feat: AI 업셀링 CRM - Clawdbot Gateway 기반 맞춤 추천 시스템

키오스크 적립 시 Clawdbot Gateway(Claude Max)를 통해 구매 이력 기반 맞춤 제품 추천을 생성하고, 마이페이지 방문 시 바텀시트 팝업으로 표시. - ai_recommendations SQLite 테이블 추가 (스키마 + 마이그레이션) - clawdbot_client.py: Gateway WebSocket 프로토콜 v3 Python 클라이언트 - app.py: 추천 생성 + GET/POST API 엔드포인트 - my_page.html: 바텀시트 UI (슬라이드업 애니메이션, 1.5초 후 자동 표시) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 19:57:03 +09:00
parent a3ff69b67f
commit b5a99f7b3b
5 changed files with 506 additions and 1 deletions
--- a/backend/app.py
+++ b/backend/app.py
@@ -1109,7 +1109,7 @@ def my_page():
        tx_dict['created_at'] = utc_to_kst_str(tx['created_at'])
        transactions.append(tx_dict)

-    return render_template('my_page.html', user=user, transactions=transactions)
+    return render_template('my_page.html', user=user, transactions=transactions, user_id=user['id'])


 # ============================================================================
@@ -1885,6 +1885,137 @@ def admin():
                           recent_tokens=recent_tokens)


+# ============================================================================
+# AI 업셀링 추천
+# ============================================================================
+
+def _generate_upsell_recommendation(user_id, transaction_id, sale_items, user_name):
+    """키오스크 적립 후 AI 업셀링 추천 생성 (fire-and-forget)"""
+    from services.clawdbot_client import generate_upsell
+
+    if not sale_items:
+        return
+
+    # 현재 구매 품목
+    current_items = ', '.join(item['name'] for item in sale_items if item.get('name'))
+    if not current_items:
+        return
+
+    # 최근 구매 이력 수집
+    recent_products = current_items  # 기본값
+    try:
+        conn = db_manager.get_sqlite_connection()
+        cursor = conn.cursor()
+        cursor.execute("""
+            SELECT ct.transaction_id
+            FROM claim_tokens ct
+            WHERE ct.claimed_by_user_id = ? AND ct.transaction_id != ?
+            ORDER BY ct.claimed_at DESC LIMIT 5
+        """, (user_id, transaction_id))
+        recent_tokens = cursor.fetchall()
+
+        if recent_tokens:
+            all_products = []
+            mssql_session = db_manager.get_session('PM_PRES')
+            for token in recent_tokens:
+                rows = mssql_session.execute(text("""
+                    SELECT ISNULL(G.GoodsName, '') AS goods_name
+                    FROM SALE_SUB S
+                    LEFT JOIN PM_DRUG.dbo.CD_GOODS G ON S.DrugCode = G.DrugCode
+                    WHERE S.SL_NO_order = :tid
+                """), {'tid': token['transaction_id']}).fetchall()
+                for r in rows:
+                    if r.goods_name:
+                        all_products.append(r.goods_name)
+            if all_products:
+                recent_products = ', '.join(set(all_products))
+    except Exception as e:
+        logging.warning(f"[AI추천] 구매 이력 수집 실패 (현재 품목만 사용): {e}")
+
+    # Claude로 추천 생성
+    logging.info(f"[AI추천] 생성 시작: user={user_name}, items={current_items}")
+    rec = generate_upsell(user_name, current_items, recent_products)
+
+    if not rec:
+        logging.warning("[AI추천] 생성 실패 (AI 응답 없음)")
+        return
+
+    # SQLite에 저장
+    try:
+        conn = db_manager.get_sqlite_connection()
+        cursor = conn.cursor()
+        expires_at = (datetime.now() + timedelta(days=7)).strftime('%Y-%m-%d %H:%M:%S')
+        cursor.execute("""
+            INSERT INTO ai_recommendations
+            (user_id, transaction_id, recommended_product, recommendation_message,
+             recommendation_reason, trigger_products, ai_raw_response, expires_at)
+            VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+        """, (
+            user_id, transaction_id,
+            rec['product'], rec['message'], rec['reason'],
+            json.dumps([item['name'] for item in sale_items], ensure_ascii=False),
+            json.dumps(rec, ensure_ascii=False),
+            expires_at
+        ))
+        conn.commit()
+        logging.info(f"[AI추천] 저장 완료: user_id={user_id}, product={rec['product']}")
+    except Exception as e:
+        logging.warning(f"[AI추천] DB 저장 실패: {e}")
+
+
+@app.route('/api/recommendation/<int:user_id>')
+def api_get_recommendation(user_id):
+    """마이페이지용 AI 추천 조회"""
+    conn = db_manager.get_sqlite_connection()
+    cursor = conn.cursor()
+
+    now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    cursor.execute("""
+        SELECT id, recommended_product, recommendation_message, created_at
+        FROM ai_recommendations
+        WHERE user_id = ? AND status = 'active'
+          AND (expires_at IS NULL OR expires_at > ?)
+        ORDER BY created_at DESC LIMIT 1
+    """, (user_id, now))
+
+    rec = cursor.fetchone()
+    if not rec:
+        return jsonify({'success': True, 'has_recommendation': False})
+
+    # 표시 횟수 업데이트
+    cursor.execute("""
+        UPDATE ai_recommendations
+        SET displayed_count = displayed_count + 1,
+            displayed_at = COALESCE(displayed_at, ?)
+        WHERE id = ?
+    """, (now, rec['id']))
+    conn.commit()
+
+    return jsonify({
+        'success': True,
+        'has_recommendation': True,
+        'recommendation': {
+            'id': rec['id'],
+            'product': rec['recommended_product'],
+            'message': rec['recommendation_message']
+        }
+    })
+
+
+@app.route('/api/recommendation/<int:rec_id>/dismiss', methods=['POST'])
+def api_dismiss_recommendation(rec_id):
+    """추천 닫기"""
+    conn = db_manager.get_sqlite_connection()
+    cursor = conn.cursor()
+    now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    cursor.execute("""
+        UPDATE ai_recommendations SET status = 'dismissed', dismissed_at = ?
+        WHERE id = ?
+    """, (now, rec_id))
+    conn.commit()
+    return jsonify({'success': True})
+
+
 # ============================================================================
 # 알림톡 로그
 # ============================================================================
@@ -2195,6 +2326,12 @@ def api_kiosk_claim():
        except Exception as alimtalk_err:
            logging.warning(f"[알림톡] 발송 예외 (적립은 완료): {alimtalk_err}")

+        # AI 업셀링 추천 생성 (fire-and-forget)
+        try:
+            _generate_upsell_recommendation(user_id, transaction_id, sale_items, user_name)
+        except Exception as rec_err:
+            logging.warning(f"[AI추천] 생성 예외 (적립은 완료): {rec_err}")
+
        return jsonify({
            'success': True,
            'message': f'{claimed_points}P 적립 완료!',