test: Add comprehensive tests for OpenAI-compatible TTS endpoint
- Refactor existing tests to use a shared mock engine fixture. - Add tests for unsupported response formats. - Add tests for engine synthesis failures. - Add tests for 'engine:model_id' parsing in the 'model' parameter. - Add tests for different audio response formats (opus, flac).
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@ -2,37 +2,52 @@ import pytest
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from fastapi.testclient import TestClient
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from unittest.mock import AsyncMock, MagicMock
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from app.routers.openai_compatible import OpenAISpeechRequest
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import os
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def test_openai_speech_endpoint_success(app_client, app_instance, tmp_path):
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# 1. Setup Mock Engine
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@pytest.fixture(autouse=True)
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def mock_engine_registry(app_instance, tmp_path):
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"""
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Fixture to set up a mock engine and inject it into the app_instance's registry
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for each test. This ensures a clean state and isolated mocks.
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"""
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mock_engine = MagicMock()
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# Mock synthesis to return a dummy file path
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dummy_file = tmp_path / "test_output.wav"
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dummy_file.write_bytes(b"fake audio data")
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mock_engine.synthesize = AsyncMock(return_value=str(dummy_file))
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# Inject mock engine into registry
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app_instance.ENGINE_REGISTRY["mock-engine"] = mock_engine
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# Add common mock methods for engine interface
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mock_engine.list_models.return_value = ["model1", "model2"]
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mock_engine.list_voices.return_value = ["speaker1", "speaker2"]
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mock_engine.healthcheck.return_value = {"status": "ok"}
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app_instance.ENGINE_REGISTRY["mock-engine"] = mock_engine
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app_instance.ENGINE_REGISTRY["kokoro"] = mock_engine # For tts-1 mapping test
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return mock_engine
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# --- Existing Tests (Modified to use fixture) ---
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def test_openai_speech_endpoint_success(app_client, mock_engine_registry, tmp_path):
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# Use the mock_engine_registry fixture to get the mock_engine
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mock_engine = mock_engine_registry
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# 2. Make Request
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payload = {
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"model": "mock-engine",
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"input": "Hello OpenAI",
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"voice": "default",
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"voice": "speaker1",
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"response_format": "wav"
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}
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response = app_client.post("/v1/audio/speech", json=payload)
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# 3. Assertions
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assert response.status_code == 200
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assert response.headers["content-type"] == "audio/wav"
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assert response.content == b"fake audio data"
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# Verify engine call
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mock_engine.synthesize.assert_called_once_with(
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text="Hello OpenAI",
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speaker="default",
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model=None,
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speaker="speaker1",
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model=None, # Explicitly no model_id in this case
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fmt="wav"
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)
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@ -46,21 +61,13 @@ def test_openai_speech_endpoint_engine_not_found(app_client):
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assert response.status_code == 404
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assert "not found" in response.json()["detail"]
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def test_openai_speech_endpoint_tts_1_mapping(app_client, app_instance, tmp_path):
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# Setup Mock Engine for 'kokoro' (simulating it's active)
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mock_engine = MagicMock()
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dummy_file = tmp_path / "tts1_output.mp3"
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dummy_file.write_bytes(b"mp3 data")
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mock_engine.synthesize = AsyncMock(return_value=str(dummy_file))
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def test_openai_speech_endpoint_tts_1_mapping(app_client, mock_engine_registry):
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mock_engine = mock_engine_registry # 'kokoro' engine is mapped to this mock
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# Inject into registry
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app_instance.ENGINE_REGISTRY["kokoro"] = mock_engine
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# Request 'tts-1' -> should map to 'kokoro'
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payload = {
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"model": "tts-1",
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"input": "Mapping test",
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"voice": "alloy",
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"voice": "speaker1",
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"response_format": "mp3"
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}
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response = app_client.post("/v1/audio/speech", json=payload)
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@ -69,6 +76,105 @@ def test_openai_speech_endpoint_tts_1_mapping(app_client, app_instance, tmp_path
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assert response.headers["content-type"] == "audio/mpeg"
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mock_engine.synthesize.assert_called_once()
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# Check that speaker passed through
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args, kwargs = mock_engine.synthesize.call_args
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assert kwargs["speaker"] == "alloy"
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assert kwargs["speaker"] == "speaker1"
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assert kwargs["fmt"] == "mp3"
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# --- New Test Cases ---
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def test_openai_speech_endpoint_unsupported_format(app_client, mock_engine_registry):
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mock_engine = mock_engine_registry
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payload = {
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"model": "mock-engine",
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"input": "Test text.",
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"voice": "speaker1",
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"response_format": "unsupported_format" # This should be caught by pydantic's Literal
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}
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response = app_client.post("/v1/audio/speech", json=payload)
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assert response.status_code == 422 # Unprocessable Entity due to Pydantic validation
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assert "response_format" in response.json()["detail"][0]["loc"]
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def test_openai_speech_endpoint_engine_synthesis_failure(app_client, mock_engine_registry):
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mock_engine = mock_engine_registry
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mock_engine.synthesize.side_effect = RuntimeError("Mock synthesis failed")
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payload = {
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"model": "mock-engine",
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"input": "This text will fail.",
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"voice": "speaker1"
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}
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response = app_client.post("/v1/audio/speech", json=payload)
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assert response.status_code == 500
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assert "Mock synthesis failed" in response.json()["detail"]
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def test_openai_speech_endpoint_model_id_parsing(app_client, mock_engine_registry, tmp_path):
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mock_engine = mock_engine_registry
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# Ensure a different dummy file for this test's synthesis result
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dummy_file = tmp_path / "model_id_output.wav"
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dummy_file.write_bytes(b"model id audio data")
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mock_engine.synthesize.return_value = str(dummy_file)
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# For this test, we simulate an engine that supports a model_id
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app_instance = app_client.app
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app_instance.ENGINE_REGISTRY["xtts"] = mock_engine # Map 'xtts' to our mock
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payload = {
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"model": "xtts:multilingual", # Test parsing 'engine:model_id'
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"input": "Testing specific model.",
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"voice": "speaker1",
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"response_format": "wav"
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}
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response = app_client.post("/v1/audio/speech", json=payload)
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assert response.status_code == 200
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assert response.headers["content-type"] == "audio/wav"
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assert response.content == b"model id audio data"
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mock_engine.synthesize.assert_called_once_with(
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text="Testing specific model.",
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speaker="speaker1",
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model="multilingual", # Verify model_id was passed correctly
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fmt="wav"
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)
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def test_openai_speech_endpoint_different_audio_formats(app_client, mock_engine_registry, tmp_path):
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mock_engine = mock_engine_registry
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# Test opus format
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opus_dummy_file = tmp_path / "test_output.opus"
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opus_dummy_file.write_bytes(b"opus data")
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mock_engine.synthesize.return_value = str(opus_dummy_file)
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payload_opus = {
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"model": "mock-engine",
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"input": "Hello opus.",
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"voice": "speaker1",
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"response_format": "opus"
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}
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response_opus = app_client.post("/v1/audio/speech", json=payload_opus)
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assert response_opus.status_code == 200
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assert response_opus.headers["content-type"] == "audio/opus"
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assert response_opus.content == b"opus data"
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mock_engine.synthesize.assert_called_with(text="Hello opus.", speaker="speaker1", model=None, fmt="opus")
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# Reset mock and test flac format
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mock_engine.synthesize.reset_mock()
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flac_dummy_file = tmp_path / "test_output.flac"
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flac_dummy_file.write_bytes(b"flac data")
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mock_engine.synthesize.return_value = str(flac_dummy_file)
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payload_flac = {
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"model": "mock-engine",
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"input": "Hello flac.",
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"voice": "speaker1",
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"response_format": "flac"
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}
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response_flac = app_client.post("/v1/audio/speech", json=payload_flac)
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assert response_flac.status_code == 200
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assert response_flac.headers["content-type"] == "audio/flac"
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assert response_flac.content == b"flac data"
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mock_engine.synthesize.assert_called_with(text="Hello flac.", speaker="speaker1", model=None, fmt="flac")
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