ref-count bug
* build and run test
* gbnf -> lark syntax
* conditionally include llguidance test based on LLAMA_LLGUIDANCE flag
* rename llguidance test file to test-grammar-llguidance.cpp
* add gh action for llg test
* align tests with LLG grammar syntax and JSON Schema spec
* llama_tokenizer() in fact requires valid utf8
* update llg
* format file
* add $LLGUIDANCE_LOG_LEVEL support
* fix whitespace
* fix warning
* include <cmath> for INFINITY
* add final newline
* fail llama_sampler_init_llg() at runtime
* Link gbnf_to_lark.py script; fix links; refer to llg docs for lexemes
* simplify #includes
* improve doc string for LLAMA_LLGUIDANCE
* typo in merge
* bump llguidance to 0.6.12
* An empty tool_call_id is better than none!
* sync: minja (tool call name optional https://github.com/google/minja/pull/36)
* Force-disable parallel_tool_calls if template doesn't support it
* More debug logs
* Llama 3.x tools: accept / trigger on more varied spaced outputs
* Fix empty content for functionary v3.2 tool call
* Add proper tool call docs to server README
* readme: function calling *is* supported now
* Apply suggestions from code review
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
The va_copy man page states that va_end must be called to revert
whatever the copy did. For some implementaions, not calling va_end
has no consequences. For others it could leak memory.
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
This commit enables the `--no-warmup` option for the llama-embeddings.
The motivation for this change is to allow the user to disable the
warmup when running the the program.
* Added the ability to use guide tokens for OuteTTS, greatly improving TTS recitation accuracy over long input sequences.
* applied linting suggestions, updated to latest llama_vocab changes, added a safety check, added newline to guide token start
* cli : auto activate conversation mode if chat template is detected
* add warn on bad template
* update readme (writing with the help of chatgpt)
* update readme (2)
* do not activate -cnv for non-instruct models
* common : support tag-based hf_repo like on ollama
* fix build
* various fixes
* small fixes
* fix style
* fix windows build?
* move common_get_hf_file to common.cpp
* fix complain with noreturn
* GGUF: C++ refactor, backend support, misc fixes
remove ggml_tensor.backend
update CODEOWNERS [no ci]
remove gguf_get_data from API
revise GGUF API data types
In common/common.cpp:
* Convert usage of stat() function call to check if file exists to standard library function std::filesystem::exists (error unable to match to correct function signature)
* Additional conditions to check if PATH_MAX is already defined in WIN32 environment (warning it is already defined in MSYS2)
In examples/run/run.cpp:
* Add io.h header inclusion (error cannot find function _get_osfhandle)
* Change initialisers for OVERLAPPED to empty struct (warning about uninitialised members)
* Add initialiser for hFile (warning it may be uninitialised)
* Add cast for curl_off_t percentage value to long int in generate_progress_prefix function (warning that curl_off_t is long long int)
In ggml/src/ggml-opencl/ggml-opencl.cpp:
* Initialise certain declared cl_mem variables to nullptr for greater safety (warning about B_d variable possibly used unassigned)
* server : add "tokens" output
ggml-ci
* server : output embeddings for all tokens when pooling = none
ggml-ci
* server : update readme [no ci]
* server : fix spacing [no ci]
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* server : be explicit about the pooling type in the tests
ggml-ci
* server : update /embeddings and /v1/embeddings endpoints
ggml-ci
* server : do not normalize embeddings when there is no pooling
ggml-ci
* server : update readme
ggml-ci
* server : fixes
* tests : update server tests
ggml-ci
* server : update readme [no ci]
* server : remove rebase artifact
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* sampling : refactor + optimize penalties sampler
ggml-ci
* common : apply ignore_eos as logit bias
ggml-ci
* batched : remove penalties sampler
* params : allow penalty_last_n == -1 to be equal to context size
ggml-ci
* common : by default, move the penalties at the end of the sampling chain
ggml-ci
* common : ignore all EOG tokens
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* common : move back the penalties at the front of the sampling chain
ggml-ci
* readme : restore hint about --ignore-eos flag [no ci]
* llama : minor
ggml-ci
* webui : update
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
