ydy0615
2fdc996af9
Added a new `.coveragerc` file configuring coverage thresholds and exclusions. Included `pytest.ini` to enable coverage reporting for multiple backend modules (`main`, `llm`, `prompt`, `geoip`, `tts_asr`) with a 90 % fail‑under requirement and detailed HTML output. Implemented a suite of unit tests: * `test_geoip.py` – validates geo‑location lookup logic. * `test_llm_extended.py` – tests LLm response extraction and Ollama interactions. * `test_main_endpoints.py` – covers API endpoints for completions, OCR, and TTS. * `test_prompt_extended.py` – verifies language sanitization, timestamp generation, and prompt building. * `test_tts_asr_coverage.py` – checks device detection, cache clearing, and model loading under various environment configurations. * `test_tts_asr_extended.py` – further tests TTS/ASR device selection and time‑outs. Updated `backend/requirements.txt` to use newer, compatible packages, removed obsolete testing dependencies, and added `qwen-tts`. Modified `backend/tts_asr.py` to work with the new `Qwen3TTSModel`, simplified imports, and adjusted device mapping logic. Additionally, frontend changes added a new `TreeNodeItem` component, updated Markdown rendering, added TTS instruction fields, and reworked context menu handling. No breaking changes were introduced.
328 lines
10 KiB
Python
328 lines
10 KiB
Python
import os
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import sys
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import time
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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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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 _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device=None):
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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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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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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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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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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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# --- 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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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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# --- 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_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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# --- 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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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_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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# --- 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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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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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_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_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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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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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_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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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_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):
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tts.get_api_key("wrong-key")
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def test_get_api_key_missing_key_raises():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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with pytest.raises(Exception):
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tts.get_api_key("")
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# --- Pydantic models ---
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def test_tts_request_model():
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tts = _reload_tts_asr()
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req = tts.TTSRequest(text="hello")
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assert req.text == "hello"
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assert req.voice == "af_bella"
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assert req.rate == 1.0
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assert req.format == "wav"
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def test_asr_request_model():
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tts = _reload_tts_asr()
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req = tts.ASRRequest(audio_base64="base64data", language="zh")
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assert req.audio_base64 == "base64data"
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assert req.language == "zh"
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# --- Device capabilities ---
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def test_detect_device_capabilities_cpu():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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caps = tts._detect_device_capabilities()
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assert caps.device == "cpu"
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assert caps.mps_available is False
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assert caps.cuda_available is False
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def test_detect_device_capabilities_mps():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=True)
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caps = tts._detect_device_capabilities()
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assert caps.device == "mps"
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assert caps.mps_available is True
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def test_detect_device_capabilities_cuda():
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tts = _reload_tts_asr(cuda_avail=True, mps_avail=False)
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caps = tts._detect_device_capabilities()
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assert caps.device == "cuda"
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assert caps.cuda_available is True
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# --- Apple Silicon check ---
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def test_is_apple_silicon_windows():
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tts = _reload_tts_asr()
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assert tts._is_apple_silicon() is False
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# --- Model size ---
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def test_recommended_model_size_auto():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False, env_device="cpu")
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size = tts._get_recommended_model_size()
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assert size in tts.WHISPER_MODEL_SIZES or size == "auto"
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def test_recommended_model_size_explicit():
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tts = _reload_tts_asr(cuda_avail=False, mps_avail=False)
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os.environ["TTS_ASR_MODEL_SIZE"] = "tiny"
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import importlib
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importlib.reload(tts)
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size = tts._get_recommended_model_size()
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assert size == "tiny"
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