Refactor settings store to rename proModel to proThinking and update related logic; enhance CSS for energy efficiency and reduced motion preferences; improve i18n translations for better clarity and consistency; modify proBlock utility functions for clearer instruction handling; streamline Vite configuration by removing unnecessary Univer.js dependencies.
This commit is contained in:
“ydy0615”
@@ -1,327 +1,193 @@
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import os
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import sys
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import time
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import asyncio
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import types
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import pytest
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from pathlib import Path
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from unittest.mock import MagicMock
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from unittest.mock import MagicMock, patch
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BACKEND_DIR = Path(__file__).resolve().parents[1]
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if str(BACKEND_DIR) not in sys.path:
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sys.path.insert(0, str(BACKEND_DIR))
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def _make_torch_stub(cuda_avail=False, mps_avail=False):
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class DummyTensor:
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def __matmul__(self, other): return self
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def matmul(self, other): return self
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stub = types.SimpleNamespace()
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stub.float32 = "float32"
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stub.float16 = "float16"
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stub.randn = lambda *a, **k: DummyTensor()
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stub.mm = lambda a, b: DummyTensor()
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stub.from_numpy = lambda arr: DummyTensor()
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stub.nn = types.SimpleNamespace()
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stub.nn.Linear = MagicMock(return_value=MagicMock())
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stub.nn.Module = type("Module", (), {})
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stub.no_grad = MagicMock()
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stub.no_grad.return_value.__enter__ = MagicMock(return_value=None)
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stub.no_grad.return_value.__exit__ = MagicMock(return_value=False)
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stub.backends = types.SimpleNamespace()
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stub.backends.mps = types.SimpleNamespace()
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stub.backends.mps.is_available = lambda: mps_avail
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stub.backends.mps.is_built = lambda: mps_avail
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stub.cuda = types.SimpleNamespace()
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stub.cuda.is_available = lambda: cuda_avail
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stub.cuda.device_count = lambda: 1 if cuda_avail else 0
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stub.cuda.get_device_properties = lambda n: types.SimpleNamespace(total_memory=8*1024*1024*1024)
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stub.cuda.empty_cache = lambda: None
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stub.mps = types.SimpleNamespace()
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stub.mps.is_available = lambda: mps_avail
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stub.mps.is_built = lambda: mps_avail
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stub.mps.empty_cache = lambda: None
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stub.device = lambda s: s
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stub.Tensor = MagicMock()
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return stub
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def _make_mlx_stub():
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"""Create minimal MLX stub for testing without Apple Silicon"""
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mlx = types.SimpleNamespace()
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mlx.core = types.SimpleNamespace()
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mx_array = type('mx.array', (), {'item': lambda self: 1})
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mlx.core.array = mx_array
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mlx.nn = types.SimpleNamespace()
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return mlx
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def _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device=None):
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def _make_mlx_audio_stub():
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"""Create minimal mlx-audio stub"""
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stt = types.SimpleNamespace()
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stt.utils = types.SimpleNamespace()
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def mock_load(path, **kwargs):
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model = MagicMock()
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return model
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stt.utils.load = mock_load # type: ignore
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qwen3_asr_mod = types.SimpleNamespace()
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qwen3_asr_mod.Qwen3ASRModel = type('Qwen3ASRModel', (), {})
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qwen3_asr_mod.ForcedAlignerModel = type('ForcedAlignerModel', (), {})
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stt.models = types.SimpleNamespace() # type: ignore
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stt.models.qwen3_asr = qwen3_asr_mod # type: ignore
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audio = types.SimpleNamespace()
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audio.stt = stt # type: ignore
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return audio
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def _reload_tts_asr_with_mocks():
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"""Reload tts_asr with mocked MLX dependencies"""
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for mod_name in list(sys.modules.keys()):
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if mod_name.startswith("tts_asr") or mod_name == "torch":
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if 'tts_asr' in mod_name or 'mlx' in mod_name:
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del sys.modules[mod_name]
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torch_stub = _make_torch_stub(cuda_avail=cuda_avail, mps_avail=mps_avail)
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sys.modules["torch"] = torch_stub
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if env_device is not None:
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os.environ["TTS_ASR_DEVICE"] = env_device
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elif "TTS_ASR_DEVICE" in os.environ:
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del os.environ["TTS_ASR_DEVICE"]
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mlx_stub = _make_mlx_stub()
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sys.modules['mlx'] = mlx_stub # type: ignore
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sys.modules['mlx.core'] = mlx_stub.core # type: ignore
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sys.modules['mlx.nn'] = mlx_stub.nn # type: ignore
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audio_stub = _make_mlx_audio_stub()
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sys.modules['mlx-audio'] = audio_stub # type: ignore
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sys.modules['mlx_audio'] = audio_stub # type: ignore
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sys.modules['mlx_audio.stt'] = audio_stub.stt # type: ignore
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sys.modules['mlx_audio.stt.utils'] = audio_stub.stt.utils # type: ignore
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sys.modules['mlx_audio.stt.models'] = audio_stub.stt.models # type: ignore
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sys.modules['mlx_audio.stt.models.qwen3_asr'] = audio_stub.stt.models.qwen3_asr # type: ignore
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import tts_asr
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tts_asr._device_caps = None
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tts_asr._tts_pipeline = None
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tts_asr._asr_pipeline = None
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tts_asr._tts_last_used = 0
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tts_asr._asr_last_used = 0
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return tts_asr
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@pytest.fixture(autouse=True)
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def _clean_tts_env():
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def _clean_env():
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"""Clean ASR-related env vars before/after each test"""
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saved = {}
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for k in ["TTS_ASR_DEVICE", "TTS_ASR_IDLE_TIMEOUT", "TTS_ASR_MODEL_SIZE",
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"TTS_ASR_QUANTIZE", "TTS_ASR_OFFLINE_MODE", "TTS_ASR_WARMUP",
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"TTS_ASR_MPS_MEMORY_LIMIT_MB"]:
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for k in ['HF_ENDPOINT']:
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saved[k] = os.environ.get(k)
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if k in os.environ:
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del os.environ[k]
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yield
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for k, v in saved.items():
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if v is not None:
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os.environ[k] = v
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elif k in os.environ:
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del os.environ[k]
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os.environ[k] = v # type: ignore (unused var)
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# --- Cache clearing ---
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def test_clear_cuda_cache():
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tts = _reload_tts_asr(cuda_avail=True, mps_avail=False, env_device="cpu")
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tts._clear_cuda_cache()
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class TestRequestResponseModels:
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"""Pydantic 数据模型测试"""
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def test_tts_request_defaults(self):
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tts = _reload_tts_asr_with_mocks()
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req = tts.TTSRequest(text="hello")
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assert req.text == "hello"
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assert req.speaker == "Vivian"
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def test_clear_mps_cache():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=True, env_device="cpu")
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tts._clear_mps_cache()
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def test_asr_request_defaults(self):
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tts = _reload_tts_asr_with_mocks()
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req = tts.ASRRequest(audio_base64="dGVzdA==")
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assert req.audio_base64 == "dGVzdA=="
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assert req.language == "zh-CN"
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def test_asr_request_custom_language(self):
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tts = _reload_tts_asr_with_mocks()
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req = tts.ASRRequest(audio_base64="dGVzdA==", language="en")
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assert req.language == "en"
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# --- Model cache check ---
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def test_check_model_cached_non_offline():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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os.environ["TTS_ASR_OFFLINE_MODE"] = "false"
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import importlib
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importlib.reload(tts)
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assert tts._check_model_cached("openai/whisper-tiny") is True
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def test_model_status_defaults(self):
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tts = _reload_tts_asr_with_mocks()
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status = tts.ModelStatus(tts_loaded=False, asr_loaded=True, device="cpu")
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assert not status.tts_loaded
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assert status.asr_loaded
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def test_check_model_cached_offline_mode():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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os.environ["TTS_ASR_OFFLINE_MODE"] = "true"
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import importlib
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importlib.reload(tts)
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assert tts._check_model_cached("openai/whisper-tiny") is False
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class TestDeviceDetection:
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"""设备检测测试"""
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def test_device_map_returns_string(self):
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tts = _reload_tts_asr_with_mocks()
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device = tts._get_device_map()
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assert isinstance(device, str)
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# --- Torch dtype ---
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def test_get_torch_dtype_cpu():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="cpu")
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assert tts._get_torch_dtype() == "float32"
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class TestModelLoading:
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"""模型加载测试"""
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def test_get_torch_dtype_mps():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=True, env_device="mps")
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assert tts._get_torch_dtype() == "float32"
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def test_load_asr_skips_when_mlx_unavailable(self):
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"""mlx_audio 未安装时应跳过 ASR"""
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for mod_name in list(sys.modules.keys()):
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if 'tts_asr' in mod_name or 'mlx' in mod_name:
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del sys.modules[mod_name]
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# Don't inject mlx stubs — simulate missing MLX
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import tts_asr # noqa: F811
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def test_get_torch_dtype_cuda():
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tts = _reload_tts_asr(cuda_avail=True, mps_avail=False, env_device="cuda")
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assert tts._get_torch_dtype() == "float16"
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assert tts_asr.Qwen3ASRModel is None
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tts_asr._load_asr_models() # should not crash
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assert tts_asr._asr_model is None
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def test_load_asr_from_path_success(self):
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tts = _reload_tts_asr_with_mocks()
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# Mock snapshot_download to return a path, mock stt_load to succeed
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with patch('backend.tts_asr.snapshot_download', return_value='/fake/path'): # type: ignore
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tts._load_asr_from_path('/fake/path')
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# --- Device detection ---
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def test_get_device_cpu_env():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="cpu")
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assert tts._get_device() == "cpu"
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assert tts._asr_model is not None # type: ignore (MagicMock)
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def test_get_device_mps_available():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=True, env_device="mps")
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assert tts._get_device() == "mps"
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class TestWarmupFunctions:
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"""预热函数测试"""
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def test_warmup_functions_callable(self):
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tts = _reload_tts_asr_with_mocks()
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assert callable(tts._warmup_tts) # type: ignore (unused var)
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assert callable(tts._warmup_all)
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def test_get_device_mps_not_available_falls_back():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="mps")
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assert tts._get_device() == "cpu"
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def test_warmup_asr_skips_when_mlx_unavailable(self):
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for mod_name in list(sys.modules.keys()):
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if 'tts_asr' in mod_name or 'mlx' in mod_name:
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del sys.modules[mod_name]
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import tts_asr # noqa: F811
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assert tts_asr.Qwen3ASRModel is None
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def test_get_device_cuda_available():
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tts = _reload_tts_asr(cuda_avail=True, mps_avail=False, env_device="cuda")
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assert tts._get_device() == "cuda"
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def test_warmup_all_runs_without_error(self):
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tts = _reload_tts_asr_with_mocks()
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# Set global models so warmup returns immediately without actual loading
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tts._tts_model = MagicMock()
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def test_get_device_cuda_not_available_falls_back():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="cuda")
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assert tts._get_device() == "cpu"
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async def run(): # type: ignore (unused var)
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await tts._warmup_all()
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asyncio.get_event_loop().run_until_complete(run()) # type: ignore
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def test_get_device_auto_mps():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=True, env_device=None)
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assert tts._get_device() == "mps"
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class TestRouteRegistration:
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"""路由注册测试"""
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def test_get_device_auto_cuda():
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tts = _reload_tts_asr(cuda_avail=True, mps_avail=False, env_device=None)
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assert tts._get_device() == "cuda"
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def test_register_function_exists(self):
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tts = _reload_tts_asr_with_mocks()
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assert callable(tts.register_tts_asr_routes)
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def test_router_prefix(self):
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tts = _reload_tts_asr_with_mocks()
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assert hasattr(tts.router, 'routes')
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def test_get_device_auto_cpu():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device=None)
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assert tts._get_device() == "cpu"
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class TestModelConstants:
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"""模型常量测试"""
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def test_device_arg_cuda():
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tts = _reload_tts_asr(cuda_avail=True, mps_avail=False, env_device="cuda")
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assert tts._device_arg() == "cuda:0"
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def test_asr_model_id(self):
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tts = _reload_tts_asr_with_mocks()
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assert 'Qwen3-ASR' in tts.ASR_MODEL_ID_MS
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def test_device_arg_cpu():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="cpu")
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assert tts._device_arg() == "cpu"
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def test_device_arg_mps():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=True, env_device="mps")
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assert tts._device_arg() == "mps"
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def test_test_device_capability_cpu():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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ok, err = tts._test_device_capability("cpu")
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assert ok is True
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assert err == ""
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def test_test_device_capability_mps_not_available():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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ok, err = tts._test_device_capability("mps")
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assert ok is False
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assert len(err) > 0
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def test_test_device_capability_cuda_not_available():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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ok, err = tts._test_device_capability("cuda")
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assert ok is False
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assert len(err) > 0
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def test_test_device_capability_unknown_device():
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tts = _reload_tts_asr()
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ok, err = tts._test_device_capability("vulkan")
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assert ok is False
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assert len(err) > 0
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# --- Idle model unload ---
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def test_check_and_unload_idle_models_timeout_zero():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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os.environ["TTS_ASR_IDLE_TIMEOUT"] = "0"
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tts._tts_pipeline = "pipeline"
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tts._asr_pipeline = "pipeline"
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tts._tts_last_used = time.time()
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tts._asr_last_used = time.time()
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tts._check_and_unload_idle_models()
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assert tts._tts_pipeline == "pipeline"
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def test_check_and_unload_idle_models_unloads_when_expired():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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os.environ["TTS_ASR_IDLE_TIMEOUT"] = "1"
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tts._tts_pipeline = "pipeline"
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tts._asr_pipeline = "pipeline"
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tts._tts_last_used = time.time() - 10
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tts._asr_last_used = time.time() - 10
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import importlib
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importlib.reload(tts)
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tts._check_and_unload_idle_models()
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assert True # Function executed without error
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def test_check_and_unload_idle_models_keeps_when_not_expired():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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os.environ["TTS_ASR_IDLE_TIMEOUT"] = "60"
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tts._tts_pipeline = "pipeline"
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tts._asr_pipeline = "pipeline"
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tts._tts_last_used = time.time()
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tts._asr_last_used = time.time()
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tts._check_and_unload_idle_models()
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assert tts._tts_pipeline == "pipeline"
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# --- API key ---
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def test_get_api_key_success():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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key = tts.get_api_key("your-secret-key-here")
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assert key == "your-secret-key-here"
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def test_get_api_key_wrong_key_raises():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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||||
with pytest.raises(Exception):
|
||||
tts.get_api_key("wrong-key")
|
||||
|
||||
|
||||
def test_get_api_key_missing_key_raises():
|
||||
tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
|
||||
with pytest.raises(Exception):
|
||||
tts.get_api_key("")
|
||||
|
||||
|
||||
# --- Pydantic models ---
|
||||
def test_tts_request_model():
|
||||
tts = _reload_tts_asr()
|
||||
req = tts.TTSRequest(text="hello")
|
||||
assert req.text == "hello"
|
||||
assert req.voice == "af_bella"
|
||||
assert req.rate == 1.0
|
||||
assert req.format == "wav"
|
||||
|
||||
|
||||
def test_asr_request_model():
|
||||
tts = _reload_tts_asr()
|
||||
req = tts.ASRRequest(audio_base64="base64data", language="zh")
|
||||
assert req.audio_base64 == "base64data"
|
||||
assert req.language == "zh"
|
||||
|
||||
|
||||
# --- Device capabilities ---
|
||||
def test_detect_device_capabilities_cpu():
|
||||
tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
|
||||
caps = tts._detect_device_capabilities()
|
||||
assert caps.device == "cpu"
|
||||
assert caps.mps_available is False
|
||||
assert caps.cuda_available is False
|
||||
|
||||
|
||||
def test_detect_device_capabilities_mps():
|
||||
tts = _reload_tts_asr(cuda_avail=False, mps_avail=True)
|
||||
caps = tts._detect_device_capabilities()
|
||||
assert caps.device == "mps"
|
||||
assert caps.mps_available is True
|
||||
|
||||
|
||||
def test_detect_device_capabilities_cuda():
|
||||
tts = _reload_tts_asr(cuda_avail=True, mps_avail=False)
|
||||
caps = tts._detect_device_capabilities()
|
||||
assert caps.device == "cuda"
|
||||
assert caps.cuda_available is True
|
||||
|
||||
|
||||
# --- Apple Silicon check ---
|
||||
def test_is_apple_silicon_windows():
|
||||
tts = _reload_tts_asr()
|
||||
assert tts._is_apple_silicon() is False
|
||||
|
||||
|
||||
# --- Model size ---
|
||||
def test_recommended_model_size_auto():
|
||||
tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="cpu")
|
||||
size = tts._get_recommended_model_size()
|
||||
assert size in tts.WHISPER_MODEL_SIZES or size == "auto"
|
||||
|
||||
|
||||
def test_recommended_model_size_explicit():
|
||||
tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
|
||||
os.environ["TTS_ASR_MODEL_SIZE"] = "tiny"
|
||||
import importlib
|
||||
importlib.reload(tts)
|
||||
size = tts._get_recommended_model_size()
|
||||
assert size == "tiny"
|
||||
def test_align_model_id(self):
|
||||
tts = _reload_tts_asr_with_mocks()
|
||||
assert 'ForcedAligner' in tts.ALIGN_MODEL_ID_MS
|
||||
|
||||
Reference in New Issue
Block a user