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fix(trust): suppress duplicate_photo for established retailers (1000+ feedback)

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Large retailers like Newegg legitimately reuse manufacturer stock photos
across listings. Duplicate photo hash is not a scam signal for sellers
with 1000+ feedback — suppress the red flag for them.
This commit is contained in:
pyr0ball 2026-03-27 01:07:42 -07:00
parent 98695b00f0
commit a61166f48a
1 changed files with 10 additions and 1 deletions
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11
app/trust/aggregator.py
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@ -9,6 +9,11 @@ HARD_FILTER_AGE_DAYS = 7
HARD_FILTER_BAD_RATIO_MIN_COUNT = 20 HARD_FILTER_BAD_RATIO_MIN_COUNT = 20
HARD_FILTER_BAD_RATIO_THRESHOLD = 0.80 HARD_FILTER_BAD_RATIO_THRESHOLD = 0.80
# Sellers above this feedback count are treated as established retailers.
# Stock photo reuse (duplicate_photo) is suppressed for them — large retailers
# legitimately share manufacturer images across many listings.
_ESTABLISHED_RETAILER_FEEDBACK_THRESHOLD = 1000
# Title keywords that suggest cosmetic damage or wear (free-tier title scan). # Title keywords that suggest cosmetic damage or wear (free-tier title scan).
# Description-body scan (paid BSL feature) runs via BTF enrichment — not implemented yet. # Description-body scan (paid BSL feature) runs via BTF enrichment — not implemented yet.
_SCRATCH_DENT_KEYWORDS = frozenset([ _SCRATCH_DENT_KEYWORDS = frozenset([
@ -103,7 +108,11 @@ class Aggregator:
red_flags.append("low_feedback_count") red_flags.append("low_feedback_count")
if signal_scores.get("price_vs_market") == 0: # only flag when data exists and price is genuinely <50% of market if signal_scores.get("price_vs_market") == 0: # only flag when data exists and price is genuinely <50% of market
red_flags.append("suspicious_price") red_flags.append("suspicious_price")
if photo_hash_duplicate: is_established_retailer = (
seller is not None
and seller.feedback_count >= _ESTABLISHED_RETAILER_FEEDBACK_THRESHOLD
)
if photo_hash_duplicate and not is_established_retailer:
red_flags.append("duplicate_photo") red_flags.append("duplicate_photo")
if listing_title and _has_damage_keywords(listing_title): if listing_title and _has_damage_keywords(listing_title):
red_flags.append("scratch_dent_mentioned") red_flags.append("scratch_dent_mentioned")