diff --git a/.github/workflows/build-baseline.yml b/.github/workflows/build-baseline.yml index 3665962..858c737 100644 --- a/.github/workflows/build-baseline.yml +++ b/.github/workflows/build-baseline.yml @@ -163,6 +163,7 @@ jobs: - name: Install node dependencies run: npm ci - name: Sync Python dependencies + if: runner.os != 'Windows' || runner.arch != 'ARM64' # llvmlite lacks wheel for Windows ARM64 run: uv sync --project services/analysis-engine --group dev --frozen - name: Build frontend run: npm run build --workspace @bandscope/desktop diff --git a/docs/plans/2026-03-28-ml-engine-integration.md b/docs/plans/2026-03-28-ml-engine-integration.md new file mode 100644 index 0000000..9918980 --- /dev/null +++ b/docs/plans/2026-03-28-ml-engine-integration.md @@ -0,0 +1,59 @@ +# ML Engine Integration Plan + +## Overview +Now that the basic IPC and React/Python orchestrator boundaries are proven (Issue #26 epics), the next phase is replacing the hardcoded, instantaneous mock data with real digital signal processing (DSP) and Machine Learning (ML) inference. + +This document outlines the MECE execution strategy to incrementally substitute mock systems with reality. + +## Execution Tracks + +### Track 1: Temporal Foundation (#105) +- **Goal**: Replace simple count-based anchors with a real tempo and beat grid. +- **Tech**: Add `librosa` or `soundfile` for robust decoding. +- **Output**: Real file ingestion and tempo/beat arrays. + +### Track 2: Spectral & Stem Separation (#106) +- **Goal**: Deconstruct the mixed audio into isolated stems. +- **Tech**: Integrate `demucs` (or a smaller alternative) running locally. +- **Output**: 4 or 6 discrete stems (vocals, bass, drums, other). + +### Track 3: Harmonic & Pitch Pipelines (#107) +- **Goal**: Replace hardcoded `C#m7` strings with DSP-derived chord and pitch arrays. +- **Tech**: Chromagram extraction and Viterbi decoding for chords. YIN/pYIN for pitch ranges. +- **Output**: Accurate harmonic sequences tied to Track 1's beat grid. + +### Track 4: Structural Graph Assembly (#108) +- **Goal**: Infer boundaries (Verse, Chorus) and detect which roles (stems) are playing. +- **Tech**: Self-similarity matrices and energy thresholding on the stems. +- **Output**: The true `PartGraph` and `Section` payloads. + +### Track 5: Orchestration & UX (#109) +- **Goal**: Handle the fact that ML takes minutes, not milliseconds. +- **Tech**: Async progress callbacks, IPC streaming updates. +- **Output**: Responsive UI during long-running tasks. + +## Security Notes + +### Attack Surface +The integration of ML libraries like `librosa`, `torch`, and `demucs` exposes the desktop app to complex audio processing pipelines that parse potentially malformed user-provided audio files. + +### Trust Boundary +The primary trust boundary is between the user's filesystem (audio files) and the Python local analysis engine. All input audio is untrusted. + +### Mitigations +We will restrict audio ingestion through `librosa`/`soundfile` using strict format constraints. We will execute ML tasks locally, without reaching out to external networks, and run them under low privileges where possible. + +### Test Points +- Loading truncated or corrupted WAV/MP3 files. +- Providing extremely large audio files to test OOM behavior. +- Validating that no external network calls occur during offline ML processing. + +### Realistic Threats +- OOM (Out Of Memory) crashing the user's host OS during `demucs` execution. +- Arbitrary code execution (ACE) vulnerabilities within C-level parsing dependencies of `librosa`/`soundfile`. + +### Remaining Risk +Large ML dependencies carry high vulnerability footprints. We depend on upstream patching for zero-days in C-level audio codec libraries. + +1. **Supply Chain**: Must follow `docs/security/dependency-policy.md`. Large ML dependencies carry high vulnerability footprints. +2. **Execution**: Must gracefully handle lack of GPU/MPS, defaulting to CPU chunks without OOM-crashing the host OS. diff --git a/services/analysis-engine/pyproject.toml b/services/analysis-engine/pyproject.toml index bb6c604..964007e 100644 --- a/services/analysis-engine/pyproject.toml +++ b/services/analysis-engine/pyproject.toml @@ -8,6 +8,9 @@ version = "0.1.0" description = "BandScope local-first analysis engine" requires-python = ">=3.12" dependencies = [ + "librosa>=0.11.0", + "numba<0.63.0", + "soundfile>=0.13.1", "yt-dlp>=2026.3.17", ] diff --git a/services/analysis-engine/src/bandscope_analysis/cli.py b/services/analysis-engine/src/bandscope_analysis/cli.py index 6b1d3c4..8c694fd 100644 --- a/services/analysis-engine/src/bandscope_analysis/cli.py +++ b/services/analysis-engine/src/bandscope_analysis/cli.py @@ -3,10 +3,15 @@ from __future__ import annotations import json +import logging import sys from datetime import UTC, datetime -from bandscope_analysis.api import run_analysis_job +from bandscope_analysis.api import get_analysis_status, run_analysis_job +from bandscope_analysis.temporal import TemporalAnalyzer + +# Temporary logging setup for temporal analyzer +logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") def failed_cli_response(message: str) -> dict[str, object]: @@ -26,23 +31,66 @@ def failed_cli_response(message: str) -> dict[str, object]: def main() -> int: """Read a job payload from stdin and print a structured job response to stdout.""" + # Read all input from stdin first + input_data = sys.stdin.read().strip() + + # Check if there are command line arguments (fallback for manual testing) + if len(sys.argv) > 1: + if sys.argv[1] == "--status": + json.dump(get_analysis_status(), sys.stdout) + return 0 + elif sys.argv[1] == "--job" and len(sys.argv) > 2: + input_data = sys.argv[2] + if not input_data.startswith("{"): + try: + with open(input_data, "r", encoding="utf-8") as f: + input_data = f.read() + except Exception as e: + json.dump(failed_cli_response(f"Failed to read job file: {e}"), sys.stdout) + return 1 + + if not input_data: + json.dump(failed_cli_response("Empty input"), sys.stdout) + return 0 + try: - payload = json.load(sys.stdin) + payload = json.loads(input_data) except json.JSONDecodeError as error: json.dump(failed_cli_response(f"Invalid analysis job request: {error.msg}"), sys.stdout) return 0 + if not isinstance(payload, dict): json.dump( failed_cli_response("Invalid analysis job request: invalid field 'root'"), sys.stdout ) return 0 + job_id = payload.get("jobId") if not isinstance(job_id, str) or not job_id.strip(): json.dump( failed_cli_response("Invalid analysis job request: invalid field 'jobId'"), sys.stdout ) return 0 + request = payload.get("request") + + # Temporary: Inject temporal analyzer call if it's a local file, just to prove it works + # before full orchestrator integration + if ( + isinstance(request, dict) + and request.get("sourceKind") == "local_audio" + and "localSource" in request + ): + audio_path = request["localSource"].get("sourcePath") + if audio_path: + logging.info(f"Extracting temporal features from {audio_path}...") + try: + temporal_analyzer = TemporalAnalyzer() + features = temporal_analyzer.analyze(audio_path) + logging.info(f"Extracted BPM: {features['bpm']}") + except Exception as e: + logging.warning(f"Temporal analysis failed, continuing with mock: {e}") + requested_at = datetime.now(UTC).isoformat().replace("+00:00", "Z") response = run_analysis_job(job_id, request, requested_at) json.dump(response, sys.stdout) diff --git a/services/analysis-engine/src/bandscope_analysis/temporal/__init__.py b/services/analysis-engine/src/bandscope_analysis/temporal/__init__.py new file mode 100644 index 0000000..62967e7 --- /dev/null +++ b/services/analysis-engine/src/bandscope_analysis/temporal/__init__.py @@ -0,0 +1,6 @@ +"""Temporal analysis module (audio decoding, tempo, beat tracking).""" + +from .analyzer import TemporalAnalyzer +from .model import TemporalFeatures + +__all__ = ["TemporalAnalyzer", "TemporalFeatures"] diff --git a/services/analysis-engine/src/bandscope_analysis/temporal/analyzer.py b/services/analysis-engine/src/bandscope_analysis/temporal/analyzer.py new file mode 100644 index 0000000..dc9113c --- /dev/null +++ b/services/analysis-engine/src/bandscope_analysis/temporal/analyzer.py @@ -0,0 +1,77 @@ +"""Temporal analyzer implementation for audio ingestion and beat tracking.""" + +from __future__ import annotations + +import logging +from pathlib import Path +from typing import Any + +import librosa +import numpy as np +from numpy.typing import NDArray + +from .model import TemporalFeatures + +logger = logging.getLogger(__name__) + +# Standard sample rate for BandScope analysis +TARGET_SR = 44100 + + +class TemporalAnalyzer: + """Analyzes temporal features (BPM, beats) from audio files.""" + + def __init__(self) -> None: + """Initialize the temporal analyzer.""" + pass + + def analyze(self, audio_path: str | Path) -> TemporalFeatures: + """Decode audio and extract temporal features. + + Args: + audio_path: Path to the audio file. + + Returns: + TemporalFeatures containing BPM and beat grids. + """ + path_str = str(audio_path) + logger.info(f"Loading and decoding audio: {path_str}") + + try: + # Load audio, converting to mono and standardizing sample rate + y, sr = librosa.load(path_str, sr=TARGET_SR, mono=True) + + # Ensure it's a 1D float array for librosa + if not isinstance(y, np.ndarray): + raise ValueError("Expected numpy array from librosa.load") + + y_array: NDArray[np.floating[Any]] = y + duration = float(librosa.get_duration(y=y_array, sr=sr)) + + logger.info("Extracting tempo and beat tracking...") + # Use librosa's robust beat tracker + tempo, beat_frames = librosa.beat.beat_track(y=y_array, sr=sr) + + # Convert frame indices to time (seconds) + beat_times: NDArray[np.floating[Any]] = librosa.frames_to_time(beat_frames, sr=sr) + + # Extract downbeats (simple approximation: every 4th beat) + # A real model might use madmom or complex DBNs for precise downbeats + downbeat_times = [float(bt) for i, bt in enumerate(beat_times) if i % 4 == 0] + + bpm_val = float(tempo[0]) if isinstance(tempo, np.ndarray) else float(tempo) + + logger.info(f"Analysis complete: {bpm_val:.1f} BPM, {len(beat_times)} beats detected.") + + return { + "bpm": bpm_val, + "beat_times": [float(bt) for bt in beat_times], + "downbeat_times": downbeat_times, + "duration_seconds": duration, + "sample_rate": int(sr), + "audio_path": path_str, + } + + except Exception as e: + logger.error(f"Failed to analyze audio {path_str}: {e}") + raise ValueError(f"Temporal analysis failed: {e}") from e diff --git a/services/analysis-engine/src/bandscope_analysis/temporal/model.py b/services/analysis-engine/src/bandscope_analysis/temporal/model.py new file mode 100644 index 0000000..b3958e9 --- /dev/null +++ b/services/analysis-engine/src/bandscope_analysis/temporal/model.py @@ -0,0 +1,16 @@ +"""Data models for temporal analysis.""" + +from __future__ import annotations + +from typing import TypedDict + + +class TemporalFeatures(TypedDict): + """Features extracted during temporal analysis.""" + + bpm: float + beat_times: list[float] + downbeat_times: list[float] + duration_seconds: float + sample_rate: int + audio_path: str diff --git a/services/analysis-engine/tests/test_cli.py b/services/analysis-engine/tests/test_cli.py index 1504a02..f63089a 100644 --- a/services/analysis-engine/tests/test_cli.py +++ b/services/analysis-engine/tests/test_cli.py @@ -220,3 +220,155 @@ def test_cli_module_runs_as_main(monkeypatch) -> None: assert exit_signal.code == 0 assert json.loads(stdout.getvalue())["jobId"] == "job-4" + + +def test_cli_main_empty_input(monkeypatch) -> None: + """Ensure empty input yields an error.""" + stdin = io.StringIO("") + stdout = io.StringIO() + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + assert cli.main() == 0 + assert "Empty input" in stdout.getvalue() + + +def test_cli_main_status_arg(monkeypatch) -> None: + """Ensure --status returns the analysis engine status.""" + stdin = io.StringIO("") + stdout = io.StringIO() + monkeypatch.setattr(cli.sys, "argv", ["cli.py", "--status"]) + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + assert cli.main() == 0 + assert "ready" in stdout.getvalue() + + +def test_cli_main_job_arg_invalid_file(monkeypatch, tmp_path) -> None: + """Ensure --job with missing file yields an error.""" + stdin = io.StringIO("") + stdout = io.StringIO() + non_existent = tmp_path / "nope.json" + monkeypatch.setattr(cli.sys, "argv", ["cli.py", "--job", str(non_existent)]) + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + assert cli.main() == 1 + assert "Failed to read job file" in stdout.getvalue() + + +def test_cli_main_job_arg_valid_file(monkeypatch, tmp_path) -> None: + """Ensure --job with valid file processes the job.""" + job_file = tmp_path / "job.json" + job_file.write_text( + json.dumps( + { + "jobId": "job-file", + "request": { + "sourceKind": "demo", + "sourceLabel": "Late Night Set", + "roleFocus": ["keys-right"], + }, + } + ) + ) + stdin = io.StringIO("") + stdout = io.StringIO() + monkeypatch.setattr(cli.sys, "argv", ["cli.py", "--job", str(job_file)]) + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + assert cli.main() == 0 + assert "job-file" in stdout.getvalue() + + +def test_cli_main_job_arg_json_string(monkeypatch) -> None: + """Ensure --job with raw JSON string processes the job.""" + json_str = json.dumps( + { + "jobId": "job-raw", + "request": { + "sourceKind": "demo", + "sourceLabel": "Raw String", + "roleFocus": ["keys-right"], + }, + } + ) + stdin = io.StringIO("") + stdout = io.StringIO() + monkeypatch.setattr(cli.sys, "argv", ["cli.py", "--job", json_str]) + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + assert cli.main() == 0 + assert "job-raw" in stdout.getvalue() + + +def test_cli_main_temporal_analyzer_mock(monkeypatch) -> None: + """Ensure the temporal analyzer injection block is covered and handles errors.""" + stdin = io.StringIO( + json.dumps( + { + "jobId": "job-audio", + "request": { + "sourceKind": "local_audio", + "projectId": "p1", + "sourceLabel": "test.wav", + "roleFocus": [], + "localSource": { + "sourcePath": "/invalid/path.wav", + "fileName": "test.wav", + "extension": "wav", + "fileSizeBytes": 100, + }, + }, + } + ) + ) + stdout = io.StringIO() + + class FakeAnalyzer: + def analyze(self, path): + raise RuntimeError("mocked failure") + + monkeypatch.setattr(cli, "TemporalAnalyzer", FakeAnalyzer) + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + monkeypatch.setattr(cli.sys, "argv", ["cli.py"]) + + assert cli.main() == 0 + res = json.loads(stdout.getvalue()) + assert res["jobId"] == "job-audio" + + +def test_cli_main_temporal_analyzer_mock_success(monkeypatch) -> None: + """Ensure the temporal analyzer injection block succeeds.""" + stdin = io.StringIO( + json.dumps( + { + "jobId": "job-audio-success", + "request": { + "sourceKind": "local_audio", + "projectId": "p1", + "sourceLabel": "test.wav", + "roleFocus": [], + "localSource": { + "sourcePath": "/valid/path.wav", + "fileName": "test.wav", + "extension": "wav", + "fileSizeBytes": 100, + }, + }, + } + ) + ) + stdout = io.StringIO() + + class FakeAnalyzerSuccess: + def analyze(self, path): + return {"bpm": 120.0, "beats": []} + + monkeypatch.setattr(cli, "TemporalAnalyzer", FakeAnalyzerSuccess) + monkeypatch.setattr(cli.sys, "stdin", stdin) + monkeypatch.setattr(cli.sys, "stdout", stdout) + monkeypatch.setattr(cli.sys, "argv", ["cli.py"]) + + assert cli.main() == 0 + res = json.loads(stdout.getvalue()) + assert res["jobId"] == "job-audio-success" diff --git a/services/analysis-engine/tests/test_temporal.py b/services/analysis-engine/tests/test_temporal.py new file mode 100644 index 0000000..28f9586 --- /dev/null +++ b/services/analysis-engine/tests/test_temporal.py @@ -0,0 +1,70 @@ +"""Tests for temporal analysis module.""" + +from pathlib import Path + +import numpy as np +import pytest +import soundfile as sf + +from bandscope_analysis.temporal import TemporalAnalyzer + + +@pytest.fixture +def dummy_audio_file(tmp_path: Path) -> Path: + """Create a short dummy audio file (sine wave with a clear beat).""" + sr = 44100 + duration = 5.0 # 5 seconds to give beat tracker enough data + t = np.linspace(0, duration, int(sr * duration), endpoint=False) + + # 440 Hz sine wave + some volume modulation for "beats" + # A clear 120 BPM transient + audio = np.zeros_like(t) + beat_interval = int(sr * 60 / 120) # 0.5s intervals + for i in range(0, len(audio), beat_interval): + end = min(i + int(sr * 0.1), len(audio)) + audio[i:end] = np.sin(2 * np.pi * 100 * t[i:end]) # Drum-like thud + + file_path = tmp_path / "test_audio.wav" + sf.write(str(file_path), audio, sr) + return file_path + + +def test_temporal_analyzer_basic(dummy_audio_file: Path) -> None: + """Test that the analyzer can decode audio and return valid features.""" + analyzer = TemporalAnalyzer() + features = analyzer.analyze(dummy_audio_file) + + assert features["sample_rate"] == 44100 + assert features["duration_seconds"] == pytest.approx(5.0, abs=0.1) + # librosa might not get exactly 120 with short synth data, but should be > 0 + assert features["bpm"] > 0 + assert isinstance(features["beat_times"], list) + assert isinstance(features["downbeat_times"], list) + + +def test_temporal_analyzer_file_not_found() -> None: + """Test that analyzer raises appropriate error for missing files.""" + analyzer = TemporalAnalyzer() + with pytest.raises(ValueError, match="Temporal analysis failed"): + analyzer.analyze("nonexistent_file.wav") + + +def test_temporal_analyzer_invalid_y_type(monkeypatch, tmp_path): + """Ensure temporal analyzer raises ValueError if librosa returns non-ndarray.""" + import librosa + + from bandscope_analysis.temporal.analyzer import TemporalAnalyzer + + def fake_load(*args, **kwargs): + return "not-an-array", 22050 + + monkeypatch.setattr(librosa, "load", fake_load) + + test_wav = tmp_path / "test.wav" + test_wav.write_bytes(b"dummy") + + analyzer = TemporalAnalyzer() + import pytest + + with pytest.raises(ValueError, match="Expected numpy array"): + analyzer.analyze(test_wav) diff --git a/services/analysis-engine/uv.lock b/services/analysis-engine/uv.lock index 3d49324..4529aa0 100644 --- a/services/analysis-engine/uv.lock +++ b/services/analysis-engine/uv.lock @@ -1,12 +1,88 @@ version = 1 revision = 3 requires-python = ">=3.12" +resolution-markers = [ + "python_full_version >= '3.13'", + "python_full_version < '3.13'", +] + +[[package]] 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