merge: T57 significance-aware retrieval ranking

chat/state/memory.py

@@ -94,6 +94,14 @@ def get_pinned(conn: Connection, owner_id: str) -> list[dict]:
 _SIGNIFICANCE_WEIGHT = 0.3
 _RECENCY_WEIGHT = 0.5
 
+# T57 (Phase 3, §11.1): significance multiplier applied to the SQL ORDER BY in
+# ``search_memories`` so that the FTS over-fetch already prefers
+# higher-significance rows for tied / near-tied BM25 ranks. Module-level so it
+# can be tuned without a code change. BM25 ``rank`` is lower-is-better, so the
+# bias is *subtracted* from rank in the ASC ordering — equivalent to multiplying
+# a higher-is-better score by a positive constant per the spec wording.
+SIGNIFICANCE_RANK_BIAS = 0.5
+
 
 def search_memories(
     conn: Connection,
@@ -137,10 +145,15 @@ def search_memories(
         "JOIN memories m ON m.id = memories_fts.rowid "
         f"WHERE m.owner_id = ? AND m.{witness_col} = 1 "
         "AND memories_fts MATCH ? "
-        "ORDER BY memories_fts.rank "
+        # T57: significance multiplier biases the FTS over-fetch order. BM25
+        # ``rank`` is lower-is-better, so subtracting ``significance * BIAS``
+        # surfaces higher-significance rows above lower-significance rows with
+        # equal/near-equal match strength. Equivalent to ``score × constant``
+        # per §11.1 once the rank is inverted to a higher-is-better score.
+        "ORDER BY (memories_fts.rank - m.significance * ?) ASC "
         "LIMIT ?"
     )
-    cur = conn.execute(sql, (owner_id, query, over_fetch))
+    cur = conn.execute(sql, (owner_id, query, SIGNIFICANCE_RANK_BIAS, over_fetch))
     rows = cur.fetchall()
     if not rows:
         return []