Convert examples to ruff-format (#18400)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

examples/offline_inference/batch_llm_inference.py

@@ -17,12 +17,14 @@ Ray Data provides functionality for:
 Learn more about Ray Data's LLM integration:
 https://docs.ray.io/en/latest/data/working-with-llms.html
 """
+
 import ray
 from packaging.version import Version
 from ray.data.llm import build_llm_processor, vLLMEngineProcessorConfig
 
-assert Version(ray.__version__) >= Version(
-    "2.44.1"), "Ray version must be at least 2.44.1"
+assert Version(ray.__version__) >= Version("2.44.1"), (
+    "Ray version must be at least 2.44.1"
+)
 
 # Uncomment to reduce clutter in stdout
 # ray.init(log_to_driver=False)
@@ -53,20 +55,18 @@ config = vLLMEngineProcessorConfig(
 vllm_processor = build_llm_processor(
     config,
     preprocess=lambda row: dict(
-        messages=[{
-            "role": "system",
-            "content": "You are a bot that responds with haikus."
-        }, {
-            "role": "user",
-            "content": row["text"]
-        }],
+        messages=[
+            {"role": "system", "content": "You are a bot that responds with haikus."},
+            {"role": "user", "content": row["text"]},
+        ],
         sampling_params=dict(
             temperature=0.3,
             max_tokens=250,
-        )),
+        ),
+    ),
     postprocess=lambda row: dict(
         answer=row["generated_text"],
-        **row  # This will return all the original columns in the dataset.
+        **row,  # This will return all the original columns in the dataset.
     ),
 )