chore: updated dev deps

.hooks/generate_docs.py

@@ -11,8 +11,6 @@
     PythonHandler,
 )
 
-# ruff: noqa: T201
-
 
 class CustomMarkdownConverter(MarkdownConverter):  # type: ignore[misc]
     # Strip extra whitespace from code blocks

dreadnode/agent/agent.py

@@ -259,7 +259,7 @@ class TaskAgent(Agent):
     """
 
     def model_post_init(self, _: t.Any) -> None:
-        from dreadnode.agent.tools import finish_task, update_todo
+        from dreadnode.agent.tools import finish_task, update_todo  # noqa: PLC0415
 
         if not any(tool for tool in self.tools if tool.name == "finish_task"):
             self.tools.append(finish_task)

dreadnode/agent/events.py

@@ -108,10 +108,10 @@ class AgentEnd(Event):
 
 
 def rebuild_event_models() -> None:
-    from dreadnode.agent.agent import Agent  # noqa: F401
-    from dreadnode.agent.reactions import Reaction  # noqa: F401
-    from dreadnode.agent.result import AgentResult  # noqa: F401
-    from dreadnode.agent.thread import Thread  # noqa: F401
+    from dreadnode.agent.agent import Agent  # noqa: F401,PLC0415
+    from dreadnode.agent.reactions import Reaction  # noqa: F401,PLC0415
+    from dreadnode.agent.result import AgentResult  # noqa: F401,PLC0415
+    from dreadnode.agent.thread import Thread  # noqa: F401,PLC0415
 
     rebuild_dataclass(Event)  # type: ignore[arg-type]
     rebuild_dataclass(AgentStart)  # type: ignore[arg-type]

dreadnode/agent/hooks/summarize.py

@@ -23,7 +23,7 @@
 def _is_context_length_error(error: Exception) -> bool:
     """Checks if an exception is likely due to exceeding the context window."""
     with contextlib.suppress(ImportError):
-        from litellm.exceptions import ContextWindowExceededError
+        from litellm.exceptions import ContextWindowExceededError  # noqa: PLC0415
 
         if isinstance(error, ContextWindowExceededError):
             return True

dreadnode/api/client.py

@@ -393,7 +393,7 @@ def export_runs(
         Returns:
             A DataFrame containing the exported run data.
         """
-        import pandas as pd
+        import pandas as pd  # noqa: PLC0415
 
         response = self.request(
             "GET",
@@ -430,7 +430,7 @@ def export_metrics(
         Returns:
             A DataFrame containing the exported metric data.
         """
-        import pandas as pd
+        import pandas as pd  # noqa: PLC0415
 
         response = self.request(
             "GET",
@@ -470,7 +470,7 @@ def export_parameters(
         Returns:
             A DataFrame containing the exported parameter data.
         """
-        import pandas as pd
+        import pandas as pd  # noqa: PLC0415
 
         response = self.request(
             "GET",
@@ -511,7 +511,7 @@ def export_timeseries(
         Returns:
             A DataFrame containing the exported timeseries data.
         """
-        import pandas as pd
+        import pandas as pd  # noqa: PLC0415
 
         response = self.request(
             "GET",

dreadnode/cli/agent/cli.py

@@ -99,7 +99,7 @@ async def run(
     config_default = None
     with contextlib.suppress(Exception):
         config_default = config_model()
-        config_parameter = t.Optional[config_parameter]  # type: ignore [assignment] # noqa: UP007
+        config_parameter = config_parameter | None  # type: ignore [assignment]
 
     async def agent_cli(*, config: t.Any = config_default) -> None:
         agent = hydrate_agent(agent_blueprint, config)

dreadnode/cli/main.py

@@ -202,9 +202,9 @@ def clone(
 
 @cli.command(help="Show versions and exit.", group="Meta")
 def version() -> None:
-    import importlib.metadata
-    import platform
-    import sys
+    import importlib.metadata  # noqa: PLC0415
+    import platform  # noqa: PLC0415
+    import sys  # noqa: PLC0415
 
     version = importlib.metadata.version("dreadnode")
     python_version = f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}"

dreadnode/cli/profile/cli.py

@@ -59,7 +59,7 @@ def switch(
 
     # If no profile provided, prompt user to choose
     if profile is None:
-        from rich.prompt import Prompt
+        from rich.prompt import Prompt  # noqa: PLC0415
 
         profiles = list(config.servers.keys())
         rich.print("\nAvailable profiles:")

dreadnode/convert.py

@@ -8,7 +8,7 @@
 
 def run_span_to_graph(run: "RunSpan") -> "nx.DiGraph":
     try:
-        import networkx as nx
+        import networkx as nx  # noqa: PLC0415 # pyright: ignore[reportMissingModuleSource]
     except ImportError as e:
         raise RuntimeError("The `networkx` package is required for graph conversion") from e
 

dreadnode/data_types/audio.py

@@ -10,14 +10,14 @@
 
 def check_imports() -> None:
     try:
-        import soundfile as sf  # type: ignore[import-untyped,unused-ignore]  # noqa: F401
+        import soundfile as sf  # type: ignore[import-untyped,unused-ignore]  # noqa: F401,PLC0415
     except ImportError as e:
         raise ImportError(
             "Audio processing requires `soundfile`. Install with: pip install dreadnode[multimodal]"
         ) from e
 
     try:
-        import numpy as np  # type: ignore[import-untyped,unused-ignore]  # noqa: F401
+        import numpy as np  # type: ignore[import-untyped,unused-ignore]  # noqa: F401,PLC0415
     except ImportError as e:
         raise ImportError(
             "Audio processing requires `numpy`. Install with: pip install dreadnode[multimodal]"
@@ -78,7 +78,7 @@ def _process_audio_data(self) -> tuple[bytes, str, int | None, float | None]:
         Returns:
             A tuple of (audio_bytes, format_name, sample_rate, duration)
         """
-        import numpy as np
+        import numpy as np  # noqa: PLC0415
 
         if isinstance(self._data, str | Path) and Path(self._data).exists():
             return self._process_file_path()
@@ -94,7 +94,7 @@ def _process_file_path(self) -> tuple[bytes, str, int | None, float | None]:
         Returns:
             A tuple of (audio_bytes, format_name, sample_rate, duration)
         """
-        import soundfile as sf  # type: ignore[import-not-found,unused-ignore]
+        import soundfile as sf  # type: ignore[import-not-found,unused-ignore]  # noqa: PLC0415
 
         path_str = str(self._data)
         audio_bytes = Path(path_str).read_bytes()
@@ -113,8 +113,8 @@ def _process_numpy_array(self) -> tuple[bytes, str, int | None, float | None]:
         Returns:
             A tuple of (audio_bytes, format_name, sample_rate, duration)
         """
-        import numpy as np  # type: ignore[import-not-found,unused-ignore]
-        import soundfile as sf  # type: ignore[import-not-found,unused-ignore]
+        import numpy as np  # type: ignore[import-not-found,unused-ignore]  # noqa: PLC0415
+        import soundfile as sf  # type: ignore[import-not-found,unused-ignore]  # noqa: PLC0415
 
         if self._sample_rate is None:
             raise ValueError('Argument "sample_rate" is required when using numpy arrays.')
@@ -151,7 +151,7 @@ def _generate_metadata(
         Returns:
             A dictionary of metadata
         """
-        import numpy as np  # type: ignore[import-not-found,unused-ignore]
+        import numpy as np  # type: ignore[import-not-found,unused-ignore]  # noqa: PLC0415
 
         metadata: dict[str, str | int | float | None] = {
             "extension": format_name.lower(),

dreadnode/data_types/image.py

@@ -11,14 +11,14 @@
 
 def check_imports() -> None:
     try:
-        import PIL  # type: ignore[import,unused-ignore]  # noqa: F401
+        import PIL  # type: ignore[import,unused-ignore]  # noqa: F401,PLC0415
     except ImportError as e:
         raise ImportError(
             "Image processing requires `pillow`. Install with: pip install dreadnode[multimodal]"
         ) from e
 
     try:
-        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: F401
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: F401,PLC0415
     except ImportError as e:
         raise ImportError(
             "Image processing requires `numpy`. Install with: pip install dreadnode[multimodal]"
@@ -83,8 +83,8 @@ def _process_image_data(self) -> tuple[bytes, str, str | None, int | None, int |
         Returns:
             A tuple of (image_bytes, image_format, mode, width, height)
         """
-        import numpy as np  # type: ignore[import,unused-ignore]
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         if isinstance(self._data, (str, Path)) and Path(self._data).exists():
             return self._process_file_path()
@@ -104,7 +104,7 @@ def _process_file_path(self) -> tuple[bytes, str, str | None, int | None, int |
         Returns:
             A tuple of (image_bytes, image_format, mode, width, height)
         """
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         path_str = str(self._data)
         image_bytes = Path(path_str).read_bytes()
@@ -122,7 +122,7 @@ def _process_pil_image(self) -> tuple[bytes, str, str | None, int | None, int |
         Returns:
             A tuple of (image_bytes, image_format, mode, width, height)
         """
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         if not isinstance(self._data, PIL.Image.Image):
             raise TypeError(f"Expected PIL.Image, got {type(self._data)}")
@@ -160,8 +160,8 @@ def _process_numpy_array(self) -> tuple[bytes, str, str | None, int | None, int
         Returns:
             A tuple of (image_bytes, image_format, mode, width, height)
         """
-        import numpy as np  # type: ignore[import,unused-ignore]
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         buffer = io.BytesIO()
         image_format = self._format or "png"
@@ -191,7 +191,7 @@ def _process_raw_bytes(self) -> tuple[bytes, str, str | None, int | None, int |
         Returns:
             A tuple of (image_bytes, image_format, mode, width, height)
         """
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         if not isinstance(self._data, bytes):
             raise TypeError(f"Expected bytes, got {type(self._data)}")
@@ -216,7 +216,7 @@ def _process_base64_string(self) -> tuple[bytes, str, str | None, int | None, in
         Returns:
             A tuple of (image_bytes, image_format, mode, width, height)
         """
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         if not isinstance(self._data, str):
             raise TypeError(f"Expected str, got {type(self._data)}")
@@ -253,8 +253,8 @@ def _generate_metadata(
         self, image_format: str, mode: str | None, width: int | None, height: int | None
     ) -> dict[str, str | int | None]:
         """Generate metadata for the image."""
-        import numpy as np  # type: ignore[import,unused-ignore]
-        import PIL.Image  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
+        import PIL.Image  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         metadata: dict[str, str | int | None] = {
             "extension": image_format.lower(),
@@ -313,7 +313,7 @@ def _ensure_valid_image_array(
         self, array: "np.ndarray[t.Any, np.dtype[t.Any]]"
     ) -> "np.ndarray[t.Any, np.dtype[t.Any]]":
         """Convert numpy array to a format suitable for PIL."""
-        import numpy as np  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         grayscale_dim = 2
         rgb_dim = 3

dreadnode/data_types/table.py

@@ -78,8 +78,8 @@ def _to_dataframe(self) -> "pd.DataFrame":
         Returns:
             A pandas DataFrame representation of the input data
         """
-        import numpy as np
-        import pandas as pd
+        import numpy as np  # noqa: PLC0415
+        import pandas as pd  # noqa: PLC0415
 
         if isinstance(self._data, pd.DataFrame):
             return self._data
@@ -134,8 +134,8 @@ def _generate_metadata(self, data_frame: "pd.DataFrame") -> dict[str, t.Any]:
         Returns:
             A dictionary of metadata
         """
-        import numpy as np
-        import pandas as pd
+        import numpy as np  # noqa: PLC0415
+        import pandas as pd  # noqa: PLC0415
 
         metadata = {
             "extension": self._format,

dreadnode/data_types/video.py

@@ -62,10 +62,12 @@ def to_serializable(self) -> tuple[bytes, dict[str, t.Any]]:
         Returns:
             A tuple of (video_bytes, metadata_dict)
         """
-        import numpy as np  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         try:
-            from moviepy.video.VideoClip import VideoClip  # type: ignore[import,unused-ignore]
+            from moviepy.video.VideoClip import (  # type: ignore[import,unused-ignore,import-untyped]  # noqa: PLC0415
+                VideoClip,
+            )
         except ImportError:
             VideoClip = None  # noqa: N806
 
@@ -120,7 +122,7 @@ def _process_numpy_array(self) -> tuple[bytes, dict[str, t.Any]]:
         Returns:
             A tuple of (video_bytes, metadata_dict)
         """
-        import numpy as np  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         if not self._fps:
             raise ValueError("fps is required for numpy array video frames")
@@ -135,7 +137,7 @@ def _process_numpy_array(self) -> tuple[bytes, dict[str, t.Any]]:
 
     def _extract_frames_from_data(self) -> "list[NDArray[t.Any]]":
         """Extract frames from numpy array or list data."""
-        import numpy as np  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         frames = []
         rgb_dim = 3
@@ -157,10 +159,12 @@ def _create_video_from_frames_data(
         self, frames: "list[NDArray[t.Any]]"
     ) -> tuple[bytes, dict[str, t.Any]]:
         """Create video file from frames."""
-        import numpy as np  # type: ignore[import,unused-ignore]
+        import numpy as np  # type: ignore[import,unused-ignore]  # noqa: PLC0415
 
         try:
-            from moviepy.video.io import ImageSequenceClip  # type: ignore[import,unused-ignore]
+            from moviepy.video.io import (  # type: ignore[import,unused-ignore,import-untyped]  # noqa: PLC0415
+                ImageSequenceClip,
+            )
         except ImportError as e:
             raise ImportError(
                 "Video processing from numpy arrays requires moviepy. "
@@ -207,7 +211,9 @@ def _process_moviepy_clip(self) -> tuple[bytes, dict[str, t.Any]]:
         Returns:
             A tuple of (video_bytes, metadata_dict)
         """
-        from moviepy.video.VideoClip import VideoClip  # type: ignore[import,unused-ignore]
+        from moviepy.video.VideoClip import (  # noqa: PLC0415
+            VideoClip,  # type: ignore[import,unused-ignore]
+        )
 
         if not isinstance(self._data, VideoClip):
             raise TypeError("data must be a MoviePy VideoClip object")

dreadnode/main.py

@@ -224,10 +224,7 @@ def configure(
                 with contextlib.suppress(Exception):
                     user_config = UserConfig.read()
                     profile_name = profile or os.environ.get(ENV_PROFILE)
-                    if profile_name:
-                        active_profile = profile_name
-                    else:
-                        active_profile = user_config.active_profile_name
+                    active_profile = profile_name or user_config.active_profile_name
 
                     if active_profile:
                         config_source = f"profile: {active_profile}"
@@ -945,7 +942,7 @@ def log_params(self, **params: JsonValue) -> None:
     def log_metric(
         self,
         name: str,
-        value: float | bool,
+        value: float | bool,  # noqa: FBT001
         *,
         step: int = 0,
         origin: t.Any | None = None,
@@ -1036,7 +1033,7 @@ def log_metric(
     def log_metric(
         self,
         name: str,
-        value: float | bool | Metric,
+        value: float | bool | Metric,  # noqa: FBT001
         *,
         step: int = 0,
         origin: t.Any | None = None,

dreadnode/scorers/classification.py

@@ -33,7 +33,7 @@ def zero_shot_classification(
     )
 
     try:
-        from transformers import (  # type: ignore [attr-defined,import-not-found,unused-ignore]
+        from transformers import (  # type: ignore [attr-defined,import-not-found,unused-ignore]  # noqa: PLC0415
             pipeline,
         )
     except ImportError:

dreadnode/scorers/harm.py

@@ -31,7 +31,7 @@ def detect_harm_with_openai(
         model: The moderation model to use.
         name: Name of the scorer.
     """
-    import openai
+    import openai  # noqa: PLC0415
 
     async def evaluate(data: t.Any) -> Metric:
         text = str(data)