Lint

Author: Smartappli

llama_cpp/llama.py

@@ -1,59 +1,56 @@
 from __future__ import annotations
 
+import contextlib
+import ctypes
+import fnmatch
+import json
+import multiprocessing
 import os
 import sys
-import uuid
 import time
-import json
-import ctypes
 import typing
-import fnmatch
+import uuid
 import warnings
-import contextlib
-import multiprocessing
+from collections import deque
+from pathlib import Path
 
 from typing import (
     Any,
+    Callable,
+    Deque,
+    Dict,
+    Generator,
+    Iterator,
     List,
     Literal,
     Optional,
-    Union,
-    Generator,
     Sequence,
-    Iterator,
-    Deque,
-    Callable,
-    Dict,
-)
-from collections import deque
-from pathlib import Path
-
-
-from .llama_types import *
-from .llama_grammar import LlamaGrammar
-from .llama_cache import (
-    BaseLlamaCache,  # type: ignore
+    Union,
 )
-from .llama_tokenizer import BaseLlamaTokenizer, LlamaTokenizer
-import llama_cpp.llama_cpp as llama_cpp
-import llama_cpp.llama_chat_format as llama_chat_format
-
-from llama_cpp.llama_speculative import LlamaDraftModel
 
 import numpy as np
 import numpy.typing as npt
 
+from llama_cpp import llama_chat_format, llama_cpp
+from llama_cpp.llama_speculative import LlamaDraftModel
+
 from ._internals import (
-    _LlamaModel,  # type: ignore
-    _LlamaContext,  # type: ignore
     _LlamaBatch,  # type: ignore
-    _LlamaTokenDataArray,  # type: ignore
-    _LlamaSamplingParams,  # type: ignore
+    _LlamaContext,  # type: ignore
+    _LlamaModel,  # type: ignore
     _LlamaSamplingContext,  # type: ignore
+    _LlamaSamplingParams,  # type: ignore
+    _LlamaTokenDataArray,  # type: ignore
     _normalize_embedding,  # type: ignore
 )
 from ._logger import set_verbose
 from ._utils import suppress_stdout_stderr
+from .llama_cache import (
+    BaseLlamaCache,  # type: ignore
+)
+from .llama_grammar import LlamaGrammar
+from .llama_tokenizer import BaseLlamaTokenizer, LlamaTokenizer
+from .llama_types import *
 
 
 class Llama:
@@ -1036,7 +1033,7 @@ def _create_completion(
         assert self._ctx is not None
         assert suffix is None or suffix.__class__ is str
 
-        completion_id: str = f"cmpl-{str(uuid.uuid4())}"
+        completion_id: str = f"cmpl-{uuid.uuid4()!s}"
         created: int = int(time.time())
         bos_token_id: int = self.token_bos()
         cls_token_id: int = self._model.token_cls()
@@ -2127,7 +2124,7 @@ def from_pretrained(
         local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
         cache_dir: Optional[Union[str, os.PathLike[str]]] = None,
         **kwargs: Any,
-    ) -> "Llama":
+    ) -> Llama:
         """Create a Llama model from a pretrained model name or path.
         This method requires the huggingface-hub package.
         You can install it with `pip install huggingface-hub`.
@@ -2142,7 +2139,7 @@ def from_pretrained(
         Returns:
             A Llama model."""
         try:
-            from huggingface_hub import hf_hub_download, HfFileSystem
+            from huggingface_hub import HfFileSystem, hf_hub_download
             from huggingface_hub.utils import validate_repo_id
         except ImportError:
             raise ImportError(