[Bugfix][Refactor] Unify model management in frontend (#11660)

Signed-off-by: Joe Runde <Joseph.Runde@ibm.com>

vllm/entrypoints/openai/serving_completion.py

@@ -21,10 +21,8 @@ from vllm.entrypoints.openai.protocol import (CompletionLogProbs,
                                               RequestResponseMetadata,
                                               UsageInfo)
 # yapf: enable
-from vllm.entrypoints.openai.serving_engine import (BaseModelPath,
-                                                    LoRAModulePath,
-                                                    OpenAIServing,
-                                                    PromptAdapterPath)
+from vllm.entrypoints.openai.serving_engine import OpenAIServing
+from vllm.entrypoints.openai.serving_models import OpenAIServingModels
 from vllm.logger import init_logger
 from vllm.outputs import RequestOutput
 from vllm.sampling_params import BeamSearchParams, SamplingParams
@@ -41,18 +39,14 @@ class OpenAIServingCompletion(OpenAIServing):
         self,
         engine_client: EngineClient,
         model_config: ModelConfig,
-        base_model_paths: List[BaseModelPath],
+        models: OpenAIServingModels,
         *,
-        lora_modules: Optional[List[LoRAModulePath]],
-        prompt_adapters: Optional[List[PromptAdapterPath]],
         request_logger: Optional[RequestLogger],
         return_tokens_as_token_ids: bool = False,
     ):
         super().__init__(engine_client=engine_client,
                          model_config=model_config,
-                         base_model_paths=base_model_paths,
-                         lora_modules=lora_modules,
-                         prompt_adapters=prompt_adapters,
+                         models=models,
                          request_logger=request_logger,
                          return_tokens_as_token_ids=return_tokens_as_token_ids)
         diff_sampling_param = self.model_config.get_diff_sampling_param()
@@ -170,7 +164,7 @@ class OpenAIServingCompletion(OpenAIServing):
 
         result_generator = merge_async_iterators(*generators)
 
-        model_name = self._get_model_name(lora_request)
+        model_name = self.models.model_name(lora_request)
         num_prompts = len(engine_prompts)
 
         # Similar to the OpenAI API, when n != best_of, we do not stream the