v2.2.1: frontend closed-source + Docker one-click deploy
- Remove frontend source code (now in private repo) - Add pre-built frontend/dist/ with Nginx serving - Simplify docker-compose.yml (no Node.js build needed) - Update README with docs index and Docker deploy guide - Add admin order list and AI analysis stats tabs - Add quick trade API routes - Clean up redundant files (package-lock.json, yarn.lock, .iml) - Add GitHub Actions workflow for frontend update automation
This commit is contained in:
TIANHE
@@ -1071,3 +1071,450 @@ def get_system_strategies():
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import traceback
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logger.error(traceback.format_exc())
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return jsonify({'code': 0, 'msg': str(e), 'data': None}), 500
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# ==================== Admin Orders ====================
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@user_bp.route('/admin-orders', methods=['GET'])
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@login_required
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@admin_required
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def get_admin_orders():
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"""
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Get all orders across the system (admin only).
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Merges qd_membership_orders and qd_usdt_orders into a unified list.
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Query params:
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page: int (default 1)
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page_size: int (default 20, max 100)
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status: str (optional, filter by status: paid/pending/confirmed/expired/all)
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search: str (optional, search by username/email)
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"""
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try:
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page = request.args.get('page', 1, type=int)
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page_size = request.args.get('page_size', 20, type=int)
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status_filter = request.args.get('status', '', type=str).strip().lower()
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search = request.args.get('search', '', type=str).strip()
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page_size = min(100, max(1, page_size))
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offset = (page - 1) * page_size
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with get_db_connection() as db:
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cur = db.cursor()
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# --- USDT Orders (primary) ---
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usdt_conditions = []
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usdt_params = []
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if status_filter and status_filter != 'all':
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usdt_conditions.append("o.status = ?")
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usdt_params.append(status_filter)
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if search:
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usdt_conditions.append("(u.username ILIKE ? OR u.email ILIKE ? OR u.nickname ILIKE ?)")
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like_val = f"%{search}%"
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usdt_params.extend([like_val, like_val, like_val])
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usdt_where = ""
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if usdt_conditions:
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usdt_where = "WHERE " + " AND ".join(usdt_conditions)
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# Count
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cur.execute(
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f"SELECT COUNT(*) as cnt FROM qd_usdt_orders o LEFT JOIN qd_users u ON u.id = o.user_id {usdt_where}",
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tuple(usdt_params)
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)
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usdt_total = cur.fetchone()['cnt']
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# --- Membership Orders (mock) ---
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mock_conditions = []
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mock_params = []
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if status_filter and status_filter != 'all':
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mock_conditions.append("m.status = ?")
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mock_params.append(status_filter)
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if search:
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mock_conditions.append("(u.username ILIKE ? OR u.email ILIKE ? OR u.nickname ILIKE ?)")
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like_val = f"%{search}%"
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mock_params.extend([like_val, like_val, like_val])
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mock_where = ""
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if mock_conditions:
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mock_where = "WHERE " + " AND ".join(mock_conditions)
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cur.execute(
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f"SELECT COUNT(*) as cnt FROM qd_membership_orders m LEFT JOIN qd_users u ON u.id = m.user_id {mock_where}",
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tuple(mock_params)
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)
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mock_total = cur.fetchone()['cnt']
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total = usdt_total + mock_total
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# Use UNION ALL to merge both tables into one sorted list
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# We select a unified schema
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union_sql = f"""
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SELECT * FROM (
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SELECT
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o.id,
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'usdt' AS order_type,
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o.user_id,
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u.username,
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u.nickname,
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u.email AS user_email,
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o.plan,
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o.amount_usdt AS amount,
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'USDT' AS currency,
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o.chain,
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o.address,
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o.tx_hash,
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o.status,
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o.created_at,
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o.paid_at,
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o.confirmed_at,
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o.expires_at
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FROM qd_usdt_orders o
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LEFT JOIN qd_users u ON u.id = o.user_id
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{usdt_where}
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UNION ALL
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SELECT
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m.id,
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'mock' AS order_type,
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m.user_id,
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u.username,
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u.nickname,
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u.email AS user_email,
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m.plan,
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m.price_usd AS amount,
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'USD' AS currency,
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'' AS chain,
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'' AS address,
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'' AS tx_hash,
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m.status,
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m.created_at,
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m.paid_at,
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NULL AS confirmed_at,
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NULL AS expires_at
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FROM qd_membership_orders m
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LEFT JOIN qd_users u ON u.id = m.user_id
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{mock_where}
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) AS combined
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ORDER BY combined.created_at DESC
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LIMIT ? OFFSET ?
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"""
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all_params = list(usdt_params) + list(mock_params) + [page_size, offset]
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cur.execute(union_sql, tuple(all_params))
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rows = cur.fetchall() or []
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# Summary stats
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cur.execute(
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f"""SELECT
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COUNT(*) AS total_orders,
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COALESCE(SUM(CASE WHEN status IN ('paid','confirmed') THEN 1 ELSE 0 END), 0) AS paid_orders,
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COALESCE(SUM(CASE WHEN status = 'pending' THEN 1 ELSE 0 END), 0) AS pending_orders,
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COALESCE(SUM(CASE WHEN status IN ('expired','cancelled','failed') THEN 1 ELSE 0 END), 0) AS failed_orders,
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COALESCE(SUM(CASE WHEN status IN ('paid','confirmed') THEN amount_usdt ELSE 0 END), 0) AS total_revenue
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FROM qd_usdt_orders"""
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)
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summary_row = cur.fetchone() or {}
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cur.close()
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items = []
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for row in rows:
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created_at = row.get('created_at')
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paid_at = row.get('paid_at')
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confirmed_at = row.get('confirmed_at')
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expires_at = row.get('expires_at')
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if hasattr(created_at, 'isoformat'):
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created_at = created_at.isoformat()
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if hasattr(paid_at, 'isoformat'):
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paid_at = paid_at.isoformat()
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if hasattr(confirmed_at, 'isoformat'):
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confirmed_at = confirmed_at.isoformat()
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if hasattr(expires_at, 'isoformat'):
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expires_at = expires_at.isoformat()
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items.append({
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'id': row['id'],
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'order_type': row.get('order_type') or '',
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'user_id': row.get('user_id'),
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'username': row.get('username') or '',
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'nickname': row.get('nickname') or '',
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'user_email': row.get('user_email') or '',
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'plan': row.get('plan') or '',
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'amount': float(row.get('amount') or 0),
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'currency': row.get('currency') or '',
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'chain': row.get('chain') or '',
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'address': row.get('address') or '',
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'tx_hash': row.get('tx_hash') or '',
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'status': row.get('status') or '',
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'created_at': created_at,
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'paid_at': paid_at,
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'confirmed_at': confirmed_at,
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'expires_at': expires_at
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})
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return jsonify({
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'code': 1,
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'msg': 'success',
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'data': {
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'items': items,
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'total': total,
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'page': page,
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'page_size': page_size,
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'summary': {
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'total_orders': int(summary_row.get('total_orders') or 0),
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'paid_orders': int(summary_row.get('paid_orders') or 0),
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'pending_orders': int(summary_row.get('pending_orders') or 0),
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'failed_orders': int(summary_row.get('failed_orders') or 0),
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'total_revenue': round(float(summary_row.get('total_revenue') or 0), 2)
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}
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}
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})
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except Exception as e:
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logger.error(f"get_admin_orders failed: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return jsonify({'code': 0, 'msg': str(e), 'data': None}), 500
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# ==================== Admin AI Analysis Stats ====================
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@user_bp.route('/admin-ai-stats', methods=['GET'])
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@login_required
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@admin_required
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def get_admin_ai_stats():
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"""
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Get AI analysis usage statistics across the system (admin only).
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Does NOT expose analysis results, only aggregated counts/stats.
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Query params:
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page: int (default 1)
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page_size: int (default 20, max 100)
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search: str (optional, search by username)
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"""
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try:
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page = request.args.get('page', 1, type=int)
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page_size = request.args.get('page_size', 20, type=int)
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search = request.args.get('search', '', type=str).strip()
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page_size = min(100, max(1, page_size))
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offset = (page - 1) * page_size
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with get_db_connection() as db:
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cur = db.cursor()
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# --- Overall summary (from qd_analysis_tasks + qd_analysis_memory) ---
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cur.execute("""
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SELECT
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COUNT(*) AS total_tasks,
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COUNT(DISTINCT user_id) AS unique_users,
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COUNT(DISTINCT symbol) AS unique_symbols,
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COUNT(DISTINCT market) AS unique_markets
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FROM qd_analysis_tasks
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""")
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task_summary = cur.fetchone() or {}
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memory_summary = {}
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try:
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cur.execute("""
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SELECT
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COUNT(*) AS total_memory,
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COALESCE(SUM(CASE WHEN was_correct = true THEN 1 ELSE 0 END), 0) AS correct_count,
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COALESCE(SUM(CASE WHEN was_correct = false THEN 1 ELSE 0 END), 0) AS incorrect_count,
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COALESCE(SUM(CASE WHEN user_feedback = 'helpful' THEN 1 ELSE 0 END), 0) AS helpful_count,
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COALESCE(SUM(CASE WHEN user_feedback = 'not_helpful' THEN 1 ELSE 0 END), 0) AS not_helpful_count
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FROM qd_analysis_memory
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""")
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memory_summary = cur.fetchone() or {}
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except Exception as mem_err:
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logger.warning(f"qd_analysis_memory query failed (table/column may not exist): {mem_err}")
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db.rollback()
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cur = db.cursor() # re-create cursor after rollback
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memory_summary = {}
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# --- Per-user stats ---
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user_conditions = []
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user_params = []
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if search:
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user_conditions.append("(u.username ILIKE ? OR u.nickname ILIKE ? OR u.email ILIKE ?)")
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like_val = f"%{search}%"
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user_params.extend([like_val, like_val, like_val])
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user_where = ""
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if user_conditions:
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user_where = "WHERE " + " AND ".join(user_conditions)
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# Count distinct users who have analysis records
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cur.execute(
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f"""
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SELECT COUNT(DISTINCT t.user_id) AS cnt
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FROM qd_analysis_tasks t
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LEFT JOIN qd_users u ON u.id = t.user_id
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{user_where}
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""",
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tuple(user_params)
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)
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user_total = cur.fetchone()['cnt']
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# Get per-user aggregated stats
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cur.execute(
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f"""
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SELECT
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t.user_id,
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u.username,
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u.nickname,
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u.email,
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COUNT(*) AS analysis_count,
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COUNT(DISTINCT t.symbol) AS symbol_count,
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COUNT(DISTINCT t.market) AS market_count,
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MAX(t.created_at) AS last_analysis_at,
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MIN(t.created_at) AS first_analysis_at
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FROM qd_analysis_tasks t
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LEFT JOIN qd_users u ON u.id = t.user_id
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{user_where}
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GROUP BY t.user_id, u.username, u.nickname, u.email
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ORDER BY analysis_count DESC
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LIMIT ? OFFSET ?
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""",
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tuple(user_params) + (page_size, offset)
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)
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user_rows = cur.fetchall() or []
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# Get per-user analysis_memory stats (correct/helpful counts)
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user_ids = [r['user_id'] for r in user_rows if r.get('user_id')]
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memory_stats_map = {}
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if user_ids:
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try:
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placeholders = ','.join(['?'] * len(user_ids))
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cur.execute(
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f"""
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SELECT
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user_id,
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COUNT(*) AS memory_count,
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COALESCE(SUM(CASE WHEN was_correct = true THEN 1 ELSE 0 END), 0) AS correct,
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COALESCE(SUM(CASE WHEN was_correct = false THEN 1 ELSE 0 END), 0) AS incorrect,
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COALESCE(SUM(CASE WHEN user_feedback = 'helpful' THEN 1 ELSE 0 END), 0) AS helpful,
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COALESCE(SUM(CASE WHEN user_feedback = 'not_helpful' THEN 1 ELSE 0 END), 0) AS not_helpful
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FROM qd_analysis_memory
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WHERE user_id IN ({placeholders})
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GROUP BY user_id
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""",
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tuple(user_ids)
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)
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for row in (cur.fetchall() or []):
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memory_stats_map[row['user_id']] = {
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'memory_count': row['memory_count'],
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'correct': row['correct'],
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'incorrect': row['incorrect'],
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'helpful': row['helpful'],
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'not_helpful': row['not_helpful']
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}
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except Exception as mem_err:
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logger.warning(f"qd_analysis_memory per-user query failed: {mem_err}")
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db.rollback()
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cur = db.cursor() # re-create cursor after rollback
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memory_stats_map = {}
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# Get recent analysis records (last 50)
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cur.execute(
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"""
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SELECT
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t.id,
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t.user_id,
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u.username,
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u.nickname,
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t.market,
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t.symbol,
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t.model,
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t.status,
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t.created_at,
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t.completed_at
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FROM qd_analysis_tasks t
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LEFT JOIN qd_users u ON u.id = t.user_id
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ORDER BY t.created_at DESC
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LIMIT 50
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"""
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)
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recent_rows = cur.fetchall() or []
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cur.close()
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# Build per-user items
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user_items = []
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for row in user_rows:
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uid = row.get('user_id')
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ms = memory_stats_map.get(uid, {})
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last_at = row.get('last_analysis_at')
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first_at = row.get('first_analysis_at')
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if hasattr(last_at, 'isoformat'):
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last_at = last_at.isoformat()
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if hasattr(first_at, 'isoformat'):
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first_at = first_at.isoformat()
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user_items.append({
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'user_id': uid,
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'username': row.get('username') or '',
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'nickname': row.get('nickname') or '',
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'email': row.get('email') or '',
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'analysis_count': row.get('analysis_count') or 0,
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'symbol_count': row.get('symbol_count') or 0,
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'market_count': row.get('market_count') or 0,
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'correct': ms.get('correct', 0),
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'incorrect': ms.get('incorrect', 0),
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'helpful': ms.get('helpful', 0),
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'not_helpful': ms.get('not_helpful', 0),
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'last_analysis_at': last_at,
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'first_analysis_at': first_at
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})
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# Build recent records
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recent_items = []
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for row in recent_rows:
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created_at = row.get('created_at')
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completed_at = row.get('completed_at')
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if hasattr(created_at, 'isoformat'):
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created_at = created_at.isoformat()
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if hasattr(completed_at, 'isoformat'):
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completed_at = completed_at.isoformat()
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recent_items.append({
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'id': row['id'],
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'user_id': row.get('user_id'),
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'username': row.get('username') or '',
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'nickname': row.get('nickname') or '',
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'market': row.get('market') or '',
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'symbol': row.get('symbol') or '',
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'model': row.get('model') or '',
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'status': row.get('status') or '',
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'created_at': created_at,
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'completed_at': completed_at
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})
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return jsonify({
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'code': 1,
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'msg': 'success',
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'data': {
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'user_stats': user_items,
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'user_total': user_total,
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'page': page,
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'page_size': page_size,
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'recent': recent_items,
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'summary': {
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'total_analyses': int(task_summary.get('total_tasks') or 0),
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'unique_users': int(task_summary.get('unique_users') or 0),
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'unique_symbols': int(task_summary.get('unique_symbols') or 0),
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'unique_markets': int(task_summary.get('unique_markets') or 0),
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'total_memory': int(memory_summary.get('total_memory') or 0),
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'correct_count': int(memory_summary.get('correct_count') or 0),
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'incorrect_count': int(memory_summary.get('incorrect_count') or 0),
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'helpful_count': int(memory_summary.get('helpful_count') or 0),
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'not_helpful_count': int(memory_summary.get('not_helpful_count') or 0)
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}
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}
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})
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except Exception as e:
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logger.error(f"get_admin_ai_stats failed: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return jsonify({'code': 0, 'msg': str(e), 'data': None}), 500
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Reference in New Issue
Block a user