fix(explore): diversify "more like this" so it stops getting stuck (#1188)
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Pure nearest-cosine piled near-identical images into the neighbour grid — a
reposted banner filled all 24 slots, and once you wandered into a B&W /
comic-panel cluster every neighbour was more of the same with no way back to
colour without the Random button (operator-reported, with screenshot).

similar() now over-fetches a wide candidate pool (5x the requested limit, cap
200), then diversifies down to `limit`:
- pHash near-duplicate collapse: drop candidates within 6 Hamming bits of the
  anchor or an already-kept candidate, so a repost (and the anchor's own clones)
  appears at most once.
- MMR re-rank: greedily pick for closeness-to-anchor minus similarity-to-already
  -picked (lambda 0.55), so the result SPANS clusters instead of returning 40
  variations of one image. Falls back to nearest-order on any failure / small
  pool, so existing nearest-first behaviour is unchanged when there's nothing to
  diversify.

Frontend forwardTarget drops the now-redundant skip-nearest-third hack (the list
is already diversified server-side) — plain random-over-unvisited gives the
variance now.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
This commit is contained in:
2026-06-30 09:01:01 -04:00
parent 715e276c03
commit 0f472b2f9e
3 changed files with 115 additions and 15 deletions
+23
View File
@@ -87,6 +87,29 @@ async def test_similar_composes_with_tag_filter(db):
assert [i.id for i in res] == [tagged.id] # scope AND-narrows the ranked set
@pytest.mark.asyncio
async def test_similar_collapses_near_duplicate_phashes(db):
# The reported failure: a reposted image fills the whole neighbour grid.
# A wall of same-pHash reposts must collapse to at most one, and the
# genuinely distinct images must still come through.
src = await _img(db, 1, _vec(1, 0))
dupes = []
for n in range(2, 7): # 5 near-identical reposts
r = await _img(db, n, _vec(1, 0.01 * n))
r.phash = "ffffffffffffffff" # identical perceptual hash
dupes.append(r)
distinct_a = await _img(db, 7, _vec(1, 1))
distinct_a.phash = "0000000000000000"
distinct_b = await _img(db, 8, _vec(0, 1))
distinct_b.phash = "0f0f0f0f0f0f0f0f"
await db.flush()
res = await GalleryService(db).similar(src.id, limit=10)
ids = [i.id for i in res]
assert sum(1 for d in dupes if d.id in ids) <= 1 # repost wall collapsed
assert distinct_a.id in ids and distinct_b.id in ids
@pytest.mark.asyncio
async def test_similar_respects_limit(db):
src = await _img(db, 1, _vec(1, 0))