Fix Black formatting for lint CI

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: gitttt-1234

sleap_nn/cli.py

@@ -763,13 +763,19 @@ def system():
 )
 @click.option("--backbone", type=str, help="Override backbone architecture")
 @click.option("--batch-size", type=int, help="Override batch size")
-@click.option(
-    "-i", "--interactive", is_flag=True, help="Launch interactive TUI mode"
-)
+@click.option("-i", "--interactive", is_flag=True, help="Launch interactive TUI mode")
 @click.option("--analyze-only", is_flag=True, help="Only show dataset analysis")
 @click.option("--show-yaml", is_flag=True, help="Print YAML to stdout")
 def config(
-    slp_path, output, view, pipeline, backbone, batch_size, interactive, analyze_only, show_yaml
+    slp_path,
+    output,
+    view,
+    pipeline,
+    backbone,
+    batch_size,
+    interactive,
+    analyze_only,
+    show_yaml,
 ):
     """Generate training configuration from SLP file.
 

sleap_nn/config_generator/recommender.py

@@ -163,9 +163,7 @@ def recommend_pipeline(stats: DatasetStats) -> PipelineRecommendation:
         )
     else:
         if stats.num_edges == 0:
-            warnings.append(
-                "No edges in skeleton - bottom-up requires edges for PAFs"
-            )
+            warnings.append("No edges in skeleton - bottom-up requires edges for PAFs")
             return PipelineRecommendation(
                 recommended="centroid",
                 reason="No skeleton edges available for bottom-up",
@@ -241,7 +239,9 @@ def _recommend_scale(stats: DatasetStats) -> Tuple[float, str]:
         return (1.0, "Image size suitable for full resolution")
 
 
-def _recommend_batch_size(stats: DatasetStats, backbone: BackboneType) -> Tuple[int, str]:
+def _recommend_batch_size(
+    stats: DatasetStats, backbone: BackboneType
+) -> Tuple[int, str]:
     """Recommend batch size based on estimated memory usage.
 
     Args:

sleap_nn/config_generator/tui/app.py

@@ -266,7 +266,9 @@ def _compose_data_tab(self) -> ComposeResult:
             with RadioSet(id="view-type"):
                 yield RadioButton("Side View (±15° rotation)", id="view-side")
                 yield RadioButton("Top View (±180° rotation)", id="view-top")
-                yield RadioButton("Unknown (conservative defaults)", id="view-unknown", value=True)
+                yield RadioButton(
+                    "Unknown (conservative defaults)", id="view-unknown", value=True
+                )
 
             yield Rule()
 
@@ -399,9 +401,9 @@ async def on_mount(self) -> None:
         self.query_one("#memory-gauge", MemoryGauge).update_estimate(mem)
 
         # Update recommendation panel
-        self.query_one("#recommendation-panel", RecommendationPanel).update_recommendation(
-            self._recommendation
-        )
+        self.query_one(
+            "#recommendation-panel", RecommendationPanel
+        ).update_recommendation(self._recommendation)
 
         # Initial YAML preview
         self._update_yaml_preview()
@@ -567,13 +569,19 @@ def _update_ui_from_generator(self) -> None:
         self.query_one("#sigma-input", Input).value = str(self.generator._sigma)
 
         # Output stride
-        self.query_one("#output-stride-select", Select).value = self.generator._output_stride
+        self.query_one("#output-stride-select", Select).value = (
+            self.generator._output_stride
+        )
 
         # Batch size
-        self.query_one("#batch-size-input", Input).value = str(self.generator._batch_size)
+        self.query_one("#batch-size-input", Input).value = str(
+            self.generator._batch_size
+        )
 
         # Max epochs
-        self.query_one("#max-epochs-input", Input).value = str(self.generator._max_epochs)
+        self.query_one("#max-epochs-input", Input).value = str(
+            self.generator._max_epochs
+        )
 
         # Learning rate
         self.query_one("#learning-rate-input", Input).value = str(