Add vLLM v0.18.1 source tree with KV transfer abort fix

third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:

  vllm/v1/core/sched/scheduler.py:
    Replace fatal assert with graceful skip when KV transfer callback
    arrives for an already-aborted request during PD disaggregated serving.

Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

third_party/vllm/tests/entrypoints/openai/test_serving_models.py

@@ -0,0 +1,133 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from http import HTTPStatus
+from unittest.mock import MagicMock
+
+import pytest
+
+from vllm.config import ModelConfig
+from vllm.engine.protocol import EngineClient
+from vllm.entrypoints.openai.engine.protocol import (
+    ErrorResponse,
+)
+from vllm.entrypoints.openai.models.protocol import BaseModelPath
+from vllm.entrypoints.openai.models.serving import OpenAIServingModels
+from vllm.entrypoints.serve.lora.protocol import (
+    LoadLoRAAdapterRequest,
+    UnloadLoRAAdapterRequest,
+)
+from vllm.lora.request import LoRARequest
+
+MODEL_NAME = "hmellor/tiny-random-LlamaForCausalLM"
+BASE_MODEL_PATHS = [BaseModelPath(name=MODEL_NAME, model_path=MODEL_NAME)]
+LORA_LOADING_SUCCESS_MESSAGE = "Success: LoRA adapter '{lora_name}' added successfully."
+LORA_UNLOADING_SUCCESS_MESSAGE = (
+    "Success: LoRA adapter '{lora_name}' removed successfully."
+)
+
+
+async def _async_serving_models_init() -> OpenAIServingModels:
+    mock_engine_client = MagicMock(spec=EngineClient)
+    # Set the max_model_len attribute to avoid missing attribute
+    mock_model_config = MagicMock(spec=ModelConfig)
+    mock_model_config.max_model_len = 2048
+    mock_engine_client.model_config = mock_model_config
+    mock_engine_client.input_processor = MagicMock()
+    mock_engine_client.io_processor = MagicMock()
+    mock_engine_client.renderer = MagicMock()
+
+    serving_models = OpenAIServingModels(
+        engine_client=mock_engine_client,
+        base_model_paths=BASE_MODEL_PATHS,
+        lora_modules=None,
+    )
+    await serving_models.init_static_loras()
+
+    return serving_models
+
+
+@pytest.mark.asyncio
+async def test_serving_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_models.model_name(request) == request.lora_name
+
+
+@pytest.mark.asyncio
+async def test_load_lora_adapter_success():
+    serving_models = await _async_serving_models_init()
+    request = LoadLoRAAdapterRequest(lora_name="adapter", lora_path="/path/to/adapter2")
+    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 "adapter" in serving_models.lora_requests
+    assert serving_models.lora_requests["adapter"].lora_name == "adapter"
+
+
+@pytest.mark.asyncio
+async def test_load_lora_adapter_missing_fields():
+    serving_models = await _async_serving_models_init()
+    request = LoadLoRAAdapterRequest(lora_name="", lora_path="")
+    response = await serving_models.load_lora_adapter(request)
+    assert isinstance(response, ErrorResponse)
+    assert response.error.type == "InvalidUserInput"
+    assert response.error.code == HTTPStatus.BAD_REQUEST
+
+
+@pytest.mark.asyncio
+async def test_load_lora_adapter_duplicate():
+    serving_models = await _async_serving_models_init()
+    request = LoadLoRAAdapterRequest(
+        lora_name="adapter1", lora_path="/path/to/adapter1"
+    )
+    response = await serving_models.load_lora_adapter(request)
+    assert response == LORA_LOADING_SUCCESS_MESSAGE.format(lora_name="adapter1")
+    assert len(serving_models.lora_requests) == 1
+
+    request = LoadLoRAAdapterRequest(
+        lora_name="adapter1", lora_path="/path/to/adapter1"
+    )
+    response = await serving_models.load_lora_adapter(request)
+    assert isinstance(response, ErrorResponse)
+    assert response.error.type == "InvalidUserInput"
+    assert response.error.code == HTTPStatus.BAD_REQUEST
+    assert len(serving_models.lora_requests) == 1
+
+
+@pytest.mark.asyncio
+async def test_unload_lora_adapter_success():
+    serving_models = await _async_serving_models_init()
+    request = LoadLoRAAdapterRequest(
+        lora_name="adapter1", lora_path="/path/to/adapter1"
+    )
+    response = await serving_models.load_lora_adapter(request)
+    assert len(serving_models.lora_requests) == 1
+
+    request = UnloadLoRAAdapterRequest(lora_name="adapter1")
+    response = await serving_models.unload_lora_adapter(request)
+    assert response == LORA_UNLOADING_SUCCESS_MESSAGE.format(lora_name="adapter1")
+    assert len(serving_models.lora_requests) == 0
+
+
+@pytest.mark.asyncio
+async def test_unload_lora_adapter_missing_fields():
+    serving_models = await _async_serving_models_init()
+    request = UnloadLoRAAdapterRequest(lora_name="", lora_int_id=None)
+    response = await serving_models.unload_lora_adapter(request)
+    assert isinstance(response, ErrorResponse)
+    assert response.error.type == "InvalidUserInput"
+    assert response.error.code == HTTPStatus.BAD_REQUEST
+
+
+@pytest.mark.asyncio
+async def test_unload_lora_adapter_not_found():
+    serving_models = await _async_serving_models_init()
+    request = UnloadLoRAAdapterRequest(lora_name="nonexistent_adapter")
+    response = await serving_models.unload_lora_adapter(request)
+    assert isinstance(response, ErrorResponse)
+    assert response.error.type == "NotFoundError"
+    assert response.error.code == HTTPStatus.NOT_FOUND