[Bugfix][Refactor] Unify model management in frontend

tests/entrypoints/openai/test_cli_args.py

@@ -4,7 +4,7 @@
 
 from vllm.entrypoints.openai.cli_args import (make_arg_parser,
                                               validate_parsed_serve_args)
-from vllm.entrypoints.openai.serving_engine import LoRAModulePath
+from vllm.entrypoints.openai.serving_models import LoRAModulePath
 from vllm.utils import FlexibleArgumentParser
 
 from ...utils import VLLM_PATH

tests/entrypoints/openai/test_lora_lineage.py

@@ -55,7 +55,10 @@ def server_with_lora_modules_json(zephyr_lora_files):
         "64",
     ]
 
-    with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
+    # Enable the /v1/load_lora_adapter endpoint
+    envs = {"VLLM_ALLOW_RUNTIME_LORA_UPDATING": "True"}
+
+    with RemoteOpenAIServer(MODEL_NAME, args, env_dict=envs) as remote_server:
         yield remote_server
 
 
@@ -67,8 +70,8 @@ async def client_for_lora_lineage(server_with_lora_modules_json):
 
 
 @pytest.mark.asyncio
-async def test_check_lora_lineage(client_for_lora_lineage: openai.AsyncOpenAI,
-                                  zephyr_lora_files):
+async def test_static_lora_lineage(client_for_lora_lineage: openai.AsyncOpenAI,
+                                   zephyr_lora_files):
     models = await client_for_lora_lineage.models.list()
     models = models.data
     served_model = models[0]
@@ -81,3 +84,26 @@ async def test_check_lora_lineage(client_for_lora_lineage: openai.AsyncOpenAI,
     assert all(lora_model.parent == MODEL_NAME for lora_model in lora_models)
     assert lora_models[0].id == "zephyr-lora"
     assert lora_models[1].id == "zephyr-lora2"
+
+
+@pytest.mark.asyncio
+async def test_dynamic_lora_lineage(
+        client_for_lora_lineage: openai.AsyncOpenAI, zephyr_lora_files):
+
+    response = await client_for_lora_lineage.post("load_lora_adapter",
+                                                  cast_to=str,
+                                                  body={
+                                                      "lora_name":
+                                                      "zephyr-lora-3",
+                                                      "lora_path":
+                                                      zephyr_lora_files
+                                                  })
+    # Ensure adapter loads before querying /models
+    assert "success" in response
+
+    models = await client_for_lora_lineage.models.list()
+    models = models.data
+    dynamic_lora_model = models[-1]
+    assert dynamic_lora_model.root == zephyr_lora_files
+    assert dynamic_lora_model.parent == MODEL_NAME
+    assert dynamic_lora_model.id == "zephyr-lora-3"

tests/entrypoints/openai/test_serving_chat.py

@@ -8,7 +8,8 @@
 from vllm.engine.multiprocessing.client import MQLLMEngineClient
 from vllm.entrypoints.openai.protocol import ChatCompletionRequest
 from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
-from vllm.entrypoints.openai.serving_engine import BaseModelPath
+from vllm.entrypoints.openai.serving_models import (BaseModelPath,
+                                                    OpenAIServingModels)
 from vllm.transformers_utils.tokenizer import get_tokenizer
 
 MODEL_NAME = "openai-community/gpt2"
@@ -50,14 +51,13 @@ async def _async_serving_chat_init():
     engine = MockEngine()
     model_config = await engine.get_model_config()
 
+    models = OpenAIServingModels(model_config, BASE_MODEL_PATHS)
     serving_completion = OpenAIServingChat(engine,
                                            model_config,
-                                           BASE_MODEL_PATHS,
+                                           models,
                                            response_role="assistant",
                                            chat_template=CHAT_TEMPLATE,
                                            chat_template_content_format="auto",
-                                           lora_modules=None,
-                                           prompt_adapters=None,
                                            request_logger=None)
     return serving_completion
 
@@ -72,14 +72,14 @@ def test_serving_chat_should_set_correct_max_tokens():
     mock_engine.get_tokenizer.return_value = get_tokenizer(MODEL_NAME)
     mock_engine.errored = False
 
+    models = OpenAIServingModels(base_model_paths=BASE_MODEL_PATHS,
+                                 model_config=MockModelConfig())
     serving_chat = OpenAIServingChat(mock_engine,
                                      MockModelConfig(),
-                                     BASE_MODEL_PATHS,
+                                     models,
                                      response_role="assistant",
                                      chat_template=CHAT_TEMPLATE,
                                      chat_template_content_format="auto",
-                                     lora_modules=None,
-                                     prompt_adapters=None,
                                      request_logger=None)
     req = ChatCompletionRequest(
         model=MODEL_NAME,
@@ -115,14 +115,14 @@ def test_serving_chat_could_load_correct_generation_config():
     mock_engine.errored = False
 
     # Initialize the serving chat
+    models = OpenAIServingModels(base_model_paths=BASE_MODEL_PATHS,
+                                 model_config=mock_model_config)
     serving_chat = OpenAIServingChat(mock_engine,
                                      mock_model_config,
-                                     BASE_MODEL_PATHS,
+                                     models,
                                      response_role="assistant",
                                      chat_template=CHAT_TEMPLATE,
                                      chat_template_content_format="auto",
-                                     lora_modules=None,
-                                     prompt_adapters=None,
                                      request_logger=None)
     req = ChatCompletionRequest(
         model=MODEL_NAME,

tests/entrypoints/openai/test_serving_engine.py → tests/entrypoints/openai/test_serving_models.py

@@ -4,11 +4,11 @@
 import pytest
 
 from vllm.config import ModelConfig
-from vllm.engine.protocol import EngineClient
 from vllm.entrypoints.openai.protocol import (ErrorResponse,
                                               LoadLoraAdapterRequest,
                                               UnloadLoraAdapterRequest)
-from vllm.entrypoints.openai.serving_engine import BaseModelPath, OpenAIServing
+from vllm.entrypoints.openai.serving_models import (BaseModelPath,
+                                                    OpenAIServingModels)
 from vllm.lora.request import LoRARequest
 
 MODEL_NAME = "meta-llama/Llama-2-7b"
@@ -19,101 +19,99 @@
     "Success: LoRA adapter '{lora_name}' removed successfully.")
 
 
-async def _async_serving_engine_init():
-    mock_engine_client = MagicMock(spec=EngineClient)
+async def _async_serving_models_init() -> OpenAIServingModels:
     mock_model_config = MagicMock(spec=ModelConfig)
     # Set the max_model_len attribute to avoid missing attribute
     mock_model_config.max_model_len = 2048
 
-    serving_engine = OpenAIServing(mock_engine_client,
-                                   mock_model_config,
-                                   BASE_MODEL_PATHS,
-                                   lora_modules=None,
-                                   prompt_adapters=None,
-                                   request_logger=None)
-    return serving_engine
+    serving_models = OpenAIServingModels(base_model_paths=BASE_MODEL_PATHS,
+                                         model_config=mock_model_config,
+                                         lora_modules=None,
+                                         prompt_adapters=None)
+
+    return serving_models
 
 
 @pytest.mark.asyncio
 async def test_serving_model_name():
-    serving_engine = await _async_serving_engine_init()
-    assert serving_engine._get_model_name(None) == MODEL_NAME
+    serving_models = await _async_serving_models_init()
+    assert serving_models.model_name(None) == MODEL_NAME
     request = LoRARequest(lora_name="adapter",
                           lora_path="/path/to/adapter2",
                           lora_int_id=1)
-    assert serving_engine._get_model_name(request) == request.lora_name
+    assert serving_models.model_name(request) == request.lora_name
 
 
 @pytest.mark.asyncio
 async def test_load_lora_adapter_success():
-    serving_engine = await _async_serving_engine_init()
+    serving_models = await _async_serving_models_init()
     request = LoadLoraAdapterRequest(lora_name="adapter",
                                      lora_path="/path/to/adapter2")
-    response = await serving_engine.load_lora_adapter(request)
+    response = await serving_models.load_lora_adapter(request)
     assert response == LORA_LOADING_SUCCESS_MESSAGE.format(lora_name='adapter')
-    assert len(serving_engine.lora_requests) == 1
-    assert serving_engine.lora_requests[0].lora_name == "adapter"
+    assert len(serving_models.lora_requests) == 1
+    assert serving_models.lora_requests[0].lora_name == "adapter"
 
 
 @pytest.mark.asyncio
 async def test_load_lora_adapter_missing_fields():
-    serving_engine = await _async_serving_engine_init()
+    serving_models = await _async_serving_models_init()
     request = LoadLoraAdapterRequest(lora_name="", lora_path="")
-    response = await serving_engine.load_lora_adapter(request)
+    response = await serving_models.load_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
     assert response.type == "InvalidUserInput"
     assert response.code == HTTPStatus.BAD_REQUEST
 
 
 @pytest.mark.asyncio
 async def test_load_lora_adapter_duplicate():
-    serving_engine = await _async_serving_engine_init()
+    serving_models = await _async_serving_models_init()
     request = LoadLoraAdapterRequest(lora_name="adapter1",
                                      lora_path="/path/to/adapter1")
-    response = await serving_engine.load_lora_adapter(request)
+    response = await serving_models.load_lora_adapter(request)
     assert response == LORA_LOADING_SUCCESS_MESSAGE.format(
         lora_name='adapter1')
-    assert len(serving_engine.lora_requests) == 1
+    assert len(serving_models.lora_requests) == 1
 
     request = LoadLoraAdapterRequest(lora_name="adapter1",
                                      lora_path="/path/to/adapter1")
-    response = await serving_engine.load_lora_adapter(request)
+    response = await serving_models.load_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
     assert response.type == "InvalidUserInput"
     assert response.code == HTTPStatus.BAD_REQUEST
-    assert len(serving_engine.lora_requests) == 1
+    assert len(serving_models.lora_requests) == 1
 
 
 @pytest.mark.asyncio
 async def test_unload_lora_adapter_success():
-    serving_engine = await _async_serving_engine_init()
+    serving_models = await _async_serving_models_init()
     request = LoadLoraAdapterRequest(lora_name="adapter1",
                                      lora_path="/path/to/adapter1")
-    response = await serving_engine.load_lora_adapter(request)
-    assert len(serving_engine.lora_requests) == 1
+    response = await serving_models.load_lora_adapter(request)
+    assert len(serving_models.lora_requests) == 1
 
     request = UnloadLoraAdapterRequest(lora_name="adapter1")
-    response = await serving_engine.unload_lora_adapter(request)
+    response = await serving_models.unload_lora_adapter(request)
     assert response == LORA_UNLOADING_SUCCESS_MESSAGE.format(
         lora_name='adapter1')
-    assert len(serving_engine.lora_requests) == 0
+    assert len(serving_models.lora_requests) == 0
 
 
 @pytest.mark.asyncio
 async def test_unload_lora_adapter_missing_fields():
-    serving_engine = await _async_serving_engine_init()
+    serving_models = await _async_serving_models_init()
     request = UnloadLoraAdapterRequest(lora_name="", lora_int_id=None)
-    response = await serving_engine.unload_lora_adapter(request)
+    response = await serving_models.unload_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
     assert response.type == "InvalidUserInput"
     assert response.code == HTTPStatus.BAD_REQUEST
 
 
 @pytest.mark.asyncio
 async def test_unload_lora_adapter_not_found():
-    serving_engine = await _async_serving_engine_init()
+    serving_models = await _async_serving_models_init()
     request = UnloadLoraAdapterRequest(lora_name="nonexistent_adapter")
-    response = await serving_engine.unload_lora_adapter(request)
+    response = await serving_models.unload_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
     assert response.type == "InvalidUserInput"
     assert response.code == HTTPStatus.BAD_REQUEST