chore: enable pyupgrade fixes

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

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
This commit is contained in:
Ihar Hrachyshka 2025-03-26 18:33:23 -04:00
parent ffe3d0b2cd
commit 1deb95f922
319 changed files with 2843 additions and 3033 deletions

View file

@ -4,12 +4,12 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Any, Dict
from typing import Any
from .config import PromptGuardConfig # noqa: F401
from .config import PromptGuardConfig
async def get_provider_impl(config: PromptGuardConfig, deps: Dict[str, Any]):
async def get_provider_impl(config: PromptGuardConfig, deps: dict[str, Any]):
from .prompt_guard import PromptGuardSafetyImpl
impl = PromptGuardSafetyImpl(config, deps)

View file

@ -5,7 +5,7 @@
# the root directory of this source tree.
from enum import Enum
from typing import Any, Dict
from typing import Any
from pydantic import BaseModel, field_validator
@ -26,7 +26,7 @@ class PromptGuardConfig(BaseModel):
return v
@classmethod
def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> Dict[str, Any]:
def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:
return {
"guard_type": "injection",
}

View file

@ -5,7 +5,7 @@
# the root directory of this source tree.
import logging
from typing import Any, Dict, List
from typing import Any
import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer
@ -49,8 +49,8 @@ class PromptGuardSafetyImpl(Safety, ShieldsProtocolPrivate):
async def run_shield(
self,
shield_id: str,
messages: List[Message],
params: Dict[str, Any] = None,
messages: list[Message],
params: dict[str, Any] = None,
) -> RunShieldResponse:
shield = await self.shield_store.get_shield(shield_id)
if not shield:
@ -81,7 +81,7 @@ class PromptGuardShield:
self.tokenizer = AutoTokenizer.from_pretrained(model_dir)
self.model = AutoModelForSequenceClassification.from_pretrained(model_dir, device_map=self.device)
async def run(self, messages: List[Message]) -> RunShieldResponse:
async def run(self, messages: list[Message]) -> RunShieldResponse:
message = messages[-1]
text = interleaved_content_as_str(message.content)