fix(pc):

.pre-commit-config.yaml

@@ -9,7 +9,7 @@ repos:
         args: [--py311-plus]
 
   - repo: https://github.com/psf/black
-    rev: 23.11.0
+    rev: 25.11.0
     hooks:
       - id: black
         language_version: python3.11
@@ -21,11 +21,11 @@ repos:
         language_version: python3.11
         additional_dependencies: [flake8-docstrings]
 
-  - repo: https://github.com/PyCQA/isort
-    rev: 7.0.0
-    hooks:
-      - id: isort
-        args: [--profile, black]
+  # - repo: https://github.com/PyCQA/isort
+  #   rev: 7.0.0
+  #   hooks:
+  #     - id: isort
+  #       args: [--profile, black]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.5.0

agentic_security/agents/operator_crew.py

@@ -246,9 +246,9 @@ async def run_crew():
 os.environ["OPENAI_API_KEY"] = os.environ.get(
     "DEEPSEEK_API_KEY", ""
 )  # CrewAI uses OPENAI_API_KEY
-os.environ[
-    "OPENAI_MODEL_NAME"
-] = "deepseek:chat"  # Specify DeepSeek model (adjust if needed)
+os.environ["OPENAI_MODEL_NAME"] = (
+    "deepseek:chat"  # Specify DeepSeek model (adjust if needed)
+)
 
 if __name__ == "__main__":
     asyncio.run(run_crew())

agentic_security/integrations/__init__.py

@@ -5,8 +5,6 @@ from typing import Protocol
 class IntegrationProto(Protocol):
     def __init__(
         self, prompt_groups: list, tools_inbox: asyncio.Queue, opts: dict = {}
-    ):
-        ...
+    ): ...
 
-    async def apply(self) -> list:
-        ...
+    async def apply(self) -> list: ...

agentic_security/logutils.py

@@ -129,7 +129,7 @@ def time_execution_async(
     [Callable[P, Coroutine[Any, Any, R]]], Callable[P, Coroutine[Any, Any, R]]
 ]:
     def decorator(
-        func: Callable[P, Coroutine[Any, Any, R]]
+        func: Callable[P, Coroutine[Any, Any, R]],
     ) -> Callable[P, Coroutine[Any, Any, R]]:
         @wraps(func)
         async def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:

agentic_security/probe_data/modules/rl_model.py

@@ -121,8 +121,7 @@ class CloudRLPromptSelector(PromptSelectionInterface):
         current_prompt: str,
         reward: float,
         passed_guard: bool,
-    ) -> None:
-        ...
+    ) -> None: ...
 
 
 class QLearningPromptSelector(PromptSelectionInterface):