baalajimaestro/llama.cpp
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

Compare commits

base: baalajimaestro:eebae1a368cf5e976d5da6e4ea303d0cdbef6047
Branches Tags
baalajimaestro:master
..
compare: baalajimaestro:f343259cf7d3a7fa97a8f4dbe906a0f77f858168
Branches Tags
baalajimaestro:master

No commits in common. "eebae1a368cf5e976d5da6e4ea303d0cdbef6047" and "f343259cf7d3a7fa97a8f4dbe906a0f77f858168" have entirely different histories.
eebae1a368 ... f343259cf7

11 changed files with 237 additions and 63 deletions
Show stats Expand all files Collapse all files

5
CHANGELOG.md
View file

@ -7,11 +7,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased]
## [0.2.53]
- feat: Update llama.cpp to ggerganov/llama.cpp@cb49e0f8c906e5da49e9f6d64a57742a9a241c6a
- fix: eos/bos_token set correctly for Jinja2ChatFormatter and automatic chat formatter by @CISC in #1230
## [0.2.52]
- feat: Update llama.cpp to ggerganov/llama.cpp@a33e6a0d2a66104ea9a906bdbf8a94d050189d91

2
llama_cpp/__init__.py
View file

@ -1,4 +1,4 @@
from .llama_cpp import *
from .llama import *
__version__ = "0.2.53"
__version__ = "0.2.52"

22
llama_cpp/_internals.py
View file

@ -357,6 +357,21 @@ class _LlamaContext:
penalty_present,
)
def sample_classifier_free_guidance(
self,
candidates: "_LlamaTokenDataArray",
guidance_ctx: "_LlamaContext",
scale: float,
):
assert self.ctx is not None
assert guidance_ctx.ctx is not None
llama_cpp.llama_sample_classifier_free_guidance(
self.ctx,
llama_cpp.byref(candidates.candidates),
guidance_ctx.ctx,
scale,
)
def sample_softmax(self, candidates: "_LlamaTokenDataArray"):
assert self.ctx is not None
llama_cpp.llama_sample_softmax(
@ -705,7 +720,7 @@ class _LlamaSamplingContext:
return ctx_main.model.detokenize(self.prev[-n:]).decode("utf-8")
def sample(
self, ctx_main: _LlamaContext, idx: int = 0, logits_array: Optional[npt.NDArray[np.single]] = None
self, ctx_main: _LlamaContext, ctx_cfg: Optional[_LlamaContext] = None, idx: int = 0, logits_array: Optional[npt.NDArray[np.single]] = None
):
n_vocab = ctx_main.model.n_vocab()
id: int = 0
@ -726,6 +741,11 @@ class _LlamaSamplingContext:
) # TODO: Only create this once
token_data_array.copy_logits(logits_array)
if ctx_cfg is not None:
ctx_main.sample_classifier_free_guidance(
token_data_array, ctx_cfg, self.params.cfg_scale
)
# apply penalties
if len(self.prev) > 0:
nl_token = ctx_main.model.token_nl()

4
llama_cpp/llama.py
View file

@ -408,8 +408,8 @@ class Llama:
except:
bos_token_id = self.token_bos()
eos_token = self._model.token_get_text(eos_token_id)
bos_token = self._model.token_get_text(bos_token_id)
eos_token = self.detokenize([eos_token_id]).decode("utf-8")
bos_token = self.detokenize([bos_token_id]).decode("utf-8")
if self.verbose:
print(f"Using chat template: {template}", file=sys.stderr)

178
llama_cpp/llama_cpp.py
View file

@ -111,7 +111,6 @@ if TYPE_CHECKING:
F = TypeVar("F", bound=Callable[..., Any])
def ctypes_function_for_shared_library(lib: ctypes.CDLL):
def ctypes_function(
name: str, argtypes: List[Any], restype: Any, enabled: bool = True
@ -265,7 +264,6 @@ LLAMA_TOKEN_TYPE_BYTE = 6
# LLAMA_FTYPE_MOSTLY_IQ3_M = 27, // except 1d tensors
# LLAMA_FTYPE_MOSTLY_IQ2_S = 28, // except 1d tensors
# LLAMA_FTYPE_MOSTLY_IQ2_M = 29, // except 1d tensors
# LLAMA_FTYPE_MOSTLY_IQ4_XS = 30, // except 1d tensors
# LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
# };
@ -297,7 +295,6 @@ LLAMA_FTYPE_MOSTLY_IQ3_S = 26
LLAMA_FTYPE_MOSTLY_IQ3_M = 27
LLAMA_FTYPE_MOSTLY_IQ2_S = 28
LLAMA_FTYPE_MOSTLY_IQ2_M = 29
LLAMA_FTYPE_MOSTLY_IQ4_XS = 30
LLAMA_FTYPE_GUESSED = 1024
# enum llama_rope_scaling_type {
@ -551,7 +548,6 @@ class llama_model_params(ctypes.Structure):
# float yarn_beta_fast; // YaRN low correction dim
# float yarn_beta_slow; // YaRN high correction dim
# uint32_t yarn_orig_ctx; // YaRN original context size
# float defrag_thold; // defragment the KV cache if holes/size > thold, < 0 disabled (default)
# ggml_backend_sched_eval_callback cb_eval;
# void * cb_eval_user_data;
@ -584,7 +580,6 @@ class llama_context_params(ctypes.Structure):
yarn_beta_fast (float): YaRN low correction dim
yarn_beta_slow (float): YaRN high correction dim
yarn_orig_ctx (int): YaRN original context size
defrag_thold (float): defragment the KV cache if holes/size > thold, < 0 disabled (default)
cb_eval (ggml_backend_sched_eval_callback): callback for scheduling eval
cb_eval_user_data (ctypes.ctypes.c_void_p): user data for cb_eval
type_k (int): data type for K cache
@ -610,7 +605,6 @@ class llama_context_params(ctypes.Structure):
("yarn_beta_fast", ctypes.c_float),
("yarn_beta_slow", ctypes.c_float),
("yarn_orig_ctx", ctypes.c_uint32),
("defrag_thold", ctypes.c_float),
("cb_eval", ggml_backend_sched_eval_callback),
("cb_eval_user_data", ctypes.c_void_p),
("type_k", ctypes.c_int),
@ -939,6 +933,18 @@ def llama_supports_gpu_offload() -> bool:
...
# LLAMA_API DEPRECATED(bool llama_mmap_supported (void), "use llama_supports_mmap() instead");
@ctypes_function("llama_mmap_supported", [], ctypes.c_bool)
def llama_mmap_supported() -> bool:
...
# LLAMA_API DEPRECATED(bool llama_mlock_supported(void), "use llama_supports_mlock() instead");
@ctypes_function("llama_mlock_supported", [], ctypes.c_bool)
def llama_mlock_supported() -> bool:
...
# LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx);
@ctypes_function("llama_get_model", [llama_context_p_ctypes], llama_model_p_ctypes)
def llama_get_model(ctx: llama_context_p, /) -> Optional[llama_model_p]:
@ -1147,6 +1153,47 @@ def llama_model_quantize(
...
# // Apply a LoRA adapter to a loaded model
# // path_base_model is the path to a higher quality model to use as a base for
# // the layers modified by the adapter. Can be NULL to use the current loaded model.
# // The model needs to be reloaded before applying a new adapter, otherwise the adapter
# // will be applied on top of the previous one
# // Returns 0 on success
# LLAMA_API DEPRECATED(int32_t llama_apply_lora_from_file(
# struct llama_context * ctx,
# const char * path_lora,
# float scale,
# const char * path_base_model,
# int32_t n_threads),
# "use llama_model_apply_lora_from_file instead");
@ctypes_function(
"llama_apply_lora_from_file",
[
llama_context_p_ctypes,
ctypes.c_char_p,
ctypes.c_float,
ctypes.c_char_p,
ctypes.c_int32,
],
ctypes.c_int32,
)
def llama_apply_lora_from_file(
ctx: llama_context_p,
path_lora: Union[ctypes.c_char_p, bytes],
scale: Union[ctypes.c_float, float],
path_base_model: Union[ctypes.c_char_p, bytes],
n_threads: Union[ctypes.c_int32, int],
/,
) -> int:
"""Apply a LoRA adapter to a loaded model
path_base_model is the path to a higher quality model to use as a base for
the layers modified by the adapter. Can be NULL to use the current loaded model.
The model needs to be reloaded before applying a new adapter, otherwise the adapter
will be applied on top of the previous one
Returns 0 on success"""
...
# LLAMA_API int32_t llama_model_apply_lora_from_file(
# const struct llama_model * model,
# const char * path_lora,
@ -1168,7 +1215,7 @@ def llama_model_apply_lora_from_file(
model: llama_model_p,
path_lora: Union[ctypes.c_char_p, bytes],
scale: Union[ctypes.c_float, float],
path_base_model: Union[ctypes.c_char_p, bytes, None],
path_base_model: Union[ctypes.c_char_p, bytes],
n_threads: Union[ctypes.c_int32, int],
/,
) -> int:
@ -1595,6 +1642,72 @@ def llama_save_session_file(
# //
# // Run the llama inference to obtain the logits and probabilities for the next token(s).
# // tokens + n_tokens is the provided batch of new tokens to process
# // n_past is the number of tokens to use from previous eval calls
# // Returns 0 on success
# // DEPRECATED: use llama_decode() instead
# LLAMA_API DEPRECATED(int llama_eval(
# struct llama_context * ctx,
# llama_token * tokens,
# int32_t n_tokens,
# int32_t n_past),
# "use llama_decode() instead");
@ctypes_function(
"llama_eval",
[
llama_context_p_ctypes,
llama_token_p,
ctypes.c_int32,
ctypes.c_int32,
],
ctypes.c_int,
)
def llama_eval(
ctx: llama_context_p,
tokens: CtypesArray[llama_token],
n_tokens: Union[ctypes.c_int, int],
n_past: Union[ctypes.c_int, int],
/,
) -> int:
"""Run the llama inference to obtain the logits and probabilities for the next token(s).
tokens + n_tokens is the provided batch of new tokens to process
n_past is the number of tokens to use from previous eval calls
Returns 0 on success
DEPRECATED: use llama_decode() instead"""
...
# // Same as llama_eval, but use float matrix input directly.
# // DEPRECATED: use llama_decode() instead
# LLAMA_API DEPRECATED(int llama_eval_embd(
# struct llama_context * ctx,
# float * embd,
# int32_t n_tokens,
# int32_t n_past),
# "use llama_decode() instead");
@ctypes_function(
"llama_eval_embd",
[
llama_context_p_ctypes,
ctypes.POINTER(ctypes.c_float),
ctypes.c_int32,
ctypes.c_int32,
],
ctypes.c_int,
)
def llama_eval_embd(
ctx: llama_context_p,
embd: CtypesArray[ctypes.c_float],
n_tokens: Union[ctypes.c_int, int],
n_past: Union[ctypes.c_int, int],
/,
) -> int:
"""Same as llama_eval, but use float matrix input directly.
DEPRECATED: use llama_decode() instead"""
...
# // Return batch for single sequence of tokens starting at pos_0
# //
# // NOTE: this is a helper function to facilitate transition to the new batch API - avoid using it
@ -2129,6 +2242,35 @@ def llama_sample_apply_guidance(
...
# LLAMA_API DEPRECATED(void llama_sample_classifier_free_guidance(
# struct llama_context * ctx,
# llama_token_data_array * candidates,
# struct llama_context * guidance_ctx,
# float scale),
# "use llama_sample_apply_guidance() instead");
@ctypes_function(
"llama_sample_classifier_free_guidance",
[
llama_context_p_ctypes,
llama_token_data_array_p,
llama_context_p_ctypes,
ctypes.c_float,
],
None,
)
def llama_sample_classifier_free_guidance(
ctx: llama_context_p,
candidates: Union[
CtypesArray[llama_token_data_array], CtypesPointerOrRef[llama_token_data_array]
],
guidance_ctx: llama_context_p,
scale: Union[ctypes.c_float, float],
/,
):
"""Apply classifier-free guidance to the logits as described in academic paper "Stay on topic with Classifier-Free Guidance" https://arxiv.org/abs/2306.17806"""
...
# /// @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.
# LLAMA_API void llama_sample_softmax(
# struct llama_context * ctx,
@ -2327,6 +2469,28 @@ def llama_sample_temp(
...
# LLAMA_API DEPRECATED(void llama_sample_temperature(
# struct llama_context * ctx,
# llama_token_data_array * candidates,
# float temp),
# "use llama_sample_temp instead");
@ctypes_function(
"llama_sample_temperature",
[llama_context_p_ctypes, llama_token_data_array_p, ctypes.c_float],
None,
)
def llama_sample_temperature(
ctx: llama_context_p,
candidates: Union[
CtypesArray[llama_token_data_array], CtypesPointerOrRef[llama_token_data_array]
],
temp: Union[ctypes.c_float, float],
/,
):
"""use llama_sample_temp instead"""
...
# /// @details Apply constraints from grammar
# LLAMA_API void llama_sample_grammar(
# struct llama_context * ctx,

38
llama_cpp/server/app.py
View file

@ -200,7 +200,7 @@ async def authenticate(
"/v1/completions",
summary="Completion",
dependencies=[Depends(authenticate)],
response_model=Union[
response_model= Union[
llama_cpp.CreateCompletionResponse,
str,
],
@ -216,14 +216,14 @@ async def authenticate(
"title": "Completion response, when stream=False",
}
},
"text/event-stream": {
"text/event-stream":{
"schema": {
"type": "string",
"title": "Server Side Streaming response, when stream=True. "
+ "See SSE format: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format", # noqa: E501
"example": """data: {... see CreateCompletionResponse ...} \\n\\n data: ... \\n\\n ... data: [DONE]""",
"title": "Server Side Streaming response, when stream=True. " +
"See SSE format: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format", # noqa: E501
"example": """data: {... see CreateCompletionResponse ...} \\n\\n data: ... \\n\\n ... data: [DONE]"""
}
}
},
},
}
},
@ -290,7 +290,7 @@ async def create_completion(
inner_send_chan=send_chan,
iterator=iterator(),
),
sep="\n",
sep='\n',
)
else:
return iterator_or_completion
@ -310,10 +310,10 @@ async def create_embedding(
@router.post(
"/v1/chat/completions",
summary="Chat",
dependencies=[Depends(authenticate)],
response_model=Union[llama_cpp.ChatCompletion, str],
"/v1/chat/completions", summary="Chat", dependencies=[Depends(authenticate)],
response_model= Union[
llama_cpp.ChatCompletion, str
],
responses={
"200": {
"description": "Successful Response",
@ -321,21 +321,19 @@ async def create_embedding(
"application/json": {
"schema": {
"anyOf": [
{
"$ref": "#/components/schemas/CreateChatCompletionResponse"
}
{"$ref": "#/components/schemas/CreateChatCompletionResponse"}
],
"title": "Completion response, when stream=False",
}
},
"text/event-stream": {
"text/event-stream":{
"schema": {
"type": "string",
"title": "Server Side Streaming response, when stream=True"
+ "See SSE format: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format", # noqa: E501
"example": """data: {... see CreateChatCompletionResponse ...} \\n\\n data: ... \\n\\n ... data: [DONE]""",
"title": "Server Side Streaming response, when stream=True" +
"See SSE format: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format", # noqa: E501
"example": """data: {... see CreateChatCompletionResponse ...} \\n\\n data: ... \\n\\n ... data: [DONE]"""
}
}
},
},
}
},
@ -385,7 +383,7 @@ async def create_chat_completion(
inner_send_chan=send_chan,
iterator=iterator(),
),
sep="\n",
sep='\n',
)
else:
return iterator_or_completion

2
llama_cpp/server/errors.py
View file

@ -22,7 +22,6 @@ from llama_cpp.server.types import (
CreateChatCompletionRequest,
)
class ErrorResponse(TypedDict):
"""OpenAI style error response"""
@ -208,3 +207,4 @@ class RouteErrorHandler(APIRoute):
)
return custom_route_handler

15
llama_cpp/server/model.py
View file

@ -88,15 +88,15 @@ class LlamaProxy:
assert (
settings.hf_tokenizer_config_path is not None
), "hf_tokenizer_config_path must be set for hf-tokenizer-config"
chat_handler = llama_cpp.llama_chat_format.hf_tokenizer_config_to_chat_completion_handler(
chat_handler = (
llama_cpp.llama_chat_format.hf_tokenizer_config_to_chat_completion_handler(
json.load(open(settings.hf_tokenizer_config_path))
)
)
tokenizer: Optional[llama_cpp.BaseLlamaTokenizer] = None
if settings.hf_pretrained_model_name_or_path is not None:
tokenizer = llama_tokenizer.LlamaHFTokenizer.from_pretrained(
settings.hf_pretrained_model_name_or_path
)
tokenizer = llama_tokenizer.LlamaHFTokenizer.from_pretrained(settings.hf_pretrained_model_name_or_path)
draft_model = None
if settings.draft_model is not None:
@ -126,15 +126,12 @@ class LlamaProxy:
kwargs = {}
if settings.hf_model_repo_id is not None:
create_fn = functools.partial(
llama_cpp.Llama.from_pretrained,
repo_id=settings.hf_model_repo_id,
filename=settings.model,
)
create_fn = functools.partial(llama_cpp.Llama.from_pretrained, repo_id=settings.hf_model_repo_id, filename=settings.model)
else:
create_fn = llama_cpp.Llama
kwargs["model_path"] = settings.model
_model = create_fn(
**kwargs,
# Model Params

12
llama_cpp/server/settings.py
View file

@ -45,11 +45,11 @@ class ModelSettings(BaseSettings):
default=False, description="Whether to only return the vocabulary."
)
use_mmap: bool = Field(
default=llama_cpp.llama_supports_mmap(),
default=llama_cpp.llama_mmap_supported(),
description="Use mmap.",
)
use_mlock: bool = Field(
default=llama_cpp.llama_supports_mlock(),
default=llama_cpp.llama_mlock_supported(),
description="Use mlock.",
)
kv_overrides: Optional[List[str]] = Field(
@ -74,9 +74,7 @@ class ModelSettings(BaseSettings):
ge=0,
description="The number of threads to use when batch processing.",
)
rope_scaling_type: int = Field(
default=llama_cpp.LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED
)
rope_scaling_type: int = Field(default=llama_cpp.LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED)
rope_freq_base: float = Field(default=0.0, description="RoPE base frequency")
rope_freq_scale: float = Field(
default=0.0, description="RoPE frequency scaling factor"
@ -195,4 +193,6 @@ class Settings(ServerSettings, ModelSettings):
class ConfigFileSettings(ServerSettings):
"""Configuration file format settings."""
models: List[ModelSettings] = Field(default=[], description="Model configs")
models: List[ModelSettings] = Field(
default=[], description="Model configs"
)

2
vendor/llama.cpp vendored

@ -1 +1 @@
Subproject commit 08c5ee87e4cceb603ecceac90734fcdade57311b
Subproject commit a33e6a0d2a66104ea9a906bdbf8a94d050189d91