Files
yellowjacket/backend/autotag/recommend.go
T
yonluandClaude Opus 4.8 65048401e8 feat: autotag scoring overhaul, dump-based explore index, and lyrics search
Consolidates in-progress work across autotag, explore, and library:

- autotag: beets/Picard-informed scoring engine — ID-first matching, VA
  handling, recommendation tiers, and a merged distance/rank cascade, with
  an eval harness for regression tracking.
- explore: offline MusicBrainz dump import/incremental refresh replaces the
  legacy tier crawl; index-first local search with fuzzy matching and a
  dedicated ranker; disk-free guards for dump downloads.
- library: artist-credit extraction and matching.
- lyrics: owned-library lyric search (FTS) with LRCLIB backfill.

Also: rewrite README to be user-focused, and migrate upstream to
git.ljones.me/yonlu/yellowjacket.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-24 12:14:20 -04:00

134 lines
3.8 KiB
Go

package autotag
// Recommendation is a qualitative confidence tier for a group's
// ranked candidates — the piece a raw score can't express on its
// own. Modeled on beets' Recommendation enum: the tier starts from
// the top candidate's absolute score and is then CAPPED by defects
// (ambiguity with a different release group, missing/unmatched
// tracks, thin evidence). Auto-accept (plan 011) should require
// RecommendationStrong; the review UI can badge the rest.
type Recommendation string
// Recommendation tiers, weakest to strongest.
const (
RecommendationNone Recommendation = "none"
RecommendationLow Recommendation = "low"
RecommendationMedium Recommendation = "medium"
RecommendationStrong Recommendation = "strong"
)
const (
// Absolute score tiers.
strongScoreThresh = 0.90
mediumScoreThresh = 0.75
// A runner-up from a DIFFERENT release group within this margin
// of the top score makes the match ambiguous — two genuinely
// different albums both fit, so a human should look. Editions
// of the same release group are expected to score nearly
// identically and never count as ambiguity.
ambiguityMargin = 0.05
)
// Recommend derives the confidence tier for a ranked candidate
// list. candidates must already be sorted best-first (the shape
// RankCandidates returns).
func Recommend(g Group, candidates []Candidate) Recommendation {
if len(candidates) == 0 {
return RecommendationNone
}
top := candidates[0]
var rec Recommendation
switch {
case top.Score >= strongScoreThresh:
rec = RecommendationStrong
case top.Score >= mediumScoreThresh:
rec = RecommendationMedium
default:
return RecommendationLow
}
// Cap: a different release group scoring within the ambiguity
// margin means the score alone can't pick between two albums.
if rivalWithinMargin(top, candidates[1:]) {
rec = minRecommendation(rec, RecommendationMedium)
}
// Cap: missing or unmatched tracks mean the alignment itself is
// incomplete, however good the matched tracks look (beets caps
// these penalties at "medium" the same way).
for _, a := range top.Alignments {
if a.Status == AlignmentMissing || a.Status == AlignmentUnmatched {
rec = minRecommendation(rec, RecommendationMedium)
break
}
}
// Cap: tiny folders can't corroborate a match strongly enough
// to act on without review, whatever the arithmetic says.
if len(g.Tracks) < evidenceFullTracks {
rec = minRecommendation(rec, RecommendationMedium)
}
return rec
}
// rivalWithinMargin reports whether any candidate from a different
// release group scores within ambiguityMargin of the top candidate.
func rivalWithinMargin(top Candidate, rest []Candidate) bool {
for _, c := range rest {
if top.Score-c.Score > ambiguityMargin {
// Sorted descending: everything further is farther away.
return false
}
if !sameReleaseGroup(top, c) {
return true
}
}
return false
}
// sameReleaseGroup reports whether two candidates belong to the
// same release group — by MBID when both carry one, by normalized
// title + artist-credit otherwise (local candidates may lack RG
// MBIDs).
func sameReleaseGroup(a, b Candidate) bool {
if a.ReleaseGroupMBID != "" && b.ReleaseGroupMBID != "" {
return a.ReleaseGroupMBID == b.ReleaseGroupMBID
}
return Normalize(a.Title) == Normalize(b.Title) &&
Normalize(a.ArtistCredit) == Normalize(b.ArtistCredit)
}
// recommendationRank orders tiers for min-comparison.
func recommendationRank(r Recommendation) int {
switch r {
case RecommendationNone:
return 0
case RecommendationLow:
return 1
case RecommendationMedium:
return 2
case RecommendationStrong:
return 3
default:
return 0
}
}
// minRecommendation returns the weaker of two tiers.
func minRecommendation(a, b Recommendation) Recommendation {
if recommendationRank(a) <= recommendationRank(b) {
return a
}
return b
}