This commit is contained in:
baalajimaestro 2023-09-11 09:49:41 +05:30
commit 97c5ef3242
Signed by: baalajimaestro
GPG key ID: F93C394FE9BBAFD5
5 changed files with 249 additions and 414 deletions

View file

@ -506,7 +506,7 @@ _lib.llama_mlock_supported.argtypes = []
_lib.llama_mlock_supported.restype = c_bool
# LLAMA_API int llama_n_vocab(const struct llama_context * ctx);
# LLAMA_API int llama_n_vocab (const struct llama_context * ctx);
def llama_n_vocab(ctx: llama_context_p) -> int:
return _lib.llama_n_vocab(ctx)
@ -515,7 +515,7 @@ _lib.llama_n_vocab.argtypes = [llama_context_p]
_lib.llama_n_vocab.restype = c_int
# LLAMA_API int llama_n_ctx (const struct llama_context * ctx);
# LLAMA_API int llama_n_ctx (const struct llama_context * ctx);
def llama_n_ctx(ctx: llama_context_p) -> int:
return _lib.llama_n_ctx(ctx)
@ -524,7 +524,16 @@ _lib.llama_n_ctx.argtypes = [llama_context_p]
_lib.llama_n_ctx.restype = c_int
# LLAMA_API int llama_n_embd (const struct llama_context * ctx);
# LLAMA_API int llama_n_ctx_train(const struct llama_context * ctx);
def llama_n_ctx_train(ctx: llama_context_p) -> int:
return _lib.llama_n_ctx_train(ctx)
_lib.llama_n_ctx_train.argtypes = [llama_context_p]
_lib.llama_n_ctx_train.restype = c_int
# LLAMA_API int llama_n_embd (const struct llama_context * ctx);
def llama_n_embd(ctx: llama_context_p) -> int:
return _lib.llama_n_embd(ctx)
@ -542,7 +551,7 @@ _lib.llama_vocab_type.argtypes = [llama_context_p]
_lib.llama_vocab_type.restype = c_int
# LLAMA_API int llama_model_n_vocab(const struct llama_model * model);
# LLAMA_API int llama_model_n_vocab (const struct llama_model * model);
def llama_model_n_vocab(model: llama_model_p) -> int:
return _lib.llama_model_n_vocab(model)
@ -551,7 +560,7 @@ _lib.llama_model_n_vocab.argtypes = [llama_model_p]
_lib.llama_model_n_vocab.restype = c_int
# LLAMA_API int llama_model_n_ctx (const struct llama_model * model);
# LLAMA_API int llama_model_n_ctx (const struct llama_model * model);
def llama_model_n_ctx(model: llama_model_p) -> int:
return _lib.llama_model_n_ctx(model)
@ -560,7 +569,16 @@ _lib.llama_model_n_ctx.argtypes = [llama_model_p]
_lib.llama_model_n_ctx.restype = c_int
# LLAMA_API int llama_model_n_embd (const struct llama_model * model);
# LLAMA_API int llama_model_n_ctx_train(const struct llama_model * model);
def llama_model_n_ctx_train(model: llama_model_p) -> int:
return _lib.llama_model_n_ctx_train(model)
_lib.llama_model_n_ctx_train.argtypes = [llama_model_p]
_lib.llama_model_n_ctx_train.restype = c_int
# LLAMA_API int llama_model_n_embd (const struct llama_model * model);
def llama_model_n_embd(model: llama_model_p) -> int:
return _lib.llama_model_n_embd(model)
@ -1046,74 +1064,14 @@ def llama_grammar_free(grammar: llama_grammar_p):
_lib.llama_grammar_free.argtypes = [llama_grammar_p]
_lib.llama_grammar_free.restype = None
# //
# // Beam search
# //
# LLAMA_API struct llama_grammar * llama_grammar_copy(const struct llama_grammar * grammar);
def llama_grammar_copy(grammar: llama_grammar_p) -> llama_grammar_p:
return _lib.llama_grammar_copy(grammar)
# struct llama_beam_view {
# const llama_token * tokens;
# size_t n_tokens;
# float p; // Cumulative beam probability (renormalized relative to all beams)
# bool eob; // Callback should set this to true when a beam is at end-of-beam.
# };
class llama_beam_view(ctypes.Structure):
_fields_ = [
("tokens", llama_token_p),
("n_tokens", c_size_t),
("p", c_float),
("eob", c_bool),
]
# // Passed to beam_search_callback function.
# // Whenever 0 < common_prefix_length, this number of tokens should be copied from any of the beams
# // (e.g. beams[0]) as they will be removed (shifted) from all beams in all subsequent callbacks.
# // These pointers are valid only during the synchronous callback, so should not be saved.
# struct llama_beams_state {
# struct llama_beam_view * beam_views;
# size_t n_beams; // Number of elements in beam_views[].
# size_t common_prefix_length; // Current max length of prefix tokens shared by all beams.
# bool last_call; // True iff this is the last callback invocation.
# };
class llama_beams_state(ctypes.Structure):
_fields_ = [
("beam_views", POINTER(llama_beam_view)),
("n_beams", c_size_t),
("common_prefix_length", c_size_t),
("last_call", c_bool),
]
# // Type of pointer to the beam_search_callback function.
# // void* callback_data is any custom data passed to llama_beam_search, that is subsequently
# // passed back to beam_search_callback. This avoids having to use global variables in the callback.
# typedef void (*llama_beam_search_callback_fn_t)(void * callback_data, struct llama_beams_state);
llama_beam_search_callback_fn_t = ctypes.CFUNCTYPE(None, c_void_p, llama_beams_state)
# /// @details Deterministically returns entire sentence constructed by a beam search.
# /// @param ctx Pointer to the llama_context.
# /// @param callback Invoked for each iteration of the beam_search loop, passing in beams_state.
# /// @param callback_data A pointer that is simply passed back to callback.
# /// @param n_beams Number of beams to use.
# /// @param n_past Number of tokens already evaluated.
# /// @param n_predict Maximum number of tokens to predict. EOS may occur earlier.
# /// @param n_threads Number of threads as passed to llama_eval().
# LLAMA_API void llama_beam_search(struct llama_context * ctx, llama_beam_search_callback_fn_t callback, void * callback_data, size_t n_beams, int n_past, int n_predict, int n_threads);
def llama_beam_search(
ctx: llama_context_p,
callback: "ctypes._CFuncPtr[None, c_void_p, llama_beams_state]", # type: ignore
callback_data: c_void_p,
n_beams: c_size_t,
n_past: c_int,
n_predict: c_int,
n_threads: c_int,
):
return _lib.llama_beam_search(
ctx, callback, callback_data, n_beams, n_past, n_predict, n_threads
)
_lib.llama_grammar_copy.argtypes = [llama_grammar_p]
_lib.llama_grammar_copy.restype = llama_grammar_p
# //
# // Sampling functions
@ -1436,6 +1394,74 @@ _lib.llama_grammar_accept_token.argtypes = [
llama_token,
]
_lib.llama_grammar_accept_token.restype = None
# //
# // Beam search
# //
# struct llama_beam_view {
# const llama_token * tokens;
# size_t n_tokens;
# float p; // Cumulative beam probability (renormalized relative to all beams)
# bool eob; // Callback should set this to true when a beam is at end-of-beam.
# };
class llama_beam_view(ctypes.Structure):
_fields_ = [
("tokens", llama_token_p),
("n_tokens", c_size_t),
("p", c_float),
("eob", c_bool),
]
# // Passed to beam_search_callback function.
# // Whenever 0 < common_prefix_length, this number of tokens should be copied from any of the beams
# // (e.g. beams[0]) as they will be removed (shifted) from all beams in all subsequent callbacks.
# // These pointers are valid only during the synchronous callback, so should not be saved.
# struct llama_beams_state {
# struct llama_beam_view * beam_views;
# size_t n_beams; // Number of elements in beam_views[].
# size_t common_prefix_length; // Current max length of prefix tokens shared by all beams.
# bool last_call; // True iff this is the last callback invocation.
# };
class llama_beams_state(ctypes.Structure):
_fields_ = [
("beam_views", POINTER(llama_beam_view)),
("n_beams", c_size_t),
("common_prefix_length", c_size_t),
("last_call", c_bool),
]
# // Type of pointer to the beam_search_callback function.
# // void* callback_data is any custom data passed to llama_beam_search, that is subsequently
# // passed back to beam_search_callback. This avoids having to use global variables in the callback.
# typedef void (*llama_beam_search_callback_fn_t)(void * callback_data, struct llama_beams_state);
llama_beam_search_callback_fn_t = ctypes.CFUNCTYPE(None, c_void_p, llama_beams_state)
# /// @details Deterministically returns entire sentence constructed by a beam search.
# /// @param ctx Pointer to the llama_context.
# /// @param callback Invoked for each iteration of the beam_search loop, passing in beams_state.
# /// @param callback_data A pointer that is simply passed back to callback.
# /// @param n_beams Number of beams to use.
# /// @param n_past Number of tokens already evaluated.
# /// @param n_predict Maximum number of tokens to predict. EOS may occur earlier.
# /// @param n_threads Number of threads as passed to llama_eval().
# LLAMA_API void llama_beam_search(struct llama_context * ctx, llama_beam_search_callback_fn_t callback, void * callback_data, size_t n_beams, int n_past, int n_predict, int n_threads);
def llama_beam_search(
ctx: llama_context_p,
callback: "ctypes._CFuncPtr[None, c_void_p, llama_beams_state]", # type: ignore
callback_data: c_void_p,
n_beams: c_size_t,
n_past: c_int,
n_predict: c_int,
n_threads: c_int,
):
return _lib.llama_beam_search(
ctx, callback, callback_data, n_beams, n_past, n_predict, n_threads
)
# Performance information
@ -1494,6 +1520,7 @@ _lib.llama_log_set.restype = None
def llama_dump_timing_info_yaml(stream: ctypes.c_void_p, ctx: llama_context_p):
return _lib.llama_dump_timing_info_yaml(stream, ctx)
_lib.llama_dump_timing_info_yaml.argtypes = [ctypes.c_void_p, llama_context_p]
_lib.llama_dump_timing_info_yaml.restype = None

478
poetry.lock generated
View file

@ -16,23 +16,24 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
[[package]]
name = "anyio"
version = "3.6.2"
version = "3.7.1"
description = "High level compatibility layer for multiple asynchronous event loop implementations"
optional = false
python-versions = ">=3.6.2"
python-versions = ">=3.7"
files = [
{file = "anyio-3.6.2-py3-none-any.whl", hash = "sha256:fbbe32bd270d2a2ef3ed1c5d45041250284e31fc0a4df4a5a6071842051a51e3"},
{file = "anyio-3.6.2.tar.gz", hash = "sha256:25ea0d673ae30af41a0c442f81cf3b38c7e79fdc7b60335a4c14e05eb0947421"},
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
]
[package.dependencies]
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
idna = ">=2.8"
sniffio = ">=1.1"
[package.extras]
doc = ["packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
test = ["contextlib2", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "uvloop (>=0.15)"]
trio = ["trio (>=0.16,<0.22)"]
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
trio = ["trio (<0.22)"]
[[package]]
name = "babel"
@ -48,24 +49,6 @@ files = [
[package.dependencies]
pytz = {version = ">=2015.7", markers = "python_version < \"3.9\""}
[[package]]
name = "beautifulsoup4"
version = "4.12.2"
description = "Screen-scraping library"
optional = false
python-versions = ">=3.6.0"
files = [
{file = "beautifulsoup4-4.12.2-py3-none-any.whl", hash = "sha256:bd2520ca0d9d7d12694a53d44ac482d181b4ec1888909b035a3dbf40d0f57d4a"},
{file = "beautifulsoup4-4.12.2.tar.gz", hash = "sha256:492bbc69dca35d12daac71c4db1bfff0c876c00ef4a2ffacce226d4638eb72da"},
]
[package.dependencies]
soupsieve = ">1.2"
[package.extras]
html5lib = ["html5lib"]
lxml = ["lxml"]
[[package]]
name = "black"
version = "23.7.0"
@ -367,26 +350,15 @@ test = ["iso8601", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-co
test-randomorder = ["pytest-randomly"]
tox = ["tox"]
[[package]]
name = "cssselect"
version = "1.2.0"
description = "cssselect parses CSS3 Selectors and translates them to XPath 1.0"
optional = false
python-versions = ">=3.7"
files = [
{file = "cssselect-1.2.0-py2.py3-none-any.whl", hash = "sha256:da1885f0c10b60c03ed5eccbb6b68d6eff248d91976fcde348f395d54c9fd35e"},
{file = "cssselect-1.2.0.tar.gz", hash = "sha256:666b19839cfaddb9ce9d36bfe4c969132c647b92fc9088c4e23f786b30f1b3dc"},
]
[[package]]
name = "diskcache"
version = "5.6.1"
version = "5.6.3"
description = "Disk Cache -- Disk and file backed persistent cache."
optional = false
python-versions = ">=3"
files = [
{file = "diskcache-5.6.1-py3-none-any.whl", hash = "sha256:558c6a2d5d7c721bb00e40711803d6804850c9f76c426ed81ecc627fe9d2ce2d"},
{file = "diskcache-5.6.1.tar.gz", hash = "sha256:e4c978532feff5814c4cc00fe1e11e40501985946643d73220d41ee7737c72c3"},
{file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
{file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
]
[[package]]
@ -427,16 +399,17 @@ test = ["pytest (>=6)"]
[[package]]
name = "fastapi"
version = "0.103.0"
version = "0.103.1"
description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
optional = true
python-versions = ">=3.7"
files = [
{file = "fastapi-0.103.0-py3-none-any.whl", hash = "sha256:61ab72c6c281205dd0cbaccf503e829a37e0be108d965ac223779a8479243665"},
{file = "fastapi-0.103.0.tar.gz", hash = "sha256:4166732f5ddf61c33e9fa4664f73780872511e0598d4d5434b1816dc1e6d9421"},
{file = "fastapi-0.103.1-py3-none-any.whl", hash = "sha256:5e5f17e826dbd9e9b5a5145976c5cd90bcaa61f2bf9a69aca423f2bcebe44d83"},
{file = "fastapi-0.103.1.tar.gz", hash = "sha256:345844e6a82062f06a096684196aaf96c1198b25c06b72c1311b882aa2d8a35d"},
]
[package.dependencies]
anyio = ">=3.7.1,<4.0.0"
pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
starlette = ">=0.27.0,<0.28.0"
typing-extensions = ">=4.5.0"
@ -663,128 +636,22 @@ completion = ["shtab"]
docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)"]
testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
[[package]]
name = "lxml"
version = "4.9.3"
description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, != 3.4.*"
files = [
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]
[[package]]
name = "requests"
version = "2.30.0"
version = "2.31.0"
description = "Python HTTP for Humans."
optional = false
python-versions = ">=3.7"
files = [
{file = "requests-2.30.0-py3-none-any.whl", hash = "sha256:10e94cc4f3121ee6da529d358cdaeaff2f1c409cd377dbc72b825852f2f7e294"},
{file = "requests-2.30.0.tar.gz", hash = "sha256:239d7d4458afcb28a692cdd298d87542235f4ca8d36d03a15bfc128a6559a2f4"},
{file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
{file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
]
[package.dependencies]
@ -1784,17 +1603,6 @@ files = [
{file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"},
]
[[package]]
name = "soupsieve"
version = "2.4.1"
description = "A modern CSS selector implementation for Beautiful Soup."
optional = false
python-versions = ">=3.7"
files = [
{file = "soupsieve-2.4.1-py3-none-any.whl", hash = "sha256:1c1bfee6819544a3447586c889157365a27e10d88cde3ad3da0cf0ddf646feb8"},
{file = "soupsieve-2.4.1.tar.gz", hash = "sha256:89d12b2d5dfcd2c9e8c22326da9d9aa9cb3dfab0a83a024f05704076ee8d35ea"},
]
[[package]]
name = "sse-starlette"
version = "1.6.5"
@ -1992,4 +1800,4 @@ server = ["fastapi", "pydantic-settings", "sse-starlette", "uvicorn"]
[metadata]
lock-version = "2.0"
python-versions = "^3.8.1"
content-hash = "2d6f31cfa093c4f9522a66101e3ea1d4092cfcdb983260e315ba5c80c9245a32"
content-hash = "46f61f5544850ef5226db1475d3fa8627a14e23209b1465181dda0e6704409e9"

View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "llama_cpp_python"
version = "0.1.83"
version = "0.1.84"
description = "Python bindings for the llama.cpp library"
authors = ["Andrei Betlen <abetlen@gmail.com>"]
license = "MIT"
@ -16,7 +16,7 @@ include = [
python = "^3.8.1"
typing-extensions = "^4.7.1"
numpy = "^1.24.4"
diskcache = "^5.6.1"
diskcache = "^5.6.3"
uvicorn = { version = "^0.23.2", optional = true }
fastapi = { version = ">=0.100.0", optional = true }
sse-starlette = { version = ">=1.6.1", optional = true }
@ -26,9 +26,9 @@ pydantic-settings = { version = ">=2.0.1", optional = true }
black = "^23.7.0"
twine = "^4.0.2"
mkdocs = "^1.5.2"
mkdocstrings = {extras = ["python"], version = "^0.22.0"}
mkdocs-material = "^9.2.5"
pytest = "^7.4.0"
mkdocstrings = {extras = ["python"], version = "^0.23.0"}
mkdocs-material = "^9.2.8"
pytest = "^7.4.2"
httpx = "^0.24.1"
scikit-build = "0.17.6"

View file

@ -10,7 +10,7 @@ setup(
description="A Python wrapper for llama.cpp",
long_description=long_description,
long_description_content_type="text/markdown",
version="0.1.83",
version="0.1.84",
author="Andrei Betlen",
author_email="abetlen@gmail.com",
license="MIT",

2
vendor/llama.cpp vendored

@ -1 +1 @@
Subproject commit 69fdbb9abc8907dd2a9ffdd840cba92d678a660a
Subproject commit 21ac3a1503001020122db5dce6adf34b761675f5