[tech debt] Revisit lora request model checker (#20636)

Signed-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>

tests/entrypoints/openai/test_serving_models.py

@@ -57,7 +57,8 @@ async def test_load_lora_adapter_success():
     response = await serving_models.load_lora_adapter(request)
     assert response == LORA_LOADING_SUCCESS_MESSAGE.format(lora_name='adapter')
     assert len(serving_models.lora_requests) == 1
-    assert serving_models.lora_requests[0].lora_name == "adapter"
+    assert "adapter" in serving_models.lora_requests
+    assert serving_models.lora_requests["adapter"].lora_name == "adapter"
 
 
 @pytest.mark.asyncio

vllm/entrypoints/openai/serving_engine.py

@@ -438,9 +438,7 @@ class OpenAIServing:
 
         if self._is_model_supported(request.model):
             return None
-        if request.model in [
-                lora.lora_name for lora in self.models.lora_requests
-        ]:
+        if request.model in self.models.lora_requests:
             return None
         if envs.VLLM_ALLOW_RUNTIME_LORA_UPDATING and request.model and (
                 load_result := await self.models.resolve_lora(request.model)):
@@ -466,9 +464,8 @@ class OpenAIServing:
             None, PromptAdapterRequest]]:
         if self._is_model_supported(request.model):
             return None, None
-        for lora in self.models.lora_requests:
-            if request.model == lora.lora_name:
-                return lora, None
+        if request.model in self.models.lora_requests:
+            return self.models.lora_requests[request.model], None
         for prompt_adapter in self.models.prompt_adapter_requests:
             if request.model == prompt_adapter.prompt_adapter_name:
                 return None, prompt_adapter

vllm/entrypoints/openai/serving_models.py

@@ -65,12 +65,13 @@ class OpenAIServingModels:
         super().__init__()
 
         self.base_model_paths = base_model_paths
+
         self.max_model_len = model_config.max_model_len
         self.engine_client = engine_client
         self.model_config = model_config
 
         self.static_lora_modules = lora_modules
-        self.lora_requests: list[LoRARequest] = []
+        self.lora_requests: dict[str, LoRARequest] = {}
         self.lora_id_counter = AtomicCounter(0)
 
         self.lora_resolvers: list[LoRAResolver] = []
@@ -138,7 +139,7 @@ class OpenAIServingModels:
                       parent=lora.base_model_name if lora.base_model_name else
                       self.base_model_paths[0].name,
                       permission=[ModelPermission()])
-            for lora in self.lora_requests
+            for lora in self.lora_requests.values()
         ]
         prompt_adapter_cards = [
             ModelCard(id=prompt_adapter.prompt_adapter_name,
@@ -155,23 +156,29 @@ class OpenAIServingModels:
             request: LoadLoRAAdapterRequest,
             base_model_name: Optional[str] = None
     ) -> Union[ErrorResponse, str]:
-        error_check_ret = await self._check_load_lora_adapter_request(request)
+        lora_name = request.lora_name
+
+        # Ensure atomicity based on the lora name
+        async with self.lora_resolver_lock[lora_name]:
+            error_check_ret = await self._check_load_lora_adapter_request(
+                request)
             if error_check_ret is not None:
                 return error_check_ret
 
-        lora_name, lora_path = request.lora_name, request.lora_path
+            lora_path = request.lora_path
             unique_id = self.lora_id_counter.inc(1)
             lora_request = LoRARequest(lora_name=lora_name,
                                        lora_int_id=unique_id,
                                        lora_path=lora_path)
-        if base_model_name is not None and self.is_base_model(base_model_name):
+            if base_model_name is not None and self.is_base_model(
+                    base_model_name):
                 lora_request.base_model_name = base_model_name
 
             # Validate that the adapter can be loaded into the engine
             # This will also pre-load it for incoming requests
             try:
                 await self.engine_client.add_lora(lora_request)
-        except BaseException as e:
+            except Exception as e:
                 error_type = "BadRequestError"
                 status_code = HTTPStatus.BAD_REQUEST
                 if "No adapter found" in str(e):
@@ -182,24 +189,25 @@ class OpenAIServingModels:
                                              err_type=error_type,
                                              status_code=status_code)
 
-        self.lora_requests.append(lora_request)
-        logger.info("Loaded new LoRA adapter: name '%s', path '%s'", lora_name,
-                    lora_path)
+            self.lora_requests[lora_name] = lora_request
+            logger.info("Loaded new LoRA adapter: name '%s', path '%s'",
+                        lora_name, lora_path)
             return f"Success: LoRA adapter '{lora_name}' added successfully."
 
     async def unload_lora_adapter(
             self,
             request: UnloadLoRAAdapterRequest) -> Union[ErrorResponse, str]:
-        error_check_ret = await self._check_unload_lora_adapter_request(request
-                                                                        )
+        lora_name = request.lora_name
+
+        # Ensure atomicity based on the lora name
+        async with self.lora_resolver_lock[lora_name]:
+            error_check_ret = await self._check_unload_lora_adapter_request(
+                request)
             if error_check_ret is not None:
                 return error_check_ret
 
-        lora_name = request.lora_name
-        self.lora_requests = [
-            lora_request for lora_request in self.lora_requests
-            if lora_request.lora_name != lora_name
-        ]
+            # Safe to delete now since we hold the lock
+            del self.lora_requests[lora_name]
             logger.info("Removed LoRA adapter: name '%s'", lora_name)
             return f"Success: LoRA adapter '{lora_name}' removed successfully."
 
@@ -213,8 +221,7 @@ class OpenAIServingModels:
                 status_code=HTTPStatus.BAD_REQUEST)
 
         # Check if the lora adapter with the given name already exists
-        if any(lora_request.lora_name == request.lora_name
-               for lora_request in self.lora_requests):
+        if request.lora_name in self.lora_requests:
             return create_error_response(
                 message=
                 f"The lora adapter '{request.lora_name}' has already been "
@@ -227,17 +234,16 @@ class OpenAIServingModels:
     async def _check_unload_lora_adapter_request(
             self,
             request: UnloadLoRAAdapterRequest) -> Optional[ErrorResponse]:
-        # Check if either 'lora_name' or 'lora_int_id' is provided
-        if not request.lora_name and not request.lora_int_id:
+        # Check if 'lora_name' is not provided return an error
+        if not request.lora_name:
             return create_error_response(
                 message=
-                "either 'lora_name' and 'lora_int_id' needs to be provided.",
+                "'lora_name' needs to be provided to unload a LoRA adapter.",
                 err_type="InvalidUserInput",
                 status_code=HTTPStatus.BAD_REQUEST)
 
         # Check if the lora adapter with the given name exists
-        if not any(lora_request.lora_name == request.lora_name
-                   for lora_request in self.lora_requests):
+        if request.lora_name not in self.lora_requests:
             return create_error_response(
                 message=
                 f"The lora adapter '{request.lora_name}' cannot be found.",
@@ -260,9 +266,8 @@ class OpenAIServingModels:
         """
         async with self.lora_resolver_lock[lora_name]:
             # First check if this LoRA is already loaded
-            for existing in self.lora_requests:
-                if existing.lora_name == lora_name:
-                    return existing
+            if lora_name in self.lora_requests:
+                return self.lora_requests[lora_name]
 
             base_model_name = self.model_config.model
             unique_id = self.lora_id_counter.inc(1)
@@ -279,7 +284,7 @@ class OpenAIServingModels:
 
                     try:
                         await self.engine_client.add_lora(lora_request)
-                        self.lora_requests.append(lora_request)
+                        self.lora_requests[lora_name] = lora_request
                         logger.info(
                             "Resolved and loaded LoRA adapter '%s' using %s",
                             lora_name, resolver.__class__.__name__)