Fix discovery to actually use negative affinity signals

Previously the engine was blind to dislikes/dismissals:
- _build_user_tag_profile only used liked/watched (positive only)
- dismiss_penalty was capped at 80% so hated content still surfaced
- _search_and_store had zero affinity filtering, any YouTube result entered the queue
- user_tag_affinity negative scores (written by dismiss/dislike) were never read

Now:
- _build_user_tag_profile reads directly from user_tag_affinity (positive + negative)
- _tag_relevance_score returns negative values, so disliked-tag channels score below zero and get dropped
- _search_and_store skips channels whose indexed videos match 3+ negatively-rated tags
- list_discovery post-filters channels already in the queue using the same neg-affinity check
- Removed the old _dismissed_channel_tags + dismiss_penalty (superseded)

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

backend/services/discovery.py

@@ -100,6 +100,7 @@ def _add_to_discovery(
 def _search_and_store(
     db: Session, user_id: int, queries: list[str],
     followed_yt_ids: set[str], score_multiplier: float, source: str,
+    neg_affinity_tags: frozenset[str] = frozenset(),
 ):
     """Run YouTube searches for the given queries and add results to discovery."""
     discovered: dict[str, dict] = {}
@@ -145,6 +146,24 @@ def _search_and_store(
         uc = db.query(UserChannel).filter_by(user_id=user_id, channel_id=channel.id).first()
         if uc and uc.status in ("followed", "dismissed"):
             continue
+
+        # Skip channels whose indexed videos heavily overlap with negatively-rated tags
+        if neg_affinity_tags and not is_new and channel.crawled_at:
+            neg_hit = 0
+            vtags = db.execute(
+                text("SELECT tags FROM videos WHERE channel_id = :cid AND tags IS NOT NULL LIMIT 20"),
+                {"cid": channel.id},
+            ).scalars().all()
+            for tags_json in vtags:
+                try:
+                    for tag in json.loads(tags_json or "[]"):
+                        if isinstance(tag, str) and tag.lower().strip() in neg_affinity_tags:
+                            neg_hit += 1
+                except (json.JSONDecodeError, TypeError):
+                    pass
+            if neg_hit >= 3:
+                continue
+
         preview_json = json.dumps(info["previews"]) if info["previews"] else None
         _add_to_discovery(
             db, user_id, channel.id,
@@ -245,7 +264,14 @@ def crawl_by_search(db: Session, user_id: int):
     if not queries:
         return
 
-    _search_and_store(db, user_id, queries, followed_yt_ids, score_multiplier=5.0, source="search")
+    neg_tags = frozenset(
+        r["tag"] for r in db.execute(
+            text("SELECT tag FROM user_tag_affinity WHERE user_id = :user_id AND score < -2"),
+            {"user_id": user_id},
+        ).mappings().all()
+    )
+    _search_and_store(db, user_id, queries, followed_yt_ids, score_multiplier=5.0, source="search",
+                      neg_affinity_tags=neg_tags)
 
 
 def update_community_signal(db: Session, user_id: int):
@@ -355,7 +381,14 @@ def update_liked_signal(db: Session, user_id: int):
     ).scalars().all())
 
     top_tags = [t for t, _ in sorted(tag_counts.items(), key=lambda x: -x[1])[:6]]
-    _search_and_store(db, user_id, top_tags, followed_yt_ids, score_multiplier=10.0, source="liked")
+    neg_tags = frozenset(
+        r["tag"] for r in db.execute(
+            text("SELECT tag FROM user_tag_affinity WHERE user_id = :user_id AND score < -2"),
+            {"user_id": user_id},
+        ).mappings().all()
+    )
+    _search_and_store(db, user_id, top_tags, followed_yt_ids, score_multiplier=10.0, source="liked",
+                      neg_affinity_tags=neg_tags)
 
 
 def update_watch_signal(db: Session, user_id: int):
@@ -408,40 +441,27 @@ def update_watch_signal(db: Session, user_id: int):
     ).scalars().all())
 
     top_tags = [t for t, _ in sorted(qualified.items(), key=lambda x: -x[1])[:6]]
-
-    _search_and_store(db, user_id, top_tags, followed_yt_ids, score_multiplier=3.0, source="watched")
+    neg_tags = frozenset(
+        r["tag"] for r in db.execute(
+            text("SELECT tag FROM user_tag_affinity WHERE user_id = :user_id AND score < -2"),
+            {"user_id": user_id},
+        ).mappings().all()
+    )
+    _search_and_store(db, user_id, top_tags, followed_yt_ids, score_multiplier=3.0, source="watched",
+                      neg_affinity_tags=neg_tags)
 
 
 def _build_user_tag_profile(db: Session, user_id: int) -> dict[str, float]:
-    """Return a weighted tag dict from liked (weight 3) + watched (weight 1) videos."""
+    """Return tag affinity dict (positive = liked, negative = disliked/dismissed)."""
     rows = db.execute(
-        text("""
-            SELECT v.tags, MAX(uv.liked) AS liked
-            FROM user_videos uv
-            JOIN videos v ON uv.video_id = v.id
-            WHERE uv.user_id = :user_id AND (uv.liked = 1 OR uv.watched = 1)
-              AND v.tags IS NOT NULL AND v.tags != '' AND v.tags != '[]'
-            GROUP BY v.id
-        """),
+        text("SELECT tag, score FROM user_tag_affinity WHERE user_id = :user_id"),
         {"user_id": user_id},
     ).mappings().all()
-
-    profile: dict[str, float] = {}
-    for row in rows:
-        weight = 3.0 if row["liked"] else 1.0
-        try:
-            for tag in json.loads(row["tags"]):
-                if isinstance(tag, str):
-                    t = tag.lower().strip()
-                    if 3 <= len(t) <= 40:
-                        profile[t] = profile.get(t, 0.0) + weight
-        except (json.JSONDecodeError, TypeError):
-            pass
-    return profile
+    return {row["tag"]: row["score"] for row in rows}
 
 
 def _tag_relevance_score(tag_profile: dict[str, float], tags_json: str | None) -> float:
-    """Score a candidate channel's tags against the user's interest profile."""
+    """Score a channel's tags against user affinity — positive means relevant, negative means disliked."""
     if not tag_profile or not tags_json:
         return 0.0
     try:
@@ -453,35 +473,7 @@ def _tag_relevance_score(tag_profile: dict[str, float], tags_json: str | None) -
         if isinstance(tag, str):
             t = tag.lower().strip()
             score += tag_profile.get(t, 0.0)
-    return min(score, 50.0)
-
-
-def _dismissed_channel_tags(db: Session, user_id: int) -> set[str]:
-    """Collect tags of channels this user explicitly dismissed — used to avoid similar content."""
-    rows = db.execute(
-        text("""
-            SELECT v.tags
-            FROM user_channels uc
-            JOIN videos v ON v.channel_id = uc.channel_id
-            WHERE uc.user_id = :user_id AND uc.status = 'dismissed'
-              AND v.tags IS NOT NULL AND v.tags != '' AND v.tags != '[]'
-            LIMIT 500
-        """),
-        {"user_id": user_id},
-    ).mappings().all()
-
-    bad_tags: dict[str, int] = {}
-    for row in rows:
-        try:
-            for tag in json.loads(row["tags"]):
-                if isinstance(tag, str):
-                    t = tag.lower().strip()
-                    if 3 <= len(t) <= 40:
-                        bad_tags[t] = bad_tags.get(t, 0) + 1
-        except (json.JSONDecodeError, TypeError):
-            pass
-    # Only include tags that appeared in 3+ dismissed-channel videos (strong signal)
-    return {t for t, c in bad_tags.items() if c >= 3}
+    return max(-100.0, min(score, 50.0))
 
 
 def update_trending_signal(db: Session, user_id: int, regions: list[str]):
@@ -490,7 +482,6 @@ def update_trending_signal(db: Session, user_id: int, regions: list[str]):
         return
 
     tag_profile = _build_user_tag_profile(db, user_id)
-    dismiss_tags = _dismissed_channel_tags(db, user_id)
 
     followed_yt_ids = set(db.execute(
         text("""
@@ -556,10 +547,10 @@ def update_trending_signal(db: Session, user_id: int, regions: list[str]):
         if uc and uc.status in ("followed", "dismissed"):
             continue
 
-        # Score: base ×4 per region × count, boosted by tag relevance, penalised by dismiss-tag overlap
         base_score = float(info["count"]) * 4.0 * len(info["regions"])
 
-        # Tag relevance boost (requires channel to have indexed videos)
+        # Tag relevance: positive for liked content, negative for dismissed/disliked.
+        # tag_profile comes from user_tag_affinity which tracks both signals.
         tag_boost = 0.0
         if not is_new and channel.crawled_at:
             tag_rows = db.execute(
@@ -568,25 +559,8 @@ def update_trending_signal(db: Session, user_id: int, regions: list[str]):
             ).scalars().all()
             for tags_json in tag_rows:
                 tag_boost += _tag_relevance_score(tag_profile, tags_json)
-            tag_boost = min(tag_boost, 30.0)
 
-        # Dismiss penalty: if channel's tags overlap heavily with dismissed content, reduce score
-        dismiss_penalty = 0.0
-        if dismiss_tags and not is_new:
-            tag_rows2 = db.execute(
-                text("SELECT tags FROM videos WHERE channel_id = :cid AND tags IS NOT NULL LIMIT 20"),
-                {"cid": channel.id},
-            ).scalars().all()
-            for tags_json in tag_rows2:
-                try:
-                    for tag in json.loads(tags_json or "[]"):
-                        if isinstance(tag, str) and tag.lower().strip() in dismiss_tags:
-                            dismiss_penalty += 5.0
-                except (json.JSONDecodeError, TypeError):
-                    pass
-            dismiss_penalty = min(dismiss_penalty, base_score * 0.8)
-
-        final_score = base_score + tag_boost - dismiss_penalty
+        final_score = base_score + tag_boost
         if final_score <= 0:
             continue