Implement sonicSimilarity extension with real audio feature analysis

Adds internal/audiofeatures: decodes each scanned song to PCM via
ffmpeg and computes actual measured characteristics — tempo (via
autocorrelation of the frame energy envelope, left unset rather than
guessed when a clip is too short to contain a beat), an approximate
loudness figure, spectral centroid/rolloff and zero-crossing rate (via
a hand-written FFT), and a 12-bin chroma vector used both for a
Krumhansl-Kessler key estimate and as similarity-index input. No
external DSP/ML dependency.

The scanner now runs this analysis after indexing each song (as part
of the already-background scan, not on any request path) and stores
results in the existing audio_features table via the new
database.UpsertAudioFeatures/GetAudioFeatures/ListAllAudioFeatures.

internal/similarity is a small in-process nearest-neighbor index:
z-score normalizes each feature dimension across the analyzed library
and answers Nearest (ranked real distances) and Path (a feature-space
straight-line walk from one track to another, hopping to the closest
not-yet-used real song at each step — never a fabricated intermediate
track).

getSonicSimilarTracks and findSonicPath expose these through the
standard sonicMatch response, converting distance to a normalized
(0,1] similarity score. A song that hasn't been analyzed yet is simply
absent from results rather than faked.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014r98AtcBbevpscWLsfwVvv

internal/app/app.go

@@ -57,6 +57,7 @@ func Open(cfg config.Config, log *slog.Logger) (*App, error) {
 
 	prober := &metadata.Prober{FFprobePath: cfg.FFprobePath}
 	sc := scanner.New(db, prober, log)
+	sc.FFmpegPath = cfg.FFmpegPath
 
 	coverCache := filepath.Join(cfg.DataDir, "cache", "covers")
 	covers := coverart.New(coverCache, cfg.FFmpegPath)