Fix model name included in responses

vllm/entrypoints/openai/serving_chat.py

@@ -186,7 +186,7 @@ async def create_chat_completion(
             lora_request = self._maybe_get_adapters(
                 request, supports_default_mm_loras=True)
 
-            model_name = self._get_model_name(request.model, lora_request)
+            model_name = self.models.model_name(lora_request)
 
             tokenizer = await self.engine_client.get_tokenizer(lora_request)
 

vllm/entrypoints/openai/serving_classification.py

@@ -146,7 +146,7 @@ async def create_classify(
         request: ClassificationRequest,
         raw_request: Request,
     ) -> Union[ClassificationResponse, ErrorResponse]:
-        model_name = self._get_model_name(request.model)
+        model_name = self.models.model_name()
         request_id = (f"{self.request_id_prefix}-"
                       f"{self._base_request_id(raw_request)}")
 

vllm/entrypoints/openai/serving_completion.py

@@ -232,7 +232,7 @@ async def create_completion(
 
         result_generator = merge_async_iterators(*generators)
 
-        model_name = self._get_model_name(request.model, 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

vllm/entrypoints/openai/serving_embedding.py

@@ -599,7 +599,7 @@ async def create_embedding(
         See https://platform.openai.com/docs/api-reference/embeddings/create
         for the API specification. This API mimics the OpenAI Embedding API.
         """
-        model_name = self._get_model_name(request.model)
+        model_name = self.models.model_name()
         request_id = (
             f"{self.request_id_prefix}-"
             f"{self._base_request_id(raw_request, request.request_id)}")

vllm/entrypoints/openai/serving_engine.py

@@ -980,17 +980,6 @@ def _is_model_supported(self, model_name: Optional[str]) -> bool:
             return True
         return self.models.is_base_model(model_name)
 
-    def _get_model_name(
-        self,
-        model_name: Optional[str] = None,
-        lora_request: Optional[LoRARequest] = None,
-    ) -> str:
-        if lora_request:
-            return lora_request.lora_name
-        if not model_name:
-            return self.models.base_model_paths[0].name
-        return model_name
-
 
 def clamp_prompt_logprobs(
     prompt_logprobs: Union[PromptLogprobs,

vllm/entrypoints/openai/serving_pooling.py

@@ -91,7 +91,7 @@ async def create_pooling(
         if error_check_ret is not None:
             return error_check_ret
 
-        model_name = self._get_model_name(request.model)
+        model_name = self.models.model_name()
 
         request_id = f"pool-{self._base_request_id(raw_request)}"
         created_time = int(time.time())

vllm/entrypoints/openai/serving_responses.py

@@ -237,7 +237,7 @@ async def create_responses(
 
         try:
             lora_request = self._maybe_get_adapters(request)
-            model_name = self._get_model_name(request.model, lora_request)
+            model_name = self.models.model_name(lora_request)
             tokenizer = await self.engine_client.get_tokenizer(lora_request)
 
             if self.use_harmony:

vllm/entrypoints/openai/serving_score.py

@@ -353,7 +353,7 @@ async def create_score(
                 final_res_batch,
                 request_id,
                 created_time,
-                self._get_model_name(request.model),
+                self.models.model_name(),
             )
         except asyncio.CancelledError:
             return self.create_error_response("Client disconnected")
@@ -399,7 +399,7 @@ async def do_rerank(
             return self.request_output_to_rerank_response(
                 final_res_batch,
                 request_id,
-                self._get_model_name(request.model),
+                self.models.model_name(),
                 documents,
                 top_n,
             )