[Refactor] Relocate endpoint tests to mirror serving code directory structure (#37504)

Signed-off-by: sfeng33 <4florafeng@gmail.com>

tests/entrypoints/openai/speech_to_text/test_transcription_validation.py

@@ -0,0 +1,156 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+# imports for structured outputs tests
+import json
+
+import pytest
+
+from tests.entrypoints.openai.conftest import add_attention_backend
+from tests.utils import ROCM_ENV_OVERRIDES, ROCM_EXTRA_ARGS, RemoteOpenAIServer
+
+MISTRAL_FORMAT_ARGS = [
+    "--tokenizer_mode",
+    "mistral",
+    "--config_format",
+    "mistral",
+    "--load_format",
+    "mistral",
+]
+
+
+async def transcribe_and_check(
+    client,
+    model_name: str,
+    file,
+    *,
+    language: str,
+    expected_text: str,
+    expected_seconds: int | None = None,
+    case_sensitive: bool = False,
+):
+    """Run a transcription request and assert the output contains
+    *expected_text* and optionally that usage reports *expected_seconds*.
+
+    Provides detailed failure messages with the actual transcription output.
+    """
+    transcription = await client.audio.transcriptions.create(
+        model=model_name,
+        file=file,
+        language=language,
+        response_format="text",
+        temperature=0.0,
+    )
+    out = json.loads(transcription)
+    out_text = out["text"]
+    out_usage = out["usage"]
+
+    if case_sensitive:
+        assert expected_text in out_text, (
+            f"Expected {expected_text!r} in transcription output, got: {out_text!r}"
+        )
+    else:
+        assert expected_text.lower() in out_text.lower(), (
+            f"Expected {expected_text!r} (case-insensitive) in transcription "
+            f"output, got: {out_text!r}"
+        )
+
+    if expected_seconds is not None:
+        assert out_usage["seconds"] == expected_seconds, (
+            f"Expected {expected_seconds}s of audio, "
+            f"got {out_usage['seconds']}s. Full usage: {out_usage!r}"
+        )
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "model_name", ["mistralai/Voxtral-Mini-3B-2507", "Qwen/Qwen3-ASR-0.6B"]
+)
+async def test_basic_audio(mary_had_lamb, model_name, rocm_aiter_fa_attention):
+    server_args = ["--enforce-eager", *ROCM_EXTRA_ARGS]
+
+    if model_name.startswith("mistralai"):
+        server_args += MISTRAL_FORMAT_ARGS
+
+    add_attention_backend(server_args, rocm_aiter_fa_attention)
+
+    # Based on https://github.com/openai/openai-cookbook/blob/main/examples/Whisper_prompting_guide.ipynb.
+    with RemoteOpenAIServer(
+        model_name, server_args, env_dict=ROCM_ENV_OVERRIDES
+    ) as remote_server:
+        client = remote_server.get_async_client()
+        await transcribe_and_check(
+            client,
+            model_name,
+            mary_had_lamb,
+            language="en",
+            expected_text="Mary had a little lamb",
+            expected_seconds=16,
+        )
+
+
+@pytest.mark.asyncio
+async def test_basic_audio_with_lora(mary_had_lamb, rocm_aiter_fa_attention):
+    """Ensure STT (transcribe) requests can pass LoRA through to generate."""
+    # ROCm SPECIFIC CONFIGURATION:
+    # To ensure the test passes on ROCm, we modify the max model length to 512.
+    # We DO NOT apply this to other platforms to maintain strict upstream parity.
+    from vllm.platforms import current_platform
+
+    model_name = "ibm-granite/granite-speech-3.3-2b"
+    lora_model_name = "speech"
+    server_args = [
+        "--enforce-eager",
+        "--enable-lora",
+        "--max-lora-rank",
+        "64",
+        "--lora-modules",
+        f"{lora_model_name}={model_name}",
+        "--max-model-len",
+        "512" if current_platform.is_rocm() else "2048",
+        "--max-num-seqs",
+        "1",
+    ]
+
+    add_attention_backend(server_args, rocm_aiter_fa_attention)
+
+    # Based on https://github.com/openai/openai-cookbook/blob/main/examples/Whisper_prompting_guide.ipynb.
+    with RemoteOpenAIServer(
+        model_name, server_args, env_dict=ROCM_ENV_OVERRIDES
+    ) as remote_server:
+        client = remote_server.get_async_client()
+        await transcribe_and_check(
+            client,
+            lora_model_name,
+            mary_had_lamb,
+            language="en",
+            expected_text="mary had a little lamb",
+            expected_seconds=16,
+        )
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "model_name", ["google/gemma-3n-E2B-it", "Qwen/Qwen3-ASR-0.6B"]
+)
+async def test_basic_audio_foscolo(foscolo, rocm_aiter_fa_attention, model_name):
+    # Gemma accuracy on some of the audio samples we use is particularly bad,
+    # hence we use a different one here. WER is evaluated separately.
+    server_args = ["--enforce-eager", *ROCM_EXTRA_ARGS]
+
+    add_attention_backend(server_args, rocm_aiter_fa_attention)
+
+    with RemoteOpenAIServer(
+        model_name,
+        server_args,
+        max_wait_seconds=480,
+        env_dict=ROCM_ENV_OVERRIDES,
+    ) as remote_server:
+        client = remote_server.get_async_client()
+        await transcribe_and_check(
+            client,
+            model_name,
+            foscolo,
+            language="it",
+            expected_text="ove il mio corpo fanciulletto giacque",
+        )