[Refactor] Pass full VllmConfig to Renderer (#34485)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

tests/entrypoints/openai/test_serving_chat.py

@@ -534,11 +534,16 @@ class MockModelConfig:
         return self.diff_sampling_param or {}
 
 
+@dataclass
+class MockVllmConfig:
+    model_config: MockModelConfig
+
+
 def _build_renderer(model_config: MockModelConfig):
     _, tokenizer_name, _, kwargs = tokenizer_args_from_config(model_config)
 
     return HfRenderer(
-        model_config,
+        MockVllmConfig(model_config),
         tokenizer_kwargs={**kwargs, "tokenizer_name": tokenizer_name},
     )
 
@@ -749,7 +754,10 @@ async def test_serving_chat_mistral_token_ids_prompt_is_validated():
     mock_engine.io_processor = MagicMock()
 
     mock_tokenizer = MagicMock(spec=MistralTokenizer)
-    mock_renderer = MistralRenderer(mock_engine.model_config, tokenizer_kwargs={})
+    mock_renderer = MistralRenderer(
+        MockVllmConfig(mock_engine.model_config),
+        tokenizer_kwargs={},
+    )
     mock_renderer._tokenizer = mock_tokenizer
     # Force the Mistral chat template renderer to return token IDs.
     # Choose a prompt length that is < max_model_len, but large enough that
@@ -788,7 +796,10 @@ async def test_serving_chat_mistral_token_ids_prompt_too_long_is_rejected():
     mock_engine.io_processor = MagicMock()
 
     mock_tokenizer = MagicMock(spec=MistralTokenizer)
-    mock_renderer = MistralRenderer(mock_engine.model_config, tokenizer_kwargs={})
+    mock_renderer = MistralRenderer(
+        MockVllmConfig(mock_engine.model_config),
+        tokenizer_kwargs={},
+    )
     mock_renderer._tokenizer = mock_tokenizer
     # prompt_token_ids length == max_model_len should be rejected for
     # completion-like requests (ChatCompletionRequest).