chore: enable pyupgrade fixes (#1806)

# What does this PR do?

The goal of this PR is code base modernization.

Schema reflection code needed a minor adjustment to handle UnionTypes
and collections.abc.AsyncIterator. (Both are preferred for latest Python
releases.)

Note to reviewers: almost all changes here are automatically generated
by pyupgrade. Some additional unused imports were cleaned up. The only
change worth of note can be found under `docs/openapi_generator` and
`llama_stack/strong_typing/schema.py` where reflection code was updated
to deal with "newer" types.

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
This commit is contained in:
Ihar Hrachyshka 2025-05-01 17:23:50 -04:00 committed by GitHub
parent ffe3d0b2cd
commit 9e6561a1ec
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GPG key ID: B5690EEEBB952194
319 changed files with 2843 additions and 3033 deletions

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@ -5,18 +5,11 @@
# the root directory of this source tree.
import os
from collections.abc import Collection, Iterator, Sequence, Set
from logging import getLogger
from pathlib import Path
from typing import (
AbstractSet,
Collection,
Dict,
Iterator,
List,
Literal,
Optional,
Sequence,
Union,
cast,
)
@ -44,7 +37,7 @@ class Tokenizer:
Tokenizing and encoding/decoding text using the Tiktoken tokenizer.
"""
special_tokens: Dict[str, int]
special_tokens: dict[str, int]
num_reserved_special_tokens = 256
@ -116,9 +109,9 @@ class Tokenizer:
*,
bos: bool,
eos: bool,
allowed_special: Optional[Union[Literal["all"], AbstractSet[str]]] = None,
disallowed_special: Union[Literal["all"], Collection[str]] = (),
) -> List[int]:
allowed_special: Literal["all"] | Set[str] | None = None,
disallowed_special: Literal["all"] | Collection[str] = (),
) -> list[int]:
"""
Encodes a string into a list of token IDs.
@ -151,7 +144,7 @@ class Tokenizer:
s[i : i + TIKTOKEN_MAX_ENCODE_CHARS], MAX_NO_WHITESPACES_CHARS
)
)
t: List[int] = []
t: list[int] = []
for substr in substrs:
t.extend(
self.model.encode(
@ -177,7 +170,7 @@ class Tokenizer:
str: The decoded string.
"""
# Typecast is safe here. Tiktoken doesn't do anything list-related with the sequence.
return self.model.decode(cast(List[int], t))
return self.model.decode(cast(list[int], t))
@staticmethod
def _split_whitespaces_or_nonwhitespaces(s: str, max_consecutive_slice_len: int) -> Iterator[str]: