feat(api): My Wave sessions with a Go fallback and wave metrics (M4)

- /wave/options, POST /wave/sessions (activity, mood, seed),
  /next with reactions, PATCH to switch the context on the fly, DELETE
- the recommender is called with an 800 ms budget; on failure the api
  serves a fallback wave of likes, favourite artists and random
  available tracks with the same dislike / recent / served filters
- every served track is an impression with its source and model; wave
  events (context_type wave) set its outcome, reactions win
- library status shows the analysis queue and 7-day wave metrics:
  listen-through, early skip and like rate

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

services/api/internal/library/handler.go

@@ -261,6 +261,14 @@ func (h *Handler) GetLibraryStatus(ctx context.Context, _ gen.GetLibraryStatusRe
 	out := gen.GetLibraryStatus200JSONResponse{
 		Artists: int(c.Artists), Albums: int(c.Albums), Tracks: int(c.Tracks), Files: int(c.Files),
 		MissingFiles: int(c.Missing), FileErrors: int(c.Errors), Sources: []gen.SourceStatusItem{},
+		Analysis: gen.AnalysisStatus{
+			Queued: st.Analysis.Queued, Running: st.Analysis.Running, Done: st.Analysis.Done,
+			Failed: st.Analysis.Failed, AnalyzerVer: st.Analysis.AnalyzerVer,
+		},
+		Wave: gen.WaveMetrics{
+			Served: st.Wave.Served, Sessions: st.Wave.Sessions, ListenThroughRate: st.Wave.ListenThrough,
+			EarlySkipRate: st.Wave.EarlySkip, LikeRate: st.Wave.LikeRate,
+		},
 	}
 	for _, s := range st.Sources {
 		dto := h.sourceDTO(s)