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
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@@ -55,7 +55,7 @@ func TestGetOpenSubsonicExtensions(t *testing.T) {
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// set once Phase 3 is done.
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for _, want := range []string{
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"apiKeyAuthentication", "formPost", "getPodcastEpisode", "topSongsByArtistId", "transcodeOffset",
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"indexBasedQueue", "playbackReport", "songLyrics", "transcoding",
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"indexBasedQueue", "playbackReport", "songLyrics", "transcoding", "sonicSimilarity",
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} {
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if !names[want] {
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t.Errorf("extension %q not advertised: %v", want, names)
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