llama-cpp-python/llama_cpp/server/cli.py at main · handshape/llama-cpp-python · GitHub

History

97 lines (77 loc) · 3.19 KB

Raw

from __future__ import annotations

import argparse

from typing import List, Literal, Union, Any, Type, TypeVar

from pydantic import BaseModel

def _get_base_type(annotation: Type[Any]) -> Type[Any]:

if getattr(annotation, "__origin__", None) is Literal:

assert hasattr(annotation, "__args__") and len(annotation.__args__) >= 1 # type: ignore

return type(annotation.__args__[0]) # type: ignore

elif getattr(annotation, "__origin__", None) is Union:

assert hasattr(annotation, "__args__") and len(annotation.__args__) >= 1 # type: ignore

non_optional_args: List[Type[Any]] = [

arg for arg in annotation.__args__ if arg is not type(None) # type: ignore

]

if non_optional_args:

return _get_base_type(non_optional_args[0])

elif (

getattr(annotation, "__origin__", None) is list

or getattr(annotation, "__origin__", None) is List

assert hasattr(annotation, "__args__") and len(annotation.__args__) >= 1 # type: ignore

return _get_base_type(annotation.__args__[0]) # type: ignore

return annotation

def _contains_list_type(annotation: Type[Any] | None) -> bool:

origin = getattr(annotation, "__origin__", None)

if origin is list or origin is List:

return True

elif origin in (Literal, Union):

return any(_contains_list_type(arg) for arg in annotation.__args__) # type: ignore

else:

return False

def _parse_bool_arg(arg: str | bytes | bool) -> bool:

if isinstance(arg, bytes):

arg = arg.decode("utf-8")

true_values = {"1", "on", "t", "true", "y", "yes"}

false_values = {"0", "off", "f", "false", "n", "no"}

arg_str = str(arg).lower().strip()

if arg_str in true_values:

return True

elif arg_str in false_values:

return False

else:

raise ValueError(f"Invalid boolean argument: {arg}")

def add_args_from_model(parser: argparse.ArgumentParser, model: Type[BaseModel]):

"""Add arguments from a pydantic model to an argparse parser."""

for name, field in model.model_fields.items():

description = field.description

if field.default and description and not field.is_required():

description += f" (default: {field.default})"

base_type = (

_get_base_type(field.annotation) if field.annotation is not None else str

)

list_type = _contains_list_type(field.annotation)

if base_type is not bool:

parser.add_argument(

f"--{name}",

dest=name,

nargs="*" if list_type else None,

type=base_type,

help=description,

)

if base_type is bool:

parser.add_argument(

f"--{name}",

dest=name,

type=_parse_bool_arg,

help=f"{description}",

)

T = TypeVar("T", bound=Type[BaseModel])

def parse_model_from_args(model: T, args: argparse.Namespace) -> T:

"""Parse a pydantic model from an argparse namespace."""

return model(

**{

k: v

for k, v in vars(args).items()

if v is not None and k in model.model_fields

}

)

llama-cpp-python/llama_cpp/server/cli.py at main · handshape/llama-cpp-python · GitHub

Expand file tree

Breadcrumbs

cli.py

Latest commit

History

Breadcrumbs

cli.py

File metadata and controls