feat: move analysis cache to recordings/analyses/, prune orphans on startup

- Cache files now live in recordings/analyses/<filename>.analysis.json
  (mirroring the relative path for files in subdirectories) rather than
  alongside each audio file.
- _api_delete now removes the corresponding cache file after deleting audio.
- prune_orphan_analyses() runs at startup and removes any .analysis.json
  whose audio file no longer exists (handles files deleted outside the UI).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

README.md

@@ -159,7 +159,7 @@ Shows recordings grouped by day with collapsible sections. Features:
 - **Day groups** — recordings are grouped under a collapsible day heading showing date, file count, total duration, and total size. The most recent day is expanded by default; older days start collapsed. Expanded state is preserved across filter changes.
 - **Day highlights** — click **★ Highlights** on any day heading to run loudness analysis across all WAV/FLAC files in that day and display a combined activity timeline SVG. Orange segments show when loud sections occurred relative to the day's time span; blue shows the file extents. Labels show the start, midpoint, and end times.
 - **Inline playback** — collapsible `▶ Play` button per row; audio loads lazily via a seekable `/stream/` endpoint with HTTP Range support. Metadata is fetched immediately so the duration is visible without pressing play.
-- **Waveform analysis** — on demand per file; computes RMS per 100 ms window and highlights loud sections. Supported for WAV and FLAC (FLAC requires `numpy` + `soundfile`). Pure-Python fallback for WAV when numpy is absent. Results are cached alongside the audio file as `<filename>.analysis.json`; subsequent requests at the same threshold and min-gap settings return instantly without re-reading the audio.
+- **Waveform analysis** — on demand per file; computes RMS per 100 ms window and highlights loud sections. Supported for WAV and FLAC (FLAC requires `numpy` + `soundfile`). Pure-Python fallback for WAV when numpy is absent. Results are cached in `recordings/analyses/<filename>.analysis.json`; subsequent requests at the same threshold and min-gap settings return instantly without re-reading the audio. The cache file is deleted automatically when the audio file is deleted. Orphaned cache files (audio deleted outside the UI) are pruned on startup.
 - **Grace period** — configurable in the controls bar (default 2 s). Loud sections separated by less than this gap are merged into one. Raise this (e.g. to 15–30 s) when a single event generates many timestamps due to brief quiet gaps within it.
 - **Timestamp jump** — after analysis, click any loud-section chip to seek the player to that position and pre-fill the cut panel. Use **J** / **K** keyboard shortcuts to jump to the previous / next section while audio is playing.
 - **Cut & download** — `✂ Cut` button opens the player row and reveals a cut panel. Enter start and end times in `m:ss` or `h:mm:ss` format and click **↓ Download cut** to receive an ffmpeg-trimmed copy without re-encoding. Requires ffmpeg (included in the Docker image).

web.py

@@ -203,6 +203,33 @@ def analyze_flac(path: Path, window_samples: int = WINDOW_SAMPLES,
     return _package_result(rms_values, framerate, n_frames, window_samples, threshold, min_gap)
 
 
+# ---------------------------------------------------------------------------
+# Analysis cache helpers
+# ---------------------------------------------------------------------------
+
+def _analysis_cache_path(base: Path, audio_path: Path) -> Path:
+    rel = audio_path.relative_to(base)
+    return base / 'analyses' / rel.parent / (rel.name + '.analysis.json')
+
+
+def prune_orphan_analyses(base: Path):
+    analyses_dir = base / 'analyses'
+    if not analyses_dir.exists():
+        return
+    removed = 0
+    for cache in analyses_dir.rglob('*.analysis.json'):
+        rel = cache.relative_to(analyses_dir)
+        audio_path = base / rel.parent / rel.name[:-len('.analysis.json')]
+        if not audio_path.exists():
+            try:
+                cache.unlink()
+                removed += 1
+            except Exception:
+                pass
+    if removed:
+        print(f'Pruned {removed} orphaned analysis cache file(s)')
+
+
 # ---------------------------------------------------------------------------
 # File listing
 # ---------------------------------------------------------------------------
@@ -331,7 +358,8 @@ class _Handler(BaseHTTPRequestHandler):
         except Exception:
             pass
 
-        cache_path = path.parent / (path.name + '.analysis.json')
+        base = Path(self.recordings_dir).resolve()
+        cache_path = _analysis_cache_path(base, path)
         try:
             cached = json.loads(cache_path.read_text('utf-8'))
             if cached.get('threshold') == threshold and cached.get('min_gap') == min_gap:
@@ -353,6 +381,7 @@ class _Handler(BaseHTTPRequestHandler):
             return
 
         try:
+            cache_path.parent.mkdir(parents=True, exist_ok=True)
             tmp = cache_path.with_suffix('.tmp')
             tmp.write_text(json.dumps({'threshold': threshold, 'min_gap': min_gap, 'result': result}), 'utf-8')
             os.replace(tmp, cache_path)
@@ -481,6 +510,11 @@ class _Handler(BaseHTTPRequestHandler):
             self._json_err(500, f'Failed to delete: {e}')
             return
 
+        try:
+            _analysis_cache_path(Path(self.recordings_dir).resolve(), path).unlink()
+        except Exception:
+            pass
+
         self._send(200, json.dumps({'deleted': filename}).encode(), 'application/json')
 
     def _api_cut(self, qs):
@@ -1567,6 +1601,8 @@ def main():
     if not rec_dir.exists():
         print(f"Warning: recordings directory '{args.dir}' does not exist yet.")
 
+    prune_orphan_analyses(rec_dir.resolve())
+
     class Handler(_Handler):
         recordings_dir = str(rec_dir.resolve())
         threshold      = args.threshold