[Frontend] Add Support for MM Encoder/Decoder Beam Search (Online Transcriptions) (#36160)

Signed-off-by: Alex Brooks <albrooks@redhat.com>

tests/entrypoints/openai/test_transcription_validation_whisper.py

@@ -317,3 +317,72 @@ async def test_language_auto_detect(
     assert any(word.lower() in text_lower for word in expected_text), (
         f"Expected {expected_lang} text but got: {transcription.text}"
     )
+
+
+@pytest.mark.asyncio
+async def test_whisper_beam_search_single_beam(mary_had_lamb, whisper_client):
+    """Test beam search with encoder-decoder model (Whisper) on transcriptions with
+    one beam aligns with greedy decoding.
+    """
+    beam_transcription = await whisper_client.audio.transcriptions.create(
+        model=MODEL_NAME,
+        file=mary_had_lamb,
+        language="en",
+        response_format="text",
+        temperature=0.0,
+        extra_body=dict(
+            use_beam_search=True,
+            n=1,
+        ),
+    )
+
+    greedy_transcription = await whisper_client.audio.transcriptions.create(
+        model=MODEL_NAME,
+        file=mary_had_lamb,
+        response_format="text",
+        temperature=0.0,
+    )
+
+    greedy_res = json.loads(greedy_transcription)["text"]
+    beam_res = json.loads(beam_transcription)["text"]
+    assert greedy_res == beam_res
+
+
+@pytest.mark.asyncio
+async def test_whisper_beam_search_multibeam(mary_had_lamb, whisper_client):
+    """Test n>1 for beam search returns one transcription (best beam)."""
+    transcription = await whisper_client.audio.transcriptions.create(
+        model=MODEL_NAME,
+        file=mary_had_lamb,
+        language="en",
+        response_format="text",
+        temperature=0.0,
+        extra_body=dict(
+            use_beam_search=True,
+            n=2,
+        ),
+    )
+
+    result = json.loads(transcription)
+
+    text = result["text"]
+
+    assert text is not None
+    assert len(text) > 0
+    assert "mary had a little lamb" in text.lower()
+
+
+@pytest.mark.asyncio
+async def test_stream_with_beams_raises(winning_call, whisper_client):
+    """Test that stream=True + beam search raises bad request for now."""
+    with pytest.raises(openai.BadRequestError):
+        await whisper_client.audio.transcriptions.create(
+            model=MODEL_NAME,
+            file=winning_call,
+            language="en",
+            stream=True,
+            extra_body=dict(
+                use_beam_search=True,
+                n=2,
+            ),
+        )