Sync from v0.13

tests/v1/shutdown/test_processor_error.py

@@ -0,0 +1,71 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Test error handling in Processor. Should not impact other reqs."""
+
+import asyncio
+
+import pytest
+
+from tests.v1.shutdown.utils import SHUTDOWN_TEST_TIMEOUT_SEC
+from vllm import SamplingParams
+from vllm.engine.arg_utils import AsyncEngineArgs
+from vllm.inputs.data import TokensPrompt
+from vllm.sampling_params import RequestOutputKind
+from vllm.v1.engine.async_llm import AsyncLLM
+from vllm.v1.engine.exceptions import EngineGenerateError
+
+MODELS = ["meta-llama/Llama-3.2-1B"]
+
+
+@pytest.mark.asyncio
+@pytest.mark.timeout(SHUTDOWN_TEST_TIMEOUT_SEC)
+@pytest.mark.parametrize("model", MODELS)
+async def test_async_llm_processor_error(model: str) -> None:
+    """Test that AsyncLLM propagates a processor error.
+    Test empty tokens prompt (failure) and non-empty prompt (no failure.)
+    AsyncLLM always uses an MP client.
+    """
+    engine_args = AsyncEngineArgs(model=model, enforce_eager=True)
+    async_llm = AsyncLLM.from_engine_args(engine_args)
+
+    async def generate(request_id: str):
+        # [] is not allowed and will raise a ValueError in Processor.
+        generator = async_llm.generate(
+            TokensPrompt([]), request_id=request_id, sampling_params=SamplingParams()
+        )
+        try:
+            async for _ in generator:
+                pass
+        except Exception as e:
+            return e
+
+    NUM_REQS = 3
+    tasks = [generate(f"request-{idx}") for idx in range(NUM_REQS)]
+    outputs = await asyncio.gather(*tasks)
+
+    # Every request should have get an EngineGenerateError.
+    for output in outputs:
+        with pytest.raises(EngineGenerateError):
+            raise output
+
+    # AsyncLLM should be errored.
+    assert not async_llm.errored
+
+    # This should be no problem.
+    EXPECTED_TOKENS = 5
+    outputs = []
+    async for out in async_llm.generate(
+        "Hello my name is",
+        request_id="abc",
+        sampling_params=SamplingParams(
+            max_tokens=EXPECTED_TOKENS, output_kind=RequestOutputKind.DELTA
+        ),
+    ):
+        outputs.append(out)
+
+    generated_tokens = []
+    for out in outputs:
+        generated_tokens.extend(out.outputs[0].token_ids)
+    assert len(generated_tokens) == EXPECTED_TOKENS
+
+    async_llm.shutdown()