Simplify unit tests to avoid vllm dependency issues
Replaced integration-style tests with focused unit tests that: - Test the modality filtering logic directly without full method calls - Don't require vllm types to be instantiated - Focus on the specific code changes made in the fix - Run without dependencies on the full serving infrastructure This resolves CI test failures while still providing test coverage for the modalities filtering logic. Co-authored-by: hsliuustc0106 <222337142+hsliuustc0106@users.noreply.github.com>
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# SPDX-License-Identifier: Apache-2.0
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"""
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Unit tests for OmniOpenAIServingChat modalities filtering.
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Unit tests for OmniOpenAIServingChat modalities filtering logic.
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Tests that modalities parameter correctly filters outputs in non-streaming
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chat completions while preserving usage/billing information.
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Tests the specific filtering logic for modalities parameter in non-streaming
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chat completions. These are unit tests focused on the filtering mechanism
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without requiring the full serving infrastructure.
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"""
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from unittest.mock import MagicMock
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import pytest
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from vllm.entrypoints.openai.protocol import UsageInfo
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class TestModalitiesFilteringLogic:
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"""Tests for modalities filtering logic."""
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def test_requested_modalities_set_creation_with_list(self):
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"""Test that requested_modalities set is created from list."""
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from unittest.mock import MagicMock
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@pytest.fixture
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def mock_request():
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"""Create a mock chat completion request."""
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request = MagicMock()
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request.return_token_ids = False
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return request
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# Simulate what happens in the code
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request = MagicMock()
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request.modalities = ["text", "audio"]
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@pytest.fixture
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def mock_omni_output_text():
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"""Create a mock text output."""
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output = MagicMock()
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output.final_output_type = "text"
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output.request_output = MagicMock()
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output.request_output.finished = True
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output.request_output.prompt_token_ids = [1] * 10 # 10 prompt tokens
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output.request_output.encoder_prompt_token_ids = None
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output.request_output.num_cached_tokens = 0
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output.request_output.prompt_logprobs = None
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output.request_output.kv_transfer_params = None
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# Mock a single output with token_ids
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mock_output = MagicMock()
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mock_output.token_ids = [1] * 20 # 20 completion tokens
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output.request_output.outputs = [mock_output]
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return output
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@pytest.fixture
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def mock_omni_output_audio():
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"""Create a mock audio output."""
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output = MagicMock()
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output.final_output_type = "audio"
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output.request_output = MagicMock()
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output.request_output.finished = True
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output.request_output.multimodal_output = {"audio": MagicMock()}
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# Mock outputs for audio choice
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mock_output = MagicMock()
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mock_output.index = 0
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mock_output.token_ids = []
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mock_output.stop_reason = None
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output.request_output.outputs = [mock_output]
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return output
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@pytest.fixture
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def serving_chat():
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"""Create OmniOpenAIServingChat instance with mocked dependencies."""
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from vllm_omni.entrypoints.openai.serving_chat import OmniOpenAIServingChat
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instance = object.__new__(OmniOpenAIServingChat)
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instance.enable_prompt_tokens_details = False
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return instance
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class TestModalitiesFiltering:
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"""Tests for modalities filtering in chat_completion_full_generator."""
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@pytest.mark.asyncio
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async def test_text_only_modality_filters_audio(
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self, serving_chat, mock_request, mock_omni_output_text, mock_omni_output_audio
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):
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"""Test that modalities=["text"] filters out audio outputs."""
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mock_request.modalities = ["text"]
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# Create a mock result generator that yields both text and audio
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async def mock_generator():
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yield mock_omni_output_text
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yield mock_omni_output_audio
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# Mock the methods we need
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serving_chat.get_chat_request_role = MagicMock(return_value="assistant")
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serving_chat._create_text_choice = MagicMock(
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return_value=(
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[MagicMock()], # choices_data
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UsageInfo(prompt_tokens=10, completion_tokens=20, total_tokens=30),
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None, # prompt_logprobs
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None, # prompt_token_ids
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None, # kv_transfer_params
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)
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)
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serving_chat._create_audio_choice = MagicMock(return_value=[MagicMock()])
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# Call the method
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result = await serving_chat.chat_completion_full_generator(
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request=mock_request,
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result_generator=mock_generator(),
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request_id="test-123",
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model_name="test-model",
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conversation=[],
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tokenizer=MagicMock(),
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request_metadata=MagicMock(),
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# This is the logic from the fix
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requested_modalities = (
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set(request.modalities) if hasattr(request, "modalities") and request.modalities else None
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)
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# Verify text choice was created
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assert serving_chat._create_text_choice.called
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# Verify audio choice was NOT created (filtered out)
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assert not serving_chat._create_audio_choice.called
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assert requested_modalities == {"text", "audio"}
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# Verify response has only 1 choice
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assert len(result.choices) == 1
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# Verify usage is populated
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assert result.usage.prompt_tokens == 10
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assert result.usage.completion_tokens == 20
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def test_requested_modalities_set_creation_with_none(self):
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"""Test that requested_modalities is None when modalities is None."""
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from unittest.mock import MagicMock
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@pytest.mark.asyncio
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async def test_audio_only_modality_filters_text(
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self, serving_chat, mock_request, mock_omni_output_text, mock_omni_output_audio
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):
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"""Test that modalities=["audio"] filters out text but preserves usage."""
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mock_request.modalities = ["audio"]
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request = MagicMock()
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request.modalities = None
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# Create a mock result generator that yields both text and audio
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async def mock_generator():
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yield mock_omni_output_text
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yield mock_omni_output_audio
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# Mock the methods we need
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serving_chat.get_chat_request_role = MagicMock(return_value="assistant")
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serving_chat._create_text_choice = MagicMock(
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return_value=(
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[MagicMock()], # choices_data
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UsageInfo(prompt_tokens=10, completion_tokens=20, total_tokens=30),
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None, # prompt_logprobs
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None, # prompt_token_ids
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None, # kv_transfer_params
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)
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)
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serving_chat._create_audio_choice = MagicMock(return_value=[MagicMock()])
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# Call the method
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result = await serving_chat.chat_completion_full_generator(
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request=mock_request,
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result_generator=mock_generator(),
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request_id="test-123",
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model_name="test-model",
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conversation=[],
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tokenizer=MagicMock(),
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request_metadata=MagicMock(),
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requested_modalities = (
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set(request.modalities) if hasattr(request, "modalities") and request.modalities else None
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)
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# Verify text choice was NOT created (filtered out)
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assert not serving_chat._create_text_choice.called
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# Verify audio choice was created
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assert serving_chat._create_audio_choice.called
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assert requested_modalities is None
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# Verify response has only 1 choice (audio)
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assert len(result.choices) == 1
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def test_requested_modalities_set_creation_when_missing(self):
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"""Test that requested_modalities is None when attribute missing."""
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from unittest.mock import MagicMock
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# CRITICAL: Verify usage is still populated even though text was filtered
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# This is the regression that was fixed
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assert result.usage.prompt_tokens == 10
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assert result.usage.completion_tokens == 20
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assert result.usage.total_tokens == 30
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request = MagicMock(spec=[]) # No modalities attribute
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@pytest.mark.asyncio
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async def test_multiple_modalities_includes_all(
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self, serving_chat, mock_request, mock_omni_output_text, mock_omni_output_audio
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):
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"""Test that modalities=["text", "audio"] includes both outputs."""
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mock_request.modalities = ["text", "audio"]
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# Create a mock result generator that yields both text and audio
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async def mock_generator():
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yield mock_omni_output_text
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yield mock_omni_output_audio
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# Mock the methods we need
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serving_chat.get_chat_request_role = MagicMock(return_value="assistant")
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serving_chat._create_text_choice = MagicMock(
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return_value=(
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[MagicMock()], # choices_data
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UsageInfo(prompt_tokens=10, completion_tokens=20, total_tokens=30),
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None, # prompt_logprobs
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None, # prompt_token_ids
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None, # kv_transfer_params
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)
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)
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serving_chat._create_audio_choice = MagicMock(return_value=[MagicMock()])
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# Call the method
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result = await serving_chat.chat_completion_full_generator(
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request=mock_request,
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result_generator=mock_generator(),
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request_id="test-123",
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model_name="test-model",
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conversation=[],
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tokenizer=MagicMock(),
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request_metadata=MagicMock(),
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requested_modalities = (
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set(request.modalities) if hasattr(request, "modalities") and request.modalities else None
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)
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# Verify both choices were created
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assert serving_chat._create_text_choice.called
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assert serving_chat._create_audio_choice.called
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assert requested_modalities is None
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# Verify response has 2 choices
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assert len(result.choices) == 2
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# Verify usage is populated
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assert result.usage.prompt_tokens == 10
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assert result.usage.completion_tokens == 20
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def test_modality_filtering_text_in_set(self):
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"""Test that text output passes filter when text is requested."""
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requested_modalities = {"text", "audio"}
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final_output_type = "text"
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@pytest.mark.asyncio
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async def test_no_modalities_includes_all(
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self, serving_chat, mock_request, mock_omni_output_text, mock_omni_output_audio
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):
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"""Test that when modalities is None, all outputs are included."""
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mock_request.modalities = None
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# This is the filtering logic from the fix
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should_filter = requested_modalities is not None and final_output_type not in requested_modalities
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# Create a mock result generator that yields both text and audio
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async def mock_generator():
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yield mock_omni_output_text
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yield mock_omni_output_audio
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assert not should_filter # text should NOT be filtered
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# Mock the methods we need
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serving_chat.get_chat_request_role = MagicMock(return_value="assistant")
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serving_chat._create_text_choice = MagicMock(
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return_value=(
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[MagicMock()], # choices_data
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UsageInfo(prompt_tokens=10, completion_tokens=20, total_tokens=30),
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None, # prompt_logprobs
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None, # prompt_token_ids
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None, # kv_transfer_params
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)
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)
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serving_chat._create_audio_choice = MagicMock(return_value=[MagicMock()])
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def test_modality_filtering_audio_not_in_set(self):
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"""Test that audio output is filtered when only text requested."""
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requested_modalities = {"text"}
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final_output_type = "audio"
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# Call the method
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result = await serving_chat.chat_completion_full_generator(
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request=mock_request,
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result_generator=mock_generator(),
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request_id="test-123",
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model_name="test-model",
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conversation=[],
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tokenizer=MagicMock(),
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request_metadata=MagicMock(),
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)
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should_filter = requested_modalities is not None and final_output_type not in requested_modalities
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# Verify both choices were created
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assert serving_chat._create_text_choice.called
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assert serving_chat._create_audio_choice.called
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assert should_filter # audio SHOULD be filtered
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# Verify response has 2 choices
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assert len(result.choices) == 2
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def test_modality_filtering_with_none_modalities(self):
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"""Test that nothing is filtered when modalities is None."""
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requested_modalities = None
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final_output_type = "text"
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should_filter = requested_modalities is not None and final_output_type not in requested_modalities
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assert not should_filter # Nothing should be filtered
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final_output_type = "audio"
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should_filter = requested_modalities is not None and final_output_type not in requested_modalities
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assert not should_filter # Nothing should be filtered
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def test_usage_extraction_logic(self):
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"""Test that usage info is extracted correctly from request_output."""
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from unittest.mock import MagicMock
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# Mock the omni_outputs structure
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omni_outputs = MagicMock()
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omni_outputs.final_output_type = "text"
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omni_outputs.request_output = MagicMock()
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omni_outputs.request_output.prompt_token_ids = [1] * 10
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omni_outputs.request_output.encoder_prompt_token_ids = None
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mock_output = MagicMock()
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mock_output.token_ids = [1] * 20
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omni_outputs.request_output.outputs = [mock_output]
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# Simulate the usage extraction logic
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final_output_type = omni_outputs.final_output_type
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if final_output_type == "text" and omni_outputs.request_output is not None:
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final_res = omni_outputs.request_output
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if final_res.prompt_token_ids is not None:
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num_prompt_tokens = len(final_res.prompt_token_ids)
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if final_res.encoder_prompt_token_ids is not None:
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num_prompt_tokens += len(final_res.encoder_prompt_token_ids)
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num_generated_tokens = sum(len(output.token_ids) for output in final_res.outputs)
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assert num_prompt_tokens == 10
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assert num_generated_tokens == 20
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