feat(lotto): lotto_briefings 테이블 + CRUD 함수

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

backend/app/db.py

@@ -277,6 +277,26 @@ def init_db() -> None:
         conn.execute("CREATE INDEX IF NOT EXISTS idx_purchase_strategy ON purchase_history(source_strategy)")
         conn.execute("CREATE INDEX IF NOT EXISTS idx_purchase_checked ON purchase_history(draw_no, checked)")
 
+        # ── lotto_briefings 테이블 ─────────────────────────────────────────────
+        conn.execute("""
+            CREATE TABLE IF NOT EXISTS lotto_briefings (
+                id              INTEGER PRIMARY KEY AUTOINCREMENT,
+                draw_no         INTEGER UNIQUE NOT NULL,
+                picks           TEXT NOT NULL,
+                narrative       TEXT NOT NULL,
+                confidence      INTEGER NOT NULL,
+                model           TEXT NOT NULL,
+                tokens_input    INTEGER NOT NULL DEFAULT 0,
+                tokens_output   INTEGER NOT NULL DEFAULT 0,
+                cache_read      INTEGER NOT NULL DEFAULT 0,
+                cache_write     INTEGER NOT NULL DEFAULT 0,
+                latency_ms      INTEGER NOT NULL DEFAULT 0,
+                source          TEXT NOT NULL DEFAULT 'auto',
+                generated_at    TEXT NOT NULL DEFAULT (datetime('now','localtime'))
+            )
+        """)
+        conn.execute("CREATE INDEX IF NOT EXISTS idx_briefings_draw ON lotto_briefings(draw_no DESC)")
+
 
 # ── todos CRUD ───────────────────────────────────────────────────────────────
 
@@ -1096,3 +1116,104 @@ def update_purchase_results(purchase_id: int, results: list, total_prize: int) -
             (json.dumps(results, ensure_ascii=False), total_prize, purchase_id),
         )
 
+
+# --- Lotto Briefings ---
+
+def save_briefing(data: Dict[str, Any]) -> int:
+    with _conn() as conn:
+        cur = conn.execute("""
+            INSERT INTO lotto_briefings
+                (draw_no, picks, narrative, confidence, model,
+                 tokens_input, tokens_output, cache_read, cache_write,
+                 latency_ms, source)
+            VALUES (?,?,?,?,?,?,?,?,?,?,?)
+            ON CONFLICT(draw_no) DO UPDATE SET
+                picks=excluded.picks, narrative=excluded.narrative,
+                confidence=excluded.confidence, model=excluded.model,
+                tokens_input=excluded.tokens_input,
+                tokens_output=excluded.tokens_output,
+                cache_read=excluded.cache_read,
+                cache_write=excluded.cache_write,
+                latency_ms=excluded.latency_ms,
+                source=excluded.source,
+                generated_at=datetime('now','localtime')
+        """, (
+            data["draw_no"],
+            json.dumps(data["picks"], ensure_ascii=False),
+            json.dumps(data["narrative"], ensure_ascii=False),
+            int(data["confidence"]),
+            data["model"],
+            int(data.get("tokens_input", 0)),
+            int(data.get("tokens_output", 0)),
+            int(data.get("cache_read", 0)),
+            int(data.get("cache_write", 0)),
+            int(data.get("latency_ms", 0)),
+            data.get("source", "auto"),
+        ))
+        return cur.lastrowid
+
+
+def _briefing_row(r) -> Dict[str, Any]:
+    return {
+        "id": r["id"],
+        "draw_no": r["draw_no"],
+        "picks": json.loads(r["picks"]),
+        "narrative": json.loads(r["narrative"]),
+        "confidence": r["confidence"],
+        "model": r["model"],
+        "tokens_input": r["tokens_input"],
+        "tokens_output": r["tokens_output"],
+        "cache_read": r["cache_read"],
+        "cache_write": r["cache_write"],
+        "latency_ms": r["latency_ms"],
+        "source": r["source"],
+        "generated_at": r["generated_at"],
+    }
+
+
+def get_latest_briefing() -> Optional[Dict[str, Any]]:
+    with _conn() as conn:
+        r = conn.execute("SELECT * FROM lotto_briefings ORDER BY draw_no DESC LIMIT 1").fetchone()
+    return _briefing_row(r) if r else None
+
+
+def get_briefing(draw_no: int) -> Optional[Dict[str, Any]]:
+    with _conn() as conn:
+        r = conn.execute("SELECT * FROM lotto_briefings WHERE draw_no=?", (draw_no,)).fetchone()
+    return _briefing_row(r) if r else None
+
+
+def list_briefings(limit: int = 10) -> List[Dict[str, Any]]:
+    with _conn() as conn:
+        rows = conn.execute(
+            "SELECT * FROM lotto_briefings ORDER BY draw_no DESC LIMIT ?",
+            (limit,),
+        ).fetchall()
+    return [_briefing_row(r) for r in rows]
+
+
+def get_curator_usage(days: int = 30) -> Dict[str, Any]:
+    with _conn() as conn:
+        r = conn.execute("""
+            SELECT COUNT(*) AS calls,
+                   SUM(tokens_input) AS in_tokens,
+                   SUM(tokens_output) AS out_tokens,
+                   SUM(cache_read) AS cache_read,
+                   SUM(cache_write) AS cache_write,
+                   AVG(latency_ms) AS avg_latency
+            FROM lotto_briefings
+            WHERE generated_at >= datetime('now', ?, 'localtime')
+        """, (f"-{int(days)} days",)).fetchone()
+    cr = int(r["cache_read"] or 0)
+    cw = int(r["cache_write"] or 0)
+    return {
+        "days": days,
+        "calls": int(r["calls"] or 0),
+        "tokens_input": int(r["in_tokens"] or 0),
+        "tokens_output": int(r["out_tokens"] or 0),
+        "cache_read": cr,
+        "cache_write": cw,
+        "cache_hit_rate": round(cr / (cr + cw), 3) if (cr + cw) > 0 else 0.0,
+        "avg_latency_ms": round(float(r["avg_latency"] or 0), 1),
+    }
+