# SPDX-License-Identifier: Apache-2.0 import asyncio from contextlib import ExitStack from typing import List, Optional, Tuple import pytest from tests.v1.engine.utils import PLP_APC_UNSUPPORTED_MSG from vllm import SamplingParams from vllm.engine.arg_utils import AsyncEngineArgs from vllm.platforms import current_platform from vllm.sampling_params import RequestOutputKind from vllm.v1.engine.async_llm import AsyncLLM if not current_platform.is_cuda(): pytest.skip(reason="V1 currently only supported on CUDA.", allow_module_level=True) ENGINE_ARGS = AsyncEngineArgs(model="meta-llama/Llama-3.2-1B-Instruct", enforce_eager=True, disable_log_requests=True) async def generate(engine: AsyncLLM, request_id: str, output_kind: RequestOutputKind, max_tokens: int, prompt_logprobs: Optional[int] = None) -> Tuple[int, str]: # Ensure generate doesn't complete too fast for cancellation test. await asyncio.sleep(0.2) count = 0 sampling_params = SamplingParams(max_tokens=max_tokens, output_kind=output_kind, temperature=0, prompt_logprobs=prompt_logprobs) async for out in engine.generate(request_id=request_id, prompt="Hello my name is Robert and", sampling_params=sampling_params): num_tokens = len(out.outputs[0].token_ids) if output_kind == RequestOutputKind.DELTA: count += num_tokens else: count = num_tokens await asyncio.sleep(0.) return count, request_id @pytest.mark.parametrize( "output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY]) @pytest.mark.asyncio async def test_async_llm_refuses_prompt_logprobs_with_apc( monkeypatch, output_kind: RequestOutputKind): """Test passes if AsyncLLM raises an exception when it is configured for automatic prefix caching and it receives a request with prompt_logprobs enabled, which is incompatible.""" # TODO(rickyx): Remove monkeypatch VLLM_USE_V1 setting once we have a # better way to test V1 so that in the future when we switch, we don't # have to change all the tests. monkeypatch.setenv("VLLM_USE_V1", "1") # Create AsyncLLM engine with APC apc_engine_args = AsyncEngineArgs(model="facebook/opt-125m", enable_prefix_caching=True, gpu_memory_utilization=0.8, disable_log_requests=True) engine = AsyncLLM.from_engine_args(apc_engine_args) try: with pytest.raises(ValueError) as excinfo: # Issue a request with prompt logprobs enabled, which should fail await asyncio.create_task( generate(engine, "request-0", output_kind, 10, prompt_logprobs=5)) # Validate exception string is correct assert str(excinfo.value) == PLP_APC_UNSUPPORTED_MSG finally: # Shut down engine engine.shutdown() @pytest.mark.parametrize( "output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY]) @pytest.mark.asyncio async def test_load(monkeypatch, output_kind: RequestOutputKind): # TODO(rickyx): Remove monkeypatch once we have a better way to test V1 # so that in the future when we switch, we don't have to change all the # tests. with monkeypatch.context() as m, ExitStack() as after: m.setenv("VLLM_USE_V1", "1") engine = AsyncLLM.from_engine_args(ENGINE_ARGS) after.callback(engine.shutdown) NUM_REQUESTS = 10000 NUM_EXPECTED_TOKENS = 10 request_ids = [f"request-{i}" for i in range(NUM_REQUESTS)] # Create concurrent requests. tasks = [] for request_id in request_ids: tasks.append( asyncio.create_task( generate(engine, request_id, output_kind, NUM_EXPECTED_TOKENS))) # Confirm that we got all the EXPECTED tokens from the requests. done, pending = await asyncio.wait(tasks, return_when=asyncio.FIRST_EXCEPTION) for task in pending: task.cancel() for task in done: num_generated_tokens, request_id = await task assert num_generated_tokens == NUM_EXPECTED_TOKENS, ( f"{request_id} generated {num_generated_tokens} but " f"expected {NUM_EXPECTED_TOKENS}") assert not engine.output_processor.has_unfinished_requests() @pytest.mark.parametrize( "output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY]) @pytest.mark.asyncio async def test_abort(monkeypatch, output_kind: RequestOutputKind): with monkeypatch.context() as m, ExitStack() as after: m.setenv("VLLM_USE_V1", "1") engine = AsyncLLM.from_engine_args(ENGINE_ARGS) after.callback(engine.shutdown) NUM_REQUESTS = 100 NUM_EXPECTED_TOKENS = 100 REQUEST_IDS_TO_ABORT = range(1, 100, 10) request_ids = [f"request-{i}" for i in range(NUM_REQUESTS)] # Create concurrent requests. tasks: List[asyncio.Task] = [] for request_id in request_ids: tasks.append( asyncio.create_task( generate(engine, request_id, output_kind, NUM_EXPECTED_TOKENS))) # API server cancels requests when they disconnect. for idx in REQUEST_IDS_TO_ABORT: tasks[idx].cancel() await asyncio.sleep(0.1) # Confirm the other requests are okay. for idx, task in enumerate(tasks): # Confirm that it was actually canceled. if idx in REQUEST_IDS_TO_ABORT: with pytest.raises(asyncio.CancelledError): await task else: # Otherwise, make sure the request was not impacted. num_generated_tokens, request_id = await task assert num_generated_tokens == NUM_EXPECTED_TOKENS, ( f"{request_id} generated {num_generated_tokens} but " f"expected {NUM_EXPECTED_TOKENS}") assert not engine.output_processor.has_unfinished_requests() # Confirm we can do another generation. request_id = f"request-{REQUEST_IDS_TO_ABORT[0]}" task = asyncio.create_task( generate(engine, request_id, output_kind, NUM_EXPECTED_TOKENS)) num_generated_tokens, request_id = await task assert num_generated_tokens == NUM_EXPECTED_TOKENS assert not engine.output_processor.has_unfinished_requests()