diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 9af94bb..389e143 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -18,6 +18,9 @@ jobs: - name: Install backend dependencies run: | python -m pip install --upgrade pip + # CPU torch first: hosted runners have no GPU, and PyPI torch drags + # the multi-GB nvidia-*-cu13 wheel stack that fills the runner disk. + pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu pip install -e .[dev] - name: Compile backend sources @@ -26,6 +29,7 @@ jobs: - name: Run backend contract lane run: | PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 pytest \ + -m "not cuda" \ tests/test_web_utils.py \ tests/test_web_api.py \ tests/test_pipeline_status_api.py \ @@ -76,6 +80,9 @@ jobs: - name: Install backend dependencies run: | python -m pip install --upgrade pip + # CPU torch first: hosted runners have no GPU, and PyPI torch drags + # the multi-GB nvidia-*-cu13 wheel stack that fills the runner disk. + pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu pip install -e .[dev] - name: Run critical-module coverage gate @@ -108,6 +115,9 @@ jobs: - name: Install backend dependencies run: | python -m pip install --upgrade pip + # CPU torch first: hosted runners have no GPU, and PyPI torch drags + # the multi-GB nvidia-*-cu13 wheel stack that fills the runner disk. + pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu pip install -e .[dev] - name: Generate canonical benchmark dashboard fixture @@ -202,6 +212,9 @@ jobs: - name: Install backend dependencies and security tooling run: | python -m pip install --upgrade pip + # CPU torch first: hosted runners have no GPU, and PyPI torch drags + # the multi-GB nvidia-*-cu13 wheel stack that fills the runner disk. + pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu pip install -e .[dev] pip install pip-audit cyclonedx-bom @@ -257,6 +270,9 @@ jobs: - name: Install backend dependencies run: | python -m pip install --upgrade pip + # CPU torch first: hosted runners have no GPU, and PyPI torch drags + # the multi-GB nvidia-*-cu13 wheel stack that fills the runner disk. + pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu pip install -e .[dev] - name: Prepare compose environment @@ -323,6 +339,9 @@ jobs: - name: Install backend dependencies run: | python -m pip install --upgrade pip + # CPU torch first: hosted runners have no GPU, and PyPI torch drags + # the multi-GB nvidia-*-cu13 wheel stack that fills the runner disk. + pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu pip install -e .[dev] - name: Install frontend dependencies diff --git a/.gitignore b/.gitignore index 1063899..22a5d35 100644 --- a/.gitignore +++ b/.gitignore @@ -19,6 +19,7 @@ venv/ # Testing .pytest_cache/ .coverage +coverage.remaining.json htmlcov/ .mypy_cache/ diff --git a/frontend/e2e/conversion-workflow.live.spec.ts b/frontend/e2e/conversion-workflow.live.spec.ts index 1317dc2..c9ffa03 100644 --- a/frontend/e2e/conversion-workflow.live.spec.ts +++ b/frontend/e2e/conversion-workflow.live.spec.ts @@ -19,6 +19,10 @@ test.describe('Live backend conversion workflow', () => { buffer: createWavBuffer(), }) + // Workflows no longer auto-submit: generation starts from the explicit + // button (f74d4c7). + await page.getByTestId('start-generation-button').click() + await expect(page.getByText('Ready for Conversion').first()).toBeVisible({ timeout: 20_000 }) await page.getByRole('button', { name: /Convert Workflow Song/ }).click() diff --git a/frontend/e2e/full-ui-local.live.spec.ts b/frontend/e2e/full-ui-local.live.spec.ts index 396333d..ed38fd8 100644 --- a/frontend/e2e/full-ui-local.live.spec.ts +++ b/frontend/e2e/full-ui-local.live.spec.ts @@ -105,6 +105,9 @@ test.describe('Local full UI workflow coverage', () => { mimeType: 'audio/wav', buffer: createWavBuffer(24_000, 4), }) + // Workflows no longer auto-submit: generation starts from the explicit + // button (f74d4c7). + await page.getByTestId('start-generation-button').click() await expect(page.getByText('Ready for Conversion').first()).toBeVisible({ timeout: 20_000 }) await page.getByRole('button', { name: /Convert Workflow Song/ }).click() await expect(page.getByText('Conversion complete', { exact: true })).toBeVisible({ timeout: 15_000 }) diff --git a/frontend/package-lock.json b/frontend/package-lock.json index 629aaaa..18d2e0f 100644 --- a/frontend/package-lock.json +++ b/frontend/package-lock.json @@ -50,22 +50,47 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/@babel/code-frame": { + "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.7.tgz", + "integrity": "sha512-Aup7aUOfpbAUg2ROOJN6Iw5f9DMBlzu0mIkm/malLQFN/YQgO48wCj0Kxa3sEHJvPVFg7siR+qRInwXd2qhQKw==", + "dev": true, + "license": "MIT", + "dependencies": { + "@babel/helper-validator-identifier": "^7.29.7", + "js-tokens": "^4.0.0", + "picocolors": "^1.1.1" + }, + "engines": { + "node": ">=6.9.0" + } + }, + "node_modules/@babel/compat-data": { + "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.29.7.tgz", + "integrity": "sha512-locTkQyKvwIEgBzVrn8693ebc97F2U8ZHjbXwDXJ5Fn2TCpNwTlKcaKLkdHop5c/icOFE7qt7Q9JC5hnKNa6Gg==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=6.9.0" + } + }, "node_modules/@babel/core": { - 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"@rollup/rollup-win32-x64-msvc": "4.56.0", - "fsevents": "~2.3.2" - } - }, "node_modules/wavesurfer.js": { "version": "7.12.1", "resolved": "https://registry.npmjs.org/wavesurfer.js/-/wavesurfer.js-7.12.1.tgz", @@ -4411,6 +4387,34 @@ "node": ">=0.10.0" } }, + "node_modules/ws": { + "version": "8.21.3", + "resolved": "https://registry.npmjs.org/ws/-/ws-8.21.3.tgz", + "integrity": "sha512-201TZ/kPWxoPr/OKWjquZR1SWKXcvxdH+e1xrx89b3YbmzLMFCLfnaG1HFIgWzJOEWZ7MvpK++odZufgYR50Rw==", + "license": "MIT", + "engines": { + "node": ">=10.0.0" + }, + "peerDependencies": { + "bufferutil": "^4.0.1", + "utf-8-validate": ">=5.0.2" + }, + "peerDependenciesMeta": { + "bufferutil": { + "optional": true + }, + "utf-8-validate": { + "optional": true + } + } + }, + "node_modules/yallist": { + "version": "3.1.1", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", + "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==", + "dev": true, + "license": "ISC" + }, "node_modules/yocto-queue": { "version": "0.1.0", "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz", diff --git a/frontend/playwright.live.config.ts b/frontend/playwright.live.config.ts index bc32800..91fc6a1 100644 --- a/frontend/playwright.live.config.ts +++ b/frontend/playwright.live.config.ts @@ -1,8 +1,13 @@ import { defineConfig } from '@playwright/test' +import { existsSync } from 'node:fs' const FRONTEND_PORT = Number(process.env.AUTOVOICE_PLAYWRIGHT_PORT ?? 4273) const BACKEND_PORT = Number(process.env.AUTOVOICE_LIVE_BACKEND_PORT ?? 5051) -const BACKEND_PYTHON = process.env.AUTOVOICE_PYTHON ?? '/home/kp/anaconda3/envs/autovoice-thor/bin/python' +// Canonical Jetson interpreter when present; plain python3 elsewhere (hosted +// CI runners), overridable via AUTOVOICE_PYTHON either way. +const JETSON_PYTHON = '/home/kp/anaconda3/envs/autovoice-thor/bin/python' +const BACKEND_PYTHON = + process.env.AUTOVOICE_PYTHON ?? (existsSync(JETSON_PYTHON) ? JETSON_PYTHON : 'python3') const HOST = '127.0.0.1' export default defineConfig({ diff --git a/requirements-runtime.txt b/requirements-runtime.txt index 3d7f2da..8e489df 100644 --- a/requirements-runtime.txt +++ b/requirements-runtime.txt @@ -5,7 +5,11 @@ torch>=2.0 torchaudio>=2.0 numpy>=1.24 scipy>=1.10 -librosa>=0.10 +# <0.11: pyin's voiced decision changed in 0.11 (white noise scores ~0.43 +# voiced vs 0.0 on 0.10), which silently shifts the calibrated multi-speaker +# voicing gates (multi_speaker_merge_voiced_min et al). Re-calibrate before +# raising this bound. +librosa>=0.10,<0.11 soundfile>=0.12 # Web diff --git a/requirements.lock b/requirements.lock index 4c8f1b2..3c716fb 100644 --- a/requirements.lock +++ b/requirements.lock @@ -5,12 +5,12 @@ "backend": { "requirements_runtime": { "path": "requirements-runtime.txt", - "sha256": "a2e2fc3c1448ddd6b1caf661daa56a6b37086c36aba586b4e3a2f29a0a916133", - "line_count": 31 + "sha256": "c013d714111e1198048b2a47bbdf7a05b706ae5e5cb05f3686877ed957726f56", + "line_count": 32 }, "frontend_lock": { "path": "frontend/package-lock.json", - "sha256": "558b5c2635ba523d61778d507ad4103c2454455f89d884e863bc96f8dbec0980" + "sha256": "7c3533742d66c2192afe519fb6b605c140f05ba0663a60af412aa3f7de8dfe39" } }, "images": { diff --git a/scripts/run_remaining_module_coverage.py b/scripts/run_remaining_module_coverage.py index 8699af4..f30ae98 100644 --- a/scripts/run_remaining_module_coverage.py +++ b/scripts/run_remaining_module_coverage.py @@ -37,6 +37,7 @@ "tests/test_platform_scripts.py", "tests/test_quality_upgrades.py", "tests/test_web_app_lifecycle.py", + "tests/test_web_persistence_store.py", "tests/test_web_utils.py", "tests/test_web_api_config_endpoints.py", "tests/test_web_api_utility.py", @@ -78,8 +79,20 @@ def load_percent_covered(path: str, files: dict[str, dict[str, object]]) -> floa def main() -> int: + # On CUDA-less machines (hosted CI) deselect @pytest.mark.cuda tests: they + # need real GPU hardware. The Jetson runs the full set, so its coverage + # numbers remain the canonical ones. + pytest_args = ["-q"] + try: + import torch + cuda_ok = torch.cuda.is_available() + except Exception: + cuda_ok = False + if not cuda_ok: + pytest_args = ["-m", "not cuda", "-q"] + run([sys.executable, "-m", "coverage", "erase"]) - run([sys.executable, "-m", "coverage", "run", "-m", "pytest", "-p", "no:cov", *TEST_PATHS, "-q"]) + run([sys.executable, "-m", "coverage", "run", "-m", "pytest", "-p", "no:cov", *TEST_PATHS, *pytest_args]) run([sys.executable, "-m", "coverage", "json", "-o", str(COVERAGE_JSON)]) report_include = ",".join(MODULE_THRESHOLDS) run([sys.executable, "-m", "coverage", "report", "-m", f"--include={report_include}"]) diff --git a/src/auto_voice/inference/singing_conversion_pipeline.py b/src/auto_voice/inference/singing_conversion_pipeline.py index 495834e..9927539 100644 --- a/src/auto_voice/inference/singing_conversion_pipeline.py +++ b/src/auto_voice/inference/singing_conversion_pipeline.py @@ -44,6 +44,10 @@ def _voiced_fraction(audio: np.ndarray, sample_rate: int, max_s: float = 20.0) - (calibrated leads: 0.76-0.87); harmony stacks / textures it would butcher score low (calibrated: 0.14-0.51). Measured on up to ``max_s`` of active audio with pyin fmin=80 fmax=1000, matching the calibration convention. + + Calibration is coupled to librosa 0.10 pyin semantics (0.11 changed the + voiced decision: white noise jumps from 0.0 to ~0.43) — hence the + ``librosa<0.11`` bound in requirements-runtime.txt. """ import librosa diff --git a/src/auto_voice/web/api_profiles.py b/src/auto_voice/web/api_profiles.py index 275f137..e05c9bc 100644 --- a/src/auto_voice/web/api_profiles.py +++ b/src/auto_voice/web/api_profiles.py @@ -1399,7 +1399,7 @@ def add_sample_from_path(profile_id: str): from auto_voice.audio.separation import VocalSeparator - if _dep('torch_available'): + if _dep('torch_available') and _dep('torch').cuda.is_available(): _dep('torch').cuda.empty_cache() _dep('torch').cuda.synchronize() diff --git a/src/auto_voice/web/karaoke_api.py b/src/auto_voice/web/karaoke_api.py index 3406e0c..8937174 100644 --- a/src/auto_voice/web/karaoke_api.py +++ b/src/auto_voice/web/karaoke_api.py @@ -511,15 +511,17 @@ def upload_song(): secure_name = secure_filename(song_file.filename) file_ext = os.path.splitext(secure_name)[1].lower() + # Ensure the temp directory exists before handing it to + # NamedTemporaryFile (it does not create missing parents). + upload_dir = '/tmp/autovoice_karaoke' + os.makedirs(upload_dir, exist_ok=True) + tmp_file = tempfile.NamedTemporaryFile( suffix=file_ext, delete=False, - dir='/tmp/autovoice_karaoke' + dir=upload_dir ) - # Ensure directory exists - os.makedirs(os.path.dirname(tmp_file.name), exist_ok=True) - song_file.save(tmp_file.name) tmp_file.close() diff --git a/tests/live_backend_server.py b/tests/live_backend_server.py index 71ef5ec..6e2529b 100644 --- a/tests/live_backend_server.py +++ b/tests/live_backend_server.py @@ -12,6 +12,11 @@ from pathlib import Path from typing import Any +# The default DB backend is the production MySQL server, which does not exist +# on CI runners (and db.schema reads AUTOVOICE_DB_TYPE at import time) — the +# deterministic harness always runs on sqlite. +os.environ.setdefault("AUTOVOICE_DB_TYPE", "sqlite") + import numpy as np import torch @@ -301,11 +306,101 @@ def _seed_profile(store: VoiceProfileStore, *, profile_id: str, name: str, train ) +class _HarnessCuda: + """CPU-safe stand-in reporting one fake GPU. + + The production readiness probe (and the gpu/system-info endpoints) + require CUDA; this deterministic harness must present a ready backend on + CPU-only machines (hosted CI) too. Everything not overridden proxies to + the real torch.cuda. + """ + + def __getattr__(self, name: str) -> Any: + return getattr(torch.cuda, name) + + @staticmethod + def is_available() -> bool: + return True + + @staticmethod + def device_count() -> int: + return 1 + + @staticmethod + def get_device_name(index: int = 0) -> str: + return "Deterministic Harness GPU" + + @staticmethod + def get_device_properties(index: int = 0) -> Any: + import types as _types + return _types.SimpleNamespace( + name="Deterministic Harness GPU", + total_memory=8 * 1024 ** 3, + major=8, + minor=7, + multi_processor_count=1, + ) + + @staticmethod + def memory_allocated(index: int = 0) -> int: + return 0 + + @staticmethod + def memory_reserved(index: int = 0) -> int: + return 0 + + @staticmethod + def empty_cache() -> None: + return None + + @staticmethod + def synchronize() -> None: + return None + + +class _HarnessTorch: + """torch proxy whose .cuda is the harness fake; all else is real.""" + + cuda = _HarnessCuda() + + def __getattr__(self, name: str) -> Any: + return getattr(torch, name) + + def build_app(data_dir: Path): from auto_voice.web import api as web_api from auto_voice.web import karaoke_api import auto_voice.web.audio_router as audio_router + web_api.torch = _HarnessTorch() + + # Keep the harness sqlite DB inside the throwaway data dir (the default + # path is relative to the web server's cwd). + from auto_voice.db import schema as db_schema + db_schema.DATABASE_PATH = data_dir / "autovoice.db" + db_schema.init_database("sqlite") + + # Serve deterministic benchmark evidence: the System page fetches + # /reports/benchmarks/latest, and a 404 leaves an unavoidable browser + # console error that fails the zero-console-error acceptance check. + import json as _json + + reports_dir = data_dir / "reports" + latest_dir = reports_dir / "benchmarks" / "latest" + latest_dir.mkdir(parents=True, exist_ok=True) + _now = _iso_now() + (latest_dir / "benchmark_dashboard.json").write_text(_json.dumps({ + "generated_at": _now, + "target_hardware": "deterministic-harness", + "pipelines": {}, + }), encoding="utf-8") + (latest_dir / "release_evidence.json").write_text(_json.dumps({ + "generated_at": _now, + "ready": True, + "notes": "deterministic harness fixture", + }), encoding="utf-8") + web_api._reports_dir = lambda: reports_dir + app, socketio = create_app( config={ "TESTING": True, diff --git a/tests/test_fork_hq_lane.py b/tests/test_fork_hq_lane.py index 256da95..e23a575 100644 --- a/tests/test_fork_hq_lane.py +++ b/tests/test_fork_hq_lane.py @@ -33,7 +33,8 @@ def infer(self, audio, spk, emb, sr): monkeypatch.setattr(p, "_get_separator", lambda: FakeSep()) monkeypatch.setattr(p, "_get_model_manager", lambda: FakeMM()) - monkeypatch.setattr(p, "_extract_pitch", lambda a, sr: np.zeros(8, np.float32)) + monkeypatch.setattr(p, "_extract_pitch", + lambda a, sr, method=None: np.zeros(8, np.float32)) res = p._convert_song_fork_hq(str(song), "prof-1", 1.0, 0.9, True, "balanced", 0.0) diff --git a/tests/test_platform_scripts.py b/tests/test_platform_scripts.py index 53698b0..6f93a5f 100644 --- a/tests/test_platform_scripts.py +++ b/tests/test_platform_scripts.py @@ -106,7 +106,14 @@ def test_dependency_contract_enforces_high_critical_audit_policy(tmp_path): assert report["audits"]["npm-audit"]["ok"] is False -def test_common_env_prefers_canonical_python_over_stale_python(): +def test_common_env_prefers_canonical_python_over_stale_python(tmp_path): + # A fake HOME carrying the canonical env makes this deterministic on + # machines without the real autovoice-thor conda env (hosted CI). + fake_home = tmp_path / "home" + canonical = fake_home / "anaconda3" / "envs" / "autovoice-thor" / "bin" / "python" + canonical.parent.mkdir(parents=True) + canonical.write_text("#!/bin/sh\n") + canonical.chmod(0o755) command = ( "export PYTHON=/tmp/not-autovoice-python; " "source scripts/common_env.sh && " @@ -119,7 +126,7 @@ def test_common_env_prefers_canonical_python_over_stale_python(): capture_output=True, text=True, env={ - "HOME": os.environ.get("HOME", ""), + "HOME": str(fake_home), "PATH": os.environ.get("PATH", ""), "AUTOVOICE_ENV_NAME": "autovoice-thor", }, @@ -737,6 +744,7 @@ def test_preflight_full_hardware_rc_accepts_explicit_benchmark_report(tmp_path): "--no-require-jetson", "--no-require-docker", "--no-require-tensorrt-suite", + "--no-require-gitnexus", ], cwd=PROJECT_ROOT, capture_output=True, diff --git a/tests/test_trainer_comprehensive.py b/tests/test_trainer_comprehensive.py index 722214a..c5819fd 100644 --- a/tests/test_trainer_comprehensive.py +++ b/tests/test_trainer_comprehensive.py @@ -337,8 +337,13 @@ def test_custom_config(self): assert trainer.early_stopping_patience == 3 assert trainer.early_stopping_min_delta == 0.001 + @pytest.mark.cuda def test_cuda_device_auto_selection(self): - """Trainer auto-selects CUDA if available.""" + """Trainer auto-selects CUDA if available. + + Marked cuda: Trainer.__init__ moves internal modules to the selected + device, so with is_available stubbed True this still needs a real GPU. + """ from auto_voice.training.trainer import Trainer model = MockModel() diff --git a/tests/test_training_job_manager.py b/tests/test_training_job_manager.py index 648b231..da6d508 100644 --- a/tests/test_training_job_manager.py +++ b/tests/test_training_job_manager.py @@ -63,9 +63,15 @@ def mock_training_samples(): @pytest.fixture def job_manager(temp_job_storage): - """TrainingJobManager instance for testing.""" + """TrainingJobManager instance for testing. + + GPU availability is stubbed so the queue/persistence logic under test + runs on CPU-only machines (hosted CI); the GPU gate itself is covered by + tests/test_gpu_enforcement.py. + """ from auto_voice.training.job_manager import TrainingJobManager - return TrainingJobManager(storage_path=temp_job_storage) + with patch("torch.cuda.is_available", return_value=True): + return TrainingJobManager(storage_path=temp_job_storage) # ============================================================================ @@ -200,7 +206,8 @@ def test_job_manager_initialization(self, temp_job_storage): """TrainingJobManager initializes with storage path.""" from auto_voice.training.job_manager import TrainingJobManager - manager = TrainingJobManager(storage_path=temp_job_storage) + with patch("torch.cuda.is_available", return_value=True): + manager = TrainingJobManager(storage_path=temp_job_storage) assert manager.storage_path == temp_job_storage assert manager.is_initialized @@ -209,7 +216,8 @@ def test_job_manager_creates_storage_directory(self, temp_job_storage): from auto_voice.training.job_manager import TrainingJobManager new_path = temp_job_storage / "jobs" - manager = TrainingJobManager(storage_path=new_path) + with patch("torch.cuda.is_available", return_value=True): + manager = TrainingJobManager(storage_path=new_path) assert new_path.exists() def test_job_manager_has_empty_queue_initially(self, job_manager): diff --git a/tests/test_training_job_manager_phase5.py b/tests/test_training_job_manager_phase5.py index 44a4a6c..764bd50 100644 --- a/tests/test_training_job_manager_phase5.py +++ b/tests/test_training_job_manager_phase5.py @@ -100,11 +100,17 @@ def train(self, training_dir, resume_from=None): decoder_module = types.ModuleType("auto_voice.models.svc_decoder") decoder_module.CoMoSVCDecoder = FakeModel + # The diffusion_mel architecture (the default) imports DiffusionMelDecoder + # inside run_training and moves it to the CUDA device; fake it so these + # queue-orchestration tests run on CPU-only machines (hosted CI) too. + diffusion_module = types.ModuleType("auto_voice.models.diffusion_decoder") + diffusion_module.DiffusionMelDecoder = FakeModel trainer_module = types.ModuleType("auto_voice.training.trainer") trainer_module.Trainer = FakeTrainer return { "auto_voice.models.svc_decoder": decoder_module, + "auto_voice.models.diffusion_decoder": diffusion_module, "auto_voice.training.trainer": trainer_module, }, trainer_instances diff --git a/tests/test_web_persistence_store.py b/tests/test_web_persistence_store.py new file mode 100644 index 0000000..bd8a901 --- /dev/null +++ b/tests/test_web_persistence_store.py @@ -0,0 +1,301 @@ +"""Round-trip unit tests for the JSON-backed AppStateStore. + +These cover the store's CRUD surfaces and normalizer edge branches directly: +they are the CPU-only coverage source for src/auto_voice/web/persistence.py +in the remaining-module coverage gate (the API suites only graze it). +""" +import json + +import pytest + +from auto_voice.web.persistence import ( + AppStateStore, + _coerce_bool, + _coerce_float, + _coerce_optional_int, + _normalize_app_settings, + _normalize_audio_router_config, + _normalize_device_config, + _normalize_karaoke_session, + _normalize_pitch_config, + _normalize_separation_config, +) + + +@pytest.fixture +def store(tmp_path): + return AppStateStore(data_dir=str(tmp_path)) + + +class TestCoercions: + @pytest.mark.parametrize("value,expected", [ + ("true", True), ("1", True), ("YES", True), ("on", True), + ("false", False), ("0", False), ("No", False), ("off", False), + ]) + def test_coerce_bool_strings(self, value, expected): + assert _coerce_bool(value, not expected) is expected + + def test_coerce_bool_fallbacks(self): + assert _coerce_bool(None, True) is True + assert _coerce_bool("maybe", False) is True # non-empty string -> bool() + assert _coerce_bool(0, True) is False + + def test_coerce_float_invalid_and_clamped(self): + assert _coerce_float("not-a-number", 0.5) == 0.5 + assert _coerce_float(None, 0.25) == 0.25 + assert _coerce_float(9.0, 0.5) == 2.0 # clamped to maximum + assert _coerce_float(-1.0, 0.5) == 0.0 # clamped to minimum + + def test_coerce_optional_int(self): + assert _coerce_optional_int(None) is None + assert _coerce_optional_int("") is None + assert _coerce_optional_int("7") == 7 + with pytest.raises(ValueError): + _coerce_optional_int(True) + + +class TestNormalizers: + def test_app_settings_legacy_realtime(self): + settings = _normalize_app_settings({"preferred_pipeline": "realtime"}) + assert settings["preferred_offline_pipeline"] == "realtime" + assert settings["preferred_live_pipeline"] == "realtime" + assert settings["preferred_pipeline"] == "realtime" + + def test_audio_router_invalid_values_fall_back(self): + config = _normalize_audio_router_config({ + "speaker_gain": "loud", # invalid float -> default + "speaker_enabled": "off", + "speaker_device": "not-an-int", # invalid -> default + "headphone_device": "3", + "sample_rate": "broken", # invalid -> keep default + }) + assert config["speaker_enabled"] is False + assert config["headphone_device"] == 3 + assert config["speaker_device"] == _normalize_audio_router_config({})["speaker_device"] + assert config["sample_rate"] == _normalize_audio_router_config({})["sample_rate"] + + def test_device_config_bad_sample_rate_ignored(self): + config = _normalize_device_config({ + "input_device_id": 4, + "output_device_id": "", + "sample_rate": "junk", + }) + assert config["input_device_id"] == "4" + assert config["output_device_id"] is None + assert config["sample_rate"] == _normalize_device_config({})["sample_rate"] + + def test_separation_config_invalid_segment_and_shifts(self): + default = _normalize_separation_config({}) + config = _normalize_separation_config({ + "segment_length": "oops", + "shifts": "nope", + "device": "tpu", # not accepted -> default retained + }) + assert config["segment_length"] == default["segment_length"] + assert config["shifts"] == default["shifts"] + assert config["device"] == default["device"] + assert _normalize_separation_config({"segment_length": -2})["segment_length"] is None + assert _normalize_separation_config({"segment_length": ""})["segment_length"] is None + + def test_pitch_config_device_and_invalid_ints(self): + default = _normalize_pitch_config({}) + config = _normalize_pitch_config({"hop_length": "bad", "device": "cuda"}) + assert config["hop_length"] == default["hop_length"] + assert config["device"] == "cuda" + assert config["use_gpu"] is True + cpu = _normalize_pitch_config({"device": "cpu"}) + assert cpu["use_gpu"] is False + + def test_karaoke_session_normalization(self): + assert _normalize_karaoke_session(None) is None + assert _normalize_karaoke_session({"session_id": " "}) is None + session = _normalize_karaoke_session({ + "session_id": " s1 ", + "requested_pipeline": " REALTIME ", + "is_active": "yes", + "speaker_embedding": [0.1, 0.2], + "stats": {"frames": 5}, + }) + assert session["session_id"] == "s1" + assert session["requested_pipeline"] == "realtime" + assert session["resolved_pipeline"] == "realtime" + assert session["is_active"] is True + assert session["speaker_embedding"] == [0.1, 0.2] + assert session["stats"] == {"frames": 5} + no_embedding = _normalize_karaoke_session({"session_id": "s2", + "speaker_embedding": "oops"}) + assert no_embedding["speaker_embedding"] is None + + +class TestStoreReadWrite: + def test_corrupt_json_returns_default(self, store): + store._files["presets"].write_text("{not json", encoding="utf-8") + assert store.list_presets() == [] + + def test_training_jobs_roundtrip_and_filter(self, store): + store.save_training_job({"job_id": "j1", "profile_id": "p1", "created_at": "2026-01-01"}) + store.save_training_job({"job_id": "j2", "profile_id": "p2", "created_at": "2026-01-02"}) + assert store.get_training_job("j1")["profile_id"] == "p1" + assert [j["job_id"] for j in store.list_training_jobs()] == ["j2", "j1"] + assert [j["job_id"] for j in store.list_training_jobs("p1")] == ["j1"] + + def test_background_jobs_roundtrip_and_filter(self, store): + store.save_background_job({"job_id": "b1", "job_type": "export", "created_at": "1"}) + store.save_background_job({"job_id": "b2", "job_type": "import", "created_at": "2"}) + assert store.get_background_job("b2")["job_type"] == "import" + assert [j["job_id"] for j in store.list_background_jobs("export")] == ["b1"] + + def test_presets_crud(self, store): + store.save_preset({"id": "pr1", "created_at": "1"}) + assert store.get_preset("pr1") is not None + assert [p["id"] for p in store.list_presets()] == ["pr1"] + assert store.delete_preset("pr1") is True + assert store.delete_preset("pr1") is False + + def test_conversion_history_crud(self, store): + store.save_conversion_record({"id": "c1", "profile_id": "p1", "created_at": "1"}) + store.save_conversion_record({"id": "c2", "profile_id": "p2", "created_at": "2"}) + assert store.get_conversion_record("c1")["profile_id"] == "p1" + assert [r["id"] for r in store.list_conversion_history("p2")] == ["c2"] + assert store.delete_conversion_record("c1") is True + assert store.delete_conversion_record("missing") is False + + def test_conversion_workflows_crud(self, store): + store.save_conversion_workflow({"workflow_id": "w1", "status": "done", "created_at": "1"}) + store.save_conversion_workflow({"workflow_id": "w2", "status": "running", "updated_at": "2"}) + assert store.get_conversion_workflow("w2")["status"] == "running" + assert [w["workflow_id"] for w in store.list_conversion_workflows("done")] == ["w1"] + assert [w["workflow_id"] for w in store.list_conversion_workflows()] == ["w2", "w1"] + assert store.delete_conversion_workflow("w1") is True + assert store.delete_conversion_workflow("w1") is False + + def test_diarization_results_crud(self, store): + store.save_diarization_result({"diarization_id": "d1", "created_at": 1}) + store.save_diarization_result({"diarization_id": "d2", "created_at": 2}) + assert store.get_diarization_result("d1") is not None + assert [d["diarization_id"] for d in store.list_diarization_results()] == ["d2", "d1"] + assert store.delete_diarization_result("d2") is True + assert store.delete_diarization_result("d2") is False + + def test_diarization_segment_assignments(self, store): + assert store.get_diarization_segment_assignments("p1") == {} + saved = store.save_diarization_segment_assignment("p1", "seg-0", "/a.wav") + assert saved == {"seg-0": "/a.wav"} + assert store.get_diarization_segment_assignments("p1") == {"seg-0": "/a.wav"} + assert store.delete_diarization_segment_assignments("p1") is True + assert store.delete_diarization_segment_assignments("p1") is False + + def test_checkpoints_crud(self, store): + store.save_checkpoint("p1", {"id": "ck1", "created_at": "1"}) + store.save_checkpoint("p1", {"id": "ck2", "created_at": "2"}) + assert store.get_checkpoint("p1", "ck1") is not None + assert [c["id"] for c in store.list_checkpoints("p1")] == ["ck2", "ck1"] + assert store.delete_checkpoint("p1", "missing") is False + assert store.delete_checkpoint("p1", "ck1") is True + assert store.delete_checkpoint("p1", "ck2") is True # empties the profile map + assert store.list_checkpoints("p1") == [] + + def test_webhooks_crud(self, store): + store.save_webhook({"id": "wh1", "created_at": "1"}) + assert store.get_webhook("wh1") is not None + assert [w["id"] for w in store.list_webhooks()] == ["wh1"] + assert store.delete_webhook("wh1") is True + assert store.delete_webhook("wh1") is False + + def test_loaded_models_crud(self, store): + store.save_loaded_model("fork", {"model_type": "fork", "loaded_at": "1"}) + assert store.get_loaded_model("fork") is not None + assert len(store.list_loaded_models()) == 1 + assert store.delete_loaded_model("fork") is True + assert store.delete_loaded_model("fork") is False + store.save_loaded_model("hq", {"model_type": "hq"}) + store.clear_loaded_models() + assert store.list_loaded_models() == [] + + def test_config_updates_roundtrip(self, store): + sep = store.update_separation_config({"model": "htdemucs_ft"}) + assert sep["model"] == "htdemucs_ft" + assert store.get_separation_config()["model"] == "htdemucs_ft" + pitch = store.update_pitch_config({"device": "cuda"}) + assert pitch["use_gpu"] is True + router = store.update_audio_router_config({"speaker_gain": 1.5}) + assert router["speaker_gain"] == 1.5 + device = store.update_device_config({"input_device_id": 2}) + assert device["input_device_id"] == "2" + + +class TestYoutubeHistoryAndAssets: + def test_youtube_history_crud(self, store): + store.save_youtube_history_item({"id": "y1", "timestamp": "1"}) + store.save_youtube_history_item({"id": "y2", "timestamp": "2"}) + store.save_youtube_history_item({"id": "y1", "timestamp": "3"}) # replaces + assert store.get_youtube_history_item("y1")["timestamp"] == "3" + assert store.get_youtube_history_item("missing") is None + assert [i["id"] for i in store.list_youtube_history(limit=1)] == ["y1"] + assert store.delete_youtube_history_item("y2") is True + assert store.delete_youtube_history_item("y2") is False + export = store.export_youtube_history() + assert export["count"] == 1 and export["items"][0]["id"] == "y1" + + def test_purge_youtube_history_deletes_managed_assets(self, store, tmp_path): + managed = tmp_path / "managed" + managed.mkdir() + inside = managed / "song.wav" + inside.write_bytes(b"x") + outside = tmp_path / "outside.wav" + outside.write_bytes(b"y") + store.save_youtube_history_item({ + "id": "y1", "timestamp": "1", + "audioPath": str(inside), + "filteredPath": str(outside), + "audio_path": "\x00bad\x00path", # unresolvable -> skipped + }) + result = store.purge_youtube_history(delete_assets=True, managed_roots=[managed]) + assert result["purged_items"] == 1 + assert str(inside) in result["deleted_files"] + assert str(outside) in result["skipped_files"] + assert not inside.exists() + assert outside.exists() + assert store.list_youtube_history() == [] + + def test_purge_without_delete_keeps_files(self, store, tmp_path): + wav = tmp_path / "keep.wav" + wav.write_bytes(b"x") + store.save_youtube_history_item({"id": "y1", "timestamp": "1", "audioPath": str(wav)}) + result = store.purge_youtube_history(delete_assets=False) + assert result["deleted_files"] == [] + assert wav.exists() + + def test_asset_registry_crud(self, store, tmp_path): + record = store.register_asset(tmp_path / "a.wav", kind="song", owner_id="p1") + again = store.register_asset(tmp_path / "a.wav", kind="song", owner_id="p1") + assert record["asset_id"] == again["asset_id"] # stable id per path + assert store.get_asset(record["asset_id"])["kind"] == "song" + assert store.get_asset("missing") is None + store.register_asset(tmp_path / "b.wav", kind="song", owner_id="p2") + assert len(store.list_assets()) == 2 + assert [a["owner_id"] for a in store.list_assets(owner_id="p2")] == ["p2"] + assert store.delete_asset(record["asset_id"]) is True + assert store.delete_asset(record["asset_id"]) is False + + +class TestKaraokeSessions: + def test_karaoke_session_store_roundtrip(self, store): + saved = store.save_karaoke_session({"session_id": "s1", "last_activity": 2}) + assert saved["session_id"] == "s1" + store.save_karaoke_session({"session_id": "s2", "last_activity": 5}) + sessions = store.list_karaoke_sessions() + assert [s["session_id"] for s in sessions] == ["s2", "s1"] + assert store.get_karaoke_session("s1")["session_id"] == "s1" + assert store.get_karaoke_session("missing") is None + assert store.delete_karaoke_session("s1") is True + assert store.delete_karaoke_session("s1") is False + + def test_karaoke_session_requires_id(self, store): + with pytest.raises(ValueError): + store.save_karaoke_session({"song_id": "x"}) + + def test_list_skips_malformed_snapshots(self, store): + store._write("karaoke_sessions", {"bad": {"song_id": "no-session-id"}, + "ok": {"session_id": "s9"}}) + assert [s["session_id"] for s in store.list_karaoke_sessions()] == ["s9"]