feat(social): add listening activity, shared rooms and modern chat

services/recommender/pipu_rec/wave/engine.py

@@ -313,6 +313,7 @@ def build_batch(
     rng: np.random.Generator | None = None,
     ranker: Ranker | None = None,
     ctx: Context | None = None,
+    friend_ids: list[str] | None = None,
 ) -> list[Pick]:
     """Кандидаты → фильтры → оценка → соответствие контексту → MMR с правилами разнообразия."""
     rng = rng or np.random.default_rng()
@@ -363,6 +364,8 @@ def build_batch(
         if seeds:
             q = index.emb[seeds].mean(axis=0)
             add(_top((index.emb @ q).astype(np.float64), allowed & index.has_emb, 100), "seed")
+    friends = [index.pos[t] for t in (friend_ids or []) if t in index.pos and allowed[index.pos[t]]][:10]
+    add(friends, "friends")
     query = np.maximum(sim_session, sim_taste) if svec is not None or len(centroids) else None
     if query is not None:
         # «Новое» помечаем раньше audio_sim: неслышанный трек рядом со вкусом считается исследованием.
@@ -446,6 +449,8 @@ def build_batch(
         pred = ranker.predict(x)
         score = np.argsort(np.argsort(pred)) / max(len(pred) - 1, 1)
 
+    # Social influence is small, context-sensitive, and survives the learned ranker.
+    score = score + 0.06 * np.isin(cand, friends) * f
     # 5. MMR + правила: 1 трек исполнителя на пачку, не больше 2 на последние 10; доля «нового».
     picks: list[Pick] = []
     chosen: list[int] = []
@@ -457,6 +462,8 @@ def build_batch(
         best_j, best_v = -1, -np.inf
         for j in order:
             i = int(cand[j])
+            if sources[i] == "friends" and any(p.source == "friends" for p in picks):
+                continue
             a = index.artist[i]
             if any(index.artist[c] == a for c in chosen) or recent_artists.count(a) >= 2:
                 continue
@@ -471,7 +478,9 @@ def build_batch(
                 continue
             if chosen:
                 chosen_artists = {index.artist[c] for c in chosen}
-                rest = [j for j in order if index.artist[int(cand[j])] in chosen_artists]
+                social_chosen = any(p.source == "friends" for p in picks)
+                rest = [j for j in order if index.artist[int(cand[j])] in chosen_artists
+                        and not (sources[int(cand[j])] == "friends" and social_chosen)]
                 if not rest:
                     break
                 best_j = max(rest, key=lambda j: score[j])