"""
Placeholder test to verify test infrastructure works.
This test validates that conftest.py fixtures are properly loaded
and available for use in actual tests.
"""
import numpy as np
class TestFixturesAvailable:
"""Test that pytest fixtures from conftest.py are working."""
def test_mock_audio_data_fixture(self, mock_audio_data):
"""Verify mock_audio_data fixture produces valid audio array."""
# Should be numpy array
assert isinstance(mock_audio_data, np.ndarray)
# Should be float32
assert mock_audio_data.dtype == np.float32
# Should be 1 second at 16kHz = 16000 samples
assert mock_audio_data.shape == (16000,)
# Values should be in valid audio range [-1, 1]
assert mock_audio_data.min() >= -1.0
assert mock_audio_data.max() <= 1.0
def test_sample_skill_data_fixture(self, sample_skill_data):
"""Verify sample_skill_data fixture has expected structure."""
# Required fields exist
assert "id" in sample_skill_data
assert "name" in sample_skill_data
assert "system_prompt" in sample_skill_data
assert "metadata" in sample_skill_data
# Types are correct
assert isinstance(sample_skill_data["id"], str)
assert isinstance(sample_skill_data["metadata"], dict)
assert isinstance(sample_skill_data["personality_traits"], list)
def test_mock_sounddevice_fixture(self, mock_sounddevice):
"""Verify mock_sounddevice fixture is properly configured."""
# Should have InputStream mock
assert mock_sounddevice.InputStream is not None
# InputStream should support context manager
stream = mock_sounddevice.InputStream()
assert hasattr(stream, "__enter__")
assert hasattr(stream, "__exit__")
def test_mock_onnx_model_fixture(self, mock_onnx_model):
"""Verify mock_onnx_model fixture provides recognize method."""
model = mock_onnx_model.load_model("test")
# Should have recognize method
assert hasattr(model, "recognize")
# Recognize should return expected text
result = model.recognize(np.zeros(16000))
assert result == "transcribed text"
def test_mock_tts_model_fixture(self, mock_tts_model):
"""Verify mock_tts_model fixture provides generate_audio method."""
model = mock_tts_model.TTSModel.load_model("test")
# Should have expected attributes
assert model.sample_rate == 24000
assert hasattr(model, "generate_audio")
# generate_audio should return mock with numpy method
result = model.generate_audio("test text")
audio = result.numpy()
assert isinstance(audio, np.ndarray)
