vllm/tests/entrypoints/openai/test_serving_models.py
Russell Bryant e489ad7a21
[Misc] Add SPDX-License-Identifier headers to python source files (#12628)
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**

commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:18:24 2025 -0500

    Add SPDX license headers to python source files
    
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
    also be easily used by tools to help manage license compliance.
    
The Linux Foundation runs license scans against the codebase to help
ensure
    we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
    
    More information can be found on the SPDX site:
    
    - https://spdx.dev/learn/handling-license-info/
    
    Signed-off-by: Russell Bryant <rbryant@redhat.com>

commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:36:32 2025 -0500

    Check for SPDX headers using pre-commit
    
    Signed-off-by: Russell Bryant <rbryant@redhat.com>

---------

Signed-off-by: Russell Bryant <rbryant@redhat.com>
2025-02-02 11:58:18 -08:00

124 lines
5.1 KiB
Python

# SPDX-License-Identifier: Apache-2.0
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.protocol import (ErrorResponse,
LoadLoraAdapterRequest,
UnloadLoraAdapterRequest)
from vllm.entrypoints.openai.serving_models import (BaseModelPath,
OpenAIServingModels)
from vllm.lora.request import LoRARequest
MODEL_NAME = "meta-llama/Llama-2-7b"
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_model_config = MagicMock(spec=ModelConfig)
mock_engine_client = MagicMock(spec=EngineClient)
# Set the max_model_len attribute to avoid missing attribute
mock_model_config.max_model_len = 2048
serving_models = OpenAIServingModels(engine_client=mock_engine_client,
base_model_paths=BASE_MODEL_PATHS,
model_config=mock_model_config,
lora_modules=None,
prompt_adapters=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 serving_models.lora_requests[0].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.type == "InvalidUserInput"
assert response.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.type == "InvalidUserInput"
assert response.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.type == "InvalidUserInput"
assert response.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.type == "NotFoundError"
assert response.code == HTTPStatus.NOT_FOUND