[CI][RFC] Replace black-jupyter with ruff-format (#37210)

Co-authored-by: Alison Shao <a.shao@wustl.edu>

examples/runtime/engine/fastapi_engine_inference.py

@@ -130,7 +130,7 @@ def send_requests(server_url, prompts, max_new_tokens, temperature):
     """Sends generation requests to the running server for a list of prompts."""
     # Iterate through prompts and send requests
     for i, prompt in enumerate(prompts):
-        print(f"\n[{i+1}/{len(prompts)}] Sending prompt: '{prompt}'")
+        print(f"\n[{i + 1}/{len(prompts)}] Sending prompt: '{prompt}'")
         payload = {
             "prompt": prompt,
             "max_new_tokens": max_new_tokens,

examples/runtime/engine/offline_batch_inference_qwen_1m.py

@@ -17,8 +17,7 @@ def load_prompt() -> str:
     # https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/1m.txt
 
     with urlopen(
-        "https://qianwen-res.oss-cn-beijing.aliyuncs.com"
-        "/Qwen2.5-1M/test-data/64k.txt",
+        "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/64k.txt",
         timeout=5,
     ) as response:
         prompt = response.read().decode("utf-8")
@@ -41,9 +40,7 @@ def process_requests(llm: sgl.Engine, prompts: list[str]) -> None:
     for output in outputs:
         prompt_token_ids = output["meta_info"]["prompt_tokens"]
         generated_text = output["text"]
-        print(
-            f"Prompt length: {prompt_token_ids}, " f"Generated text: {generated_text!r}"
-        )
+        print(f"Prompt length: {prompt_token_ids}, Generated text: {generated_text!r}")
 
 
 # Create an LLM.

examples/runtime/qwen3_vl_reranker.py

@@ -44,7 +44,7 @@ def rerank_text_only():
 
     print("Results (sorted by relevance):")
     for i, result in enumerate(results):
-        print(f"  {i+1}. Score: {result['score']:.4f} - {result['document'][:60]}...")
+        print(f"  {i + 1}. Score: {result['score']:.4f} - {result['document'][:60]}...")
     print()
 
 
@@ -99,7 +99,7 @@ def rerank_with_images():
 
     print("Results (sorted by relevance):")
     for i, result in enumerate(results):
-        print(f"  {i+1}. Index: {result['index']}, Score: {result['score']:.4f}")
+        print(f"  {i + 1}. Index: {result['index']}, Score: {result['score']:.4f}")
     print()
 
 
@@ -149,7 +149,7 @@ def rerank_multimodal_query():
 
     print("Results (sorted by relevance):")
     for i, result in enumerate(results):
-        print(f"  {i+1}. Index: {result['index']}, Score: {result['score']:.4f}")
+        print(f"  {i + 1}. Index: {result['index']}, Score: {result['score']:.4f}")
     print()