Apply ruff formatting to context-window changes

Author: beacoder

python_agent_harness/client.py

@@ -237,9 +237,7 @@ def context_window(self) -> int:
         the default for that access and recovers once the file is fixed.
         """
         try:
-            return config.get_context_window_for_model(
-                self.model, config_path=self._config_path
-            )
+            return config.get_context_window_for_model(self.model, config_path=self._config_path)
         except Exception:
             # a malformed context_windows section must not break the
             # loop: use the safe default, retry on the next access

tests/test_session.py

@@ -818,13 +818,9 @@ def test_switch_model_re_resolves_context_window(self):
             p = os.path.join(d, "config.json")
             with open(p, "w", encoding="utf-8") as f:
                 f.write('{"context_windows": {"deepseek-v4*": 1000000}}')
-            client = Client(
-                base_url="http://x/v1", api_key="k", model="gpt-5-mini", config_path=p
-            )
+            client = Client(base_url="http://x/v1", api_key="k", model="gpt-5-mini", config_path=p)
             self.addCleanup(client.close)
-            session = RecordingSession(
-                model_profiles={"deepseek": {"model": "deepseek-v4-flash"}}
-            )
+            session = RecordingSession(model_profiles={"deepseek": {"model": "deepseek-v4-flash"}})
             session.client = client
             self.assertEqual(client.context_window, 128_000)
             success, _ = session.switch_model("deepseek")
@@ -835,9 +831,7 @@ def test_switch_model_resets_calibrator(self):
         """Switching models must drop the token-calibration factor: it
         was tuned to the previous model's tokenizer and would skew the
         first context estimates for the new model."""
-        session = RecordingSession(
-            model_profiles={"deepseek": {"model": "deepseek-v4-flash"}}
-        )
+        session = RecordingSession(model_profiles={"deepseek": {"model": "deepseek-v4-flash"}})
         session.calibrator.factor = 2.5
         session.calibrator.last_raw_estimate = 1234
         success, _ = session.switch_model("deepseek")