* Rudimentary support of openai chat completions tools calls
-Most small models are not smart enough to do this, especially a combined tool call + role play response, but at least this allows experimentation along these lines with koboldcpp
* try to also support specified function and tool choice set to none
Allow tools start and end messages to be configured in adapter
Try to force grammar to specific function call if specified (untested)
* ensure tools get listed right after user content and before end of user message content
* omit grammars approach try prompting instead
-use more extensive json parsing and direct instructions to models to try to obtain the desired result
-seems to work relatively well with Mistral-7B-Instruct-v.0.3.Q4_K_M.gguf and neuralhermes-2.5-mistral-7b.Q4_K_M.gguf
-question of whether this is too opinionated of an approach, should the instructions be things that can be passed with the prompt template?
* add back llamacpp recommended json grammar
Go back to adding grammar but use "official" llamacpp grammar only not a custom one just for openai
* Tidy up, remove unnecessary globals
* clarity
* fix missing local variable error
This worked to fix the error I mentioned on my last comment
---------
Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>
* Add the DRY dynamic N-gram anti-repetition sampler
The DRY (Do not Repeat Yourself) sampler is a dynamic N-gram
repetition penalty that negatively scores tokens that would extend
sequences that already appear in the context.
See this discussion for a motivation and explanation of the sampler:
https://github.com/oobabooga/text-generation-webui/pull/5677
This implementation of DRY mostly aligns with the obabooga version
with a few modifications. It uses a more efficient linear scanning
algorithm to identify repetitions. It also supports multi-token
sequence breakers. As a limitation, this implementation reuses
the rep pen range parameter, rather than introducing a new range
just for the DRY sampler.
There is a separate change to lite.koboldai.net that exposes the DRY
sampler parameters to KoboldAI Lite, so none of the embed files have
been changed as part of this commit.
* Update default DRY parameters to match lite
* Improve DRY token debug logging
* Replace `and` with `&&` to fix MSVC compile error
Little known fact: The C++98 standard defines `and` as an
alternative token for the `&&` operator (along with a bunch
of other digraphs). MSVC does not allow these without using
the /Za option or including the <iso646.h> header. Change to
the more standard operator to make this code more portable.
* Fix MSVC compile error because log is not constexpr
Replace the compile-time computation with a floating-point
approximation of log(std::numeric_limits<float>::max()).
* Remove unused llama sampler variables and clean up sequence breakers.
* Remove KCPP_SAMPLER_DRY as a separate enum entry
The DRY sampler is effectively a repetition penalty and there
are very few reasons to apply it at a different place in sampler
order than the standard single-token penalty. There are also
multiple projects that have dependencies on the existing sampler
IDs, including KoboldAI, KoboldAI Lite, and Silly Tavern. In order
to minimize the impact of the dependencies of adding the DRY sampler
to koboldcpp, it makes the most sense to not add a new ID for now,
and instead to piggyback on KCPP_SAMPLER_REP_PEN. In the future
if we find a use case for splitting the application of rep pen and DRY
we can introduce a new enum entry then.
* Add the dry_penalty_last_n to independently control DRY penalty range
This parameter follows the oobabooga semantics: it's optional, with a
default value of zero. Zero means that DRY should sample the entire
context. Otherwise, it's the number of tokens from the end of the
context that are scanned for repetitions.
* Limit sequence breaker lengths in tokens and characters
The core DRY sampler algorithm is linear in the context length, but
there are several parts of the sampler related to multi-token
sequence breakers that are potentially quadratic. Without any
restrictions, a suitably crafted context and sequence breaker could
result in a denial-of-service attack on a server running koboldcpp.
This change limits the maximum number of characters and the maximum
token length of a sequence breaker in order to limit the maximum
overhead associated with the sampler.
This change also improves some comments, adding more detail and
changing the wording to increase clarity.
* Modify the deprecation-warning 'main' binary to build every time, instead of only when a legacy binary is present. This is to help users of tutorials and other instruction sets from knowing what to do when the 'main' binary is missing and they are trying to follow instructions.
* Adjusting 'server' name-deprecation binary to build all the time, similar to the 'main' legacy name binary.
* Arm AArch64: optimized GEMV and GEMM kernels for q4_0_q8_0, and q8_0_q8_0 quantization
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add copyright claim only to ggml-aarch64.cpp and ggml-aarch64.h files
* Arm AArch64: minor code refactoring for rebase
* Arm AArch64: minor code refactoring for resolving a build issue with cmake
* Arm AArch64: minor code refactoring to split the Q4_0_AARC64 type into three separate types: Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8
* Arm AArch64: minor code change for resolving a build issue with server-windows
* retrigger checks
* Arm AArch64: minor code changes for rebase
* Arm AArch64: minor changes to skip the pr#7433 vec_dot code for arm cpus with SVE VL not equal to 256 bits
* Arm AArch64: remove stale LLAMA_QKK_64 from CMakeLists.txt and delete build.zig
* Arm AArch64: add reference scalar gemm and gemv, and avoid dynamic memory allocations during quantization for Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8
* Arm AArch64: add multithreaded quantization support for the new types: Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8
* Arm AArch64: minor code refactoring
* Arm AArch64: simplify logic for calling gemm and gemv functions in ggml_compute_forward_mul_mat
* Arm AArch64: minimize changes in ggml_compute_forward_mul_mat
* Arm AArch64: minor code refactoring, and add reference scalar code to quantize routines for new quant types
* Arm AArch64: minor code refactoring
* Arm AArch64: minor code refactoring
* Arm AArch64: minor code refactoring
* rebase on the latest master commit 3fd62a6 and adapt to the new directory structure
* Arm AArch64: remove a redundant comment
* Arm AArch64: add pragma in ggml-aarch64.c to turn -Woverlength-strings warning off
* Arm AArch64: use __aarch64__ check to guard 64-bit neon kernels
* Arm AArch64: update docs/build.md README to include compile time flags for buiilding the Q4_0_4_4 quant type
* Adding a simple program to provide a deprecation warning that can exist to help people notice the binary name change from #7809 and migrate to the new filenames.
* Build legacy replacement binaries only if they already exist. Check for their existence every time so that they are not ignored.
* conv transpose 1d passing test for 1d input and kernel
* working for different input and output channel counts, added test for variable stride
* initial draft appears to work with stride other than 1
* working with all old and new conv1d tests
* added a test for large tensors
* removed use cuda hardcoding
* restored test-conv-transpose.c
* removed unused arugments, and fixed bug where test failure would cause subsequent tests to fail
* fixed accumulator bug
* added test to test-backend-ops
* fixed mistake
* addressed review
* fixed includes
* removed blank lines
* style and warning fixes
* return failure when test fails
* fix supports_op
---------
Co-authored-by: slaren <slarengh@gmail.com>
`emplace_back` repeatedly-called is slower than preallocating the vector to the vocab size and directly inserting the data. Some rudimentary profiling with `chrono` improves the performance of this block of code from ~500us/op to ~40us/op.
Overall, this slightly improves the sampling performance which has a more substantial impact for the `examples/lookahead` implementation -- I am able to see a ~10% performance boost in lookahead inference.
* py : type-check all Python scripts with Pyright
* server-tests : use trailing slash in openai base_url
* server-tests : add more type annotations
* server-tests : strip "chat" from base_url in oai_chat_completions
* server-tests : model metadata is a dict
* ci : disable pip cache in type-check workflow
The cache is not shared between branches, and it's 250MB in size,
so it would become quite a big part of the 10GB cache limit of the repo.
* py : fix new type errors from master branch
* tests : fix test-tokenizer-random.py
Apparently, gcc applies optimisations even when pre-processing,
which confuses pycparser.
* ci : only show warnings and errors in python type-check
The "information" level otherwise has entries
from 'examples/pydantic_models_to_grammar.py',
which could be confusing for someone trying to figure out what failed,
considering that these messages can safely be ignored
even though they look like errors.
